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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Machine learning enabled discovery of application dependent design principles for two-dimensional materials

Abstract The unique electronic and mechanical properties of two-dimensional (2D) materials make them promising next-generation candidates for a variety of applications. Large-scale searches for high-performing 2D materials are limited to calculating descriptors with computationally demanding first-principles density functional theory. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity and train an ensemble of models to predict thermodynamic, mechanical and electronic properties. We carry out a screening of nearly 45,000 structures for two separate applications: mechanical strength and photovoltaics. By collecting statistics of the screened candidates, we investigate structural and compositional design principles that impact the properties of the structures surveyed. Our approach recovers some well-accepted design rules: hybrid organic-inorganic perovskites with lead and tin tend to be good candidates for solar cell applications and titanium based MXenes usually have high stiffness coefficients. Interestingly, other members of the group 4 elements also contribute to increasing the mechanical strength of MXenes. For all-inorganic perovskites, we discover some compositions that have not been deeply studied in the field of photovoltaics and thus open up paths for further investigation. We open-source the code-base to spur further development in this space.

Venturi, Victor (ORCID:0000000156727549)↗
DOE OSTI2024

3D‐Mapping and Manipulation of Photocurrent in an Optoelectronic Diamond Device

Abstract Establishing connections between material impurities and charge transport properties in emerging electronic and quantum materials, such as wide‐bandgap semiconductors, demands new diagnostic methods tailored to these unique systems. Many such materials host optically‐active defect centers which offer a powerful in situ characterization system, but one that typically relies on the weak spin‐electric field coupling to measure electronic phenomena. In this work, charge‐state sensitive optical microscopy is combined with photoelectric detection of an array of nitrogen‐vacancy (NV) centers to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. Optical control is used to change the charge state of background impurities inside the diamond on‐demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. Conducting channels that control carrier flow, key steps toward optically reconfigurable, wide‐bandgap optoelectronics are then engineered using light. This work might be extended to probe other wide‐bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic and quantum technologies.

Wood, Alexander A.↗
DOE OSTI2025

Machine Learning Enabled Advanced Electron Tomography for Resolving Chemical Inhomogeneity and Materials Dynamics in Lithium-Ion Battery Electrodes

The objective of this project is to develop machine learning-assisted electron microscopy, together with three-dimensional, cryogenic, and in-situ imaging techniques, for resolving chemical inhomogeneity and materials dynamics in lithium battery electrodes and interfaces. The project aims to expand the spatial, temporal, and dimensional resolution of transmission electron microscopy and to enable quantitative analysis of beam-sensitive battery materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Harnessing Quantum Capacitance in 2D Material/Molecular Layer Junctions for Novel Electronic Device Functionality

Two-dimensional (2D) materials promise advances in electronic devices beyond Moore’s scaling law through extended functionality, such as non-monotonic dependence of device parameters on input parameters. However, the robustness and performance of effects like negative differential resistance (NDR) and anti-ambipolar behavior have been limited in scale and robustness by relying on atomic defects and complex heterojunctions. In this paper, we introduce a novel device concept that utilizes the quantum capacitance of junctions between 2D materials and molecular layers. We realized a variable capacitance 2D molecular junction (vc2Dmj) diode through the scalable integration of graphene and single layers of stearic acid. The vc2Dmj exhibits NDR with a substantial peak-to-valley ratio even at room temperature and an active negative resistance region. The origin of this unique behavior was identified through thermoelectric measurements and ab initio calculations to be a hybridization effect between graphene and the molecular layer. The enhancement of device parameters through morphology optimization highlights the potential of our approach toward new functionalities that advance the landscape of future electronics.

2D materials↗
DOE OSTI2025

Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods

The field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. To overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. Here, this approach has been applied to 2D systems of wide interest, including graphene, phosphorene, MoS 2 , CrI 3 , VSe 2 , GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.

2D materials↗
DOE OSTI2022

Fatigue crack growth resistance of a mesoscale composite microstructure Haynes 282 fabricated via electron beam melting additive manufacturing

Materials synthesis via additive manufacturing gives unprecedented control over the solidified microstructure. While a number of studies have demonstrated the ability to produce spatially varying microstructures, little work exists to understand the behavior of such “composite” materials. In this work, we utilized electron beam melting to process Ni-based superalloy Haynes 282 and produce compact tension samples with a spatially varying mesoscale structure. Fatigue crack growth experiments reveal that the crack growth rate is dependent on the degree of microstructural heterogeneity. This work demonstrates that the crack growth resistance can be tailored within a component using electron beam melting additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rugged bialkali photocathodes encapsulated with graphene and thin metal film

Protection of free-electron sources has been technically challenging due to lack of materials that transmit electrons while preventing corrosive gas molecules. Two-dimensional materials uniquely possess both of required properties. Here, we report three orders of magnitude increase in active pressure and factor of two enhancement in the lifetime of high quantum efficiency (QE) bialkali photocathodes (cesium potassium antimonide (CsK 2 Sb)) by encapsulating them in graphene and thin nickel (Ni) film. The photoelectrons were extracted through the graphene protection layer in a reflection mode, and we achieved QE of ~ 0.17% at ~ 3.4 eV, 1/e lifetime of 188 h with average current of 8.6 nA under continuous illumination, and no decrease of QE at the pressure of as high as ~ 1 × 10 –3 Pa. In comparison, the QE decreased drastically at 10 –6 Pa for bare, non-protected CsK 2 Sb photocathodes and their 1/e lifetime under continuous illumination was ~ 48 h. We attributed the improvements to the gas impermeability and photoelectron transparency of graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Long-Range Resonant Charge Transport through Open-Shell Donor–Acceptor Macromolecules

A grand challenge in molecular electronics is the development of molecular materials that can facilitate efficient longrange charge transport. Research spanning more than two decades has been fueled by the prospects of creating a new generation of miniaturized electronic technologies based on molecules whose synthetic tunability offers tailored electronic properties and functions unattainable with conventional electronic materials. However, current design paradigms produce molecules that exhibit off-resonant transport under low bias, which limits the conductance of molecular materials to unsatisfactorily low levels several orders of magnitude below the conductance quantum 1 G 0 and often results in an exponential decay in conductance with length. Here, we demonstrate a chemically robust, air-stable, and highly tunable molecular wire platform comprised of open-shell donor−acceptor macromolecules that exhibit remarkably high conductance close to 1 G 0 over a length surpassing 20 nm under low bias, with no discernible decay with length. Single-molecule transport measurements and ab initio calculations show that the ultralong-range resonant transport arises from extended π-conjugation, a narrow bandgap, and diradical character, which synergistically enables excellent alignment of frontier molecular orbitals with the electrode Fermi energy. The implementation of this long-sought-after transport regime within molecular materials offers new opportunities for the integration of manifold properties within emerging nanoelectronic technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magneto-transport evidence for strong topological insulator phase in ZrTe5

Abstract The identification of a non-trivial band topology usually relies on directly probing the protected surface/edge states. But, it is difficult to achieve electronically in narrow-gap topological materials due to the small (meV) energy scales. Here, we demonstrate that band inversion, a crucial ingredient of the non-trivial band topology, can serve as an alternative, experimentally accessible indicator. We show that an inverted band can lead to a four-fold splitting of the non-zero Landau levels, contrasting the two-fold splitting (spin splitting only) in the normal band. We confirm our predictions in magneto-transport experiments on a narrow-gap strong topological insulator, zirconium pentatelluride (ZrTe 5 ), with the observation of additional splittings in the quantum oscillations and also an anomalous peak in the extreme quantum limit. Our work establishes an effective strategy for identifying the band inversion as well as the associated topological phases for future topological materials research.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Chapter 12: Photoelectron Spectroscopy Methods in Solar Cell Research

Photoelectron spectroscopy (PES), also referred to as photoemission spectroscopy, is a direct experimental method for assessing the chemical and electronic properties of materials. The technique is becoming increasingly important in the research of photovoltaic (PV) devices--where, more specifically, X-ray photoelectron spectroscopy (XPS) is used primarily to measure the chemical properties such as composition and contamination of solar cell materials, whereas ultraviolet photoelectron spectroscopy (UPS) reveals key electronic properties such as work function and electronic energy-level positions. PES is a surface-sensitive technique ideally suited for the analysis of thin films and interfaces, either completed ones or during their formation process. Because the new generation of PV devices comprise a multitude of complex interfaces--each of which plays a critical role for performance and functionality--PES analysis of functional cell components has gained even more relevance.

photoelectron spectroscopy↗
DOE OSTI2025

The future of the correlated electron problem

A central problem in modern condensed matter physics is the understanding of materials with strong electron correlations. Despite extensive work, the essential physics of many of these systems is not understood and there is very little ability to make predictions in this class of materials. In this manuscript we share our personal views on the major open problems in the field of correlated electron systems. We discuss some possible routes to make progress in this rich and fascinating field. This manuscript is the result of the vigorous discussions and deliberations that took place at Johns Hopkins University during a three-day workshop January 27, 28, and 29, 2020 that brought together six senior scientists and 46 more junior scientists. Our hope, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies.

Alexandradinata, Aris [Univ. of Illinois at Urbana↗
DOE OSTI2020

Triple ionic–electronic conducting oxides for next-generation electrochemical devices

Triple ionic–electronic conductors (TIECs) are materials that can simultaneously transport electronic species alongside two ionic species. The recent emergence of TIECs provides intriguing opportunities to maximize performance in a variety of electrochemical devices, including fuel cells, membrane reactors and electrolysis cells. However, the potential application of these nascent materials is limited by lack of fundamental knowledge of their transport properties and electrocatalytic activity. The goal of this Review is to summarize and analyse the current understanding of TIEC transport and electrochemistry in single-phase materials, including defect formation and conduction mechanisms. In this work, we particularly focus on the discovery criteria (for example, crystal structure and ion electronegativity), design principles (for example, cation and anion substitution chemistry) and operating conditions (for example, atmosphere) of materials that enable deliberate tuning of the conductivity of each charge carrier. Lastly, we identify important areas for further advances, including higher chemical stability, lower operating temperatures and discovery of n-type TIEC materials.

25 ENERGY STORAGE↗
DOE OSTI2023

First-Principles Investigation of Electrides Derived from Sodalites

Recently, electride materials, with excess anionic electrons confined in their empty space, have received growing attention due to their promising applications in catalysis, nonlinear optics, and spin electronics. However, the utilization of electride materials is limited by their thermal instability. Here, we introduce an alternative way to achieve the localized anionic electron states via the removal of highly symmetric Wyckoff sites of anions from the existing sodalite compounds. Using four halide sodalites as the parental structures, our simulation reveals that the materials after the removal of anionic halide sites exhibit typical electride behaviors that are characterized by the existence of localized electronic states near the Fermi level. Compared to most previously studied electrides, these materials are expected to be more thermally stable due to the complex structural framework and thus promising for practical applications. Among them, Na 4 (AlSiO 4 ) 3 manifests magnetic electronic structure. We demonstrate that this magnetism originates from a highly localized excess electron state surrounded by electropositive alkaline cations. Here, our results suggest Na 4 (AlSiO 4 ) 3 could be a promising spintronics component, thus encouraging further experimental study.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗
DOE OSTI2022

Combining Spatial and Temporal Resolution in Cryo-TEM of Device Materials: Preprint

Cryogenic transmission electron microscopy (cryo-TEM) has been instrumental to reducing the effects of electron-beam sample interactions and enabling higher spatial resolution studies of beam sensitive materials. However, the process of thinning and freezing samples for cryo-TEM characterization is often complex and frequently involves removing materials from their environment or stimuli of interest for extended times. This can allow for structural relaxation, diffusion, and other dynamic processes to occur prior to characterization; for energy materials like battery electrodes, this makes it difficult to precisely correlate the imaged structure with native structures that evolve in-situ during device processing, operation, or aging. Here, we present methods to prepare cryo-TEM samples from energy materials during these critical processes in the relevant device lifetimes. This offers insights into improving the temporal resolution of cryo-TEM, while still exploiting its ability to achieve high spatial resolutions in characterizing beam sensitive materials.

BASIC BIOLOGICAL SCIENCES,MATERIALS SCIENCE↗
DOE OSTI2024

Direct Probing of Radiolysis Chemistry in the Gas Cell Electron Microscopy

Here, the radiolytic decomposition of materials is inevitable in electron microscopy, alongside knock-on effects, electrical charging, and heating damage. Especially with the radiation-susceptible chemistry in the fluidic phase (liquid and gas), consideration of mitigating or leveraging these phenomena is particularly important.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Arbitrary Low-Dimensional Film Transfer Enabled by GeO 2 Release Layer

Low-dimensional materials show great promise for enhanced computing and sensing performance in mission-relevant environments. However, integrating low-dimensional materials into conventional electronics remains a challenge. Here, we demonstrate a novel transfer method by which low-dimensional materials and their heterostructures can be transferred onto any arbitrary substrate. Our method relies on a water soluble GeO 2 substrate from which lowdimensional materials are transferred without significant perturbation. We apply the method to transfer a working electronic device based on a low-dimensional material. Process developments are achieved to enable the fabrication and transfer of a working electronic device, including the growth of high-k dielectric on GeO 2 by atomic layer deposition and inserting an indium diffusion barrier into the device gate stack. This work supports Sandia’s heterogeneous integration strategy to broaden the implementation of low-dimensional films and their devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗