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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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366 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Achieving 20.1% Efficiency in Organic Solar Cells Through Interconnected Fibrillar Networks via Local Molecular Stacking

ABSTRACT The performance of organic solar cells (OSCs) is governed by how molecular packing evolves into interconnected networks that facilitate exciton dissociation and charge transport. Using an all‐small‐molecule blend DR3TSBDT:Y6 as a model system, we study how local molecular stacking evolves into performance‐relevant morphology during solvent vapor annealing (SVA) and subsequent thermal annealing (TA). SVA promotes end‐to‐end stacking of amorphous acceptors to form interconnected fibrils, while TA compacts inter‐fibril spacing without disrupting favorable local order. Such molecular‐to‐morphological refinements broaden light absorption, enhance charge transport, and markedly improve device efficiency. Extending this approach to additional blend systems (D18:Y6, D18:L8‐BO, and DR3TSBDT:L8‐BO) yields similar structural evolution and performance gains, with the D18:L8‐BO system achieving up to 20.10% PCE. Our study establishes control over local stacking in amorphous acceptors into fibrillar networks as a general and effective route to realize high‐performance OSCs.

Wu, Junying↗
DOE OSTI2026

Superconducting Material Growth for Radio-Frequency (RF) Cavities

Superconducting radio-frequency (SRF) cavities, usually manufactured from Niobium (Nb), are vital components of modern particle accelerators because of their ability to achieve high acceleration gradients with little power dissipation. Naturally forming Nb surface oxides significantly alter cavity performance by changing surface resistance. A nondestructive characterization of oxide thickness is helpful for relating surface processing treatments to cavity performance. This work develops a protocol to measure Nb oxide thickness using Angle-Resolved X-ray Photoelectron Spectroscopy (ARXPS) while correcting instrumental errors. Using uniform bulk standard samples (Silver, Aluminum oxide, and Germanium), we determined a baseline correction factor to account for analyzer-related intensity evolution as the measurement angle increases. The correction factor was then applied to Nb 3d ARXPS data. Applying the Strohmeier equation to the corrected data yielded a Nb2O5 thickness of 6.04 nm, closely matching the 5.5 (±.05) nm value obtained from cross-sectional transmission electron microscopy. Our approach will bring a method to incorporate inherent errors in the thickness measurements using ARXPS and can be broadly applied to improve the accuracy of thickness measurements in a wide range of heterostructures.

Lambert, Nathan [Fermilab]↗
DOE OSTI2025

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗
DOE OSTI2026

Fingerprinting Superconductors by Disentangling Andreev and Quasiparticle Currents Across Tunable Tunnel Junctions

Tunneling Andreev reflection (TAR) spectroscopy provides a new approach to identify superconducting pairing symmetry at the atomic scale. Using atomistic superconducting transport simulations, we reveal the mechanism by which TAR can distinguish between pairing symmetries, which is complementary to traditional conductance-based techniques. In particular, owing to the additivity of the excess tunneling decay rate, the TAR spectrum is a weighted average of the contributions from quasiparticle currents, Andreev reflection, and higher-order scattering processes, and their relative weights depend on both the superconducting order parameter and the coupling strength. Within the local tunneling model, TAR dominates mid-gap conductance for s-wave superconductors, is suppressed for d-wave, and coexists with quasiparticle tunneling in sign-changing symmetries if the expectation value for the superconducting gap remains finite. Meanwhile, higher-order processes generally enhance the TAR signal when GN exceeds approximately 0.1G0. As a result, TAR provides a rich spectral fingerprint of the underlying pairing symmetry and electronic structure, enabling atomically resolved identification of unconventional superconducting states.

Maksymovych, Petro [Clemson University]↗
DOE OSTI2026

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop↗
DOE OSTI2026

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.↗
DOE OSTI2026

Lagrange-Remap strategy for multi-material fluid-solid simulations using compressive limiters

In the present work, the Lagrange-Remap strategy proposed in [1] is extended to multi-material fluid-solid simulations. Both hypo-elastic and hyper-elastic material models are considered to describe the mechanical behavior of the solids. In practice, the deviatoric stress tensor (for hypo-elastic materials) and the left Cauchy-Green tensor (for isotropic hyper-elastic materials) are remapped, while the use of compressive limiters effectively reduces numerical diffusion during the remapping step. The simplicity of this diffuse interface approach is emphasized in the context of multi-material fluid-solid simulations. A series of Lagrange-Remap test cases, involving both solids and fluids, are conducted and compared with reference Lagrangian simulations, demonstrating the robustness and accuracy of the overall numerical strategy.

Compressive limiters↗
DOE OSTI2025

Super-resolution imaging reveals resistance to mass transfer in functionalized stationary phases

Chemical separations are costly in terms of energy, time, and money. Separation methods are optimized with inefficient trial-and-error approaches that lack insight into the molecular dynamics that lead to the success or failure of a separation and, hence, ways to improve the process. We perform super-resolution imaging of fluorescent analytes in five different commercial liquid chromatography materials. Unexpectedly, we observe that chemical functionalization can block more than 50% of the material’s porous interior, rendering it inaccessible to small-molecule analytes. Only in situ imaging unveils the inaccessibility when compared to the industry-accepted ex situ characterization methods. Selectively removing some of the functionalization with solvent restores pore access without substantially altering the single-molecule kinetics that underlie the separation and agree with bulk chromatography measurements. Our molecular results determine that commercial “fully porous” stationary phases are over-functionalized and provide an alternative avenue to characterize and direct separation material design from the bottom-up.

Science & Technology - Other Topics↗
DOE OSTI2024

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from powder spectra. Using a variational autoencoder, we obtain a disentangled latent representation of spectra and successfully extract force constants for reconstructing phonon dispersions. Notably, our model demonstrates effective applicability to experimental data even when trained exclusively on physics-based simulations. The fine-tuning with experimental spectra further mitigates issues arising from domain shift. Analysis of latent space underscores the model’s versatility and generalizability, affirming its suitability for complex system applications. Furthermore, our framework’s two-stage design is promising for developing a universal pre-trained feature extractor. This approach has the potential to revolutionize neutron measurements of phonon dynamics, offering researchers a potent tool to decipher intricate spectra and gain valuable insights into the intrinsic physics of materials.

domain adaptation↗
DOE OSTI1968

Nuclear Physics Made Very, Very Easy

The fundamental approach to nuclear physics was prepared to introduce basic reactor principles to various groups of non-nuclear technical personnel associated with NERVA Test Operations. NERVA Test Operations functions as the field test group for the Nuclear Rocket Engine Program. Nuclear Engine for Rocket Vehicle Application (NERVA) program is the combined efforts of Aerojet-General Corporation as prime contractor, and Westinghouse Astronuclear Laboratory as the major subcontractor, for the assembly and testing of nuclear rocket engines. Development of the NERVA Program is under the direction of the Space Nuclear Propulsion Office, a joint agency of the U. S. Atomic Energy Commission and the National Aeronautics and Space Administration. This report is being reprinted for use in the U. S. Atomic Energy Commission and National Aeronautics and Space Administration educational and technology utilization programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Time-Resolved Stochastic Dynamics of Quantum Thermal Machines

Steady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. However, at the level of discrete stochastic realizations, heat flow is unraveled as a series of abrupt quantum jumps, each representing an exchange of finite quanta with the environment. Here, in this work, we present a framework that resolves the dynamics of quantum thermal machines into cycles classified as enginelike, coolinglike, or idle. We analyze the statistics of individual cycle types and their durations, enabling us to determine both the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles of a given type. Central to our analysis is the notion of intermittency, which captures the operational consistency of the machine by assessing the frequency and distribution of idle cycles. Our framework offers a novel approach to characterizing thermal machines, with significant relevance to experiments involving mesoscopic transport through quantum dots.

full counting statistics↗
DOE OSTI2025

Intermodal microwave-to-optical transduction using silicon-on-sapphire optomechanical ring resonator

Optomechanical and electro-optomechanical systems have emerged as one of the most promising approaches for quantum microwave-to-optical transduction to interconnect distributed quantum modalities for scaling the quantum systems. These systems use suspended structures to increase mode overlap and mitigate loss to achieve high efficiency. However, the suspended design’s poor heat dissipation under strong drive limits the ultimate efficiency. Here, we demonstrate an unsuspended optomechanical ring resonator (OMR) based on the silicon-on-sapphire (SOS) platform for microwave-to-optical frequency conversion. The OMR achieves a triply resonant optical-to-optical conversion with an enhanced coupling rateG b = 3.6 gigahertz per square-root milliwatt at a peak conversion efficiency of 1.2% with 3.6-milliwatt microwave drive power and a microwave-to-optical conversion efficiency of 1.5 × 10 −5 at 10-milliwatt optical drive power. Our results show that the unsuspended SOS platform, which mitigates the thermal effect and is compatible with superconducting qubits, is a promising platform for optomechanical circuitry and quantum transduction.

Science & Technology - Other Topics↗
DOE OSTI2024

Enhancement of the Physical and Mechanical Properties of Cellulose Nanofibril-Reinforced Lignocellulosic Foams for Packaging and Building Applications

Biobased foams have the potential to serve as eco-friendly alternatives to petroleum-based foams, provided they achieve comparable thermomechanical and physical properties. We propose a facile approach to fabricate eco-friendly cellulose nanofibril (CNF)-reinforced thermomechanical pulp (TMP) fiber-based foams via an oven-drying process with thermal conductivity as low as 0.036 W/(m·K) at a 34.4 kg/m3 density. Acrodur®, iron chloride (FeCl3), and cationic polyacrylamide (CPAM) were used to improve the foam properties. Acrodur® did not have any significant effect on the foamability and density of the foams. Mechanical, thermal, cushioning, and water absorption properties of the foams were dependent on the density and interactions of the additives with the fibers. Due to their high density, foams with CPAM and FeCl3 at a 1% additive dosage had significantly higher compressive properties at the expense of slightly higher thermal conductivity. There was slight increase in compressive properties with the addition of Acrodur®. All additives improved the water stability of the foams, rendering them stable even after 24 h of water absorption.

Chemistry↗
DOE OSTI2026

The CP-PAW Code Package for First-Principles Calculations from a User’s Perspective

CP-PAW is a combined electronic structure and ab initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as solids, liquids, and molecular systems. As the name suggests, the CP-PAW code unifies the all-electron projector augmented-wave (PAW) method with the Car–Parrinello (CP) approach to determine not only the electronic and nuclear ground states of condensed matter but also to study their properties and dynamics. In addition to briefly outlining the underlying theory, the focus will be on the unique aspects of CP-PAW and how to correctly employ them as a user. How to install CP-PAW using the new build system will also be briefly mentioned.

Blöchl, Peter E [Institute for Theoretical Physic↗
DOE OSTI2024

Enhanced Hydrogen Evolution Catalysis of Pentlandite due to the Increases in Coordination Number and Sulfur Vacancy during Cubic‐Hexagonal Phase Transition

Abstract The search for new phases is an important direction in materials science. The phase transition of sulfides results in significant changes in catalytic performance, such as MoS 2 and WS 2 . Cubic pentlandite [cPn, (Fe, Ni) 9 S 8 ] can be a functional material in batteries, solar cells, and catalytic fields. However, no report about the material properties of other phases of pentlandite exists. In this study, the unit‐cell parameters of a new phase of pentlandite, sulfur‐vacancy enriched hexagonal pentlandite (hPn), and the phase boundary between cPn and hPn are determined for the first time. Compared to cPn, the hPn shows a high coordination number, more sulfur vacancies, and high conductivity, which result in significantly higher hydrogen evolution performance of hPn than that of cPn and make the non‐nano rock catalyst hPn superior to other most known nanosulfide catalysts. The increase of sulfur vacancies during phase transition provides a new approach to designing functional materials.

Chemistry↗
DOE OSTI2026

A Reflection on the Evolution of Sodium/Metal Chloride (ZEBRA) Batteries and Lithium-Ion Cathode Materials (1975–2025): A Tribute to Johan Coetzer

This narrative summarizes, in retrospect, the enormous and quietly-conducted contribution of Dr Johan Coetzer, a South African scientist and entrepreneur, to the discovery, development and implementation of the high temperature sodium—metal chloride “ZEBRA” battery (Na/β-Al 2 O 3 , NaAlCl 4 /MCl 2 (M = Ni, Fe)). Here, this research activity was initiated in the mid 1970’s at the Council for Scientific and Industrial Research (CSIR) in South Africa and subsequently developed primarily in partnership with the Atomic Energy Research Establishment (AERE, Harwell, UK), Beta R&D (Derby, UK) and Daimler Benz (Germany), before being transferred to industry worldwide for electric vehicle and energy storage applications, albeit at a relatively low production rate. Coetzer’s wide-ranging, innovative and, at times, unconventional scientific approach also laid the foundation for the discovery and implementation of manganese-based spinel and layered metal oxide cathode materials for the Li-ion battery industry.

ZEBRA Battery↗
DOE OSTI2025

Entanglement Structure of Non-Gaussian States and How to Measure It

Rapidly growing capabilities of quantum simulators to probe quantum many-body phenomena require new methods to characterize increasingly complex states. Here, we present a protocol that constrains quantum states using experimentally measured correlation functions. This method enables measurement of a quantum state’s entanglement structure, opening a new route to study entanglement-related phenomena. Our approach extends Gaussian state parameterizations by systematically incorporating higher-order correlations. We show the protocol’s usefulness in conjunction with current and forthcoming experimental capabilities, focusing on weakly interacting fermions as a proof of concept. Here, the lowest nontrivial expansion quantitatively predicts early time thermalization dynamics, including signaling the onset of quantum chaos indicated by the entanglement Hamiltonian.

Fermi gases↗