Publications

Microbial production of iron (oxyhydr)oxides on polysaccharide rich biopolymers occurs on such a vast scale that it impacts the global iron cycle and has been responsible for major biogeochemical events. Yet the physiochemical controls these biopolymers exert on iron (oxyhydr)oxide formation are poorly understood. Here we used dynamic force spectroscopy to directly probe binding between complex, model and natural microbial polysaccharides and common iron (oxyhydr)oxides. Applying nucleation theory to our results demonstrates that if there is a strong attractive interaction between biopolymers and iron (oxyhydr)oxides, the biopolymers decrease the nucleation barriers, thus promoting mineral nucleation. These results are also supported by nucleation studies and density functional theory. Spectroscopic and thermogravimetric data provide insight into the subsequent growth dynamics and show that the degree and strength of water association with the polymers can explain the influence on iron (oxyhydr)oxide transformation rates. Combined, our results provide a mechanistic basis for understanding how polymer-mineral-water interactions alter iron (oxyhydr)oxides nucleation and growth dynamics and pave the way for an improved understanding of the consequences of polymer induced mineralization in natural systems. This journal is

The objective of the Photovoltaic Collaborative to Advance Multi-climate and Performance Research (PVCAMPER) is to create a multi-climate research platform similar to the US DOE Regional Test Center (RTC) program. Overall, the goal is to foster collaborative research and to build an international organization dedicated to sharing data and exchanging best practices related to PV performance.

The Sandia National Laboratories (SNL) staff is meeting the requirements of Nuclear Fuel Cycle and Supply Chain (NFCSC) Quality Assurance Program Document (QAPD). Each of the NFCSC FY 19 packages for SNL were reviewed. Minor errors were identified with regard to one package for the previous version of this report. Those are being rectified and future instances will indicate the appropriate entries. Aside from the minor discrepancies noted, there were no quality assurance findings this fiscal year for the NFCSC program. In particular, all of the Quality Rigor Level (QRL) level assignments were confirmed to be appropriate.

The Sandia National Laboratories (SNL) staff is meeting the requirements of the Nuclear Fuel Cycle and Supply Chain (NFCSC) Quality Assurance Program Document (QAPD)1. Each of the 46 SFWD FY 19 packages for SNL were reviewed. Six of the 46 packages had incorrect QRL categories, but technical reviews were always found to be appropriate. No major corrective actions are assigned, but recommendations have been made to adjust the identified QRL items. Additional and minor PICS:NE checkbox errors are recognized. Future training will be geared to ensure proper QRL categorizations and other check box entries in future cases

The structural and chemical characterization at the atomic-scale plays a critical role in understanding the structure-property relationship in precise electrical devices such as those produced by atomic-precision advanced manufacturing (APAM). APAM, utilizing hydrogen lithography in a scanning tunneling microscope, offers a potential pathway to ultra-efficient transistors, and has been developed to produce phosphorus (P)-based donor devices integrated into bare Si substrates. Structural characterization of the buried, Si with P dopant (Si:P) delta-layer in the devices by scanning transmission electron microscopy (STEM), however, is a challenge due to similar atomic number and low concentration of the P dopants. In this paper, we describe several efforts of utilizing advanced STEM imagining and spectroscopic techniques to quantify the Si:P deltalayers. STEM imaging combining low-angle and high-angle annular dark-field (LAADF, HAADF) detectors as well as atomic-scale elemental mapping using energy-dispersive X-ray spectroscopy (EDS) are used to reveal the P and defect distribution across the delta-layer processed under various thermal conditions.

The Office of Radiological Security (ORS) In-Device Delay (IDD) program has undertaken a project to research and develop a novel protection system for industrial irradiators that contain high-activity Co-60 sources. Based on adversary testing conducted by ORS, it is was determined that to successfully accomplish the theft of the target material, the adversary will require visual contact of the sources and source rack located at the bottom of the pool. Therefore, if a means of obscuring or visually hiding the sources in the pool can be achieved (while adhering to facility operations, safety, and regulatory requirements), then illicit source theft will be significantly hindered. This project aims to develop a low-cost, non-propriety obscurant that, when an adversary action is detected, the obscurant will be deployed into the pool quickly, rendering visual observation of the source problematic; however, this obscurant will not otherwise disturb the sources, source rack, and filtration system. The obscurant will remain in the pool until removed by another process.

The Exascale Computing Project STDA05-53 milestone status is summarized.

Recent progress in the development of dynamic strength experimental platforms is allowing for unprecedented insight into the assumptions used to construct constitutive models operating in extreme conditions. In this work, we make a quantitative assessment of how tantalum strength scales with its shear modulus to pressures of hundreds of gigapascals through a cross-platform examination of three dynamic strength experiments. Specifically, we make use of Split-Hopkinson pressure bar and Richtmyer-Meshkov instability experiments to assess the low-pressure strain and strain rate dependence. Concurrent examination of magnetically driven ramp-release experiments up to pressures of 350 GPa allows us to examine the pressure dependence. Using a modern description of the shear modulus, validated against both ab initio theory and experimental measurements, we then assess how the experimentally measured pressure dependence scales with shear modulus. We find that the common assumption of scaling strength linearly with the shear modulus is too soft at high pressures and offer discussion as to how descriptions of slip mediated plasticity could result in an alternative scaling that is consistent with the data.

In this study, I present experimental results on the equilibrium between boracite [Mg3B7O13Cl(cr)] and kurnakovite [chemical formula, Mg2B6O11.15H2O(cr); structural formula, MgB3O3(OH)5.5H2O(cr)] at 22.5 ± 0.5 °C from a long-term experiment up to 1629 days, approaching equilibrium from the direction of supersaturation, Mg3B7O13Cl(cr) + H+ + 2B(OH)4 + 18H2O(1) . 3MgB3O3(OH)5.5H2O(cr) + Cl . Based on solubility measurements, the 10-based logarithm of the equilibrium constant for the above reaction at 25 °C is determined to be 12.83 ± 0.08 (2s). Based on the equilibrium constant for dissolution of boracite, Mg3B7O13Cl(cr) + 15H2O(l) = 3Mg2+ + 7B(OH)4 + Cl + 2H+ at 25 °C measured previously (Xiong et al. 2018) and that for the reaction between boracite and kurnakovite determined here, the equilibrium constant for dissolution of kurnakovite, MgB3O3(OH)5.5H2O(cr) = Mg2+ + 3B(OH)4 + H+ + H2O(1) is derived as 14.11 ± 0.40 (2s). Using the equilibrium constant for dissolution of kurnakovite obtained in this study and the experimental enthalpy of formation for kurnakovite from the literature, a set of thermodynamic properties for kurnakovite at 25 °C and 1 bar is recommended as follows: ΔH0f = 4813.24 ± 4.92 kJ/mol, .G0f = 4232.0 ± 2.3 kJ/mol, and S0 = 414.3 ± 0.9 J/(mol.K). Among them, the Gibbs energy of formation is based on the equilibrium constant for kurnakovite determined in this study; the enthalpy of formation is from the literature (Li et al. 1997), and the standard entropy is calculated internally with the Gibbs-Helmholtz equation in this work. The thermodynamic properties of kurnakovite estimated using the group contribution method for borate minerals based on the sums of contributions from the cations, borate polyanions, and structural water to the thermodynamic properties from the literature (Li et al. 2000) are consistent, within their uncertainties, with the values listed above. Since kurnakovite usually forms in salt lakes rich in sulfate, studying the interactions of borate with sulfate is important to modeling kurnakovite in salt lakes. For this purpose, I have re-calibrated our previous model (Xiong et al. 2013) describing the interactions of borate with sulfate based on the new solubility data for borax in Na2SO4 solutions presented here.

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here, based on a silica cell bioreplication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: Size, biconcave shape, deformability, oxygen-carrying capacity, and long circulation time. Four successive nanoscale processing steps (RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicle fusion) are employed for RRBC construction. A panel of physicochemical analyses including zeta-potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirmed the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures with which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long-circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

MACCS (MELCOR Accident Consequence Code System), WinMACCS, and MelMACCS now facilitate a multi-unit consequence analysis. MACCS evaluates the consequences of an atmospheric release of radioactive gases and aerosols into the atmosphere and is most commonly used to perform probabilistic safety assessments (PSAs) and related consequence analyses for nuclear power plants (NPPs). WinMACCS is a user-friendly preprocessor for MACCS. MelMACCS extracts source-term information from a MELCOR plot file. The current development can combine an arbitrary number of source terms, representing simultaneous releases from a multi-unit facility, into a single consequence analysis. The development supports different release signatures, fission product inventories, and accident initiation times for each unit. The treatment is completely general except that the model is currently limited to collocated units. A major practical consideration for performing a multi-unit PSA is that a comprehensive treatment for more than two units may involve an intractable number of combinations of source terms. This paper proposes and evaluates an approach for reducing the number of calculations to be tractable, even for sites with eight or ten units. The approximation error introduced by the approach is acceptable and is considerably less than other errors and uncertainties inherent in a Level 3 PSA.

While dragonflies are well-known for their high success rates when hunting prey, how the underlying neural circuitry generates the prey-interception trajectories used by dragonflies to hunt remains an open question. I present a model of dragonfly prey interception that uses a neural network to calculate motor commands for prey-interception. The model uses the motor outputs of the neural network to internally generate a forward model of prey-image translation resulting from the dragonfly's own turning that can then serve as a feedback guidance signal, resulting in trajectories with final approaches very similar to proportional navigation. The neural network is biologically-plausible and can therefore can be compared against in vivo neural responses in the biological dragonfly, yet parsimonious enough that the algorithm can be implemented without requiring specialized hardware.

The widely parallel, spiking neural networks of neuromorphic processors can enable computationally powerful formulations. While recent interest has focused on primarily machine learning tasks, the space of appropriate applications is wide and continually expanding. Here, we leverage the parallel and event-driven structure to solve a steady state heat equation using a random walk method. The random walk can be executed fully within a spiking neural network using stochastic neuron behavior, and we provide results from both IBM TrueNorth and Intel Loihi implementations. Additionally, we position this algorithm as a potential scalable benchmark for neuromorphic systems.

Deep learning networks have become a vital tool for image and data processing tasks for deployed and edge applications. Resource constraints, particularly low power budgets, have motivated methods and devices for efficient on-edge inference. Two promising methods are reduced precision communication networks (e.g. binary activation spiking neural networks) and weight pruning. In this paper, we provide a preliminary exploration for combining these two methods, specifically in-training weight pruning of whetstone networks, to achieve deep networks with both sparse weights and binary activations.

For materials near the phase boundary between weak and strong topological insulators (TIs), their band topology depends on the band alignment, with the inverted (normal) band corresponding to the strong (weak) TI phase. Here, taking the anisotropic transition-metal pentatelluride ZrTe5 as an example, we show that the band inversion manifests itself as a second extremum (band gap) in the layer stacking direction, which can be probed experimentally via magnetoinfrared spectroscopy. Specifically, we find that the band anisotropy of ZrTe5 features a slow dispersion in the layer stacking direction, along with an additional set of optical transitions from a band gap next to the Brillouin zone center. Our work identifies ZrTe5 as a strong TI at liquid helium temperature and provides a new perspective in determining band inversion in layered topological materials.

Two material types identified by Sew-EZ were tested in various configurations, and under various conditions, by Sandia National Laboratories (SNL). The primary focus of this study was to assess the filtration performance of these two materials and identify if they perform similarly to certified N95 respirators. Testing was conducted on two systems which use distinctly different techniques to characterize the aerosol penetration characteristics of materials: a) R&D Filtration System: A large-scale R&D filtration system was used with testing parameters that mimicked NIOSH guidelines, where possible. Efficiency data as a function of particle size was attained using NaC1 as the test aerosol and a Scanning Mobility Particle Sizer (SMPS) for measurements. A more detailed system description can be found in Omana et al. 2020. b) Automated Tester: A commercial, automated filter tester (100Xs, Air Techniques International) was used to provide penetration/efficiency data for Sew EZ materials. The 100Xs aerosolizes a polydisperse NaC1 aerosol with a consistent concentration and size profile. The 100Xs manual (Air Techniques International 2018) states, "The aerosol particle size and distribution are designed to meet all requirements as defined in the relevant sections of NIOSH 42 CFR, Part 84 (pg. 32)."

On June 30, 2020, a Notice of Violation (NOV) was issued by the City of Albuquerque (COA) Environmental Health Department, Air Quality Program. The NOV identified two violations of New Mexico Administrative Code (NMAC) 20.11.20, Fugitive Dust Control, stemming from an August 30, 2019 inspection of the construction site at Sandia/New Mexico (SNL/NM) Building 812. After the August 30 inspection, a Post-Instruction Notification (PIN) was issued to the SNL Construction Facilities Manager. The PIN was acknowledged by Department 4722 and sent to the COA on September 13, 2020 via email. The PIN "Comply by" date was September 13, 2019 was transmitted by National Nuclear Security Administration/ Sandia Field Office (NNSA/SFO) to COA offices on November 12, 2019. The PIN response was 48 business days past due for various reasons which were explored during the causal analysis.

Here in this paper, we present an efficient approach to compute the integral of monomials and polynomials over polyhedra and regions defined by parametric curved boundary surfaces. We use Euler's theorem for homogeneous functions in combination with Stokes's theorem to reduce the integration of a monomial over a three-dimensional solid to its boundary. If the solid is a polytope, through a recursive application of these theorems, the integral is further reduced to just the evaluation of the monomial and its derivatives at the vertices of the polytope. The present approach is simpler than existing techniques that rely on repeated use of the divergence theorem, which require the antiderivative of the monomials and the projection of these functions onto hyperplanes. For convex and nonconvex polytopes, our approach does not introduce any approximation for the integration of monomials. For curved solid regions bounded by surfaces that admit a parameterization, the same approach yields simplified formulas to compute the integral of any homogeneous function, including monomials. For surfaces parameterized by polynomial surfaces (such as Bezier surface triangles and B-spline patches), the method yields machine-precision accuracy for the volumetric integration of monomials with an appropriate quadrature rule. Numerical examples over regions bounded by polynomial surfaces and rational surfaces are presented to establish the accuracy and efficiency of the method.

In May-June, 2020, a study was conducted to characterize the outgassing properties of a series PEKK (Poly(ether ketone ketone)) samples using cryo-GC/MS headspace analysis. Three sets of samples were interrogated: sample group 1 consisted of 2 additively manufactured PEKK samples (PEKK "ole and "New") prepared by KCNSC from powder material from Solvay Specialty Polymers USA, LLC. Sample groups 2 and 3 consist of 5 PEKK powder types (used as feedstock for additive manufacturing processes) and 4 additively-manufactured PEKK material lots, respectively. Contrary to expectations, all samples of PEKK material were observed to outgas sulfur-containing compounds. Other analyses (EDS/EMA, GC-TOF/MS of PEKK sample extractions) confirmed the presence of sulfur in the PEKK bulk material. Specifically, Diphenyl sulfone (used as a reagent or high-temperature solvent in the synthesis of Polyaryletherketone or PAEK polymers) was observed in three of the powders and in both the PEKK "Old" and "New" samples, suggesting that the source of the sulfur can be traced to impurities in the material left over from the synthesis process.

Recent investigations like the second and third Sandia Fracture Challenges have characterized and demonstrated the performance of a variety of failure techniques and models. These surveys have considered a wide breadth of models encapsulating both general failure criteria as well as those focusing on pore nucleation and growth. Extensive reviews exist on both topics. The former category generally consists of classic models like the Johnson-Cook or Wilkins criteria. These models were recently added to modular plasticity models in the Library of Advanced Materials for Engineering (LAME) as criteria for use with element death capabilities. The latter category was not treated in that effort. There exists a large class of failure models based on predicting the evolution of pores and failure associated with such microstructures. While the exact mechanisms and corresponding impact on the macroscale behavior remain an active area of research, a large suite of formulations have been proposed combining different features of both pore nucleation and subsequent growth. The most famous of these are based on the popular Gurson model of pore growth derived via micromechanical analysis assuming a plastically incompressible matrix. Numerous other models exist for both growth and nucleation and the Cocks-Ashby growth and Horstemeyer-Gokhale nucleation models have been used successfully in recent Sandia Fracture Challenges. This specific combination is colloquially referred to as the "BCJ-failure model as it has been frequently used with the Bammann-Chisea-Johnson plasticity model.

Reaction-diffusion systems have been widely used to study spatio-temporal phenomena in cell biology, such as cell polarization. Coupled bulk-surface models naturally include compartmentalization of cytosolic and membrane-bound polarity molecules. Here we study the distribution of the polarity protein Cdc42 in a mass-conserved membrane-bulk model, and explore the effects of diffusion and spatial dimensionality on spatio-temporal pattern formation. We first analyze a one-dimensional (1-D) model for Cdc42 oscillations in fission yeast, consisting of two diffusion equations in the bulk domain coupled to nonlinear ODEs for binding kinetics at each end of the cell. In 1-D, our analysis reveals the existence of symmetric and asymmetric steady states, as well as anti-phase relaxation oscillations typical of slow-fast systems. We then extend our analysis to a two-dimensional (2-D) model with circular bulk geometry, for which species can either diffuse inside the cell or become bound to the membrane and undergo a nonlinear reaction-diffusion process. We also consider a nonlocal system of PDEs approximating the dynamics of the 2-D membrane-bulk model in the limit of fast bulk diffusion. In all three model variants we find that mass conservation selects perturbations of spatial modes that simply redistribute mass. In 1-D, only anti-phase oscillations between the two ends of the cell can occur, and in-phase oscillations are excluded. In higher dimensions, no radially symmetric oscillations are observed. Instead, the only instabilities are symmetry-breaking, either corresponding to stationary Turing instabilities, leading to the formation of stationary patterns, or to oscillatory Turing instabilities, leading to traveling and standing waves. Codimension-two Bogdanov–Takens bifurcations occur when the two distinct instabilities coincide, causing traveling waves to slow down and to eventually become stationary patterns. Our work clarifies the effect of geometry and dimensionality on behaviors observed in mass-conserved cell polarity models.

Different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed. The performance of these different ML models was evaluated by comparing the prediction error to an existing empirical relationship used to describe LJ fluid diffusion. It was found that the ANN regression models provided superior prediction of diffusion in comparison to the existing empirical relationships.

Composition dependence of second harmonic generation, refractive index, extinction coefficient, and optical bandgap in 20 nm thick crystalline Hf1-xZrxO2 (0 ≤ x ≤ 1) thin films is reported. The refractive index exhibits a general increase with increasing ZrO2 content with all values within the range of 1.98-2.14 from 880 nm to 400 nm wavelengths. A composition dependence of the indirect optical bandgap is observed, decreasing from 5.81 eV for HfO2 to 5.17 eV for Hf0.4Zr0.6O2. The bandgap increases for compositions with x > 0.6, reaching 5.31 eV for Hf0.1Zr0.9O2. Second harmonic signals are measured for 880 nm incident light. The magnitude of the second harmonic signal scales with the magnitude of the remanant polarization in the composition series. Film compositions that display near zero remanent polarizations exhibit minimal second harmonic generation while those with maximum remanent polarization also display the largest second harmonic signal. The results are discussed in the context of ferroelectric phase assemblage in the hafnium zirconium oxide films and demonstrate a path toward a silicon-compatible integrated nonlinear optical material.

The advent of additive manufacturing (AM) has enabled topological control of structures at the micrometer scale, transforming the properties of polymers for a variety of applications. Examples include tailored mechanical responses, acoustic properties, and thermal properties. Porous polymer materials are a class of materials used for shock and blast mitigation, yet they frequently possess a lack of structural order and are largely developed and evaluated via trial-and-error. Here, we demonstrate control of shockwave dissipation through interface-dominated structures prepared by AM using 2-photon polymerization. A fractal structure with voids, or free surfaces, arranged less than 100 μm apart, allows for rarefaction interactions on the timescale of the shockwave loading. Simulations and dynamic x-ray phase contrast imaging experiments show that fractal structures with interfaces assembled within a “critical” volume reduce shockwave stress and wave velocity by over an order of magnitude within the first unit cell.

A sensor to determine water layer (WL) thickness, ranging from 0-5 mm, in salt-spray testing is presented. WL thickness is based on electrical resistivity and sensor design was guided by Finite Element Modeling with validation under known WL thicknesses. WLs were measured in continuous salt spray testing and angle of exposure played the largest role in thicknesses. At angles greater than 20' from vertical, semi-periodic run-off decreased WLs up to 80 %. Finally, exposure angle determines if thin-film conditions are achieved, likely influencing corrosion rate and morphology. Allowances for sample angle in testing standards pose a potentially large source of variability.

Magnetically driven implosions are susceptible to magnetohydrodynamic instabilities, including the magneto-Rayleigh-Taylor instability (MRTI). To reduce MRTI growth in solid-metal liner implosions, the use of a dynamic screw pinch (DSP) has been proposed [P. F. Schmit et al., Phys. Rev. Lett. 117, 205001 (2016)PRLTAO0031-900710.1103/PhysRevLett.117.205001]. In a DSP configuration, a helical return-current structure surrounds the liner, resulting in a helical magnetic field that drives the implosion. Here, we present the first experimental tests of a solid-metal liner implosion driven by a DSP. Using the 1-MA, 100-200-ns COBRA pulsed-power driver, we tested three DSP cases (with peak axial magnetic fields of 2 T, 14 T, and 20 T) and a standard z-pinch (SZP) case (with a straight return-current structure and thus zero axial field). The liners had an initial radius of 3.2 mm and were made from 650-nm-thick aluminum foil. Images collected during the experiments reveal that helical MRTI modes developed in the DSP cases, while nonhelical (azimuthally symmetric) MRTI modes developed in the SZP case. Additionally, the MRTI amplitudes for the 14-T and 20-T DSP cases were smaller than in the SZP case. Specifically, when the liner had imploded to half of its initial radius, the MRTI amplitudes for the SZP case and for the 14-T and 20-T DSP cases were, respectively, 1.1±0.3 mm, 0.7±0.2 mm, and 0.3±0.1 mm. Relative to the SZP, the stabilization obtained using the DSP agrees reasonably well with theoretical estimates.

Previous research has revealed the need for a validation study that considers several wake quantities and code types so that decisions on the trade-off between accuracy and computational cost can be well informed and appropriate to the intended application. In addition to guiding code choice and setup, rigorous model validation exercises are needed to identify weaknesses and strengths of specific models and guide future improvements. Here, we consider 13 approaches to simulating wakes observed with a nacelle-mounted lidar at the Scaled Wind Technology Facility (SWiFT) under varying atmospheric conditions. We find that some of the main challenges in wind turbine wake modeling are related to simulating the inflow. In the neutral benchmark, model performance tracked as expected with model fidelity, with large-eddy simulations performing the best. In the more challenging stable case, steady-state Reynolds-averaged Navier–Stokes simulations were found to outperform other model alternatives because they provide the ability to more easily prescribe noncanonical inflows and their low cost allows for simulations to be repeated as needed. Dynamic measurements were only available for the unstable benchmark at a single downstream distance. These dynamic analyses revealed that differences in the performance of time-stepping models come largely from differences in wake meandering. This highlights the need for more validation exercises that take into account wake dynamics and are able to identify where these differences come from: mesh setup, inflow, turbulence models, or wake-meandering parameterizations. In addition to model validation findings, we summarize lessons learned and provide recommendations for future benchmark exercises.

The objectives of this project are as follows: 1. Reduce uncertainty in PV performance models by developing and validating new and improved models and submodes. 2. Create and manage an open source repository of modeling functions and data. 3. Build and grow the PV Performance Modeling Collaborative; and, 4. Represent the US in the IEA PVPS Task 13 Working group.

This project has four main technical objectives. Develop and improve bifacial performance models by adding the capability to evaluate electrical behavior and performance of bifacial modules and arrays under realistic field conditions including irradiance variability caused by racking, module frame, and position in the array. Instrument and monitor performance of fielded bifacial systems to validate performance models and to measure, analyze and publish on bifacial energy gain. These should include both research and commercial bifacial systems and cover a variety of deployment applications. Evaluate optimal bifacial system designs using simulations leveraging high performance computing, and also using full sized and miniaturized experimental field deployments. Establish and contribute to international test standards for bifacial system performance, testing, and safety, and work with the community to establish installation and siting best practices.

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in deep clay/shale/argillaceous rock. International collaboration activities such as heater tests and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests has as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum vs. discrete) to tackle issues related to flow and transport at various scales of the host-rock and EBS design concept. Consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the EBS design. This is particularly important for backfilled repository concepts where temperature plays a key role in the EBS behavior and long-term performance. This report describes multiple R&D efforts on disposal in argillaceous geologic media through development and application of coupled THMC process models, experimental studies on clay/metal/cement barrier and host-rock (argillite) material interactions, molecular dynamic (MD) simulations of water transport during (swelling) clay dehydration, first-principles studies of metaschoepite (UO₂ corrosion product) stability, and advances in thermodynamic plus surface complexation database development. Drift-scale URL experiments provides key data for testing hydrological-chemical (HC) model involving strong couplings of fluid mixing and barrier material chemical interactions. The THM modeling focuses on heater test experiments in argillite rock and gas migration in bentonite as part of international collaboration activities at underground research laboratories (URLs). In addition, field testing at an URL involves in situ analysis of fault slip behavior and fault permeability. Pore-scale modeling of gas bubble migration is also being investigated within the gas migration modeling effort. Interaction experiments on bentonite samples from heater test under ambient and elevated temperatures permit the evaluation of ion exchange, phase stability, and mineral transformation changes that could impact clay swelling. Advances in the development, testing, and implementation of a spent nuclear fuel (SNF) degradation model coupled with canister corrosion focus on the effects of hydrogen gas generation and its integration with Geologic Disposal Safety Assessment (GDSA). GDSA integration activities includes evaluation of groundwater chemistries in shale formations.

We report on the availability and chemical utility of primary amines within metal-organic frameworks (MOFs) for cell targeting. Primary amine groups represent one of the most versatile chemical moieties for conjugation to biologically relevant molecules, including antibodies and enzymes. Specifically, we used two different chemical conjugations schemes, utilizing the amino functionality on the organic linker: first, carbodiimide chemistry was used to link the primary amine to available carboxyl groups on the protein neutravidin; second, sulfhydryl cross-linking chemistry was used via Traut's reagent scheme. Importantly, this is the first report that documents this methodology implemented with MOF systems. Finally, the ability of the EpCAM antibody targeted MOFs to bind to a human epithelial cell line (A549), a common target for imaging studies, was confirmed with confocal microscopy.

Changes in the nature, intensity, and frequency of climate-related extreme events have imposed a higher risk of failure on energy systems, especially those at the community level. Furthermore, the evolving energy demand patterns and transition towards renewable and localised energy supply can affect energy system resilience. How can an energy system be planned and reconfigured to address these challenges without compromising the system's resilience against chronic stresses and extreme events? Unlike energy system reliability, resilience is neither a common nor an explicit consideration in energy master planning at the community level. In addition, there is no universally agreed-upon method or metrics for measuring or estimating resilience and defining mitigation strategies. This paper introduces a multi-layered energy resilience framework and set of metrics for energy master planning of communities, including the new generation of district energy systems. The potential system disturbances and their short and long-term impacts on various components of the energy system are discussed for commonly expected and extreme events. Three layers of energy resilience are discussed: engineering-designed resilience, operational resilience, and community-societal resilience. A starting set of energy resilience metrics to support engineering design and energy master planning for communities is identified. Implications for future research and practice are noted.

This work presents a worldwide analysis on the yield potential and cost effectiveness of photovoltaic farms composed of monofacial fixed-tilt and single/dual (1T/2T) tracker installations, as well as their bifacial counterparts. Our approach starts by estimating the irradiance reaching both the front and rear surfaces of the modules for the different system designs (validated based on data from real photovoltaic systems and results from the literature) to estimate their energy production. Subsequently, the overall system cost during their 25-year lifetime is factored in, and the levelized cost of electricity (LCOE) is obtained. The results reveal that bifacial-1T installations increase energy yield by 35% and reach the lowest LCOE for the majority of the world (93.1% of the land area). Although dual-axis trackers achieve the highest energy generation, their costs are still too high and are therefore not as cost effective. Sensitivity analyses are also provided to show the general robustness of our findings. This work performs a comprehensive techno-economic analysis worldwide for photovoltaic systems using a combination of bifacial modules and single- and dual-axis trackers. We find that single-axis trackers with bifacial modules achieve the lowest LCOE in the majority of locations (16% reduction on average). Yield is boosted by 35% by using bifacial modules with single-axis trackers and by 40% in combination with dual-axis trackers. Energy production of photovoltaic (PV) modules can be increased not only by solar cells that are more efficient but also by innovative system concepts. In this study, we explore two such concepts in combination: tracking and bifacial modules. A tracking setup increases energy production by moving a PV module over the course of a day, so that it always faces the sun. Bifacial modules use special solar cells and a transparent cover to collect light not only from the front but also from the rear. Through recent advances, both concepts have seen price reductions that enable them to produce electricity cheaper than conventional PV systems. Here, we analyze the technical and economic aspects of combinations of these two concepts worldwide. We find that a combination of bifacial modules with one-axis trackers produces the cheapest electricity (LCOE 16% lower than conventional systems) by significantly boosting energy production (35% more than conventional systems).

A simple linear configuration for multi-line femtosecond laser electronic excitation tagging (FLEET) velocimetry is used for the first time, to the best of our knowledge, to image an overexpanded unsteady supersonic jet. The FLEET lines are spaced 0.5-1.0mmapart, and up to six lines can be used simultaneously to visualize the flowfield. These lines are created using periodic masks, despite the mask blocking 25%-30%of the 10 mJ incident beam.Maps of mean singlecomponent velocity in the direction along the principal flow axis, and turbulence intensity in that same direction, are created using multi-line FLEET, and computed velocities agree well with those obtained from single-line (traditional) FLEET. Compared to traditional FLEET, multi-line FLEET offers increased simultaneous spatial coverage and the ability to produce spatial correlations in the streamwise direction. This FLEET permutation is especially well suited for short-duration test facilities.

We present real-space quantum Monte Carlo (QMC) calculations of the scandate LaScO3 that proved to be challenging for traditional electronic structure approaches due to strong correlation effects resulting in inaccurate band gaps from DFT and GW methods when compared with existing experimental data. Besides calculating an accurate QMC band gap corrected for supercell size biases and in agreement with numerous experiments, we also predict the cohesive energy of the crystal using the standard fixed-node QMC without any empirical or nonvariational parameters. We show that promotion (optical) gap and fundamental gap agree with each other illustrating a clear absence of significant excitonic effects in the ideal crystal. We obtained these results in perfect consistency in two independent tracks that employ different basis sets (plane wave versus localized Gaussians), different codes for generating orbitals (quantum espresso versus crystal), different QMC codes (qmcpack versus qwalk) and different high-accuracy pseudopotentials (ccECPs versus Troullier-Martins) presenting the maturity and consistency of QMC methodology and tools for studies of strongly correlated problems.

Chemical security can be described as the practice of protecting chemicals from people. This editorial introduces the Special Issue on Chemical Security. Herein, we present a concise history of the use of chemicals as weapons and briefly describe consolidated global approaches needed to decrease the security risks from chemicals. We briefly introduce the contributions to this Special Issue from scientists and educators around the world on the topic of chemical security. Given recent high-profile global events that involved chemicals as weapons, improving chemical security awareness and competency is a critical need. We hope this Special Issue continues to generate conversation and collaboration on this important topic and enables educators to teach chemical security principles in their classrooms and laboratories.

Herein, we describe molecular dynamics simulations of helium implantation in geometries resembling tungsten nanotendrils observed in helium plasma exposure experiments. Helium atoms self-cluster and nucleate bubbles within the tendrillike geometries. However, helium retention in these geometries is lower than planar surfaces due to higher surface area to volume ratio which allows for continual bubble expansion and non-destructive release of helium atoms from the nanotendril. Limited diffusion of helium atoms deeper into the tendril was observed, and diffusion was enhanced with pre-existing, subsurface helium bubbles. Diffusion coefficients on the order of 10^-12 -10^-11 m² s^-1 were calculated. This suggests that while helium diffusion is low, it is still feasible that helium can diffuse to the base of a nanotendril to continue to drive fuzz growth.

The thermodynamic stability and melting point of magnesium borohydride were probed under hydrogen pressures up to 1000 bar (100 MPa) and temperatures up to 400 °C. At 400 °C, Mg(BH4)2 was found to be chemically stable between 700 and 1000 bar H2, whereas under 350 bar H2 or lower pressures, the bulk material partially decomposed into MgH2 and MgB12H12. The melting point of solvent-free Mg(BH4)2 was estimated to be 367-375 °C, which was above previously reported values by 40-90 °C. Our results indicated that a high hydrogen backpressure is needed to prevent the decomposition of Mg(BH4)2 before measuring the melting point and that molten Mg(BH4)2 can exist as a stable liquid phase between 367 and 400 °C under hydrogen overpressures of 700 bar or above. The occurrence of a pure molten Mg(BH4)2 phase enabled efficient melt-infiltration of Mg(BH4)2 into the pores of porous templated carbons (CMK-3 and CMK-8) and graphene aerogels. Both transmission electron microscopy and small-angle X-ray scattering confirmed efficient incorporation of the borohydride into the carbon pores. The Mg(BH4)2@carbon samples exhibited comparable hydrogen capacities to bulk Mg(BH4)2 upon desorption up to 390 °C based on the mass of the active component; the onset of hydrogen release was reduced by 15-25 °C compared to the bulk. Importantly, melt-infiltration under hydrogen pressure was shown to be an efficient way to introduce metal borohydrides into the pores of carbon-based materials, helping to prevent particle agglomeration and formation of stable closo-polyborate byproducts.

A series of [(SnSe)1+Î][TiSe2]q heterostructures with systematic changes in the number of TiSe2 layers in the repeating unit were synthesized, and both the structure and electronic-transport properties were characterized. The c-axis lattice parameter increased linearly as q increased, and the slope was consistent with the thickness of a TiSe2 layer. In-plane lattice constants for SnSe and TiSe2 were independent of q. Temperature-dependent resistivity and Hall coefficient data varied systematically as q was increased. The low-temperature electrical data was modeled assuming that only electrons were involved, and the data was fit to a variable range hopping mechanism. The number of carriers involved in this low-temperature transport decreased as q increased, indicating that approximately 1/10th of an electron per SnSe bilayer was transferred to the TiSe2. Calculations also indicated that there was charge donation from the SnSe layer to the TiSe2 layer, resulting in an ionic bond between the layers, which aided in stabilizing the heterostructures. The charge donation created a TiSe2-SnSe-TiSe2 block with the properties distinct from the constituent bulk properties. At high temperatures in large q samples, the transport data required holes to be activated across a band gap to be successfully modeled. This high-temperature transport scales with the number of TiSe2 layers that are not adjacent to SnSe. Using a consistent model across all of the samples significantly constrained the adjustable parameters. The charge transfer between the two constituents results in the stabilization of the heterostructure by an ionic interaction and the formation of a conducting TiSe2-SnSe-TiSe2 block. This is consistent with prior reports, where interactions between two-dimensional (2D) layers and their surroundings (i.e., adjacent layers, substrate, or atmosphere) have been shown to strongly influence the properties.

Chemical risk management is a process to control safety and security risks associated with hazardous chemicals. Chemical risk management includes the management of both chemical safety and chemical security. It is generally accepted that there are five pillars that make up chemical security management. Each of the five pillars are key components to the implementation of a chemical security risk management system. In this work, we will review the "Material Control and Accountability"pillar and how an academic institution can implement this principle using a chemical inventory management system (CIMS). A robust CIMS will improve the quality and efficiency of research, reduce time and resources associated with laboratory management, and reduce both the safety and security risks associated with chemicals.

Comprehensive inventory management is central to the efficient operation of any facility that uses and stores chemicals. There are numerous software packages available that perform this function satisfactorily. Most commercially available inventory management software is regulatory or procurement focused and usually comes with upfront or monthly fees. This report describes freely downloadable software developed at Sandia National Laboratories that delivers an effective inventory management system with an additional focus on chemical security.

To date, chemical security education practices in postsecondary institutions are poorly understood. The purpose of this study is to provide an initial understanding of the practices, attitudes, and barriers toward chemical security education for undergraduate and graduate programs in the United States (US) by surveying representatives of American Chemical Society (ACS)-approved programs. All programs with ACS-approved undergraduate chemistry programs (n = 691) were contacted for participation: 21% (n = 148) fully completed and 6% (n = 41) partially completed the survey for a combined total of 27% complete and/or partially complete surveys (n = 189). We observed that most programs currently teach chemical safety (undergraduate >99%, graduate 73%); however, only about one-third of programs teach chemical security at any education level (undergraduate 32%, graduate 34%). We also observed that safety education is provided more frequently than security education. Further, ACS-approved programs reported that their chemical safety culture was stronger than chemical security culture and felt that safety should be taught differently than security. The overwhelming majority of respondents (96%) indicated that chemical safety should be mandatory at some level, while only about half of respondents (57%) indicated that chemical security should be mandatory at some level. More efforts are needed by the chemistry community to raise awareness of the importance of chemical security education so that more institutions commit to training their faculty and students on the topic. The authors suggest that adoption of chemical security education could be increased if ACS were to advocate for chemical security by including it in its guidelines for educational program approval.

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

A central challenge in developing quantum computers and long-range quantum networks is the distribution of entanglement across many individually controllable qubits1. Colour centres in diamond have emerged as leading solid-state ‘artificial atom’ qubits2,3 because they enable on-demand remote entanglement4, coherent control of over ten ancillae qubits with minute-long coherence times5 and memory-enhanced quantum communication6. A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. So far, these efforts have been stymied by qubit inhomogeneities, low device yield and complex device requirements. Here we introduce a process for the high-yield heterogeneous integration of ‘quantum microchiplets’—diamond waveguide arrays containing highly coherent colour centres—on a photonic integrated circuit (PIC). We use this process to realize a 128-channel, defect-free array of germanium-vacancy and silicon-vacancy colour centres in an aluminium nitride PIC. Photoluminescence spectroscopy reveals long-term, stable and narrow average optical linewidths of 54 megahertz (146 megahertz) for germanium-vacancy (silicon-vacancy) emitters, close to the lifetime-limited linewidth of 32 megahertz (93 megahertz). We show that inhomogeneities of individual colour centre optical transitions can be compensated in situ by integrated tuning over 50 gigahertz without linewidth degradation. The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters7,8 and general-purpose quantum processors9–12.

Geologic reservoirs containing gas hydrate occur beneath permafrost environments and within marine continental slope sediments, representing a potentially vast natural gas source. Numerical simulators provide scientists and engineers with tools for understanding how production efficiency depends on the numerous, interdependent (coupled) processes associated with potential production strategies for these gas hydrate reservoirs. Confidence in the modeling and forecasting abilities of these gas hydrate reservoir simulators (GHRSs) grows with successful comparisons against laboratory and field test results, but such results are rare, particularly in natural settings. The hydrate community recognized another approach to building confidence in the GHRS: comparing simulation results between independently developed and executed computer codes on structured problems specifically tailored to the interdependent processes relevant for gas hydrate-bearing systems. The United States Department of Energy, National Energy Technology Laboratory, (DOE/NETL), sponsored the first international gas hydrate code comparison study, IGHCCS1, in the early 2000s. IGHCCS1 focused on coupled thermal and hydrologic processes associated with producing gas hydrates from geologic reservoirs via depressurization and thermal stimulation. Subsequently, GHRSs have advanced to model more complex production technologies and incorporate geomechanical processes into the existing framework of coupled thermal and hydrologic modeling.

Part of the Presidential Policy Directive 21 (PPD-21) (PPD 2013) mandate includes evaluating safety, security, and safeguards (or nonproliferation) mechanisms traditionally implemented within the nuclear reactors, materials, and waste sector of critical infrastructure—including a complex, dynamic set of risks and threats within an all-hazards approach. In response, research out of Sandia National Laboratories (Sandia) explores the ability of systems theory principles (hierarchy and emergence) and complex systems engineering concepts (multidomain interdependence) to better understand and address these risks and threats. Herein, this Sandia research explores the safety, safeguards, and security risks of three different nuclear sector-related activities—spent nuclear fuel transportation, small modular reactors, and portable nuclear power reactors—to investigate the complex and dynamic risk related to the PPD-21-mandated all-hazards approach. This research showed that a systems-theoretic approach can better identify inter-dependencies, conflicts, gaps, and leverage points across traditional safety, security, and safeguards hazard mitigation strategies in the nuclear reactors, materials, and waste sector. Resulting from this, mitigation strategies from applying systems theoretic principles and complex systems engineering concepts can be (1) designed to better capture interdependencies, (2) implemented to better align with real-world operational uncertainties, and (3) evaluated as a systems-level whole to better identify, characterize, and manage PPD-21's all hazards strategies.

Temperature is a difficult thermodynamic variable to measure in dynamic compression experiments. Optical pyrometry is a general-purpose technique for measuring temperature from a radiant surface, but that surface is often the interface between distinct materials with temperatures that vary spatially along the loading direction. This leads to a fundamental problem: how does the measured interface temperature relate to this temperature profile along the compression axis? Numerical analysis of loading history and thermal diffusion at these interfaces shows that seemingly subtle changes in experiment geometry can lead to very different temperature profiles. We compare these results to laboratory temperature measurements of shock-compressed tin.

Emerging classical and quantum applications require computational electromagnetics methods that can efficiently analyze complex structures over wide bandwidths, including down to very low frequencies. This work begins to address these needs by presenting a type of charge and current integral equation that has been formulated in the time domain and is applicable to dielectric regions. This system introduces charge densities as unknowns in addition to the current densities, resulting in a system that does not exhibit a low frequency breakdown. An appropriate marching-on-in-time discretization scheme is discussed so that stable and accurate results can be achieved down to very low frequencies. Numerical results are shown to verify the accuracy and stability of this formulation.

The impedance bandwidth of a microstrip patch antenna may be increased by additional resonances in the antenna structure. This work uses Characteristic Mode Analysis to show that a classic stacked patch design from the literature operates in this manner and that Coupled Mode Theory governs its operation.

The impedance bandwidth of a microstrip patch antenna may be increased by additional resonances in the antenna structure. This work uses Characteristic Mode Analysis to show that the E-shaped patch operates in this manner and that its operation is well-modeled by Coupled Mode Theory.

This paper implemented an approximate direct inverse for the surface integral equation including multilevel fast-multipole method. We apply it as a preconditioner to two examples suffering convergence problem with an iterative solver.

In the context of tropospheric chemistry, Criegee intermediates denote carbonyl oxides with biradical/zwitterionic character (R1R2COO) that form during the ozonolysis of alkenes. First discovered almost 70 years ago, stabilised versions of Criegee intermediates formed via collisional removal of excess energy have interesting kinetic and mechanistic properties. The direct production and detection of these intermediates were not reported in the literature until 2008. However, recent advances in their generation through the ultraviolet irradiation of the corresponding diiodoalkanes in excess O2 and detection by various spectroscopic techniques (photoionisation, ultraviolet, infrared, microwave and mass spectrometry) have shown that these species can react rapidly with closed-shell molecules, in many cases at or exceeding the classical gas-kinetic limit, via multiple reaction pathways. These reactions can be complex, and laboratory measurements of products and the temperature and pressure dependence of the reaction kinetics have also revealed unusual behaviour. The potential role of these intermediates in atmospheric chemistry is significant, altering models of the oxidising capacity of the Earth's atmosphere and the rate of generation of secondary organic aerosol.

Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. In this paper, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.

In finite element simulations, not all of the data are of equal importance. In fact, the primary purpose of a numerical study is often to accurately assess only one or two engineering output quantities that can be expressed as functionals. Adjoint-based error estimation provides a means to approximate the discretization error in functional quantities and mesh adaptation provides the ability to control this discretization error by locally modifying the finite element mesh. In the past, adjoint-based error estimation has only been accessible to expert practitioners in the field of solid mechanics. In this work, we present an approach to automate the process of adjoint-based error estimation and mesh adaptation on parallel machines. This process is intended to lower the barrier of entry to adjoint-based error estimation and mesh adaptation for solid mechanics practitioners. We demonstrate that this approach is effective for example problems in Poisson’s equation, nonlinear elasticity, and thermomechanical elastoplasticity.

Many social networks contain sensitive relational information. One approach to protect the sensitive relational information while offering flexibility for social network research and analysis is to release synthetic social networks at a pre-specified privacy risk level, given the original observed network. We propose the DP-ERGM procedure that synthesizes networks that satisfy the differential privacy (DP) via the exponential random graph model (EGRM). We apply DP-ERGM to a college student friendship network and compare its original network information preservation in the generated private networks with two other approaches: differentially private DyadWise Randomized Response (DWRR) and Sanitization of the Conditional probability of Edge given Attribute classes (SCEA). The results suggest that DP-EGRM preserves the original information significantly better than DWRR and SCEA in both network statistics and inferences from ERGMs and latent space models. In addition, DP-ERGM satisfies the node DP, a stronger notion of privacy than the edge DP that DWRR and SCEA satisfy.

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

We report an experimental implementation for neutron transverse polarization analysis that is capable of detecting a small angular change (≪10-3 rad) in neutron spin orientation. This approach is demonstrated for monochromatic beams, and we show that it could be extended to polychromatic neutron beams. Our approach employs a 3He spin filter inside a solenoid with an analyzing direction perpendicular to the incident neutron polarization direction. The method was tested with polarized neutron beams and a spin rotator placed inside a μ-metal shield just upstream of the analyzer. No cryogenic superconducting shields or additional neutron spin manipulations are needed. With a counting detector, we experimentally show that the angular resolution δθ=1/(PnA√N) rad is only determined by the counting statistics for the total counts N and the product of the neutron polarization Pn and the analyzing power A. With a high-flux neutron beam, 10-6 rad angular sensitivity is feasible within a day. This simple, classical-quantum-limited transverse polarization analysis scheme may reduce the overall complexity of experimental implementation for applications requiring sensitive neutron polarimetry and improve the precision in fundamental science studies and polarized neutron imaging.

Existing security models are highly linear and fail to capture the rich interactions that occur across security technology, infrastructure, cybersecurity, and human/organizational components. In this work, we will leverage insights from resilience science, complex system theory, and network theory to develop a next-generation security model based on these interactions to address challenges in complex, nonlinear risk environments and against innovative and disruptive technologies. Developing such a model is a key step forward toward a dynamic security paradigm (e.g., shifting from detection to anticipation) and establishing the foundation for designing next-generation physical security systems against evolving threats in uncontrolled or contested operational environments.

Neural network (NN) inference is an essential part of modern systems and is found at the heart of numerous applications ranging from image recognition to natural language processing. In situ NN accelerators can efficiently perform NN inference using resistive crossbars, which makes them a promising solution to the data movement challenges faced by conventional architectures. Although such accelerators demonstrate significant potential for dense NNs, they often do not benefit from sparse NNs, which contain relatively few non-zero weights. Processing sparse NNs on in situ accelerators results in wasted energy to charge the entire crossbar where most elements are zeros. To address this limitation, this letter proposes Granular Matrix Reordering (GMR): a preprocessing technique that enables an energy-efficient computation of sparse NNs on in situ accelerators. GMR reorders the rows and columns of sparse weight matrices to maximize the crossbars' utilization and minimize the total number of crossbars needed to be charged. The reordering process does not rely on sparsity patterns and incurs no accuracy loss. Overall, GMR achieves an average of 28 percent and up to 34 percent reduction in energy consumption over seven pruned NNs across four different pruning methods and network architectures.

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the "pattern" by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game decides among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make a similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information.

As more renewable generation connects to distribution systems, it is imminent that existing distribution feeders will be converted to microgrids-systems that offer resilience by providing the flexibility of supporting the grid in normal operation and operating as self-sustained islands when the grid is disconnected. However, inverter control and feeder protection will need to be tuned to the operating modes of the microgrid. This paper offers an insight into the issues involved by taking a case study of a real-world feeder located in the southwestern US that was converted to a microgrid with three solar PV units connecting to the feeder. Different inverter control configurations and adaptive protection using different settings for different operating conditions are proposed for safe operation of this microgrid. The solution also helps to create a framework for protection and coordination of other similar microgrids.

The transient drag force exerted by mobile solutes on a moving dislocation is computed using continuum theory. These mobile solutes form so-called Cottrell atmospheres around dislocations during static and dynamic strain aging. We evaluate the evolution of the drag force exerted by the atmosphere under two velocity time-histories: impulsive acceleration to a chosen velocity and a constant acceleration rate. A particular focus is on the conditions under which the stationary limit assumed by theories of dynamic strain aging is obeyed. According to our results, two conditions—one on the dislocation velocity and one on the acceleration rate—must be satisfied for the stationary limit to hold. Using the Orowan relation and a line tension model, we obtain estimates for the temperature, stress, strain rate, and dislocation density regimes where the stationary limit is valid, and compare these results with experiments for a few material systems.

Although common practice for estimating photovoltaic (PV) degradation rate (RD) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear RD based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio (PR) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, 'nonconventional' models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior.

A proof-of-principle CR-39 based neutron-recoil-spectrometer was built and fielded on the Z facility. Data from this experiment match indium activation yields within a factor of 2 using simplified instrument response function models. The data also demonstrate the need for neutron shielding in order to infer liner areal densities. A new shielded design has been developed. The spectrometer is expected to achieve signal-to-background greater than 2 for the down-scattered neutron signal and greater than 30 for the primary signal.

Accurate modeling of photovoltaic (PV) performance requires the precise calculation of module temperature. Currently, most temperature models rely on steady-state assumptions that do not account for the transient climatic conditions and thermal mass of the module. On the other hand, complex physics-based transient models are computationally expensive and difficult to parameterize. In order to address this, a new approach to transient thermal modeling was developed, in which the steady-state predictions from previous timesteps are weighted and averaged to accurately predict the module temperature at finer time scales. This model is informed by 3-D finite-element analyses, which are used to calculate the effect of wind speed and module unit mass on module temperature. The model, in application, serves as an added filter over existing steady-state models that smooths out erroneous values that are a result of intermittency in solar resource. Validation of this moving-Average model has shown that it can improve the overall PV energy performance model accuracy by as much as 0.58% over steady-state models based on mean absolute error improvements and can significantly reduce the variability between the model predictions and measured temperature times series data.

The irreversible dimerization of polycyclic aromatic hydrocarbons (PAHs)-typically pyrene (C16H10) dimerization-is widely used in combustion chemistry models to describe the soot particle inception step. This paper concerns itself with the detection and identification of dimers of flame-synthesized PAH radicals and closed-shell molecules and an experimental assessment of the role of these PAH dimers for the nucleation of soot. To this end, flame-generated species were extracted from an inverse co-flow flame of ethylene at atmospheric pressure and immediately diluted with excess nitrogen before the mixture was analyzed using flame-sampling tandem mass spectrometry with collision-induced fragmentation. Signal at m/z = 404.157 (C32H20) and m/z = 452.157 (C36H20) were detected and identified as dimers of closed-shell C16H10 and C18H10 monomers, respectively. A complex between a C13H9 radical and a C24H12 closed-shell PAH was observed at m/z = 465.164 (C37H21). However, a rigorous analysis of the flame-sampled mass spectra as a function of the dilution ratio, defined as the ratio of the flow rates of the diluent nitrogen to the sampled gases, indicates that the observed dimers are not flame-born, but are produced in the sampling line. In agreement with theoretical considerations, this paper provides experimental evidence that pyrene dimers cannot be a key intermediate in particle inception at elevated flame temperatures.

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt-VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

Copper is a commonly used interconnect metal in microelectronic interconnects due to its exceptional electrical and thermal properties. Particularly in applications of the 2.5 and 3D integration, Cu is utilized in through-silicon-vias (TSVs) and flip chip interconnects between microelectronic chips for providing miniaturization, lower power and higher performance than current 2D packaging approaches. SnAg capped Cu pillars are a common high-density interconnect technology for flip chip bonding. For these interconnects, specific properties of the Cu surface, such as roughness and cleanliness, are an important factor in the process to ensure quality solder bumps. During electroplating, tight processing parameters must be met so that defects are avoided, and high bump uniformity is achieved. An understanding of the interactions at the solder and Cu pillar interface is needed, based on the electroplating parameters, to determine the best method for populating solder on the wafer surface. In this study, surface treatment techniques such as oxygen plasma cleaning were performed on the Cu surfaces and the SnAg plating chemistry for depositing the solder were evaluated through hull cell testing to qualitatively determine the range of current densities to investigate. It was observed that current density while plating played a large role in solder bump deposition morphology. At the higher current densities greater than 60 mA/cm2, bump height non-uniformity and dendritic growth are observed and at lower current densities, less than or equal to 60 mA/cm2, uniform, continuous bump height occurred.

A true series resonance oscillator has been developed for use with a wide-range of 1-port resonance-based sensors and devices. The oscillator effectively removes the shunt capacitance Co, allowing the true series resonance to be monitored, providing the optimum sensitivity across a wide range of frequencies (i.e. kilohertz to gigahertz), shunt capacitances, and quality factors (Q) for the first time. It is well-known that non-zero shunt capacitance alters the impedance by shifting the location of the impedance minimum and the zero-phase crossing while causing significant impedance distortion. We have developed an active shunt capacitance cancelling oscillator (ASSCO) that removes any shunt capacitance across the resonator by supplying the circuit an equal 'dummy' capacitance using a cancelling current. The oscillator does not require automatic gain control (AGC) and the resonator can be grounded to reduce parasitic contributions.

Atomic precision advanced manufacturing (APAM) offers creation of donor devices in an atomically thin layer doped beyond the solid solubility limit, enabling unique device physics. This presents an opportunity to use APAM as a pathfinding platform to investigate digital electronics at the atomic limit. Scaling to smaller transistors is increasingly difficult and expensive, necessitating the investigation of alternative fabrication paths that extend to the atomic scale. APAM donor devices can be created using a scanning tunneling microscope (STM). However, these devices are not currently compatible with industry standard fabrication processes. There exists a tradeoff between low thermal budget (LT) processes to limit dopant diffusion and high thermal budget (HT) processes to grow defect-free layers of epitaxial Si and gate oxide. To this end, we have developed an LT epitaxial Si cap and LT deposited Al2O3 gate oxide integrated with an atomically precise single-electron transistor (SET) that we use as an electrometer to characterize the quality of the gate stack. The surface-gated SET exhibits the expected Coulomb blockade behavior. However, the gate’s leverage over the SET is limited by defects in the layers above the SET, including interfaces between the Si and oxide, and structural and chemical defects in the Si cap. We propose a more sophisticated gate stack and process flow that is predicted to improve performance in future atomic precision devices.

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This report is a functional review of the radionuclide containment strategies of fluoride-salt-cooled high temperature reactor (FHR), molten salt reactor (IVISR) and high temperature gas reactor (HTGR) systems. This analysis serves as a starting point for further, more in-depth analyses geared towards identifying phenomenological gaps that still exist, preventing the creation of a mechanistic source term for these reactor types. As background information to this review, an overview of how a mechanistic source term is created and used for consequence assessment necessary for licensing is provided. How mechanistic source term is used within the LMP is also provided. Third, the characteristics of non-LWR mechanistic source terms are examined This report does not assess the viability of any software system for use with advanced reactor designs, but instead covers system function requirements. Future work within the Nuclear Energy Advanced Modeling and Simulations (NEAMS) program will address such gaps.

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A collection of x-ray computed tomography scans of specimens from the Museum of Southwestern Biology.

A collection of x-ray computed tomography scans of specimens from the Museum of Southwestern Biology.

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High-performance spotlight Synthetic Aperture Radar (SAR) requires measurement of the radars motion during the synthetic aperture. A convenient coordinate frame for motion measurement is often not the convenient coordinate frame for motion compensation during the SAR data generation and image formation processing. A convenient frame for radar motion measurement is the Earth-Centered Earth-Fixed (ECEF) coordinate frame, whereas spotlight SAR processing typically require s polar coordinates from a selected Scene Reference Point (SRP). This report presents the conversion from ECEF coordinates to appropriate parameters for SAR processing.

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A collection of x-ray computed tomography scans of specimens from the Museum of Southwestern Biology.

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The term Internet of Things (loT) encompasses everything connected to the internet, but it is increasingly being used to define objects that "talk" to each other. A broader term is that loT are the devices that connect to each other and to the internet. It has been mentioned that loT offers the potential for a "Forth industrial revolution" (1). This is primally because of the ease of use and quick link-up of devices within an area. This poses options for great interactivity but also create security concerns as many of these devices may not have been vetted for industrial use. By allowing for the intercommunication of these devices and combining with automated systems, we can now gather information, provide analysis and create automotive actions. This allows for faster response times as well as lowering the overall cost for operations in nuclear power facilities. (2)

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This simple Microgrid Design Toolkit (MDT) use case will provide you an example of a basic microgrid design. It will introduce basic principles of using the MDT islanded mode optimization by modifying a baseline microgrid design and performing an analysis of the results. Please reference the MDT User Guide (SAND2020-4550) for detailed instructions on how to use the tool.

This simple Microgrid Design Toolkit (MDT) use case will provide you an example of performing microgrid sizing by identifying the types and quantities of technology to be purchased for use in a microgrid. It will introduce basic principles of using the MDT microgrid sizing capability by comparing the results of two microgrids in two different markets. Please reference the MDT User Guide (SAND2020-4550) for detailed instructions on how to use the tool.

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In a transmission line, we evaluate the coupling between a line and a tower above ground when the excitation is an El high-altitude electromagnetic pulse (HEMP). Our model focuses on capturing correctly the effect of the coupling on the peak of the HEMP induced current that propagates along the line. This assessment is necessary to accurately estimate the effect of the excitation on the systems and components of the power grid. This analysis is a step towards a quantitative evaluation of HEMP excitation on the power grid.

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SIGNAL is a first of its kind experimental wargame developed as part of the Project on Nuclear Gaming (PoNG). In this document we describe the rules and game mechanics associated with the online version of SIGNAL created by team members from the University of California, Berkeley, Sandia National Laboratories, and Lawrence Livermore National Laboratory and sponsored by the Carnegie Corporation of New York. The game was developed as part of a larger research project to develop the experimental wargaming methodology and explore its use on a model scenario: the impact of various military capabilities on conflict escalation dynamics. We discuss the results of this research in a forthcoming paper that will include this manual as an appendix. It is our hope that this manual will both contribute to our players' understanding of the game prior to play and that it will allow for replication of the SIGNAL game environment for future research purposes. The manual begins by introducing the terminology used throughout the document. It then outlines the technical requirements required to run SIGNAL. The following section provides a description of the map, resources, infrastructure, tokens, and action cards used in the game environment. The manual then describes the user interface including the chat functions, trade mechanism, currency and population counts necessary for players to plan their actions. It then turns to the sequence of player actions in the game describing the signaling, action, and upkeep phases that comprise each round of play. It then outlines the use of diplomacy including alliances with minor states and trade between players. The manual also describes the process for scoring the game and determining the winner. The manual concludes with tips for players to remember as they embark upon playing the game.

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Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia's pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

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A collection of x-ray computed tomography scans of specimens from the Museum of Southwestern Biology.

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Nuclear power offers the promise of long-term electrical power for remote areas. Recent advances in passive safety and long-life cores make a reactor that can be operated autonomously for 20 years or more a real possibility. This white paper discusses a reactor concept that offers the potential for further development, resulting in a permanently hermetically-sealed "nuclear cartridge." The term "nuclear cartridge" is meant to imply a nuclear energy source that can be inserted into a site and operated autonomously until its energy has been depleted, then withdrawn and replaced by another cartridge. The concept can be scaled for various sizes, ranging from about 1 megawatt-electric (MWe) to about 100 MWe. The paper also discusses the concept of Integrated Safety, Operations, Security, and Safeguards (ISOSS) by design as it applies to this reactor design. Finally, a discussion of smart grids and how they can benefit the transfer of power to the end user is included. The Nuclear Cartridge concept has been developed with the following characteristics in mind: highly reliable autonomous operation coupled with international monitoring, requiring minimal on-site operations personnel; walkaway passively safe design; cartridge replacement cycle on the order of 20 years; load following capability; physical security by design requiring minimal security personnel during operations; and proliferation resistance by design. As illustrated in figure 1, integrating the reactor with advanced power conversion, smart grids, and other sources of energy results in a resilient and sustainable energy source.

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An open-literature search was conducted to consider the current status of the additive manufacturing (AM) industry with respect to metal alloys and refractory high entropy alloys (RHEAs). Key areas of interest include methodologies and applications that are suitable for the nuclear and aerospace industries, as well as other industrial applications. We investigated various promising 3D metal technologies, with emphasis on cost, operation, throughput, maintenance, and output volume size. In addition, technical issues and the current status of the metal printing market are summarized. The project scope also included the manufacturing of open-literature RHEA test coupons at Sandia's laser engineered net shape (LENS) machine.

The electric power grid is one of the most critical infrastructures in the modern world, and the continued protection and resilience of this system from threats is of significant concern. One such set of threats is nanosecond-scale transient effects generated by high-altitude electromagnetic pulses, for which the effect on the power grid is still being studied. Lightning surge arresters serve as the current grid protection against fast transients but are designed and modeled for protection against lightning and switching transients. Surge arrester response to faster transients is not well known. This work defines a scalable metal-oxide surge arrester model with specific consideration to frequencies attributed to fast transient overvoltages from electromagnetic pulses. Measurements using vector network analyzer sweeps at low and high bias as well as high-voltage I-V curve traces are presented to define arrester behavior and to parameterize it from measurement data. The proposed model is compared to the standard IEEE model for lightning arresters in this paper. Furthermore, model parameters are defined by scalable terms to be easily implemented for transmission-level devices. The scalable model enables enhanced assessment of protection levels and grid susceptibility against fast transients.

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A collection of x-ray computed tomography scans of specimens from the Denver Museum of Nature & Science.

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Majorana zero modes (MZMs), fundamental building blocks for realizing topological quantum computers, can appear at the interface between a superconductor and a topological material. One of the experimental signatures that has been widely pursued to confirm the existence of MZMs is the observation of a large, quantized zero-bias conductance peak (ZBCP) in the differential conductance measurements. In this Letter, we report observation of such a large ZBCP in junction structures of normal metal (titanium/gold Ti/Au)-Dirac semimetal (cadmium-arsenide Cd3As2)-conventional superconductor (aluminum Al), with a value close to four times that of the normal state conductance. Our detailed analyses suggest that this large ZBCP is most likely not caused by MZMs. We attribute the ZBCP, instead, to the existence of a supercurrent between two far-separated superconducting Al electrodes, which shows up as a zero-bias peak because of the circuitry and thermal fluctuations of the supercurrent phase, a mechanism conceived by Ivanchenko and Zil'berman more than 50 years ago [Ivanchenko and Zil'berman, JETP 28, 1272 (1969)]. Our results thus call for extreme caution when assigning the origin of a large ZBCP to MZMs in a multiterminal semiconductor or topological insulator/semimetal setup. We thus provide criteria for identifying when the ZBCP is definitely not caused by an MZM. Furthermore, we present several remarkable experimental results of a supercurrent effect occurring over unusually long distances and clean perfect Andreev reflection features.

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