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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗
DOE OSTI2025

Thermal and mechanical influences on shear band formation and suppression in shocked 1,3,5-trinitroperhydro-1,3,5-triazine (RDX)

High-pressure shear band formation is a critical phenomenon in energetic materials because of its ability to form hotspots and influence mechanical strength. Shear banding is known to occur in a variety of these materials, but the governing dynamics of the mechanisms are not well defined for molecular crystals. Our previous work has found that at high pressures in 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), the initial formation sites for shear bands, called “embryos”, form in excess and rapidly lower deviatoric stresses prior to shear band formation and growth, suppressing the shear banding nucleation and growth. Here, in this work, we assess the influence of a variety of changes to the material state on this phenomenon, including altered initial temperature, lateral strain that confines the system in tension or pressure, and initial molecular vacancies throughout the crystal. Shear band suppression and the nature of the shear band network are assessed as a function of each of these.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Exciton-Defect Interaction and Optical Properties from a First-Principles T-Matrix Approach

Understanding exciton-defect interactions is critical for optimizing optoelectronic and quantum information applications in many materials. However, ab initio simulations of material properties with defects are often limited to high defect density. Here, we study effects of exciton-defect interactions on optical absorption and photoluminescence spectra in monolayer MoS 2 using a first-principles T-matrix approach. We demonstrate that exciton-defect bound states can be captured by the disorderaveraged Green’s function with the T-matrix approximation and further analyze their optical properties. Our approach yields photoluminescence spectra in good agreement with experiments and provides a new, computationally efficient framework for simulating optical properties of disordered 2D materials from firstprinciples.

T-matrix↗
DOE OSTI2025

Holistic Microstructure Control Strategies in Photopolymerization‐Induced Phase Separation of Acrylate Systems

Open porous materials, known for their large surface area and interconnected structures, are essential in various applications, including batteries, ion exchange, catalysis, filtration, and electronic waste recycling. A critical aspect of the functionality of porous membranes is the precise control of pore size and morphology. Photopolymerization-induced phase separation (photo-PIPS) offers a convenient and versatile methods for creating porous structures. However, controlling the porous morphology remains challenging due to the complex interplay between thermodynamics, polymerization kinetics, and monomer structures, which makes it difficult to establish the relationship between processing conditions and resulting morphology in photo-PIPS. Herein, a physics-based phase-field model capable of generating and characterizing the microstructures of porous materials based on both average and localized features is developed. Using the phase-field simulations as test bed, the effects of polarity, light intensity, and curing temperature, as well as the previously unexplored roles of chain transfer agents and substrates, on the morphology of the resulting porous microstructure are investigated. Experiments are performed to verify the results predicted by the simulations. This work lays out a comprehensive guide for designing PIPS-derived porous microstructures and offers practical engineering strategies for tailoring microstructure-level topology and size of pores for application-specific needs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗
DOE OSTI2025

Ba 1−x Sr x FeO 3−δ as an improved oxygen storage material for chemical looping air separation: a computational and experimental study

Chemical looping air separation (CLAS) is a promising technology to generate oxygen-rich gas streams to enable efficient carbon dioxide capture during fossil fuel combustion or gasification. CLAS relies on the capture and release of oxygen from the atmosphere using the redox properties of an oxygen-selective solid oxide carrier. This study investigates the redox characteristics of Ba 1−x Sr x FeO 3−δ (0.0 ≤ x ≤ 0.417, 0.0 ≤ δ ≤ 0.5) using a combination of density functional theory (DFT) calculations and experimental verification using X-ray diffraction, thermogravimetric analysis, and oxygen-temperature-programmed desorption. The DFT computed energies of the Ba 1−x Sr x FeO 3−δ perovskites reveal a composition-dependent transition from hexagonal to cubic phases as the Sr-concentration or oxygen vacancy concentration increases. Oxygen vacancy formation energies of the cubic perovskites are found to be lower than those of their hexagonal counterparts. A low oxygen diffusion barrier of ∼1 eV combined with the thermodynamic preference of Ba 1−x Sr x FeO 3−δ compositions that form in a cubic phase suggests them as promising candidates for oxygen storage applications. The experimental results corroborate this finding by identifying Ba 0.75 Sr 0.25 FeO 3−δ in the cubic phase as an optimal composition offering low-temperature oxygen storage capacities comparable to that of the state-of-the-art Sr 0.75 Ca 0.25 FeO 3−δ perovskite oxygen storage material at 325 °C and 350 °C.

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

Tunable broadband luminescence in lead-free hybrid copper halides

Metal halides are an important class of optoelectronic materials combining exceptional optical and electronic properties. An inherent advantage of metal halides is their solution synthesis and processability, which render them as low-cost and environmentally friendly materials for a range of applications from photovoltaics and photodetection to solid-state lighting (SSL). Here, in this study, we synthesized three previously unreported lead-free organic–inorganic hybrid copper halides: (OA) 4 CuX 5 (X = Br, I; OA + = C 8 H 17 NH 3+ , n-octylammonium cation) and (HA) 2 CuI 3 (HA + = C 6 H 13 NH 3 + , n-hexylammonium cation), all of which exhibit broadband emissions arising from self-trapped excitons (STEs). Among these compounds, (OA) 4 CuI 5 demonstrates tunable dual-band white-light emission with a high color rendering index value of 91 at room temperature. Temperature-dependent photoluminescence measurements and first-principles calculations reveal distinct behaviors between the two emission states in (OA) 4 CuI 5 . These findings highlight the potential of copper halide compounds for optoelectronic applications, particularly in the development of environmentally friendly solid-state lighting technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Alkylidene functionalization produces highly recyclable and scalable polyhydroxyalkanoates

Recyclable polymers that can be produced at scale and readily tuned within the same polymer framework for specific properties are important to achieving a circular materials economy. To this end, synthetic poly(3-hydroxyalkanoate)s (PHAs) have emerged as high-performance, chemically recyclable variants of biological PHAs, but their difficult monomer syntheses and suboptimal recycling efficiencies pose challenges for large-scale deployment. In this study, we investigated a β-isopropylidene PHA, i-PHA, for which the lactone monomer can be synthesized by existing industrial methods from biomass-derived isobutyric acid. The alkylidene substituent prevents decarboxylative degradation typically observed during PHA depolymerization, enabling near-quantitative chemical recycling to monomer. Controlled hydrogenation of the β-isopropylidene side group produces PHAs with diverse performance metrics that are competitive with a range of commodity polymers, spanning strong fibers to ductile thermoplastics to superglue epoxy resins.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tunable Electronic Energy Level Alignment and Exciton Diversity in Organic–Inorganic van der Waals Heterostructures

van der Waals stacking of two-dimensional (2D) materials offers a powerful platform for engineering material interfaces with tailored electronic and optical properties. While most van der Waals multilayers have featured inorganic monolayers, incorporating molecular monolayers introduces additional degrees of tunability and functionality. Here, in this study, we investigate hybrid bilayers composed of atomically thin perylene-based molecular crystals interfaced with monolayer transition metal dichalcogenides (TMDs), specifically MoS 2 and WS 2 . Using the ab initio many-body perturbation theory within the GW approximation and the Bethe-Salpeter equation approach, we predict emergent properties beyond those of the isolated constituent systems. Notably, we find substantial renormalization of monolayer molecular crystal band gap due to TMD-induced polarization. Furthermore, by varying the TMD monolayer, we demonstrate tuning of the energy level alignment of the bilayer and subsequent control over a diversity of lowest-energy excitons, which include strongly bound hybrid excitons and long-lived charge-transfer excitons. These findings establish organic-inorganic van der Waals heterostructures as a promising class of materials for tunable optoelectronic devices and quantum excitonic phenomena, expanding the design space for low-dimensional systems.

GW-BSE calculations↗
DOE OSTI2025

Thermally Evaporated Naphthalene Diimides as Electron Transport Layers for Perovskite Solar Cells

Thermally evaporated organic electron transport layers (ETLs) have the potential to enable high-performance and scalable perovskite solar cells (PSCs). Among these, naphthalene diimide (NDI)-based ETLs are a promising family of materials that exhibit the optoelectronic properties, ambient stability and versatility required of high-performance ETLs. Here, we synthesized five NDI derivatives with varying functional groups and identified the two most promising candidates for evaluating the impact of molecular structure on processability via thermal evaporation. While phosphonic acid functionalization was shown to introduce thermal instability, leading to chemical changes during evaporation, NDI-bis N-phenyl-bromide (NDI-(PhBr) 2 ) emerged as a promising ETL candidate. NDI-(PhBr) 2 demonstrated excellent compatibility with the thermal evaporation process and enabled PSCs with power conversion efficiencies (PCEs) of 15.6%, surpassing all previously reported PSCs containing thermally evaporated NDI ETLs. Furthermore, NDI-(PhBr) 2 exhibited excellent operational stability, retaining 75% of the initial PCE after 150 h of operation under continuous illumination at 65 °C. These results highlight the potential of NDI-based ETLs for advancing the scalability and performance of PSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elucidating the Origins of High Capacity in Iron-Based Conversion Materials: Benefit of Complementary Advanced Characterization toward Mechanistic Understanding

Lithium-ion batteries are recognized as an important electrochemical energy storage technology due to their superior volumetric and gravimetric energy densities. Graphite is widely used as the negative electrode, and its adoption enabled much of the modern portable electronics technology landscape. However, developing markets, such as electric vehicles and grid-scale storage, have increased demands, including higher energy content and a diverse materials supply chain. Alternatives that provide the opportunity to increase capacity and address supply chain concerns are of interest. Understanding the fundamental mechanisms that govern battery function is crucial to driving further improvements in the field. Advanced characterization techniques, such as those enabled by synchrotron light sources and high-resolution electron microscopes, that can uncover these mechanisms have become a necessity for elucidating structural evolution upon electrochemical conversion at the nano- to mesoscales. Performing these experiments with relevant electrochemistry using in situ and operando experiments imparts the ability to identify critical reaction pathways and capture intermediate (dis)charge products not discernible by traditional experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Stereochemically‐Controlled Fluorinated Copolymers for Selectively Permeable Barrier Applications

Selective oxygen permeability coupled with low water vapor transmission is essential for biomedical and packaging applications requiring controlled oxygen flux under humid conditions. However, most high‐performance barrier polymers depend on perfluoroalkyl substances (PFAS), whose persistence and regulatory restrictions limit their long‐term applicability. We designed a series of stereocontrolled thiol‐yne‐based polyesters, including both fluorinated and non‐fluorinated variants, for selective oxygen permeability with considerable water barrier performance. Tailoring polymer crystallinity and morphology tuned both oxygen transport and mechanical properties. Fluorinated polymers demonstrated enhanced hydrophobicity and water resistance while maintaining oxygen diffusivity within a range relevant to oxygen‐sensing applications. Structure–property relationships were elucidated through small‐ and wide‐angle X‐ray scattering, revealing semi‐crystalline domains influenced by fluorine content and dithiol chain length. Barrier performance was rigorously evaluated via water vapor transmission rate and dynamic vapor sorption, showing reduced water uptake with increasing dithiol monomer length and crystallinity. In conclusion, this work introduces a PFAS‐free alternative to conventional barrier materials and establishes a tunable materials platform with potential relevance for biomedical devices and packaging systems requiring controlled oxygen permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Topological surface states of semimetal TaSb 2

Topological surface states, protected by the global symmetry of the materials, are the keys to understanding various novel electrical, magnetic, and optical properties. TaSb 2 is a newly discovered topological material with unique transport phenomena, including negative magnetoresistance and resistivity plateau, whose microscopic understanding is yet to be reached. In this study, we investigate the electronic band structure of TaSb 2 using angle-resolved photoemission spectroscopy and density functional theory. Our analyses reveal distinct bulk and surface states in TaSb 2 , providing direct evidence of its topological nature. Notably, surface states predominate the electronic contribution near the Fermi level, while bulk bands are mostly located at higher binding energies. Our study underlines the importance of systematic investigations into the electronic structures of topological materials, offering insights into their fundamental properties and potential applications in future technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Counterintuitive Compatibilization of Poly(-Valerolactone) and Poly(L-Lactic Acid) by Statistical Copolymers toward Compostable and Recyclable Packaging

Poly(δ-valerolactone) (PVL) and poly(l-lactic acid) (PLLA) are bioderivable, compostable, and chemically recyclable plastics with synergistic properties for addressing plastic waste accumulation in receiving environments. Though recyclable-by-design polymers often fall short of competing with incumbent materials, blending affords a means to leverage individual component strengths toward ideal tunable properties. Polymer blends are often immiscible, but a range of methodologies are available to promote mixing. Here, we report on the compatibilization of 9 immiscible PVL and PLLA blends with three different compatibilization agents: thermoplastic starch, synthesized PVL-co-PLLA statistical copolymers (SCPs), and synthesized PVL-b-PLLA block-type copolymers. Resulting degrees of compatibilization are observed through scanning electron microscopy, corroborated by thermal and mechanical analyses monitoring performance as a function of microdomain size. Small-angle and wide-angle X-ray scattering experiments are conducted to observe the influence of compatibilizers on individual crystalline phases to further elucidate material behavior. Molecular dynamics simulations provide key insights into the interfacial interactions between homopolymers and compatibilizers. Finally, a suite of end-of-life avenues is established by biodegradation in industrial composting conditions, chemical recycling by deconstruction to hydroxymethyl esters, and direct chemical depolymerization to lactone precursors in mixed feed. Overall, we highlight several promising blends and the counterintuitive SCP compatibilization phenomenon toward high-performance, sustainable materials.

Compatibilization, copolymer compatibilizer, bio-b↗
DOE OSTI2025

Ultrafast Sintering and Dopant Effects in Garnet LLZO Solid Electrolytes

High-throughput, low-cost manufacturing, and optimization of solid electrolytes are necessary for the adoption of solid-state batteries. In this work, garnet-type Li 7 La 3 Zr 2 O 12 (LLZO) with different aliovalent dopants, 𝑇𝑎$_{^·_{𝑍𝑟}}$, 𝐴𝑙$^{··}_{𝐿𝑖}$, and 𝐺𝑎$^{··}_{𝐿𝑖}$, have been ultrafast-sintered with different temperature ramping rates. The densification behavior, phases, their evolution, and surface chemistry of different LLZO have been investigated and linked to their electrochemical performances. It has been shown that LLZO with 𝑇𝑎$_{^·_{𝑍𝑟}}$ dopant demonstrates the highest garnet phase purity and overall best electrochemical performances, and ultrafast sintering further improves densification, ionic conductivity, and electrochemical stability. On the other hand, LLZO doped with 𝐴𝑙$^{··}_{𝐿𝑖}$ and 𝐺𝑎$^{··}_{𝐿𝑖}$ are reaching higher cubic phase purities and ionic conductivities via conventional sintering, indicating undesirable dopant migration and segregation during the ultrafast sintering process. In conclusion, these findings provide insights into the manufacturing of solid electrolyte materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-resolution analysis of clay minerals and amorphous materials in martian analog environments

Mudrocks and mud-sized sediments (i.e., silt to clay) dominate the surface of Earth and Mars. These fine-grained sediments preserve a rich history of sedimentary processes from source to sink and shed light on ancient climates. However, both the physical and chemical nature of these materials make them difficult to fully characterize with traditional laboratory techniques. Here, we explore a cross-disciplinary and high-resolution approach using synchrotron radiation for X-ray diffraction, pair distribution function analysis, and submicrometer-scale X-ray fluorescence, combined with transmission electron microscopy, to better understand the nanostructure and composition of mud-sized sediments from a glacio-fluvial watershed in southwest Iceland. Our results demonstrate that sediments in the cold and wet climate of Iceland are more altered than previously thought, as evidenced by the identification of kaolinite and mixed-layer kaolinite-smectite. Additionally, sediments are enriched in amorphous materials and nanocrystalline phases, as determined from grain morphologies and compositions consistent with allophane, hisingerite, ferrihydrite, and halloysite. These alteration products are present as intimate mixtures that vary across depositional sites, demonstrating the dynamic nature of the secondary assemblage from source to sink. This work has implications for Mars, where, for example, basalt-sourced sedimentary rocks from Gale crater are abundant in clay minerals and amorphous materials. Finally, this work underpins the importance of using high-resolution techniques, a coordinated methodology, and developing innovative approaches for future planetary sample return missions (e.g., Mars sample return).

36 MATERIALS SCIENCE↗
DOE OSTI2026

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗