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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mechanisms of Three-Dimensional Solid-Phase Epitaxial Crystallization of Strontium Titanate

Strontium titanate (SrTiO 3 , STO) is a complex metal oxide with a cubic perovskite crystal structure. Due to its easily described and understood crystal structure in the cubic phase, STO is an ideal model system for exploring the mechanistic details of solid-phase epitaxy (SPE) in complex oxides. SPE is a crystallization approach that aims to guide crystal growth at low homologous temperatures to achieve targeted microstructures. Beyond planar thin films, SPE can also exploit the addition of a chemically inert, noncrystallizing, amorphous obstacle in the path of crystallization to generate complex three-dimensional structures. The introduction of this mask fundamentally alters the SPE process, inducing a transition from two- to three-dimensional geometries and from vertical to lateral crystal growth under the influence of the crystal/mask/amorphous boundary. Using a combination of molecular dynamics simulations and experiments, we identify several unique phenomena in the nanoscale growth behaviors in both conventional (unmasked) and masked SPE. Examining conventional SPE of STO, we find that crystallization at the interface is strongly correlated to, and potentially driven by, density fluctuations in the region of the amorphous STO near the crystalline/amorphous interface with a strong facet dependence. In the masked case, we find that the crystalline growth front becomes nonplanar near contact with the mask. We also observe a minimum vertical growth requirement prior to lateral crystallization. Both phenomena depend on the relative bulk and interfacial free energies of the three-phase (crystal/mask/amorphous) system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Proactively Addressing Employee Well-Being to Foster Workplace Safety in a U.S. National Laboratory

The daily conduct of high-risk, high-consequence work, by its very nature, can be mentally demanding. Research demonstrates that failure to manage or mitigate these demands can degrade psychological well-being and mental health. Degradations in employee well-being impact individual performance, jeopardizing safety and mission success in the workplace. This Commentary describes efforts taken at Sandia National Laboratories over the past eight years to evaluate, understand, learn from, and mitigate factors such as stress, burnout, work-life imbalances, and disengagement in the workplace that can degrade employee well-being. After evaluating these four facets of employee well-being, Sandia National Laboratories initiated several programs to address observations and outcomes, including the Thrive program, the Take 10 Initiative, work-life balance resources, employee resource groups such as the Sandia Parents Group, and Workplace Improvement Networks. Collectively, the intent of these programs is to ensure employee mental readiness to conduct hazardous high-risk work effectively and safely. Preliminary data suggest that these programs are succeeding. In conclusion, other national laboratories and organizations, regardless of size, may wish to apply similar approaches to improve employee well-being and thereby increase the likelihood of mission success.

Absorption↗
DOE OSTI2020

Surface Passivation by Excess Sulfur for Controlled Synthesis of Large, Thin SnS Flakes

Tin sulfide (SnS) is part of the group IV chalcogenides (SnX, GeX; X: S, Se), a family of anisotropic layered materials considered for thin film photovoltaics, optoelectronics, and valleytronics, and predicted narrow bandgap multiferroic materials. Large ultrathin SnS flakes, suitable for a variety of applications, are challenging to synthesize because of the enhanced surface reactivity due to the open layer structure of SnS which gives rise to a competition between lateral and vertical growth. Here we investigate the effects of added sulfur on passivating the surface and modifying the balance between lateral expansion and thickening of SnS flakes in chemical vapor transport from a SnS precursor. In addition, we investigate the growth of SnS flakes and compare the results of synthesis from a pure SnS precursor with growth, in which a slight excess of sulfur is supplied in different ways. Our results demonstrate that small amounts of excess sulfur can profoundly affect the size and thickness distributions of SnS flakes. The largest and thinnest flakes are obtained if (i) traces of sulfur are added and (ii) the sulfur source consists either of small Sx fragments released at high temperatures from the reactor walls, or atomic S supplied by sublimation from SnS 2 . The likely mechanism for the observed growth modifications is a transient surface passivation of SnS flakes during growth, which reduces the reactivity of the top facet of the flakes, limits vertical growth, and thus gives rise to ensembles with increased lateral size and reduced thickness.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Origin of Phase Separation in Ni-Rich Layered Oxide Cathode Materials During Electrochemical Cycling

In intercalation materials, the kinetics and uniformity of mass transport across the nanocrystalline domains dictate the structural reversibility and transport capability at the macroscopic level. (De)intercalation-induced interlayer disintegrations exhibit anisotropic crystallite size change. Due to the anisotropic mass transport mechanism, separated phases are inherently crystallographically oriented. One such material is LiNi $1–x–y$ Mn $x$ Co $y$ O 2 , which plays a pivotal role in advanced Li-ion batteries but suffers from severe phase inhomogeneities under fast charge or electrochemical aging. Here, using operando synchrotron techniques, we probe the mechanistic origins of the compositional and orientational-dependent phase separations during the electrochemical cycling of LiNi 0.8 Mn 0.1 Co 0.1 O 2 by comprehensive analysis of both in-plane and out-of-plane reflections. In the H2/H3 phase regime, in-plane domain propagation occurs due to increased covalency despite the severe decay of interlayer crystallographic order, resulting in the change of crystalline domain shape from 3D spheres to two-dimensional nanosheets. The crystallographically selective XRD line splitting is linked to the geometry of the facets as mass transfers along the ab plane. In conclusion, this work provides mechanistic insights into crystallographic orientation-dependent phase inhomogeneity under fast charge and extended cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Self-Patterning Tetrathiafulvalene Crystalline Films

Tetrathiafulvalene (TTF) crystals grown from the melt are organized as spherulites in which helicoidal fibrils growing radially from the nucleation center twist in concert with one another. Alternating bright and dark concentric bands are apparent when films are viewed between crossed polarizers, indicating an alternating pattern of crystallographic faces exposed at the film surface. Band-dependent reorganization of the TTF crystals was observed during exposure to methanol vapor. Crystalline growth appears on bright bands at the expense of the dark bands. After a 24 h period of exposure to methanol vapor, the original spherulites were completely restructured, and the films comprise isolated, concentric circles of crystallites whose orientations are determined by the initial TTF crystal fibril orientation. While the surface of these outgrowths appears faceted and smooth, cross-sectional SEM images revealed a semiporous inner structure, suggesting solvent-vapor-induced recrystallization. Collectively, these results show that crystal twisting can be used to rhythmically redistribute material. Crystal twisting is a common and often controllable phenomenon independent of molecular or crystal structure and therefore offers a generalizable path to spontaneous pattern formation in a wide range of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surface Manipulation on Pt 2.2 Ni(111) Nanocatalysts for Boosting Their ORR Performance in Alkaline Media

We have previously shown that Pt–Ni alloy nano-octahedra with {111} facets exhibit outstanding electrochemical performance in the oxygen reduction reaction (ORR) in acidic media when their surfaces are finely tailored at the atomic level. Here, in this investigation, we further refine the surface structure of Pt 2.2 Ni octahedral nanocatalysts to improve ORR performance in a 0.1 M KOH solution using diverse surface manipulation techniques. Through systematic analysis using electrochemical CO stripping, cyclic voltammetry, and X-ray photoelectron spectroscopy, we examined the surfaces of Pt 2.2 Ni octahedral nanocatalysts pretreated with various methods, including etching in acetic acid or perchloric acid, and subsequent electrochemical activation in an alkaline solution or an acidic solution. Among these treatments, those involving acidic media, particularly electrochemical cycling in acidic electrolytes, demonstrated significantly enhanced ORR activity in 0.1 M KOH. The latter exhibited a mass activity of 2.95 A/mg pt and a specific activity of 8.71 mA/cm 2 at 0.90 V, surpassing state-of-the-art Pt/C by 12-fold and 34-fold, respectively. Furthermore, this identified nanocatalyst displayed robust stability, with negligible activity decay observed after 10,000 cycles. This study suggests that the improved ORR activity can be attributed to the Pt-rich surfaces with well-preserved {111} lattices on the surface-modified Pt–Ni nano-octahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlling the Ru Island Decoration on Ni Nanoparticles to Tune the Activity for 5-Hydroxylmethylfurfural (HMF) Oxidation

Controlling the island decoration on metal nanoparticle supports is a major opportunity for improving the catalytic activity and an attractive synthetic challenge. The structure of the decorating metal determines how it interacts with the metal support and how it effectively catalyzes the reactants and the intermediates. In this work, we demonstrate that a slow-growth method maximizes the formation of Ru islands on faceted, branched Ni nanoparticles, thereby controlling the number of Ru–Ni atomic interactions and improving the catalytic activity. The Ru islands on branched Ni nanoparticles with the highest loading of Ru (9%) exhibited the highest activity for the electro-oxidation of biomass-derived 5-hydroxymethylfurfural (HMF). In conclusion, these results demonstrate the ability to synthetically control the second metal decoration to tune metal–support interactions, thereby enhancing the catalytic activity.

5-hydroxymethylfurfural↗
DOE OSTI2025

Expanding Configurational Complexity through Dipole Dilution in Pseudohalide Argyrodite Ion Conductors

The advantageous properties of (pseudo)halide argyrodite ion conductors of the formula Li 6 PS 5 X (X = Cl – , Br – , I – , CN – ) have motivated extensive studies of their structure-transport relationships, particularly as they pertain to the role of atomic site disorder. The argyrodite structure can accommodate additional configurational complexity to promote ion transport via extended three-anion site mixing and the potential for orientational disorder of molecular anions. In this work, we explore a ternary anion system including the cyanide anion, expanding site disorder and introducing dipolar orientations as an additional degree of freedom. We prepared the series Li 6 PS 5 (CN) 1–x Br x , in which the dipolar cyanide anions are systematically diluted with bromide. We find that anion disorder, as determined by synchrotron and neutron diffraction and quantified by configurational entropy (S config ), is correlated with lowered activation barriers and increased lithium ion conductivity. We propose that S config describes the electrostatic heterogeneity of the Li environments, flattening the energetic landscape for ion transport. While anion substitution strongly impacts the activation barrier for transport, the temperature-independent Arrhenius prefactor does not follow the same trend. Through heat-capacity measurements of attempt frequency and deconvolution of terms within the prefactor, we rationalize the apparent decoupling of activation energy and prefactor to strong cyanide-lithium interactions that increase the entropy of migration. Together, these results expand the structure–property relationships in the argyrodite family to encompass multiple facets of disorder and the subsequent impact on lithium ion transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Structurally Frustrated Remeika Phases: Tolerance Factor and Non-Kramers’ Ion Effects

Quantum materials that are found on the verge of structural, magnetic, and electronic instabilities are deep reservoirs for exotic phenomena. Our criteria to study the reported Ln 5 Ru 6 Sn 18 (Ln = Gd, Tb) are guided by the tolerance factor for Remeika phases─a class of intermetallic compounds with the general formula A 3 M 4 X 13 (where A = rare-earth element, M = transition metal, and X = tetrel), which can be viewed as structural analogues of pseudoperovskites (4 × ABX 3 ), with one of the tetrel atoms occupying the A-site. We have grown single crystals, up to 0.5 cm on the largest facet, of Gd 5 Ru 6 Sn 18 (a = 13.8052(12) Å) and Tb 5 Ru 6 Sn 18 (a = 13.7825(9) Å), which we expect to be on the verge of a formation instability. Bulk magnetic, heat capacity, and electrical transport measurements reveal unusual behavior that originates from the trivalent Gd and Tb ions, with deviations from typical metallic behavior and magnetic ordering that is short-range or disrupted in some other way. Furthermore, to better understand these phenomena, single-crystal neutron diffraction is investigated, which reveals short-range correlations among the partially occupied Tb and Sn sublattices, with 3D-ΔPDF analysis supporting direction-dependent local order. Taken together, these measurements show the utility of using tolerance factors in identifying materials that are likely to exhibit complex phenomena and uncover environments where a formation instability may strongly impact emergent bulk magnetic and electronic phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Descriptor-Based Analysis of Atomic Layer Deposition Mechanisms on Spinel LiMn 2 O 4 Lithium-Ion Battery Cathodes

Protective coatings have been shown to effectively suppress Mn ion dissolution from the spinel LiMn 2 O 4 lithium-ion battery cathode by stabilizing the surface against undesired side reactions with the electrolyte. In spite of extensive study, however, there remains a lack of atomic-scale understanding of how such coatings are deposited, and no molecular-level descriptor to predict trends in deposition mechanisms has been identified. We have recently shown that Al 2 O 3 coatings grown by atomic layer deposition (ALD) with alternating trimethylaluminum (TMA) and water exposures exhibit submonolayer growth because of precursor decomposition on the lithium manganate spinel (LMO) surface during early ALD pulses. In the present work, we elucidate the underlying mechanisms of this Al 2 O 3 ALD process using density functional theory (DFT) calculations and X-ray photoelectron spectroscopy (XPS) experiments, and we introduce a generalized descriptor-based framework to understand the resulting trends across a spectrum of surface structures and functionalities. We demonstrate that all decomposition products, including CH 3 -aluminum adducts and dissociated CH 3 groups, are Lewis bases and are coordinated to oxygen atoms on the LMO surface, leading to charge transfer to Lewis acidic Mn 3d states. Inert-transfer XPS supports these theoretical predictions, showing an increase in near-surface Mn 3+ content following TMA exposure and shifts in C is spectra consistent with C-O bond formation. We extend the DFT studies to various low- and high-index LMO surface facets, as a proxy for tuning the Lewis acid-base interactions between surface-bound CH 3 * and near-surface Mn ions. The thermochemistry for TMA reactions on these chemically distinct LMO surfaces demonstrates that ALD is structure-sensitive and that there is higher reactivity for TMA decomposition and Al 2 O 3 nucleation near LMO steps and defects. Motivated by the Lewis basic character of the decomposition products, we introduce the oxygen vacancy formation energy as a descriptor for decomposition energetics, and we demonstrate that all energetics are correlated to this quantity through the number of electrons that are transferred along the reaction coordinate. Finally, based on these findings, we hypothesize that improved electrochemical cycling with only 1-2 ALD cycles may be due to selective passivation of defect sites on the LMO surface that are more susceptible to Mn dissolution, and we suggest that similar descriptor-based analyses could be useful for the study of other ALD coatings on oxide substrates.

25 ENERGY STORAGE↗
DOE OSTI2024

Data Generation for Machine Learning Interatomic Potentials and Beyond

The field of data-driven chemistry is undergoing an evolution, driven by innovations in machine learning models for predicting molecular properties and behavior. Recent strides in ML-based interatomic potentials have paved the way for accurate modeling of diverse chemical and structural properties at the atomic level. The key determinant defining MLIP reliability remains the quality of the training data. A paramount challenge lies in constructing training sets that capture specific domains in the vast chemical and structural space. This Review navigates the intricate landscape of essential components and integrity of training data that ensure the extensibility and transferability of the resulting models. We delve into the details of active learning, discussing its various facets and implementations. We outline different types of uncertainty quantification applied to atomistic data acquisition and the correlations between estimated uncertainty and true error. The role of atomistic data samplers in generating diverse and informative structures is highlighted. Furthermore, we discuss data acquisition via modified and surrogate potential energy surfaces as an innovative approach to diversify training data. The Review also provides a list of publicly available data sets that cover essential domains of chemical space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation

The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. Here, this review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies.

Materials science↗
DOE OSTI2025

Single Crystals of Vanadium Oxides as a Lens for Understanding Structural and Electronic Phase Transformations, Ion Transport, Chemo-Mechanical Coupling, and Electrothermal Neuronal Emulation

Vanadium oxides cystallize in a diverse array of structures and compositions arising from the redox versatility of vanadium, variable covalency of V−O bonds, and myriad coordination geometries. Their open frameworks present abundant interstitial sites that enable insertion of guest-ions. In such compounds, V3d electron and spin localization and disorder couple strongly to structural preferences. The rich structural diversity manifests as a “rugged” free energy landscape with multiple interconvertible polymorphs. Such a landscape sets up structural, electronic, and magnetic transitions that underpin the promise of these materials as ion-insertion battery electrodes; compact primitives for brain-inspired computing, and heterogeneous catalysts. Here, we examine the structural and compositional diversity, electronic instabilities, defect dynamics, structure transformations, mechanical properties, and surface structure of vanadium oxides using single crystals as a distinctive lens. Single crystals enable the measurement of structure−function correlations without the ensemble and orientational averaging inevitable in polycrystalline materials. Their well-defined surfaces further enable examination of facet-dependent reactivity toward molecular adsorbates, ion fluxes, and lattice (mis)matched solids. We provide a comprehensive account of vanadium-oxide single-crystal studies, from delineation of common structural motifs to single-crystal growth techniques, topochemical modification strategies, mechanisms underpinning electronic instabilities, and implementation as electrothermal neurons and battery electrode materials.

Ponis, John [Texas A&M University, College Station↗
DOE OSTI2025

Cross-Scale Catalyst Modeling Applied to H 2 Storage and Release via Formic Acid

Here, we propose the Systems-to-Atoms (S2A) modeling framework that integrates the kinetics of reaction chemistry and structural configurations across various length scales with the aim of establishing a versatile template for multiscale modeling of reactive flow problems and to predict the operando activity of catalyst materials. The approach encompasses a microkinetic model to analyze surface reactions on individual facets of catalyst nanoparticles coupled with the computation of average surface reaction rates for catalyst nanoparticles of specific size distributions. Macro-homogeneous surface reaction kinetics are derived as a function of catalyst loading and used as input parameters for the continuum-scale reactor model. The cross-scale framework enables the optimization of catalyst utilization through reactor design and operating strategy. To demonstrate the framework, we studied the storage and release of hydrogen from formic acid, a promising liquid organic hydrogen carrier (LOHC), over Pd, Pt, and Cu catalysts. The framework predicts observed trends in formic acid dehydrogenation activity for catalysts with comparable weight loadings and metal particle diameters, demonstrating satisfactory quantitative alignment. Finally, the seamless transmission of parameter uncertainties between scales is also discussed.

08 HYDROGEN↗
DOE OSTI2026

Shining Light on Halide Perovskites: Teaching Analytical Chemistry Using Flexible, Inquiry-Based Experiments

Two-dimensional (2D) metal halide perovskites are promising next generation semiconducting materials at the forefront of research in solar cells, LEDs, and other devices. Here, we report on an undergraduate intermediate analytical chemistry laboratory experience where students were taught fundamental chemistry concepts, including solubility, complexation, spectroscopy, and microscopy, through the introduction and study of 2D halide perovskite materials. Students explore multiple facets of perovskite synthesis, structure, and properties through a modular set of experiments that students used to form a holistic picture of this material. Importantly, this inquiry-based lab supports students through a guided research process, and students report high interest and learning gains from an end of the semester survey. We further discuss ways to adapt this lab to course, student, equipment, and budget needs. Overall, this laboratory experience teaches and applies the fundamental concepts and tools of analytical chemistry to the contemporary materials research field.

Analytical Chemistry↗
DOE OSTI2022

Exploring Structure-Sensitive Relations for Small Species Adsorption Using Machine Learning

Accurate prediction of adsorption energies on heterogeneous catalyst surfaces is crucial to predicting reactivity and screening materials. Adsorption linear scaling relations have been developed extensively but often lack accuracy and apply to one adsorbate and a single binding site type at a time. These facts undermine their ability to predict structure sensitivity and optimal catalyst structure. Using machine learning on nearly 300 density functional theory calculations, we demonstrate that generalized coordination number scaling relations hold well for oxygen- and high-valency carbon-binding species but fail for others. Here we reveal that the valency and the electronic coupling of a species with the surface, along with the site type and its coordination environment, are critical for small species adsorption. The model simultaneously predicts the adsorption energy and preferred site and significantly outperforms linear scalings in accuracy. It can expose the structure sensitivity of chemical reactions and enable enhanced catalyst activity via engineering particle shape and facet defects. The generality of our methodology is validated by training the model with transition metal data and transferring it to predict adsorption energies on single-atom alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Pynta-An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics

Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. Here, we present Pynta, a workflow software for automating the calculation of surface and gas–surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗