Wireless networking and mobile communications is increasing around the world and in all sectors of our lives. With increasing use, the density and complexity of the systems increase with more base stations and advanced protocols to enable higher data throughputs. The security of data transported over wireless networks must also evolve with the advances in technologies enabling more capable wireless networks. However, means for analysis of the effectiveness of security approaches and implementations used on wireless networks are lacking. More specifically a capability to analyze the lower-layer protocols (i.e., Link and Physical layers) is a major challenge. An analysis approach that incorporates protocol implementations without the need for RF emissions is necessary. In this research paper several emulation tools and custom extensions that enable an analysis platform to perform cyber security analysis of lower layer wireless networks is presented. A use case of a published exploit in the 802.11 (i.e., WiFi) protocol family is provided to demonstrate the effectiveness of the described emulation platform.
The Department of Energy, in response to requests from the U.S. Congress, wishes to maintain an up-to-date table documenting the number of available full drawdowns of each of the caverns owned by the Strategic Petroleum Reserve. This information is important for assessing the SPR's ability to deliver oil to domestic oil companies expeditiously if national or world events dictate a rapid sale and deployment of the oil reserves. The evaluation of drawdown risks require the consideration of several factors regarding cavern and wellbore integrity and stability, including stress states caused by cavern geometry and operations, salt damage caused by dilatant and tensile stresses, the effect on enhanced creep on wellbore integrity, the sympathetic stress effect of operations on neighboring caverns. Based on the work over the past several years, a consensus has been built regarding the assessment of drawdown capabilities and risks for the SPR caverns. This report draws upon the recently Bayou Choctaw model upgrade and analyses to reevaluate and update the available drawdowns for each of those caverns. BC-18, 19, 101 and 102 are predicted to have conditional five available drawdowns remaining BC-15 and 17 have only one remaining drawdowns due to their proximity.
We demonstrate a controlled phase gate approach to entangling neutral atoms using a tunable, Rydberg-dressed interaction. Previous approaches utilize a “dipole blockade” or a “spin-flip blockade” and thereby lack arbitrary phase control, and are less extensible to simultaneous entangling operations in many-atom systems. We systematically study major error mechanisms that limit the fidelity of the entangling interaction and find the dominant error mechanism to be phase noise in the coherent control of the single spins. Our work charts a definitive path to high fidelity entanglement using Rydberg-state-mediated interactions in neutral atoms.
As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.
Shale is characterized by the predominant presence of nanometer-scale (1-100 nm) pores. The behavior of fluids in those pores directly controls shale gas storage and release in shale matrix and ultimately the wellbore production in unconventional reservoirs. Recently, it has been recognized that a fluid confined in nanopores can behave dramatically differently from the corresponding bulk phase due to nanopore confinement (Wang, 2014). CO2 and H2O, either preexisting or introduced, are two major components that coexist with shale gas (predominately CH4) during hydrofracturing and gas extraction. Note that liquid or supercritical CO2 has been suggested as an alternative fluid for subsurface fracturing such that CO2 enhanced gas recovery can also serve as a CO2 sequestration process. Limited data indicate that CO2 may preferentially adsorb in nanopores (particularly those in kerogen) and therefore displace CH4 in shale. Similarly, the presence of water moisture seems able to displace or trap CH4 in shale matrix. Therefore, fundamental understanding of CH4-CO2-H2O behavior and their interactions in shale nanopores is of great importance for gas production and the related CO2 sequestration. This project focuses on the systematic study of CH4-CO2-H2O interactions in shale nanopores under high-pressure and high temperature reservoir conditions. The proposed work will help to develop new stimulation strategies to enable efficient resource recovery from fewer and less environmentally impactful wells.
We present scenario and parametric analyses of the US light duty vehicle (LDV) stock, sim- ulating the evolution of the stock in order to assess the potential role and impacts of fuel cell electric vehicles (FCEVs). The analysis probes the competition of FCEVs with other LDVs and the effects of FCEV adoption on LDV fuel use and emissions. We parameterize commodity and technology prices in order to explore the sensitivities of FCEV sales and emissions to oil, natural gas, battery technology, fuel cell technology, and hydrogen produc- tion prices. We additionally explore the effects of vehicle purchasing incentives for FCEVs, identifying potential impacts and tipping points. Our analyses lead to the following conclu- sions: (1) In the business as usual scenario, FCEVs comprise 7% of all new LDV sales by 2050. (2) FCEV adoption will not substantially impact green house gas emissions without either policy intervention, significant increases in natural gas prices, or technology improve- ments that motivate low carbon hydrogen production. (3) FCEV technology cost reductions have a much greater potential for impact on FCEV sales than hydrogen fuel cost reductions. (4) FCEV purchasing incentives must be both substantial and sustained in order to motivate lasting changes to FCEV adoption.
Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.
A dual-particle imager (DPI) has been designed that is capable of detecting gamma-ray and neutron signatures from shielded SNM. The system combines liquid organic and NaI(Tl) scintillators to form a combined Compton and neutron scatter camera. Effective image reconstruction of detected particles is a crucial component for maximizing the performance of the system; however, a key deficiency exists in the widely used iterative list-mode maximum-likelihood estimation-maximization (MLEM) image reconstruction technique. For MLEM a stopping condition is required to achieve a good quality solution but these conditions fail to achieve maximum image quality. Stochastic origin ensembles (SOE) imaging is a good candidate to address this problem as it uses Markov chain Monte Carlo to reach a stochastic steady-state solution. The application of SOE to the DPI is presented in this work.
Cochran, John R.; Bennett, David G.; Degnan, Paul; Grout, Chris; Liebenberg, Gert; Little, Richard; Ramsey, Jack; Van Blerk, Japie; Van Marcke, Philippe
The community of Cordova, Alaska currently uses diesel and run-of-river hydro generation for its electricity needs. In the past, 60% of the Cordova summer load was supplied by the run-of-river generation. The majority of the time, the load was supplied only by the run-of-river generation. The bulk of generated electricity is delivered to Cordova's industrial fish processing plants and to other industrial loads. With the expansion of Cordova's fishing industry, the run-of-river generation is less often able to supply 100% of the load demand. When the run-of-river generation is not able to supply 100% of the load demand it has to be supplemented by diesel generation. There are also many times when the load demand is low and the available run-of-river generation has to be curtailed by spilling water which could be stored in an energy storage system. Sandia National Laboratories and Alaska Center for Energy and Power collaborated to evaluate how an energy storage system can be used to capture the spilled water and how it can economically and technically benefit Cordova during the fishing season and other times throughout the year. Results from this study are summarized in this report.
Prior work demonstrates that application of transcranial direct current stimulation (tDCS) improves memory. In this study, we investigated tDCS effects on face-name associative memory using both recall and recognition tests. Participants encoded face-name pairs under either active (1.5 mA) or sham (.1 mA) stimulation applied to the scalp adjacent to the left dorsolateral prefrontal cortex (dlPFC), an area known to support associative memory. Participants’ memory was then tested after study (day one) and then again after a 24-h delay (day two), to assess both immediate and delayed stimulation effects on memory. Results indicated that active relative to sham stimulation led to substantially improved recall (more than 50%) at both day one and day two. Recognition memory performance did not differ between stimulation groups at either time point. These results suggest that stimulation at encoding improves memory performance by enhancing memory for details that enable a rich recollective experience, but that these improvements are evident only under some testing conditions, especially those that rely on recollection. Overall, stimulation of the dlPFC could have led to recall improvement through enhanced encoding from stimulation or from carryover effects of stimulation that influenced retrieval processes, or both.
The three-dimensional finite element mesh capturing realistic geometries of the Bayou Choctaw site has been constructed using the sonar and seismic survey data obtained from the field. The mesh consists of hexahedral elements because the salt constitutive model is coded using hexahedral elements. Various ideas and techniques to construct finite element mesh capturing artificially and naturally formed geometries are provided. The techniques to reduce the number of elements as much as possible to save on computer run time while maintaining the computational accuracy is also introduced. The steps and methodologies could be applied to construct the meshes of Big Hill, Bryan Mound, and West Hackberry strategic petroleum reserve sites. The methodology could be applied to the complicated shape masses for various civil and geological structures.
Controlling the traffic of molecules and ions across membranes is a critical feature in a number of biologically relevant processes and highly desirable for the development of technologies based on membrane materials. In this paper, ion transport behavior of hybrid lipid/polymer membranes was studied in the absence and presence of ion transfer agents. A pH-sensitive fluorophore was used to investigate ion (H+/OH−) permeability across hybrid lipid/polymer membranes as a function of the fraction of amphiphilic block copolymer. It was observed that vesicles with intermediate lipid/polymer ratios tend to be surprisingly more permeable to ion transport than the pure lipid or pure polymer vesicles. Hybrid vesicle permeability could be further modulated with valinomycin, nigericin, or gramicidin A, which significantly expedite the dissipation of externally-imposed pH gradients by facilitating the transport of the rate-limiting co-ions (e.g. K+) ions across the membrane. For gramicidin A, ion permeability decreased with increasing polymer mole fraction, and the method of introduction of gramicidin A into the membrane played an important role. Strategies to incorporate biofunctional molecules and facilitate their activity in synthetic systems are highly desirable for developing artificial organelles or other synthetic compartmentalized structures requiring control over molecular traffic across biomimetic membranes.
We use helium released during mechanical deformation of shales as a signal to explore the effects of deformation and failure on material transport properties. A dynamic dual-permeability model with evolving pore and fracture networks is used to simulate gases released from shale during deformation and failure. Changes in material properties required to reproduce experimentally observed gas signals are explored. We model two different experiments of 4He flow rate measured from shale undergoing mechanical deformation, a core parallel to bedding and a core perpendicular to bedding. We find that the helium signal is sensitive to fracture development and evolution as well as changes in the matrix transport properties. We constrain the timing and effective fracture aperture, as well as the increase in matrix porosity and permeability. Increases in matrix permeability are required to explain gas flow prior to macroscopic failure, and the short-term gas flow postfailure. Increased matrix porosity is required to match the long-term, postfailure gas flow. Our model provides the first quantitative interpretation of helium release as a result of mechanical deformation. The sensitivity of this model to changes in the fracture network, as well as to matrix properties during deformation, indicates that helium release can be used as a quantitative tool to evaluate the state of stress and strain in earth materials.
Cyanobacterial phycobilisome (PBS) pigment-protein complexes harvest light and transfer the energy to reaction centers. Previous ensemble studies have shown that cyanobacteria respond to changes in nutrient availability by modifying the structure of PBS complexes, but this process has not been visualized for individual pigments at the single-cell level due to spectral overlap. We characterized the response of four key photosynthetic pigments to nitrogen depletion and repletion at the subcellular level in individual, live Synechocystis sp. PCC 6803 cells using hyperspectral confocal fluorescence microscopy and multivariate image analysis. Our results revealed that PBS degradation and re-synthesis comprise a rapid response to nitrogen fluctuations, with coordinated populations of cells undergoing pigment modifications. Chlorophyll fluorescence originating from photosystem I and II decreased during nitrogen starvation, but no alteration in subcellular chlorophyll localization was found. We observed differential rod and core pigment responses to nitrogen deprivation, suggesting that PBS complexes undergo a stepwise degradation process.
For nearly a century, global power systems have focused on three key functions: Generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.
When electrodes are biased above the plasma potential, electrons accelerated through the associated electron sheath can dramatically increase the ionization rate of neutrals near the electrode surface. It has previously been observed that if the ionization rate is great enough, a double layer separates a luminous high-potential plasma attached to the electrode surface (called an anode spot or fireball) from the bulk plasma. Here, results of the first 2D particle-in-cell simulations of anode spot formation are presented along with a theoretical model describing the formation process. It is found that ionization leads to the build-up of an ion-rich layer adjacent to the electrode, forming a narrow potential well near the electrode surface that traps electrons born from ionization. It is shown that anode spot onset occurs when a quasineutral region is established in the potential well and the density in this region becomes large enough to violate the steady-state Langmuir condition, which is a balance between electron and ion fluxes across the double layer. A model for steady-state properties of the anode spot is also presented, which predicts values for the anode spot size, double layer potential drop, and form of the sheath at the electrode by considering particle, power, and current balance. These predictions are found to be consistent with the presented simulation and previous experiments.
We conducted computational macroscale simulations predicting blast-induced intracranial fluid cavitation possibly leading to brain injury. To further understanding of this problem, we developed microscale models investigating the effects of blast-induced cavitation bubble collapse within white matter axonal fiber bundles of the brain. We model fiber tracks of myelinated axons whose diameters are statistically representative of white matter. Nodes of Ranvier are modeled as unmyelinated sections of axon. Extracellular matrix envelops the axon fiber bundle, and gray matter is placed adjacent to the bundle. Cavitation bubbles are initially placed assuming an intracranial wave has already produced them. Pressure pulses, of varied strengths, are applied to the upper boundary of the gray matter and propagate through the model, inducing bubble collapse. Simulations, conducted using the shock wave physics code CTH, predict an increase in pressure and von Mises stress in axons downstream of the bubbles after collapse. This appears to be the result of hydrodynamic jetting produced during bubble collapse. Interestingly, results predict axon cores suffer significantly lower shear stresses from proximal bubble collapse than does their myelin sheathing. Simulations also predict damage to myelin sheathing, which, if true, degrades axonal electrical transmissibility and general health of the white matter structures in the brain.
Photos in each group are in chronological order as captured: Group I Tank Platform Setup, November 14, 2017; Group II Tank Setup, November 15, 2017; Group III Aboveground Injestion System (AIS) Setup, November 20, 2017; Group IV Chemical Mixing, November 21, 2017; Group V KB-1 Bacteria Injection, November 27, 2017; Group VI Miscellaneous.
Over the past ten years, the Department of Energy (DOE) has helped to develop components and technologies for the Supercritical Carbon Dioxide (sCO2) power cycle capable of efficient operation at high temperatures and high efficiency. The DOE Offices of Fossil Energy, Nuclear Energy, and Energy Efficiency and Renewable Energy collaborated in the planning and execution of the sCO2 Power Cycle Summit conducted in Albuquerque, NM in November 2017. The summit brought together participants from government, national laboratories, research, and industry to engage in discussions regarding the future of sCO2 Power Cycles Technology. This report summarizes the work involved in summit planning and execution, before, during, and after the event, including the coordination between three DOE offices and technical content presented at the event.
Majumder, Erica L.W.; Wolf, Benjamin M.; Liu, Haijun; Berg, R.H.; Timlin, Jerilyn A.; Chen, Min; Blankenship, Robert E.
Far-Red Light (FRL) acclimation is a process that has been observed in cyanobacteria and algae that can grow solely on light above 700 nm. The acclimation to FRL results in rearrangement and synthesis of new pigments and pigment-protein complexes. In this study, cyanobacteria containing chlorophyll f, Synechococcus sp. PCC 7335 and Halomicronema hongdechloris, were imaged as live cells with confocal microscopy. H. hongdechloris was further studied with hyperspectral confocal fluorescence microscopy (HCFM) and freeze-substituted thin-section transmission electron microscopy (TEM). Under FRL, phycocyanin-containing complexes and chlorophyll-containing complexes were determined to be physically separated and the synthesis of red-form phycobilisome and Chl f was increased. The timing of these responses was observed. The heterogeneity and eco-physiological response of the cells was noted. Additionally, a gliding motility for H. hongdechloris is reported.
In many fields of study, from coherent Raman microscopy on living cells to time-resolved coherent Raman spectroscopy of gas-phase turbulence and combustion reaction dynamics, the need for the capability to time-resolve fast dynamical and nonrepetitive processes has led to the continued development of high-speed coherent Raman methods and new high-repetition rate laser sources, such as pulse-burst laser systems. However, much less emphasis has been placed on our ability to detect shot to shot coherent Raman spectra at equivalently high scan rates, across the kilohertz to megahertz regime. This is beyond the capability of modern scientific charge coupled device (CCD) cameras, for instance, as would be employed with a Czerny-Turner type spectrograph. As an alternative detection strategy with megahertz spectral detection rate, we demonstrate dispersive Fourier transformation detection of pulsed (~90 ps) coherent Raman signals in the time-domain. Instead of reading the frequency domain signal out using a spectrometer and CCD, the signal is transformed into a time-domain waveform through dispersive Fourier transformation in a long single-mode fiber and read-out with a fast sampling photodiode and oscilloscope. Molecular O- and S-branch rotational sideband spectra from both N2 and H2 were acquired employing this scheme, and the waveform is fitted to show highly quantitative agreement with a molecular model. The total detection time for the rotational spectrum was 20 ns, indicating an upper limit to the detection frequency of ~50 MHz, significantly faster than any other reported spectrally-resolved coherent anti-Stokes Raman detection strategy to date.
Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO2, and CO as fundamental signatures of degradation kinetics is required. This study describes an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapid acquisition FTIR spectrometer for time resolved successive spectra. The volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ∼50 μg water or CO2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. This approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.
Fatigued driving contributes to a substantial number of motor vehicle accidents each year. Music listening is often employed as a countermeasure during driving in order to mitigate the effects of fatigue. Though music listening has been established as a distractor in the sense that it increases cognitive load during driving, it is possible that increased cognitive load is desirable under particular circumstances. For instance, during situations that typically result in cognitive underload, such as driving in a low-traffic monotonous stretch of highway, it may be beneficial for cognitive load to increase, thereby necessitating allocation of greater cognitive resources to the task of driving and attenuating fatigue. In the current study, we employed a song-naming game as a countermeasure to fatigued driving in a simulated monotonous environment. During the first driving session, we established that driving performance deteriorates in the absence of an intervention following 30 min of simulated driving. During the second session, we found that a song-naming game employed at the point of fatigue onset was an effective countermeasure, as reflected by simulated driving performance that met or exceeded fresh driving behavior and was significantly better relative to fatigued performance during the first driving session.
The excimer-pumped alkali laser (XPAL) system has recently been demonstrated in several different mixtures of alkali vapor and rare gas. Without special preventive measures, plasma formation during operation of XPAL is unavoidable. Recent advancements in the availability of reliable data for electron impact collisions with atoms and molecules have enabled development of a complete reaction mechanism to investigate XPAL-induced plasmas. We report on pathways leading to plasma formation in an Ar∕C2H6∕Cs XPAL sustained at different cell temperatures. We find that depending on the operating conditions, the contribution of electron impact processes can be as little as bringing the excitation of Cs(2P) states to higher level Cs states, and can be as high as bringing Cs(2P) excited states to a full ionization. Increasing the input pumping power or cell temperature, or decreasing the C2H6 mole fraction leads to electron impact processes dominating in plasma formation over the energy pooling mechanisms previously reported in literature.
Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; Jensen, Anna M.; Malhotra, Avni; Mcfarlane, Karis J.; Norby, Richard J.; Sargsyan, Khachik; Sebestyen, Stephen D.; Shi, Xiaoying; Walker, Anthony P.; Ward, Eric J.; Warren, Jeffrey M.; Weston, David J.
We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determine if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m-2 yr-1 to a sink of 67 g C m-2 yr-1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO2 treatments.
The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.
Here, we develop a method for time-dependent topic tracking and meme trending in social media. Our objective is to identify time periods whose content differs signifcantly from normal, and we utilize two techniques to do so. The first is an information-theoretic analysis of the distributions of terms emitted during different periods of time. In the second, we cluster documents from each time period and analyze the tightness of each clustering. We also discuss a method of combining the scores created by each technique, and we provide ample empirical analysis of our methodology on various Twitter datasets.
Strike difference of the trivalent rare-earth cations from their alkali and alkaline-earth peers is in the presence of localized 4f-electrons and strong spin-orbit coupling. Placing trivalent rare-earth cations inside the fullerene molecules or in between the blocks of itinerant magnetic intermetallics gave rise to plethora of fascinating properties and materials. A long-time missing but hardly desired piece is the semiconducting or metallic compound where rare-earth cations are situated inside the oversized polyhedral cages of three-dimensional framework. In this work we present a synthesis of such compounds, rare-earth containing clathrates Ba8-xRxCu16P30. The unambiguous proofs of their composition and crystal structure were achieved by a combination of synchrotron powder diffraction, time-of-flight neutron powder diffraction, scanning-transmission electron microscopy, and electron energy-loss spectroscopy. Our quantum-mechanical calculations and experimental characterizations show that the incorporation of the rare-earth cations significantly enhances the hole mobility and concentration which results in the drastic increase in the thermoelectric performance.
Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered in an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.
We present findings on the computational complexity of computing multidimensional persistent homology. We first show that the worst-case computational complexity of multidimensional persistence is exponential. We then present an algorithm for computing multidimensional persistence which extends the algorithm given by Zomorodian and Carlsson for computing one-dimensional persistence. The computational complexity of our algorithm is polynomial in the size of the persistence module and exponential in the persistence dimension.
Miller, Andrew; Bentov, Iddo; Kumaresan, Ranjit; Cordi, Christopher; Mccorry, Patrick
Bitcoin, Ethereum and other blockchain-based cryptocurrencies, as deployed today, cannot scale for wide-spread use. A leading approach for cryptocurrency scaling is a smart contract mechanism called a payment channel which enables two mutually distrustful parties to transact efficiently (and only requires a single transaction in the blockchain to set-up). Payment channels can be linked together to form a payment network, such that payments between any two parties can (usually) be routed through the network along a path that connects them. Crucially, both parties can transact without trusting hops along the route. In this paper, we propose a novel variant of payment channels, called Sprites, that reduces the worst-case “collateral cost” that each hop along the route may incur. The benefits of Sprites are two-fold. 1) In Lightning Network, a payment across a path of ℓ channels requires locking up collateral for Θ(ℓΔ) time, where Δ is the time to commit an on-chain transaction. Sprites reduces this cost to Θ(ℓ+Δ). 2) Unlike prior work, Sprites supports partial withdrawals and deposits, during which the channel can continue to operate without interruption. In evaluating Sprites we make several additional contributions. First, our simulation-based security model is the first formalism to model timing guarantees in payment channels. Our construction is also modular, making use of a generic abstraction from folklore, called the “state channel,” which we are the first to formalize. We also provide a simulation framework for payment network protocols, which we use to confirm that the Sprites construction mitigates against throughput-reducing attacks.
Uncertainty is pervasive in all science and engineering applications. Incorporating uncertainty in physical models is therefore both natural and vital. In doing so, we often arrive at parametric systems of partial differential equations (PDEs). When passing from simulation to optimization, we obtain (typically nonconvex) infinite-dimensional optimization problems that, upon discretization, result in extremely large-scale nonlinear programs. For example, consider a linear elliptic PDE on a two- dimensional domain with a single random coeffcient. If we sampled the random input with 10,000 realizations of the coeffcient, the resulting optimization problem would have 10,000 PDE constraints. Furthermore, discretizing each PDE with piecewise linear finite elements on a 100X100 uni- form quadrilateral mesh results in 100,000,000 degrees of freedom. As a result, the critical components for ensuring mesh-independent performance of numerical optimization methods in the deterministic setting, for example, solution regularity and generalized differentiability, are even more critical in the stochastic setting.
Clays have many positive attributes leading to their use in waste isolation scenarios. One negative of their use is the formation of clay colloids that can transmit otherwise strongly sorbing contaminants long distances. In this work, we introduce a material combining a layered double hydroxide and a montmorillonite clay. This material is functionally characterized in an advective column under conditions where clay colloid formation is extensive. The material is shown to retard clay colloids once formed, and to help limit the initial formation of clay colloids. Adding this material to a waste barrier will help to limit the erosion of the clays in the barrier and limit the colloidal transport of contaminants.
The stability constant of FeB(OH)4+ is expected to find applications in many areas of study. For instance, FeB(OH)4+ may have played an important role in transport of ferrous iron in reducing water bodies at the surface of the primitive Earth. In the nearfield of geological repositories, the formation of FeB(OH)4+ can sequestrate soluble borate, lowering borate concentrations available to the formation of the Am(III)-borate aqueous complex.
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Gerberich, William; Tadmor, Ellad B.; Kysar, Jeffrey; Zimmerman, Jonathan A.; Minor, Andrew M.; Szlufarska, Izabela; Amodeo, Jonathan; Devincre, Benoit; Hintsala, Eric; Ballarini, Roberto
With rapidly increasing numbers of studies of new and exotic material uses for perovskites and quasicrystals, these demand newer instrumentation and simulation developments to resolve the revealed complexities. One such set of observational mechanics at the nanoscale is presented here for somewhat simpler material systems. The expectation is that these approaches will assist those materials scientists and physicists needing to verify atomistic potentials appropriate to the nanomechanical understanding of increasingly complex solids. The five following segments from nine University, National and Industrial Laboratories both review and forecast where some of the important approaches will allow a confirming of how in situ mechanics and nanometric visualization might unravel complex phenomena. These address two-dimensional structures, temporal models for the nanoscale, atomistic and multiscale friction fundamentals, nanoparticle surfaces and interfaces and nanomechanical fracture measurements, all coupled to in situ observational techniques. Rapid future advances in the applicability of such materials science solutions appear guaranteed.
This Federal Radiological Monitoring and Assessment Center (FRMAC) Assessment Manual has been prepared by representatives of those Federal and State agencies that can be expected to play the major roles during a radiological emergency. Federal Agencies include: the National Nuclear Security Administration (NNSA), the Nuclear Regulatory Commission (NRC), the Environmental Protection Agency (EPA), the Department of Agriculture (USDA), the Food and Drug Administration (FDA), and the Centers for Disease Control (CDC). This final manual was reviewed by experts from across the community and their input has been incorporated.
This report provides an introduction to cyber security for distributed energy resources (DER) - such as photovoltaic (PV) inverters and energy storage systems (ESS). This material is motivated by the need to assist DER vendors, aggregators, grid operators, and broader PV industry with cyber security resilience and describe the state-of-the-art for securing DER communications. The report outlines basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. Example cyber security attacks, including eavesdropping, masquerading, man-in-the-middle, replay attacks, and denial-of-service are also described. A survey of communication protocols and cyber security recommendations used by the DER and power system industry are included to elucidate the cyber security standards landscape. Lastly, a roadmap is presented to harden end-to-end communications for DER with research and industry engagement.
Understanding the interfacial behavior of two materials sliding relative to each other is import ant in computational modeling and simulating impact or shock response of components, subsystems, and even full-scale systems. Although often considered as a constant for different applications, the coefficient of friction may be dependent on a number of factors such as normal force, roughness, material type, temperature, and sliding velocity. In this study, a new method based on a Kolsky tension bar with a custom-made friction fixture was developed for measurement of the dynamic friction coefficient between two metallic materials at high sliding velocities. In this new method, polyvinylidene fluoride (PVDF) thin film force sensors were used to measure the normal force, while a strain gage on the transmission bar was used to measure the friction force. As such, the dynamic friction coefficient is calculated with the normal and friction forces. The impact velocity can be varied to investigate the dependency of friction coefficient on impact velocity. To evaluate the technique, friction coefficients between 4340 steel and 7075-T6 we re measured at three different sliding velocities of 4, 8 and 11 m/s. Effects of surface roughness, normal force, and impact speed were also explored . Decreased static and kinetic friction coefficient s were observed when the normal force was increased at constant sliding velocity. With increasing velocity, the friction coefficient remained fairly constant for the three velocities studied. Higher friction coefficients were measured when the specimen roughness was increased.
This Laboratory Directed Research and Development (LDRD) project focused on understanding the mathematical relationships that can be used in assessing the value of executing various EMP mitigation strategies on the grid. This is referred to as the EMP Resilient Grid Value Model. Because the range of mitigation strategies can contain widely differing characteristics (operational vs. technological), it is necessary to compute functions of many interrelated metrics at varying levels of fidelity that will be used to provide feedback as to the cost/benefit relationship of any proposed strategy. The value model is a hierarchical decomposition of a system of systems (SoS) model down to a grid circuit model. The model is intended to be suitable for use in subsequent decision support optimization for resilience to EMP events. The metric set goes beyond direct, technical impacts on the electrical grid to include ancillary impacts on dependent infrastructure and enterprise concerns (water, DoD, transportation, etc.).
Future nuclear arms - control agreements may place numerical limits on the total number of warheads in the nuclear arsenals of states. Verifying these limits may require inspectors to account for individual warheads, both deployed and non-deployed. This task could be accomplished with unique identifiers, but standard tagging techniques may be unacceptable in this case due to host concerns about safety and intrusiveness. To resolve this dilemma, we revisit the so - called Buddy Tag concept first proposed by Sandia National Laboratories in the early 1990s. The conceptual innovation in the Buddy Tag was to by separate the tag from the treaty limited item itself. Verification of the pairings between tags and limited items would take place during a short-notice inspection, where the host would be required to produce one buddy tag for each item. Sensors on the Buddy Tag would show that it had not been moved to the inspected site after the inspection was declared (e.g., within the last 24-48 hours). If the inspector counted more (or fewer) treaty limited items than Buddy Tags at the inspected site, a treaty violation could be asserted. Using a number of single-site inspections, an inspecting party can hold the host at risk for discovery of violating the treaty at an enterprise level by possessing more treaty limited items than the treaty allows. In this project, we developed a buddy-tag prototype for demonstration and evaluation purposes. This paper summarizes the performance requirements for an advanced Buddy Tag, the proposed conduct of operations, the design choices and functionalities of the different subsystems, and initial testing results. The report also summarizes peer review feedback obtained throughout the project.
Quantitative understanding of reactivity and stability for a chemical species is fundamental to chemistry. The concept has undergone many changes and additions throughout the history of chemistry, stemming from the ideas such as Lewis acids and bases. For a given complexing ligand (Lewis base) and a group of isovalent metal cations (Lewis acids), the stability constants of metal-ligand (ML) complexes can simply correlate to the known properties of metal ions [ionic radii (rMn+), Gibbs free energy of formation (ΔG°f, Mn+), and solvation energy (ΔG°s, Mn+)] by 2.303RT log KML = (α∗MLΔG°f, Mn+ - β∗MLrMn+ + γ∗MLΔG°s, Mn+ - ∗ML), where the coefficients (α∗ML, β∗ML, γ∗ML, and intercept δ∗ML) are determined by fitting the equation to the existing experimental data. Coefficients β∗ML and γ∗ML have the same sign and are in a linear relationship through the origin. Gibbs free energies of formation of cations (ΔG°f, Mn+) are found to be natural indices for the softness or hardness of metal cations, with positive values corresponding to soft acids and negative values to hard acids. The coefficient α∗ML is an index for the softness or hardness of a complexing ligand. Proton (H+) with the softness index of zero is a unique acid that has strong interactions with both soft and hard bases. The stability energy resulting from the acid-base interactions is determined by the term α∗MLΔG°f, Mn+; a positive product of α∗ML and ΔG°f, Mn+ indicates that the acid-base interaction between the metal cation and the complexing ligand stabilizes the complex. The terms β∗MLrMn+ and γ∗MLΔG°s, Mn+, which are related to ionic radii of metal cations, represent the steric and solvation effects of the cations. The new softness indices proposed here will help to understand the interactions of ligands (Lewis bases) with metal cations (Lewis acids) and provide guidelines for engineering materials with desired chemical reactivity and selectivity. The new correlation can also enhance our ability for predicting the speciation, mobility, and toxicity of heavy metals in the earth environments and biological systems.
There has recently been a great deal of interest in employing immiscible solutes to stabilize nanocrystalline microstructures. Existing modeling efforts largely rely on mesoscale Monte Carlo approaches that employ a simplified model of the microstructure and result in highly homogeneous segregation to grain boundaries. However, there is ample evidence from experimental and modeling studies that demonstrates segregation to grain boundaries is highly non-uniform and sensitive to boundary character. This work employs a realistic nanocrystalline microstructure with experimentally relevant global solute concentrations to illustrate inhomogeneous boundary segregation. Furthermore, experiments quantifying segregation in thin films are reported that corroborate the prediction that grain boundary segregation is highly inhomogeneous. In addition to grain boundary structure modifying the degree of segregation, the existence of a phase transformation between low and high solute content grain boundaries is predicted. In order to conduct this study, new embedded atom method interatomic potentials are developed for Pt, Au, and the PtAu binary alloy.
Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible. Projections by all models were in close agreement only in the first few years. Although the projections from LVCFlex, MA3T, LAVE-Trans, and ParaChoice were in qualitative agreement, there were significant differences in sales shares given by the different models for individual powertrain types, particularly in later years (2030 and later). For example, projected sales shares of conventional spark-ignition vehicles in 2030 for a given scenario ranged from 35% to 74%. Reasons for such differences are discussed, recognizing that these models were not developed to give quantitatively accurate predictions of future sales shares, but to represent vehicles markets realistically and capture the connections between sales and important influences. Model features were also compared at a high level, and suggestions for further comparison of models are given to enable better understanding of how different features and algorithms used in these models may give different projections.
Moaseri, Ehsan; Bollinger, Jonathan; Changalvaie, Behzad; Johnson, Lindsay; Schroer, Joseph; Johnston, Keith P.; Truskett, Thomas M.
Nanoparticle (NP) clusters with diameters ranging from 20 to 100 nm are reversibly assembled from 5 nm gold (Au) primary particles coated with glutathione (GSH) in aqueous solution as a function of pH in the range of 5.4 to 3.8. As the pH is lowered, the GSH surface ligands become partially zwitterionic and form interparticle hydrogen bonds that drive the self-limited assembly of metastable clusters in <1 min. Whereas clusters up to 20 nm in size are stable against cluster-cluster aggregation for up to 1 day, clusters up to 80 nm in size can be stabilized over this period via the addition of citrate to the solution in equal molarity with GSH molecules. The cluster diameter may be cycled reversibly by tuning pH to manipulate the colloidal interactions; however, modest background cluster-cluster aggregation occurs during cycling. Cluster sizes can be stabilized for at least 1 month via the addition of PEG-thiol as a grafted steric stabilizer, where PEG-grafted clusters dissociate back to starting primary NPs at pH 7 in fewer than 3 days. Whereas the presence of excess citrate has little effect on the initial size of the metastable clusters, it is necessary for both the cycling and dissociation to mediate the GSH-GSH hydrogen bonds. In summary, these metastable clusters exhibit significant characteristics of equilibrium self-limited assembly between primary particles and clusters on time scales where cluster-cluster aggregation is not present.
Triangle counting serves as a key building block for a set of important graph algorithms in network science. In this paper, we address the IEEE HPEC Static Graph Challenge problem of triangle counting, focusing on obtaining the best parallel performance on a single multicore node. Our implementation uses a linear algebra-based approach to triangle counting that has grown out of work related to our miniTri data analytics miniapplication [1] and our efforts to pose graph algorithms in the language of linear algebra. We leverage KokkosKernels to implement this approach efficiently on multicore architectures. Our performance results are competitive with the fastest known graph traversal-based approaches and are significantly faster than the Graph Challenge reference implementations, up to 670,000 times faster than the C++ reference and 10,000 times faster than the Python reference on a single Intel Haswell node.
We use ab initio molecular dynamics (AIMD) calculations and quasi-chemical theory (QCT) to study the inner-shell structure of F-(aq) and to evaluate that single-ion free energy under standard conditions. Following the "no split occupancies" rule, QCT calculations yield a free energy value of -101 kcal/mol under these conditions, in encouraging agreement with tabulated values (-111 kcal/mol). The AIMD calculations served only to guide the definition of an effective inner-shell constraint. QCT naturally includes quantum mechanical effects that can be concerning in more primitive calculations, including electronic polarizability and induction, electron density transfer, electron correlation, molecular/atomic cooperative interactions generally, molecular flexibility, and zero-point motion. No direct assessment of the contribution of dispersion contributions to the internal energies has been attempted here, however. We anticipate that other aqueous halide ions might be treated successfully with QCT, provided that the structure of the underlying statistical mechanical theory is absorbed, i.e., that the "no split occupancies" rule is recognized.
Nanosecond in situ x-ray diffraction and simultaneous velocimetry measurements were used to determine the crystal structure and pressure, respectively, of ramp-compressed aluminum at stress states between 111 and 475 GPa. The solid-solid Al phase transformations, fcc-hcp and hcp-bcc, are observed at 216±9 and 321±12 GPa, respectively, with the bcc phase persisting to 475 GPa. The high-pressure crystallographic texture of the hcp and bcc phases suggests close-packed or nearly close-packed lattice planes remain parallel through both transformations.
In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.
This paper proposes a method of enabling photovoltaic (PV) power plants to participate in primary frequency response by providing synthetic inertia (SI). This variation, referred to as communication enabled synthetic inertia (CE-SI), utilizes communication capabilities to provide global system frequency information to PV plants to emulate the inertial response of synchronous generators. The performance of CE-SI is analyzed with respect to the challenges associated with communication, such as latency and availability. Results indicate improvements in frequency response over SI using local frequency measurements when communication latency is sufficiently small.
Distribution system analysis with high penetrations of distributed energy resources (DER) requires quasi-static time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system, but current QSTS algorithms are prohibitively burdensome and computationally intensive. This paper proposes a novel deviation-based algorithm to calculate the critical time periods when QSTS simulations should be solved at higher or lower time-resolution. This predetermined time-step (PT) solver is a new method of performing variable time-step simulations based solely on the input data. The PT solver demonstrates high accuracy while performing the simulation up to 20 times faster.
A hierarchical control algorithm was developed to utilize photovoltaic system advanced inverter volt-VAr functions to provide distribution system voltage regulation and to mitigate 10-minute average voltages outside of ANSI Range A (0.95-1.05 pu). As with any hierarchical control strategy, the success of the control requires a sufficiently fast and reliable communication infrastructure. The communication requirements for voltage regulation were tested by varying the interval at which the controller monitors and dispatches commands and evaluating the effectiveness to mitigate distribution system over-voltages. The control strategy was demonstrated to perform well for communication intervals equal to the 10-minute ANSI metric definition or faster. The communication reliability impacted the controller performance at levels of 99% and below, depending on the communication interval, where an 8-minute communication interval could be unsuccessful with an 80% reliability. The communication delay, up to 20 seconds, was too small to have an impact on the effectiveness of the communication-based hierarchical voltage control.
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves shownonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topology resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Finally, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.
In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carrier recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.
The family of three-dimensional topological insulators opens new avenues to discover novel photophysics and to develop novel types of photodetectors. ZrTe5 has been shown to be a Dirac semimetal possessing unique topological, electronic, and optical properties. Here, we present spatially resolved photocurrent measurements on devices made of nanoplatelets of ZrTe5, demonstrating the photothermoelectric origin of the photoresponse. Because of the high electrical conductivity and good Seebeck coefficient, we obtain noise-equivalent powers as low as 42 pW/Hz1/2, at room temperature for visible light illumination, at zero bias. We also show that these devices suffer from significant ambient reactivity, such as the formation of a Te-rich surface region driven by Zr oxidation as well as severe reactions with the metal contacts. This reactivity results in significant stresses in the devices, leading to unusual geometries that are useful for gaining insight into the photocurrent mechanisms. Our results indicate that both the large photothermoelectric response and reactivity must be considered when designing or interpreting photocurrent measurements in these systems.
Woen, David H.; Chen, Guo P.; Ziller, Joseph W.; Boyle, Timothy; Furche, Filipp; Evans, William J.
The first (N=N)2- complex of a rare-earth metal with an end-on dinitrogen bridge, {K(crypt)}2{[(R2N)3Sc]2[μ-η1:η1-N2]} (crypt = 2.2.2-cryptand, R = SiMe3), has been isolated from the reduction of Sc(NR2)3 under dinitrogen at -35 °C and characterized by X-ray crystallography. The structure differs from the characteristic side-on structures previously observed for over 40 crystallographically characterized rare-earth metal (N=N)2- complexes of formula [A2Ln(THF)x]2[μ- η2:η2-N2] (Ln = Sc, Y, and lanthanides; x = 0, 1; A = anionic ligand such as amide, cyclopentadienide, and aryloxide). The 1.221(3) Å N - N distance and the 1644 cm-1 Raman stretch are consistent with the presence of an (N=N)2- bridge. The observed paramagnetism of the complex by Evans method measurements is consistent with DFT calculations that suggest a triplet (3A2) ground state in D3 symmetry involving two degenerate Sc - N2 - Sc bonding orbitals. Upon brief exposure of the orange Sc3+ bridging dinitrogen complex to UV-light, photolysis to form the monomeric Sc2+ complex, [K(crypt)][Sc(NR2)3], was observed. Conversion of the Sc2+ complex to the Sc3+ dinitrogen complex was not observed with this crypt system, but it did occur with the 18-crown-6 (crown) analog which formed {K(crown)}2{[(R2N)3Sc]2[μ- η1:η1-N2]}. This suggests the importance of the alkali metal chelating agent in the reversibility of dinitrogen binding in this scandium system.
We report atomically detailed molecular dynamics simulations of the permeation of the lethal factor (LF) N-terminal segment through the anthrax channel. The N-terminal chain is unstructured and leads the permeation process for the LF protein. The simulations were conducted in explicit solvent with milestoning theory, making it possible to extract kinetic information from nanosecond to millisecond time scales. We illustrate that the initial event is strongly influenced by the protonation states of the permeating amino acids. While the N-terminal segment passes easily at high protonation state through the anthrax channel (and the φ clamp), the initial permeation represents a critical step, which can be irreversible and establishes a hook in the channel mouth.
We investigate carrier transport in silicon-germanium nanowires with an axial p-n junction doping profile by fabricating these wires into transistors that feature separate top gates over each doping segment. By independently biasing each gate, carrier concentrations in the n- and p-side of the wire can be modulated. For these devices, which were fabricated with nickel source-drain electrical contacts, holes are the dominant charge carrier, with more favorable hole injection occurring on the p-side contact. Channel current exhibits greater sensitivity to the n-side gate, and in the reverse biased source-drain configuration, current is limited by the nickel/n-side Schottky contact.