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DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗

DOE OSTI2026

Dissecting Disorder: Defect-Driven Structural Complexity in Layered Li3InCl6 Solid Electrolyte

Halide solid electrolytes have emerged as promising candidates for solid-state batteries owing to their high oxidative stability and ionic conductivity. Among them, Li3InCl6 (LIC) has attracted significant attention. However, diffraction patterns of LIC synthesized via different methods exhibit distinct differences particularly at low-angle reflectionsindicative of underlying structural disorder. These variations are attributed to deviations from ideal crystallographic order, especially stacking faults, whose impact on structure and ion transport remains poorly understood. Here, we identify and quantify stacking faults in LIC samples prepared under different synthetic conditions. Using X-ray diffraction and time-of-flight neutron diffraction, we construct and refine stacking fault models that accurately reproduce the experimental diffraction features. LIC samples with higher degrees of stacking faults exhibit only negligible differences in ionic conductivities and activation energies. This indicates that stacking faults have a limited impact on altering the Li+ diffusion pathway along the c-axis, likely due to the high concentration of vacancies in the In layers, while Li+ diffusion remains nearly unchanged in the ab-plane. Our results account for the observed differences in diffraction patterns across samples and provide a quantitative assessment of faulting probabilities and stacking sequences. The insights gained from this study are expected to be broadly applicable to other layered halide solid electrolytes and contribute to a deeper understanding of the role of structural disorder in ion transport.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗

NASA NTRS2026

Ultrasonic Washer–Dryer System for Space Habitats: Design Upgrades and Parabolic Flight Readiness

Clothing makes up nearly 25% of all non-food supplies sent to the International Space Station (ISS). To support sustainable human missions in deep space, NASA’s Life Support and Habitation Systems Focus Area looks to advance technologies to support and improve logistics. Our team is creating a compact ultrasonic clothing washer/dryer system that bypasses traditional limitations and is suitable for space. Thermal drying uses a lot of energy to evaporate water, while our ultrasonic drying method offers a quicker, more efficient alternative. It uses piezoelectric transducers to vibrate textiles at the micron scale, mechanically removing water as cold mist rather than evaporating it. This speeds up drying and reduces energy use, no matter the fabric makeup. This paper details recent upgrades to a full-scale ultrasonic washer–dryer system, readying it for parabolic flight testing. Improvements include an enhanced human–machine interface, better packaging, and optimized performance and control. We also present extensive pre-flight ground tests conducted to ensure reliability and identify potential risks. Collaborating with P&G, we report preliminary cleaning tests using various detergents. These results lay a crucial foundation for the laundry system designed specifically for space. By cutting clothing-related payload and waste by over 97%, this technology supports long-term human exploration missions on the ISS, the Moon, Mars, and beyond.

Ultrasonic↗

DOE OSTI2026

Hierarchical low Pt-loading “core-shell” electrocatalysts for the oxygen reduction reaction in fuel cells

The sluggish kinetics of the oxygen reduction reaction (ORR) hinder cost-effective polymer electrolyte fuel cells (PEFCs), which rely on scarce, expensive platinum-based electrocatalysts (ECs). Here, we present a novel synthesis method for ORR ECs achieving exceptional platinum utilization. The design features a hierarchical “multi-carbon” support comprising carbon nanoparticles interacting with graphene nanoplatelets as the “core”, encapsulated by a porous carbon nitride (CN) “shell”. This configuration promotes strong core/shell interactions and a bimodal active site distribution, consisting of chemically dispersed Pt and Ni single-atom complexes and PtNix alloy nanoclusters embedded in the CN shell. These advantages enable high activity and durability, achieving an ORR activity of 1.6 A mgPt−1 at 0.9 V vs. RHE-an order of magnitude higher than Pt/C (0.17 A mgPt−1). A proof-of-concept PEFC demonstrates a specific power of 12.0 kW gPt−1 at 0.60 V. This approach offers a significant step toward more efficient and sustainable PEFC technologies.

Pagot, Gioele [University of Padova, Italy]↗

NASA NTRS1998

Advanced Non-Intrusive Instrumentation for Propulsion Engines

Changes in engine technology such as higher temperatures, higher tip speeds, new metal/composite/ceramic materials together with radical changes in design philosophy will require amongst other prerequisites the ability to measure and to monitor key internal gas and structural characteristics. The symposium papers presented non-intrusive measurement and analysis technologies in the following categories: Laser Point Measurements (11); Absorption and Infrared Techniques (4); Paints - Surface Sensors (6); Laser Induced Fluorescence (6); Mechanical (7); Films (5); Laser Planar Measurement (9); and a Keynote Address.

Propulsion↗

NASA NTRS1976

Reanalysis of the Apollo Cosmic Gamma-Ray Spectrum in the 0.3- to 10-MeV Energy Region

Additional data obtained from the Apollo-16 and -17 missions, together with collateral calculations on background radiation effects, have enabled an improved subtraction of unwanted backgrounds from the diffuse cosmic gamma-ray data previously reported from Apollo-15. As a result, the 1- to 10-MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflections reported previously is much less pronounced and has no more than a 1.5-σ significance. Sky occultation by the Apollo-16 spacecraft shows the bulk of the 0.3-- to 1-MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region.

Gamma Rays↗

NASA NTRSDate not supplied

Design, Development, and Test of the Advanced Apollo Orbital Assembly System

As spaceflight moves toward commercial solutions for Crew Vehicles and Space Stations, opportunity exists to lower costs with novel designs. Probe and cone docking systems provide a lightweight, low cost, and high-performance docking solution. This work revisits the Apollo probe and cone design and modifies it for the requirements of today’s computer-controlled spacecraft. This new system is called the Advanced Apollo Orbital Assembly (APOA) system, and is intended to support satellite, cargo, and space station assembly missions. A simulation of the APOA was programmed, components were sized, and a design was created by scaling the probe to the size of an EELV Secondary Payload Adapter (ESPA) tunnel. Prototype test hardware was 3D printed using Fused Deposition Modeling (FDM) methods with Polylactic Acid (PLA) material. Testing of the APOA-ESPA was conducted at Marshall Space Flight Center’s (MSFC) Flat Floor, and a test-correlated simulation is used to evaluate a Monte-Carlo of Initial Contact Conditions (ICC’s) to establish baseline performance. The successful development, test, and correlation of the APOA-ESPA proves the design validity and increases Technology Readiness Level (TRL) from 2 to 4. This work opens the door to construction of an APOA-ESPA from flight like materials, and to develop a larger scale prototype APOA. When the full scale APOA is incorporated with the Common Berthing Mechanism (CBM), becomes the Hybrid Berthing System (HBS), which allows for berthing without a robotic arm.

Berthing↗

NASA NTRSDate not supplied

Three-Dimensional, Multi-Phase Unsteady Flow of Water Undergoing Multiple Flow Regimes (Free Surface, Droplet, and Fluid Film)

Upgrades to the Mobile Launcher Rainbird nozzles were implemented for the Artemis II launch to increase water flow rates and improve the mobile launcher deck water coverage while minimizing the water throw distance to avoid impacting the Space Launch System (SLS) rocket nozzles. This analysis describes the use of a three-dimensional, multi-phase, free surface transient computational fluid dynamics (CFD) model to simulate the water flowing out through the Rainbird nozzle and ensure compliance with current Artemis requirements. Flow rates, pressures, velocities, nozzle throw distances and coverage areas were analyzed to ensure that system requirements are met. The completed results were used to make necessary modifications to the Ignition Overpressure Protection and Sound Suppression (IOP/SS) system Rainbird design by reshaping the nozzle used in the system.

CFD↗

NASA NTRS2025

High-density Boron Nitride Nanotube Composites via Surfactant-stabilized Lyotropic Liquid Crystals for Enhanced Space Radiation Shielding

Despite significant technological advancements in space exploration, human space travel and colonization remain limited by the health risks associated with space radiation. Boron nitride nanotubes (BNNTs) have been proposed as an advanced material for space applications due to their high specific strength and efficient radiation shielding capabilities. However, the practical implementation of BNNTs has been slow, primarily due to technological challenges in fabricating structural materials incorporating BNNTs. In this study, a method is presented for fabricating high-density BNNT films that are mechanically robust, exhibit high thermal conductivity, and effectively attenuate space radiation. The key advancement enabling high-density BNNT films is the successful preparation of BNNT liquid crystals (LCs), achieved through the strategic use of a commercial dodecylbenzenesulfonic acid surfactant. This surfactant ensures exceptional BNNT stability in aqueous dispersion, even at concentrations exceeding the LC phase transition threshold. Simulations, estimating the equivalent radiation dose to the human body in space, indicate that a high-density BNNT film with a surface density of 50 g cm−2 reduces the total dose equivalent rate by 56% compared to zero shielding. This enhancement would allow astronauts to extend their mission duration on the lunar surface by a factor of two.

Young-Kyeong Kim↗

DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗

DOE OSTI2026

Metrology for femtosecond pulsed x-ray heating in diamond anvil cell experiments at the European XFEL: Revisiting the iron phase diagram up to 150 GPa

The development of pulsed intense x-ray sources, such as free electron laser, offers new avenues for high pressure experiments. Here, we study the feasibility and metrology of x-ray heating in diamond anvil cells at the European x-ray free electron laser. This method enables one to volumetrically heat the sample while inhibiting chemical migration and probing the crystallographic structure of the sample throughout the heating with a high repetition rate. We focus our study on iron, whose phase diagram is well established up to 100 GPa, to explore the possibilities and limitations of this technique. We volumetrically heat iron samples at starting pressures ranging from 10 to 138 GPa, using the x-ray beam pulsed at 4.5 MHz in a serial pump-and-probe experimental design. Experimental challenges arise from temperature gradients within the sample, changes in temperature at the 100 ns timescale, the difficulty of direct temperature estimates, the effect of thermal pressure, and the presence of metastable crystallites due to rapid cycles of heating and cooling. Hence, we develop a multi-crystal-like data processing method that allows us to account for sample heterogeneity in probed conditions. We then calibrate our measurements using known physical properties of iron under pressure. Thermal pressure in our experiments increases from 4% of the isochoric prediction at 10 GPa to 23% at 138 GPa, and we show that our data are in agreement with most previous observations of iron in this pressure range. The method can now be implemented at higher pressures and temperatures and on materials with unknown phase diagrams.

Materials science↗

DOE OSTI2024

RMCProfile7 : reverse Monte Carlo for multiphase systems

This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.

Chemistry↗

DOE OSTI2025

Chemical Bond Covalency in Superionic Halide Solid‐State Electrolytes

Abstract Halide solid‐state electrolytes (SSEs) are promising superionic conductors with high oxidative stability and ionic conductivity, making them attractive for all‐solid‐state lithium‐ion batteries. However, most studies have focused on ion‐stacking structures, overlooking the role of bond characteristics in ionic transport. Here, we investigate bond dynamics and the superionic transition (SIT) in bromide electrolyte, Li 3 InBr 6 , using synchrotron X‐ray techniques and ab initio molecular dynamics (AIMD) simulations. We demonstrate that the SIT in halide SSEs is driven by a thermally induced transition in bonding character (ionic to covalent) rather than a change in crystal phase. AIMD simulations further reveal enhanced Li⁺ diffusion and collective anion motion at elevated temperatures. Expanding our study to Li 3 LnBr 6 (Ln = Gd, Tb, Ho, Tm, and Lu), we confirm the widespread occurrence of SIT in this material class, with Li 3 GdBr 6 exhibiting the highest ionic conductivity (5.2 mS cm −1 at 298 K). More importantly, the ionic‐covalent transition is highly tunable through electrolyte modifications, such as cation/anion substitution and synthesis methods. Our findings provide a new perspective on ionic transport, highlighting the critical role of chemical bond characteristics in halide SSEs.

Chemistry↗

NASA NTRSDate not supplied

STABLE Study for the Habitable Worlds Observatory

We report on progress on the STABLE study, which was awarded on the NASA 2023 ROSES D.19 opportunity. In the study, we are developing technologies for the Habitable Worlds Observatory (HWO) in four areas: Micrometeoroid Impact Mitigation, Telescope Temperature Control, Ultra-Stable Telescope Structure Materials and Modeling, and Improvement of Thermal Expansion Test Capability. This study is a collaboration between Northrop Grumman, Kratos, NeXolve, JPL, STScI, NASA’s White Sands Test Facility, and NASA Goddard’s Ultra-Stable Test Facility. We will also discuss our plans for our follow-on study as part of NASA’s 2024 ROSES D.19. In this study, we will address additional technologies as well as perform analysis of HWO architecture options.

Habitable Worlds Observatory↗

DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗

NASA NTRSDate not supplied

Material Properties and Modeling of Room Temperature Vulcanizing Silicone

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive that has successfully been used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also used to bond instrumentation plugs such as temperature and pressure sensors into the heatshields. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Heating RTV has also shown swelling, or intumescence, which can pose unique problems that lead to roughness induced boundary-layer transition, surface oxide formation and contamination of heat shield sensors. Therefore, it is crucial to understand and model the intumescence phenomenon of RTV. As data for RTV material properties is limited, the first step in modeling RTV is to collect material properties such as pyrolysis mass-loss, microstructure change, virgin and char porosity, etc. which was performed in our initial study. Additionally, thermomechanical properties such as Young’s modulus and Poisson ratio are required for modeling the intumescence of RTV, which were taken from literature and the coefficient of thermal expansion was collected using in-situ heating and Micro Computed Tomography (µ-CT) in previous studies. Finally, numerous other properties such as pyrolysis gas properties, virgin and char thermal conductivity and specific heat were compiled from previous experiments and literature into a material database that can be used for simulations. In Porous Material Analysis Toolbox based on OpenFOAM (PATO) [4], structural mechanics coupled with material response was used for simulating the intumescence of RTV as it is heated. However, since the permeability of the material is very low, the pyrolysis gas creates an internal pressure build-up as the material is being heated, significantly contributing to the deformation of the material. To correctly characterize this phenomenon, additional physics models were implemented into PATO's stress analysis solver, and results were compared with RTV dilatometry test data as a preliminary verification case. Future work will include experiments of RTV at the Plasmatron X facility and the in-situ heating cell with µ-CT, and improvement of simulation tools to more accurately model RTV intumescence.

PATO↗

DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗