Publications

Multimodal datasets of materials are rich sources of information which can be leveraged for expedited discovery of process–structure–property relationships and for designing materials with targeted structures and/or properties. For this data descriptor article, we provide a multimodal dataset of magnetron sputter-deposited molybdenum (Mo) thin films, which are used in a variety of industries including high temperature coatings, photovoltaics, and microelectronics. In this dataset we explored a process space consisting of 27 unique combinations of sputter power and Ar deposition pressure. Here, the phase, structure, surface morphology, and composition of the Mo thin films were characterized by x-ray diffraction, scanning electron microscopy, atomic force microscopy, and Rutherford backscattering spectrometry. Physical properties—namely, thickness, film stress and sheet resistance—were also measured to provide additional film characteristics and behaviors. Additionally, nanoindentation was utilized to obtain mechanical load-displacement data. The entire dataset consists of 2072 measurements including scalar values (e.g., film stress values), 2D linescans (e.g., x-ray diffractograms), and 3D imagery (e.g., atomic force microscopy images). An additional 1889 quantities, including film hardness, modulus, electrical resistivity, density, and surface roughness, were derived from the experimental datasets using traditional methods. Minimal analysis and discussion of the results are provided in this data descriptor article to limit the authors’ preconceived interpretations of the data. Overall, the data modalities are consistent with previous reports of refractory metal thin films, ensuring that a high-quality dataset was generated. The entirety of this data is committed to a public repository in the Materials Data Facility.

A cloud of very fast, O(km/s), and very fine, O(µm), particles may be ejected when a strong shock impacts and possibly melts the free surface of a solid metal. To quantify these dynamics, this work develops an ultraviolet, long-working distance, two-pulse Digital Holographic Microscopy (DHM) configuration and is the first to replace film recording with digital sensors for this challenging application. A proposed multi-iteration DHM processing algorithm is demonstrated for automated measures of the sizes, velocities, and three-dimensional positions of non-spherical particles. Ejecta as small as 2 µm diameter are successfully tracked, while uncertainty simulations indicate that particle size distributions are accurately quantified for diameters ≥4 µm. These techniques are demonstrated on three explosively driven experiments. Measured ejecta size and velocity statistics are shown to be consistent with prior film-based recording, while also revealing spatial variations in velocities and 3D positions that have yet to be widely investigated. Having eliminated time-consuming analog film processing, the methodologies proposed here are expected to significantly accelerate future experimental investigation of ejecta physics.

Focused ion beam implantation is ideally suited for placing defect centers in wide bandgap semiconductors with nanometer spatial resolution. However, the fact that only a few percent of implanted defects can be activated to become efficient single photon emitters prevents this powerful capability to reach its full potential in photonic/electronic integration of quantum defects. Here an industry adaptive scalable technique is demonstrated to deterministically create single defects in commercial grade silicon carbide by performing repeated low ion number implantation and in situ photoluminescence evaluation after each round of implantation. An array of 9 single defects in 13 targeted locations is successfully created—a ≈70% yield which is more than an order of magnitude higher than achieved in a typical single pass ion implantation. The remaining emitters exhibit non-classical photon emission statistics corresponding to the existence of at most two emitters. This approach can be further integrated with other advanced techniques such as in situ annealing and cryogenic operations to extend to other material platforms for various quantum information technologies.

Mineral dust can indirectly impact climate by nucleation of atmospheric solids, for example, by heterogeneously nucleating ice in mixed-phase clouds or by impacting the phase of aerosols and clouds through contact nucleation. The effectiveness toward nucleation of individual components of mineral dust requires further study. Here, the nucleation behavior of metal oxide nanoparticle components of atmospheric mineral dust is investigated. A long-working-distance optical trap is used to study contact and immersion nucleation of ammonium sulfate by transition-metal oxides, and an environmental chamber is used to probe depositional ice nucleation on metal oxide particles. Previous theory dictates that ice nucleation and heterogeneous nucleation of atmospheric salts can be impacted by several factors including morphology, lattice match, and surface area. Here, we observe a correlation between the cationic oxidation states of the metal oxide heterogeneous nuclei and their effectiveness in causing nucleation in both contact efflorescence mode and depositional freezing mode. In contrast to the activity of contact efflorescence, the same metal oxide particles did not cause a significant increase in efflorescence relative humidity when immersed in the droplet. These experiments suggest that metal speciation, possibly as a result of cationic charge sites, may play a role in the effectiveness of nucleation that is initiated at particle surfaces.

Lithium dendrite growth hinders the use of lithium metal anodes in commercial batteries. We present a 3D model to study the mechanical and electrochemical mechanisms that drive microscale plating. With this model, we investigate electrochemical response across a lithium protrusion characteristic of rough anode surfaces, representing the separator as a porous polymer in non-conformal contact with a lithium anode. The impact of pressure on separator morphology and electrochemical response is of particular interest, as external pressure can improve cell performance. We explore the relationships between plating propensity, stack pressure, and material properties. External pressure suppresses lithium plating due to interfacial stress and separator pore closure, leading to inhomogeneous plating rates. For moderate pressures, dendrite growth is completely suppressed, as plating will occur in the electrolyte-filled gaps between anode and separator. In fast-charging conditions and systems with low electrolyte diffusivities, the benefits of pressure are overridden by ion transport limitations.

Lithium metal solid-state batteries (LiSSBs) present new challenges in the measurement of material, component, and cell mechanical behaviors and in the measurement and theory of fundamental mechanical-electrochemical (thermodynamics, transport, and kinetics) couplings. Here, we classify the major mechanical and electrochemical-mechanical (ECM) studies underway and provide an overview of major mechanical testing platforms. We emphasize key distinctions among testing platforms, including tip- vs. platen-based sample compression, surface- vs. volume-based analysis, ease of integration with a vacuum or inert atmosphere environment, the ability to control and measure force/displacement over long periods of time, ranges of force and contact area, and others. Among the techniques we review, nanoindentation platforms offer some unique benefits associated with being able to use both tip-based nanoindentation techniques as well as platen-based compression over areas approaching 1 mm2. Sample design is also important: while most efforts are particle-based (i.e., using particles of solid electrolyte and cathode-active materials and densifying them using sintering or pressure), the resulting electrochemical response is from the overall collection of particles present. In contrast, thin-film (<1 μm) solid-state battery materials (e.g., Li, LiPON, LCO) provide well defined and uniform structures well suited for fundamental electrochemical-mechanical studies and offer an important opportunity to drive underlying scientific advances in LiSSB and other areas. We believe there are exciting opportunities to advance the measurement of both mechanical properties and electrochemical-mechanical couplings through the careful and novel co-design of test structures and experimental approaches for LiSSB materials, components, and cells.

Network intrusion detection systems (NIDS) are commonly used to detect malware communications, including command-and-control (C2) traffic from botnets. NIDS performance assessments have been studied for decades, but mathematical modeling has rarely been used to explore NIDS performance. This paper details a mathematical model that describes a NIDS performing packet inspection and its detection of malware's C2 traffic. Here, the paper further describes an emulation testbed and a set of cyber experiments that used the testbed to validate the model. These experiments included a commonly used NIDS (Snort) and traffic with contents from a pervasive malware (Emotet). Results are presented for two scenarios: a nominal scenario and a “stressed” scenario in which the NIDS cannot process all incoming packets. Model and experiment results match well, with model estimates mostly falling within 95 % confidence intervals on the experiment means. Model results were produced 70-3000 times faster than the experimental results. Consequently, the model's predictive capability could potentially be used to support decisions about NIDS configuration and effectiveness that require high confidence results, quantification of uncertainty, and exploration of large parameter spaces. Furthermore, the experiments provide an example for how emulation testbeds can be used to validate cyber models that include stochastic variability.

An analogy is drawn between the study of human behavior and the study of plutonium to demonstrate that soft and hard sciences are more similar than different, making the distinction moot and unproductive. The studies of human behavior and plutonium follow a common scientific research cycle that aligns with Thomas Kuhn’s views of scientific change. This common research cycle provides evidence that the thought processes and methodologies required for success are congruent in the soft and hard sciences. The primary implication from this analogy is that scientists in all disciplines should eradicate the distinction between soft and hard sciences. Focusing on similarities rather than differences among researchers from different disciplines is necessary to enhance collective intelligence and the type of transdisciplinary collaboration required to tackle difficult sociotechnical problems.

Room temperature operation of terahertz quantum cascade lasers (THz QCLs) has been a long-pursued goal to realize compact semiconductor THz sources. In this paper, we report on improving the maximum operating temperature of THz QCLs to ∼261 K as a step toward the realization of this goal.

Herein, we report the synthesis of a novel, tetraphenylethylene-based ligand for metal-organic frameworks (MOFs). Incorporation of this ligand into a Zn- or Eu-based MOF increased the quantum yield (QY) by almost 2.5× compared to the linker alone. Furthermore, the choice of guest solvent impacted the QY and solvatochromatic response. These shifts are consistent with solvent dielectric constant as well as molecular polarizability.

The resurgence of interest in hydrogen-related technologies has stimulated new studies aimed at advancing lesser-developed water-splitting processes, such as solar thermochemical hydrogen production (STCH). Progress in STCH has been largely hindered by a lack of new materials able to efficiently split water at a rate comparable to ceria under identical experimental conditions. BaCe0.25Mn0.75O3 (BCM) recently demonstrated enhanced hydrogen production over ceria and has the potential to further our understanding of two-step thermochemical cycles. A significant feature of the 12R hexagonal perovskite structure of BCM is the tendency to, in part, form a 6H polytype at high temperatures and reducing environments (i.e., during the first step of the thermochemical cycle), which may serve to mitigate degradation of the complex oxide. An analogous compound, namely BaNb0.25Mn0.75O3 (BNM) with a 12R structure was synthesized and displays nearly complete conversion to the 6H structure under identical reaction conditions as BCM. The structure of the BNM-6H polytype was determined from Rietveld refinement of synchrotron powder X-ray diffraction data and is presented within the context of the previously established BCM-6H structure.

Strong and ultrastrong coupling between intersubband transitions in quantum wells and cavity photons have been realized in mid-infrared and terahertz spectral regions. However, most previous works employed a large number of quantum wells on rigid substrates to achieve coupling strengths reaching the strong or ultrastrong coupling regime. In this work, we experimentally demonstrate ultrastrong coupling between the intersubband transition in a single quantum well and the resonant mode of photonic nanocavity at room temperature. We also observe strong coupling between the nanocavity resonance and the second-order intersubband transition in a single quantum well. Furthermore, we implement for the first time such intersubband cavity polariton systems on soft and flexible substrates and demonstrate that bending of the single quantum well does not significantly affect the characteristics of the cavity polaritons. This work paves the way to broaden the range of potential applications of intersubband cavity polaritons including soft and wearable photonics.

Engineering the transition metal dichalcogenide (TMD)-metal interface is critical for the development of two-dimensional semiconductor devices. By directly probing the electronic structures of WS2-Au and WSe2-Au interfaces with high spatial resolution, we delineate nanoscale heterogeneities in the composite systems that give rise to local Schottky barrier height modulations. Photoelectron spectroscopy reveals large variations (>100 meV) in TMD work function and binding energies for the occupied electronic states. Characterization of the composite systems with electron backscatter diffraction and scanning tunneling microscopy leads us to attribute these heterogeneities to differing crystallite orientations in the Au contact, suggesting an inherent role of the metal microstructure in contact formation. We then leverage our understanding to develop straightforward Au processing techniques to form TMD-Au interfaces with reduced heterogeneity. Our findings illustrate the sensitivity of TMDs’ electronic properties to metal contact microstructure and the viability of tuning the interface through contact engineering.

The magnetization patterns on three atomic layers thick islands of Co on Ru(0001) are studied by spin-polarized low-energy electron microscopy (SPLEEM). In-plane magnetized micrometer wide triangular Co islands are grown on Ru(0001). They present two different orientations correlated with two different stacking sequences which differ only in the last layer position. The stacking sequence determines the type of magnetization pattern observed: the hcp islands present very wide domain walls, while the fcc islands present domains separated by much narrower domain walls. The former is an extremely low in-plane anisotropy system. We estimate the in-plane magnetic anisotropy of the fcc regions to be 1.96 × 104 J m−3 and of the hcp ones to be 2.5 × 102 J m−3

Approximation algorithms for computationally complex problems are of significant importance in computing as they provide computational guarantees of obtaining practically useful results for otherwise computationally intractable problems. The demonstration of implementing formal approximation algorithms on spiking neuromorphic hardware is a critical step in establishing that neuromorphic computing can offer cost-effective solutions to significant optimization problems while retaining important computational guarantees on the quality of solutions. Here, we demonstrate that the Loihi platform is capable of effectively implementing the Goemans-Williamson (GW) approximation algorithm for MAXCUT, an NP-hard problem that has applications ranging from VLSI design to network analysis. We show that a Loihi implementation of the approximation step of the GW algorithm obtains equivalent maximum cuts of graphs as conventional algorithms, and we describe how different aspects of architecture precision impacts the algorithm performance.

Mixture formation in a hydrogen-fueled heavy-duty engine with direct injection and a nearly-quiescent top-hat combustion chamber was investigated using laser-induced fluorescence imaging, with 1,4-difluorobenzene serving as a fluorescent tracer seeded into hydrogen. The engine was motored at 1200 rpm, 1.0 bar intake pressure, and 335 K intake temperature. An outward opening medium-pressure hollow-cone injector was operated at two different injection pressures and five different injection timings from early injection during the intake stroke to late injection towards the end of compression stroke. Fuel fumigation upstream of the intake provided a well-mixed reference case for image calibration. This paper presents the evolution of in-cylinder equivalence ratio distribution evaluated during the injection event itself for the cylinder-axis plane and during the compression stroke at different positions of the light sheet within the swirl plane. During the injection event, the originally annular jet collapses onto the jet axis within 1°CA after jet emergence and within 10 mm downstream of the nozzle. Multiple shock cells are visible - their size decreases with decreasing pressure ratio. The results of the equivalence ratio distribution show high cyclic variability of mixing for all injection timings during the compression stroke, but only minor variability with early injection during the intake stroke. The ensemble-mean fuel distribution shows that fuel-rich zones shift from the intake side to the exhaust side of the combustion chamber as the injection is advanced. Probability density functions of global equivalence ratio and equivalence ratio at potential spark locations suggest that retarded fuel injection might significantly increase NO emissions and the cyclic variability of early flame kernel development.

Liquefied Petroleum Gas (LPG), as a common alternative fuel for internal combustion engines is currently widespread in use for fleet vehicles. However, a current majority of the LPG-fueled engines, uses port-fuel injection that offers lower power density when compared to a gasoline engine of equivalent displacement volume. This is due to the lower molecular weight and higher volatility of LPG components that displaces more air in the intake charge due to the larger volume occupied by the gaseous fuel. LPG direct-injection during the closed-valve portion of the cycle can avoid displacement of intake air and can thereby help achieve comparable gasoline-engine power densities. However, under certain engine operating conditions, direct-injection sprays can collapse and lead to sub-optimal fuel-air mixing, wall-wetting, incomplete combustion, and increased pollutant emissions. Direct-injection LPG, owing to its thermo-physical properties is more prone to spray collapse than gasoline sprays. However, the impact of spray collapse for high-volatility LPG on mixture preparation and subsequent combustion is not fully understood. To this end, direct-injection, laser-spark ignition experiments using propane as a surrogate for LPG under lean and stoichiometric engine operating conditions were carried out in an optically accessible, single cylinder, heavy-duty, diesel engine. A quick-switching parallel propane and iso-octane fuel system allows for easy comparison between the two fuels. Fuel temperature, operating equivalence ratio and injection timing are varied for a parametric study. In addition to combustion characterization using conventional cylinder pressure measurements, optical diagnostics are employed. These include infrared (IR) imaging for quantifying fuel-air mixture homogeneity and high-speed natural luminosity imaging for tracking the spatial and temporal progression of combustion. Imaging of infrared emission from compression-heated fuel does not reveal any significant differences in the signal distribution between collapsing and non-collapsing sprays at the spark timing. Irrespective of coolant temperatures, early injection timing resulted in a homogeneous mixture that lead to repeatable flame evolution with minimal cycle-to-cycle variability for both LPG and iso-octane. However, late injection timing resulted in mixture inhomogeneity and non-isotropic turbulence distribution. Under lean operation with late injection timing, LPG combustion is shown to benefit from a more favorable mixture distribution and flow properties induced by spray collapse. On the other hand, identical operating conditions proved to be detrimental for iso-octane combustion most likely caused by distribution of lean mixtures near the spark location that negatively impact initial flame kernel growth leading to increased cycle-to-cycle variability.

Coordinate transformations are a fundamental operation that must be performed by any animal relying upon sensory information to interact with the external world. We present a neural network model that performs a coordinate transformation from the dragonfly eye's frame of reference to the body's frame of reference while hunting. We demonstrate that the model successfully calculates turns required for interception, and discuss how future work will compare our model with biological dragonfly neural circuitry and guide neural-inspired neuromorphic implementations of coordinate transformations.

Shunting inhibition is a potential mechanism by which biological systems multiply two time-varying signals, most recently proposed in single neurons of the fly visual system. Our work demonstrates this effect in a biological neuron model and the equivalent circuit in neuromorphic hardware modeling dendrites. We present a multi-compartment neuromorphic dendritic model that produces a multiplication-like effect using the shunting inhibition mechanism by varying leakage along the dendritic cable. Dendritic computation in neuromorphic architectures has the potential to increase complexity in single neurons and reduce the energy footprint for neural networks by enabling computation in the interconnect.

Coordinate transformations are a fundamental operation that must be performed by any animal relying upon sensory information to interact with the external world. We present a neural network model that performs a coordinate transformation from the dragonfly eye's frame of reference to the body's frame of reference while hunting. We demonstrate that the model successfully calculates turns required for interception, and discuss how future work will compare our model with biological dragonfly neural circuitry and guide neural-inspired neuromorphic implementations of coordinate transformations.

Oscillatory devices have gained significant interest recently as key components of computing systems based on biomimetic neuronal spiking. An understanding of the time scales underlying the spiking is essential for engineering fast, controllable, low energy devices. However, we find that the intrinsic dynamics of these devices are difficult to properly characterize, as they can be heavily influenced by the external circuitry used to measure them. Here we demonstrate these challenges using a VO₂ Mott oscillator with a sub-100 nm effective size, achieved using a nanogap cut in a metallic carbon nanotube electrode. Given the nanoscale thermal volume of this device, it would be expected to exhibit rapid oscillations. However, due to external parasitics present within commonly used current sources, we see orders of magnitude slower dynamics. Here, we outline methods for determining when measurements are dominated by extrinsic factors and discuss the operating conditions under which intrinsic oscillation frequencies may be observed.

Rare-earth terephthalic acid (BDC)-based metal-organic frameworks (MOFs) are promising candidate materials for acid gas separation and adsorption from flue gas streams. However, previous simulations have shown that acid gases (H2O, NO2, and SO2) react with the hydroxyl on the BDC linkers to form protonated acid gases as a potential degradation mechanism. Herein, gas-phase computational approaches were used to identify the formation energies of these secondary protonated acid gases across multiple BDC linker molecules. Formation energies for secondary protonated acid gases were evaluated using both density functional theory (DFT) and correlated wave function methods for varying BDC-gas reaction mechanisms. Upon validation of DFT to reproduce wave function calculation results, rotated conformational linkers and chemically functionalized BDC linkers with −OH, −NH2, and −SH were investigated. The calculations show that the rotational conformation affects the molecule stability. Double-functionalized BDC linkers, where two functional groups are substituted onto BDC, showed varied reaction energies depending on whether the functional groups donate or withdraw electrons from the aromatic system. Based on these results, BDC linker design must balance adsorption performance with degradation via linker dehydrogenation for the design of stable MOFs for acid gas separations.

Chalcogenide thin films that undergo reversible phase changes show promise for use in next-generation nanophotonics, microelectronics, and other emerging technologies. One of the many studied compounds, Ge ₂ Sb ₂ Te ₅ , has demonstrated several useful properties and performance characteristics. However, the efficacy of benchmark Ge ₂ Sb ₂ Te ₅ is restricted by amorphous phase thermal stability below ∼150 °C, limiting its potential use in high-temperature applications. In response, previous studies have added a fourth species (e.g., C) to sputter-deposited Ge ₂ Sb ₂ Te ₅ , demonstrating improved thermal stability. Our current research confirms reported thermal stability enhancements and assesses the effects of carbon on crystalline phase radiation response. Through in situ transmission electron microscope irradiation studies, we examine the effect of C addition on the amorphization behavior of initially cubic and trigonal polycrystalline films irradiated using 2.8 MeV Au to various doses up to 1 × 10 ¹⁵  cm ⁻² . It was found that increased C content reduces radiation tolerance of both cubic and trigonal phases.

Discharge of sodium coolant into containment from a sodium-cooled fast reactor vessel can occur in the event of a pipe leak or break. In this situation, some of the liquid sodium droplets discharged from the coolant system will react with oxygen in the air before reaching the containment. This phase of the event is normally termed the sodium spray fire phase. Unreacted sodium droplets pool on the containment floor where continued reaction with containment atmospheric oxygen occurs. This phase of the event is normally termed the sodium pool fire phase. Both phases of these sodium-oxygen reactions (or fires) are important to model because of the heat addition and aerosol generation that occur. Any fission products trapped in the sodium coolant may also be released during this progression of events, which if released from containment could pose a health risk to workers and the public. The paper describes progress of an international collaborative research in the area of the sodium fire modeling in the sodium-cooled fast reactors between the United States and Japan under the framework of the Civil Nuclear Energy Research and Development Working Group. In this collaboration between Sandia National Laboratories and Japan Atomic Energy Agency, the validation basis for and modeling capabilities of sodium spray and pool fires in MELCOR of Sandia National Laboratories and SPHINCS of Japan Atomic Energy Agency are being enhanced. Here this study documents MELCOR and SPHINCS sodium pool fire model validation exercises against the JAEA’s sodium pool fire experiments, F7-1 and F7-2. The proposed enhancement of the sodium pool fire models in MELCOR through addition of thermal hydraulic and sodium spreading models that enable a better representation of experimental results is also described.

As atomic layer deposition (ALD) emerges as a method to fabricate architectures with atomic precision, emphasis is placed on understanding surface reactions and nucleation mechanisms. ALD of titanium dioxide with TiCl4 and water has been used to investigate deposition processes in general, but the effect of surface termination on the initial TiO2 nucleation lacks needed mechanistic insights. This work examines the adsorption of TiCl4 on Cl−, H−, and HO− terminated Si(100) and Si(111) surfaces to elucidate the general role of different surface structures and defect types in manipulating surface reactivity of growth and non-growth substrates. The surface sites and their role in the initial stages of deposition are examined by X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). Density functional theory (DFT) computations of the local functionalized silicon surfaces suggest oxygen-containing defects are primary drivers of selectivity loss on these surfaces.