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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structural Evolution of Mixed-Addenda Keggin Polyoxometalate Anions with Atom-by-Atom Substitution

Polyoxometalates (POMs) are molecular metal oxides with distinctive electronic properties that make them promising materials for applications in energy, sensors, and memory devices. One of the most promising methods of tuning the stability, photochromic, redox, and electron-spin properties of POMs is through the substitution of the metal “addenda” atoms that, along with oxygen, constitute their cage-like structures. Because traditional synthesis methods typically produce a distribution of POMs, the isolation and characterization of multimetallic POMs with predetermined stoichiometry remains challenging. The presence of multiple energetically accessible isomers further complicates the experimental characterization and theoretical modeling of multimetallic POMs. Herein, we leverage the distinguishing mass-selection capabilities of ion soft landing to prepare stoichiometrically selected Keggin PMo x W 12-x O 40 3- (x = 0 – 6, 8, 10, and 12) POMs on self-assembled monolayer surfaces free of the solvent molecules and counterions that often confound characterization of complex species at interfaces. The structures of the supported POMs are characterized with atom-by-atom precision using in situ infrared (IR) reflection absorption spectroscopy complemented by detailed density functional theory calculations. Our joint experimental and theoretical results reveal an almost linear shift in the positions of the IR bands towards lower wavenumbers with an increase in the number of lighter molybdenum atoms compared to heavier W atoms in PMoxW 12-x O 40 3- . The theoretical calculations also indicate that numerous isomeric structures may be populated at the experimental conditions and, consequently, contribute to the overall IR spectra. In conclusion, our findings indicate that in addition to the number of substituted addenda atoms and the presence of multiple isomeric structures, interactions with the surface play an important role in determining the IR spectra and structure of supported bimetallic POMs.

Prabhakaran, Venkateshkumar [Pacific Northwest Nat↗
DOE OSTI2025

First-principles investigation of the resistive switching energetics in monolayer MoS 2 : insights into metal diffusion and adsorption

A deeper understanding of resistive switching (RS) in 2D materials is essential for advancing neuromorphic computing. The Dissociation-Diffusion-Adsorption (DDA) model offers a useful framework for probing RS mechanisms in non-volatile memory (NVM) and in-memory computing. We have employed first-principles density functional theory (DFT) to explore dissociation, diffusion, and adsorption phenomena within the DDA model, focusing on the interactions between exemplary metal atoms (Au, Ag, Cu) and monolayer MoS 2 . Nudged elastic band (NEB) calculations evaluated diffusion barriers in pristine and sulfur-vacancy MoS 2 . Charged systems were modeled to assess the impact of applied bias on migration pathways. We also examined metal dissociation from bulk electrodes and adsorption at S vacancies. Ag/MoS 2 shows the lowest dissociation barrier (~0.034 eV), while Au and Cu exhibit similar values (~0.32 eV). These insights highlight Ag as a promising candidate for low-energy RS applications and provide guidance for optimizing switching efficiency in 2D memory devices.

Atomistic models↗
DOE OSTI2025

Revealing the electronic structure of the current-induced metastable state in 1T-TaS 2

Among the key features for next-generation memory devices is the need for high-contrast switching between metallic and insulating states with fast switching speed and long lifetime. However, materials exhibiting such properties are rare, and their electronic structure is often poorly understood. Here, by combining state-of-the-art devices with angle-resolved photoemission spectroscopy, we study the emergence of a metastable metallic state from the insulating ground state in the charge-density wave (CDW) material 1T-TaS 2 after applying short current pulses. Analysis of the electronic structure suggests a picture in which 1T-TaS 2 transforms from a band insulator in the commensurate CDW ground state to a correlated metal in the metastable state. Moreover, the optically induced metastable state reveals a strong similarity to the current-induced one. This work provides an extensive characterization of metastable order in 1T-TaS 2 and proves how studying electronic properties under in-operando conditions is a critical step for next-generation devices.

Huber, Maximilian [Lawrence Berkeley National Labo↗
DOE OSTI2025

Precursor reaction pathway leading to BiFeO 3 formation: insights from text-mining and chemical reaction network analyses

BiFeO 3 (BFO) is a next-generation non-toxic multiferroic material with applications in sensors, memory devices, and spintronics, where its crystallinity and crystal structure directly influence its functional properties. Designing sol–gel syntheses that result in phase-pure BFO remains a challenge due to the complex interactions between metal complexes in the precursor solution. Here, we combine text-mined data and chemical reaction network (CRN) analysis to obtain novel insight into BFO sol–gel precursor chemistry. We perform text-mining analysis of 340 synthesis recipes with the emphasis on phase-pure BFO and identify trends in the use of precursor materials, including that nitrates are the preferred metal salts, 2-methoxyethanol (2 ME) is the dominant solvent, and adding citric acid as a chelating agent frequently leads to phase-pure BFO. Our CRN analysis reveals that the thermodynamically favored reaction mechanism between bismuth nitrate and 2ME interaction involves partial solvation followed by dimerization, contradicting assumptions in previous literature. We suggest that further oligomerization, facilitated by nitrite ion bridging, is critical for achieving the pure BFO phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ferroelectric AlBN films by molecular beam epitaxy

We report the properties of molecular beam epitaxy deposited AlBN thin films on a recently developed epitaxial nitride metal electrode, Nb2N. While a control AlN thin film exhibits standard capacitive behavior, distinct ferroelectric switching is observed in the AlBN films with increasing Boron mole fraction. The measured remnant polarization Pr∼15μC/cm2 and coercive field Ec∼ 1.45 MV/cm in these films are smaller than those recently reported on films deposited by sputtering, due to incomplete wake-up, limited by current leakage. Because AlBN preserves the ultrawide energy bandgap of AlN compared to other nitride hi-K dielectrics and ferroelectrics, and it can be epitaxially integrated with GaN and AlN semiconductors, its development will enable several opportunities for unique electronic, photonic, and memory devices.

Physics↗
DOE OSTI2025

Near-field infrared imaging of polar domain walls in Ni 3 TeO 6

Domain walls are leading platforms for the development of ultra-low power switching and memory devices due to their potential to be moved, created, and erased in real time and to mitigate heat flux. Interface vs wavelength size effects unfortunately preclude the measurement of phonons by traditional spectroscopic techniques, so it has been challenging to unravel the primary excitations of the lattice and the symmetries that they represent across these functional interfaces. In this work, we employ synchrotron-based near-field infrared nanospectroscopy to image polar domain walls in multiferroic Ni 3 TeO 6 . This is a unique platform because, in addition to hosting polar and chiral domains that are interlocked with one another, Ni 3 TeO 6 displays both charged and neutral interfaces depending upon the direction allowing the development of structure–property relations. From a local structure and a strain point of view, we find charged walls that are twice as wide as neutral walls as well as strong frequency shifts of vibrational modes across the charged walls. The near-field amplitude drops across the walls as well. We discuss these trends in terms of polarization and chirality as well as phonon lifetimes at functional interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Emergent ferromagnetism and unusual irreversible magnetoresistance in an intercalated van der Waals antiferromagnet

Orthorhombic air-stable two-dimensional (2D) antiferromagnet (AFM) CrSBr has attracted much research interest lately thanks to its rich magnetic behaviors together with its remarkable electronic, excitonic, and polaritonic properties. Here, we report a reliable electrochemical intercalation method by inserting large tetrabutylammonium (TBA + ) ions into CrSBr layers. Magnetically, such intercalation efficiently suppresses the interlayer AFM and induces a ferromagnetic (FM) order with a much-enhanced transition temperature up to 200 K, nearly 70 K higher than the AFM onset of 132 K in pristine CrSBr. Electronically, the TBA + intercalation not only increases the electric conductivity of CrSBr, which is further enhanced by magnetic fields, but also introduces a giant negative irreversible magnetoresistance. This work demonstrates the tunable magnetic and electronic properties of CrSBr as well as their interplay, paving the way for advanced spintronic and magnetic memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning-based interatomic potential development and phase transition analysis of ferroelectric hafnium dioxide

The ferroelectric phase (𝑃⁢𝑐⁢𝑎⁢2 1 , which is in orthorhombic symmetry) of hafnium dioxide (HfO 2 ) has gained much attention due to its potential applications in nanoelectronics and advanced memory devices. However, its complex phase behavior under external stimuli, such as pressure and temperature, remains a subject of intense investigation. This study focuses on developing a machine learning-based interatomic potential (MLIP) that is trained with data from density-functional theory (DFT) calculations to simulate phase transitions and mechanical properties of HfO 2 . The developed MLIP predicts lattice parameters, equations of state, bulk and shear moduli, and elastic constants that closely align with DFT predictions for several phases and at various pressures. Once validated, the MLIP is used to investigate the phase transitions of ferroelectric HfO 2 (𝑃⁢𝑐⁢𝑎⁢2 1 ) under both isobaric and constant stress conditions at elevated temperatures ranging from 200 to 2500 K. We used several complementary methods, including local symmetry identification, radial distribution function, and x-ray diffraction characterization, to identify interesting phase transitions among several competitive hafnia phases predicted from our simulations. The suggested methods uniformly reveal that under pure deviatoric condition, the system favors a transition from the orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase to a tetragonal (𝑃⁢4 2 /𝑛⁢𝑚⁢𝑐) phase, whereas a zero stress condition drives the system from the 𝑃⁢𝑐⁢𝑎⁢2 1 phase to another orthorhombic (𝑃⁢𝑏⁢𝑐⁢𝑛) phase. These findings provide crucial insights into stress and temperature-induced phase behavior of hafnia, guiding future experimental and theoretical studies for optimizing hafnia-based ferroelectric devices.

Ferroelectric HfO2↗
DOE OSTI2024

Machine learning-accelerated discovery of iron cobalt phosphides as rare-earth-free magnets

Here, the discovery of rare-earth-free permanent magnets has been a goal of scientists for decades. The absence of rare-earth elements will alleviate a pressing concern about the availability of rare-earth elements used in permanent magnets. These magnets are crucial for applications such as wind turbines, electric cars, and memory devices. Rare-earth magnets are special owing to a large magnetic anisotropy energy (K 1 ). In contrast, iron cobalt phosphides hold promise since doping P into cubic FeCo can induce anisotropy, leading to a large coercivity, without introducing rare-earth elements. We present a comprehensive search over the Fe-Co-P ternary space for magnets, utilizing recently developed adaptive machine learning feedback to efficiently screen over 850 000 structures. We focus on machine learning acceleration as a paradigm for materials design. Further adaptive genetic algorithm searches and first-principles calculations aid in the identification of 16 new structures below the known convex hull. Five of them possess high magnetic polarization (J s > 1 T). The structures with desirable magnetic properties center on (Fe,Co) 2⁢ P. This supports conventional wisdom, which focuses on the mixture of the two known end compounds: Fe 2 ⁢P and Co 2 ⁢P. Our work provides guidance for synthesis. We find Fe 7 ⁢CoP 4 shows the most promise (J s = 1.03T and K 1 = 0.83MJ/m 3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Magnetic structure determination of multiple phases in the multiferroic candidate GdCrO 3

Due to their potential applications in low-power consumption and/or multistate memory devices, multiferroic materials have attracted a lot of attention in the condensed matter community. As part of the effort to identify new multiferroic compounds, perovskite-based GdCrO 3 was studied in both bulk and thin film samples. A strong enhancement of the capacitance in a field suggested ferroelectric behaviour but significant leakage and no well developed P–E hysteresis loops were observed. Measurements clearly indicate the existence of a polar phase but only below 2 K (likely connected to Gd ordering). Here the determination of the magnetic structure through neutron diffraction collected on an isotopic 160 GdCrO 3 sample at the WISH diffractometer at ISIS is reported. The presence of three successive magnetic phases as a function of temperature (commensurate, spin re-orientation and incommensurate phases once the Gd order), previously only seen by magnetization, is confirmed. Using the most recent guidelines for reporting the determined structures, we highlight the benefits of using such nomenclature for discussing physical properties and consider possible mechanisms and couplings that led this seemingly rather isotropic system to display the complex structures observed.

incommensurate magnetic structure↗
DOE OSTI2026

Tula: Optimizing Time, Cost, and Generalization in Distributed Large-Batch Training

Distributed training increases the number of batches processed per iteration either by scaling-out (adding more nodes) or scaling-up (increasing the batch-size). However, the largest configuration does not necessarily yield the best performance. Horizontal scaling introduces additional communication overhead, while vertical scaling is constrained by computation cost and device memory limits. Thus, simply increasing the batch-size leads to diminishing returns: training time and cost decrease initially but eventually plateaus, creating a knee-point in the time/cost vs. batch-size pareto curve. The optimal batch-size therefore depends on the underlying model, data and available compute resources. Large batches also suffer from worse model quality due to the well-known “generalization gap”. In this paper, we present Tula, an online service that automatically optimizes time, cost, and convergence quality for large-batch training of convolutional models. It combines parallel-systems modeling with statistical performance prediction to identify the optimal batchsize. Tula predicts training time and cost within 7.5−14% error across multiple models, and achieves up to 20× overall speedup and improves test accuracy by ≈9% on average over standard large-batch training on various vision tasks, thus successfully mitigating the generalization gap and accelerating training at the same time.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗
DOE OSTI2025

Theoretical perspective on phase stability and polarization switching in ferroelectric hafnia

Fluorite-based ferroelectric materials are revolutionizing the application space of polar semiconductors. These materials leverage robust polarization of extremely thin films, compatibility with the silicon chip processing, and decades of manufacturing experience to enable a new generation of ferroelectric memory devices. As a new paradigm for ferroelectrics, understanding of phase transitions and the switching mechanism in fluorites is essential both for advancing applications and for fundamental science. In this article, we outline the recent progress that has been made to understand the relative phase stability, phase transition and order parameter coupling, ferroelectric switching through unique nucleation and growth processes, and how defects affect these phases and processes. The main challenges, opportunities, and next steps for leveraging these materials for next-generation devices are reviewed.

Condensed Matter Physics↗
DOE OSTI2025

Properties of Electronic Materials

This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.

36 MATERIALS SCIENCE↗
NASA NTRS1966

Thin-film ferrites vapor deposited by one-step process in vacuum

Thin-film ferrites are formed by vapor deposition of a mixture of powdered ferrites and powdered boron oxide at controlled temperatures in a vacuum chamber. These films are used in memory devices for computers and as thin-film inductors in communications and telemetry systems.

Hacskaylo, M.↗
NASA NTRS1970

Digital input is buffered to real-time analog display

Buffering technique utilizes nine-bit binary counter and holding register of eight flip-flops. These flip-flops form the memory device that allows precise asynchronous conversion of the digital source data. Counter generates a waveform which is passed through a low pass filter to recover data in analog form.

Bower, K. F.↗