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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A General Strategy for Bandgap Engineering Via Anion‐Lattice Doping in High‐Entropy Oxides

Bandgap engineering is a critical tool for tailoring the electronic properties of functional materials, traditionally achieved by modifying the cation sublattice. Here, a generalizable strategy is introduced that leverages facile anion-lattice doping in high entropy materials to modulate the bandgap in high-entropy metal oxides (HEMOs). By incorporating nitrogen into a single-phase high-entropy metal oxide/nitride (HEMO:HEMN) solid solution, a substantial bandgap reduction is achieved from 3.55 eV (HEMO) to ≈2.46 eV (HEMO:HEMN), significantly enhancing electronic conductivity. Unlike conventional bandgap tuning approaches that rely on cation substitution or heterojunction formation, this method exploits anion-mediated entropy stabilization, enabling uniform bandgap narrowing across the entire solid solution. This anion-lattice engineering strategy is broadly applicable to high-entropy systems, providing a new pathway for designing energy materials with tailored electronic properties. The resulting HEMO:HEMN solid solution exhibits a tenfold increase in capacitance and capacity compared to HEMO in supercapacitor and lithium-ion battery tests, demonstrating the transformative potential of anion-driven bandgap modulation for next-generation energy storage and conversion technologies.

energy storage↗
DOE OSTI2020

Quantifying Losses and Assessing the Photovoltage Limits in Metal–Insulator–Semiconductor Water Splitting Systems

Metal–insulator–semiconductor (MIS) photo-electrocatalysts offer a pathway to stable and efficient solar water splitting. Initially motivated as a strategy to protect the underlying semiconductor photoabsorber from harsh operating conditions, the thickness of the insulator layer in MIS systems has recently been shown to be a critical design parameter which can be tuned to optimize the photovoltage. Here we analyze the underlying mechanism by which the thickness of the insulator layer impacts the performance of MIS photo-electrocatalysts. A concrete example of an Ir/HfO 2 /n-Si MIS system is investigated for the oxygen evolution reaction. The results of combined experiments and modeling suggest that the insulator thickness affects the photovoltage i) favorably by controlling the flux of charge carriers from the semiconductor to the metal electrocatalyst and ii) adversely by introducing nonidealities such as surface defect states which limit the generated photovoltage. It is important to quantify these different mechanisms and suggest avenues for addressing these nonidealities to enable the rational design of MIS systems that can approach the fundamental photovoltage limits. The analysis described in this contribution as well as the strategy toward optimizing the photovoltage are generalizable to other MIS systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating the influence of particle distribution on force and torque statistics using hierarchical machine learning

An accurate representation of hydrodynamic force and torque experienced by every particle in a distribution can be obtained from particle resolved (PR) simulations. These unique quantities are influenced by the deterministic position of surrounding particles. However, systems simulated with this methodology are typically limited to particles due to the involved computational cost. This resource requirement is a major bottleneck in analyzing the effect of variations in particle distribution. Here, this article attempts to address this bottleneck by availing relatively inexpensive deep learning models. The surrogate models that we employ in this article use a physics‐based hierarchical framework and symmetry‐preserving neural networks to achieve robustness with limited training data. This article first performs additional generalizability tests on PR data of distinct distributions that are not involved in the training process. The models are then deployed on several different particle distributions. Impact of clustering and structure on the observed statistics are investigated.

42 ENGINEERING↗
DOE OSTI2025

Calibration of multisite raters for prospective visual reads of amyloid PET scans

Abstract INTRODUCTION In multicenter Alzheimer's disease studies, amyloid positron emission tomography (PET) visual reads are typically performed centrally by a few experts. Incorporating a broader reader network enhances scalability and generalizability. METHODS Ten neuroimaging experts from eight Alzheimer's Disease Research Centers (ADRCs) visually read 180 amyloid PET scans (30 scans and 15 duplicate scans for each of four tracers, imaged across a wide variety of scanners), using preferred reading software without anatomical imaging or quantitation. Scans were classified as elevated or non‐elevated per tracer‐specific criteria. Inter‐ and intra‐rater agreement was assessed. RESULTS Inter‐rater agreement was substantial (Fleiss’κ = 0.78), with full consensus on 69% of scans. Inter‐rater reliability was substantial to perfect across tracers (Fleiss’κ = 0.70–0.87). Intra‐rater agreement was substantial to perfect (Cohen'sκ = 0.79‐1). Scans with intermediate (10–40 Centiloid) quantitation had lower reader agreement. DISCUSSION A multicenter expert network achieved substantial agreement classifying amyloid PET scans. These scans provide a standard for reader training and reliability assurance in future studies. Highlights Calibration methods ensure reliable amyloid positron emission tomography (PET) visual reads across multiple raters. Substantial agreement is possible across readers using their preferred tools. Agreement is also substantial regardless of the amyloid PET tracer used. Scans with intermediate (10–40 Centiloid) quantitation have lower reader agreement. The calibration set will become a training tool for amyloid PET visual read studies.

Neurosciences & Neurology↗
DOE OSTI2021

Leveraging Free Volume Manipulation to Improve the Membrane Separation Performance of Amine‐Functionalized PIM‐1

Abstract Gas‐separation polymer membranes display a characteristic permeability–selectivity trade‐off that has limited their industrial use. The most comprehensive approach to improving performance is to devise strategies that simultaneously increase fractional free volume, narrow free volume distribution, and enhance sorption selectivity, but generalizable methods for such approaches are exceedingly rare. Here, we present an in situ crosslinking and solid‐state deprotection method to access previously inaccessible sorption and diffusion characteristics in amine‐functionalized polymers of intrinsic microporosity. Free volume element (FVE) size can be increased while preserving a narrow FVE distribution, enabling below‐upper bound polymers to surpass the H 2 /N 2 , H 2 /CH 4 , and O 2 /N 2 upper bounds and improving CO 2 ‐based selectivities by 200 %. This approach can transform polymers into chemical analogues with improved performance, thereby overcoming traditional permeability–selectivity trade‐offs.

Mizrahi Rodriguez, Katherine↗
DOE OSTI2022

Semiconducting Copolymers with Naphthalene Imide/Amide π‐Conjugated Units: Synthesis, Crystallography, and Systematic Structure‐Property‐Mobility Correlations

Abstract In a series of n‐type semiconducting naphthalene tetracarboxydiimide ( NDI )‐dithiophene ( T2 ) copolymers, structural and electronic properties trends are systematically evaluated as the number of NDI carbonyl groups is reduced from 4 in NDI to 3 in NBL (1‐amino‐4,5‐8‐naphthalene‐tricarboxylic acid‐1,8‐lactam‐4,5‐imide) to 2 in NBA (naphthalene‐bis(4,8‐diamino‐1,5‐dicarboxyl)‐amide). As the NDI ‐ T2 backbone torsional angle falls the LUMO energy rises. However, the thienyl attachment regiochemistry also plays an important role in less symmetric NBL and NBA . Electron mobility is greatest for N2200 (0.17 cm 2 V −1 s −1 ) followed by PNBL‐3,8‐T2 and PNBA‐2,6‐T2 (0.11 cm 2 V −1 s −1 ), 0.02 cm 2 V −1 s −1 in PNBL‐4,8‐T2 , and negligible in PNBA‐3,7‐T2 . Charge transport reflects a delicate balance between electronic backbone communication (optimum for N2200 and PNBL‐4,8‐T2 ), backbone planarity (optimum for PNBA‐2,6‐T2 and PNBL‐3,8‐T2 ), LUMO energy (optimum for N2200 ), π–π stacking distance (optimum for PNBA‐2,6‐T2 ), and film crystallinity (optimum for PNBA‐2,6‐T2 and N2200 ). These results offer generalizable insight into semiconducting copolymer design.

Chen, Yao↗
DOE OSTI2024

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2022

Semiconducting Copolymers with Naphthalene Imide/Amide π-Conjugated Units: Synthesis, Crystallography, and Systematic Structure-Property-Mobility Correlations

Here, in a series of n-type semiconducting naphthalene tetracarboxydiimide (NDI)-dithiophene (T2) copolymers, structural and electronic properties trends are systematically evaluated as the number of NDI carbonyl groups is reduced from 4 in NDI to 3 in NBL (1-amino-4,5-8-naphthalene-tricarboxylic acid-1,8-lactam-4,5-imide) to 2 in NBA (naphthalene-bis(4,8-diamino-1,5-dicarboxyl)-amide). As the NDI-T2 backbone torsional angle falls the LUMO energy rises. However, the thienyl attachment regiochemistry also plays an important role in less symmetric NBL and NBA. Electron mobility is greatest for N2200 (0.17 cm 2 V –1 s –1 ) followed by PNBL-3,8-T2 and PNBA-2,6-T2 (0.11 cm 2 V –1 s –1 ), 0.02 cm 2 V –1 s –1 in PNBL-4,8-T2, and negligible in PNBA-3,7-T2. Charge transport reflects a delicate balance between electronic backbone communication (optimum for N2200 and PNBL-4,8-T2), backbone planarity (optimum for PNBA-2,6-T2 and PNBL-3,8-T2), LUMO energy (optimum for N2200), π–π stacking distance (optimum for PNBA-2,6-T2), and film crystallinity (optimum for PNBA-2,6-T2 and N2200). These results offer generalizable insight into semiconducting copolymer design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Design Rules for Two–Dimensional Organic Semiconductor–Incorporated Perovskites (OSiP) Gleaned from Thousands of Simulated Structures

Two-dimensional (2D) halide perovskites are an attractive class of hybrid perovskites that have additional optoelectronic tunability due to their accommodation of relatively large organic ligands. Nevertheless, contemporary ligand design depends on either expensive trial-and-error testing of whether a ligand can be integrated within the lattice or conservative heuristics that unduly limit the scope of ligand chemistries. Here, the structural determinants of stable ligand incorporation within Ruddlesden-Popper (RP) phase perovskites are established by molecular dynamics (MD) simulations of over ten-thousand RP-phase perovskites and training of machine learning classifiers capable of predicting structural stability based solely on generalizable ligand features. The simulation results show near-perfect predictions of positive and negative literature examples, predict trade-offs between several ligand features and stability, and ultimately predict an inexhaustibly large 2D-compatible ligand design-space.

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

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2025

Upcycling Polynorbornene Derivatives into Chemically Recyclable Multiblock Linear and Thermoset Plastics

Synthetic polymers have found widespread use, but their ineffective end-of-life treatment is causing a significant environmental and human health crisis. Here, we demonstrate the upcycling of polynorbornene derivatives (pNBEs) through their deconstruction into distinct oligomeric buildings blocks that can be repolymerized into chemically recyclable pNBEs-like multiblock polymers via dehydrogenative polymerization. The resulting materials exhibit diverse mechanical properties, while integrating high melting temperatures (T m as high as 133 °C). Notably, this method could also enable the selective deconstruction of permanently cross-linked polydicyclopentadiene (pDCPD) thermosets into telechelic-OH functionalized oligomers, overcoming the significant challenges posed by their robust network structure in recycling and degradation. The resulting pDCPD oligomers can subsequently be repolymerized with macrodiols to create multiblock thermosets with tunable mechanical properties, including Young's modulus and tensile elongation. After use, upcycled plastics could be effectively deconstructed back to the oligomers for recovery and repolymerization. Overall, this work establishes an approach that can be utilized to upcycle pNBEs into previously inaccessible multiblock thermosets and thermoplastics with full recyclability, and may be generalizable to a range of polymers to shift their end-of-life waste disposal toward sustainable recovery and reuse.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interplay Between Stereochemically Active Lone Pair Repulsions, Sigma Hole Interactions, and Delocalized Redox Processes in Topochemical Fluoride‐Ion Insertion

Topochemical insertion/extraction of cations has emerged as a generalizable strategy for modulating the crystal and electronic structure of periodic solids. In contrast, strategies for topochemical anion insertion are poorly explored and fundamental principles for designing insertion hosts to accommodate anions remain scarce. Here, we observe reversible room-temperature fluoride-ion insertion within tunnels of Sn 2 TiO 4 defined by the stereochemical expression of Sn 5 s 2 lone pairs. X-ray scattering studies of fluoride-ion-insertion-induced crystal structure modulation and X-ray absorption/emission spectroscopy probes of electronic structure along with magnetic susceptibility measurements and first-principles calculations are used to decipher design principles underpinning reversible fluoride-ion insertion and bulk diffusion. Fluoride-ion insertion is enabled by a combination of a large, polarizable tunnel, delocalized redox at Ti─O─Sn centers, inherent repulsion between the fluoride-ion and Sn 5 s 2 electron lone pairs, and the formation of dative interactions between Sn-centered σ-holes and fluoride-ions, yielding a reversible capacity of 0.5 fluoride-ions per Sn 2 TiO 4 formula unit. Our results demonstrate that the complex interplay between dative interactions and stereochemically active lone pair repulsions is critical to defining the thermodynamics and kinetics controlling fluoride-ion insertion and diffusion. As such, the design of fluoride-ion insertion hosts for anion batteries requires site-selective modification to modulate lattice—ion interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polysulfamates as “Macroisosteres” of Polyurethanes with Improved Degradability

Abstract Addressing the environmental persistence of plastics requires the development of next‐generation polymers that combine high performance with enhanced degradability. Progress toward this grand challenge has been impeded, in part, by the absence of a general blueprint for the macromolecular design of such materials. Herein, we introduce a “macroisostere” design strategy, where the carbonyl group (–CO–) in polyurethanes (PUs) is replaced with a sulfonyl group (–SO 2 –), resulting in a virtually unknown family of polymers called polysulfamates. This approach, inspired by the use of bioisosteres in drug discovery, aims to preserve key interchain interactions that contribute to thermomechanical performance while enhancing the hydrolytic lability of the polymer backbone. The optimization of a Sulfur(VI) Fluoride Exchange (SuFEx) polymerization allowed the synthesis of ten polysulfamates structurally analogous to common PUs. Comparative analysis of one PU and its polysulfamate analog showed that this isosteric substitution increases thermal stability, slightly lowers the glass transition temperature, and retains similar hardness and reduced Young's modulus. Notably, the S(VI)‐based polysulfamate demonstrated significantly enhanced hydrolytic degradability. These results highlight the potential of the “macroisostere” approach as a generalizable strategy for designing high‐performance, degradable alternatives to traditional plastics.

Chemistry↗
DOE OSTI2026

Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO 3 H 3 − (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.

HER active sites↗
DOE OSTI2026

Highly Crystalline and Porous Borocarbonitrides as Metal‐Free Catalysts for Boosted N‐Heterocycle Dehydrogenation

Safe and efficient hydrogen storage is pivotal for enabling a clean hydrogen economy. Liquid organic hydrogen carriers (LOHCs) offer a practical solution, but their deployment is hindered by the lack of highly active and economical dehydrogenation catalysts. In this work, we report a metal‐free catalyst design that overcomes the long‐standing trade‐off between crystallinity and surface area in two‐dimensional frameworks for highly efficient dehydrogenation of LOHCs. A flux‐assisted reconstruction strategy transforms amorphous borocarbonitrides (AM‐BCN) into highly crystalline, defect‐rich BCN nanosheets (C‐BCN) with large surface area and accessible porosity, as confirmed by complementary spectroscopic, x‐ray, and neutron analyses. C‐BCN catalyzes the acceptor‐less dehydrogenation of aza‐fused LOHCs with quantitative hydrogen release under mild conditions, outperforming AM‐BCN and previously reported metal‐free scaffolds. Mechanistic insights from x‐ray, neutron scattering, and theoretical calculations identify open C‐B‐N and N‐B‐N defect motifs as the primary active sites. This work establishes a generalizable strategy to engineer crystalline, porous, defect‐rich two‐dimensional lattices and demonstrates a highly active metal‐free platform for LOHC dehydrogenation with high‐purity H 2 generation.

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

Artificial intelligence to unlock real-world evidence in clinical oncology: A primer on recent advances

Purpose: Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time-consuming manual case-finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology. Methods: We performed a narrative review of the major current trends and recent literature in artificial intelligence applications in oncology. Results: Artificial intelligence (AI) approaches are increasingly used to efficiently phenotype patients and tumors at large scale. These tools also may provide novel biological insights and improve risk prediction through multimodal integration of radiographic, pathological, and genomic datasets. Custom language processing pipelines and large language models hold great promise for clinical prediction and phenotyping. Conclusions: Despite rapid advances, continued progress in computation, generalizability, interpretability, and reliability as well as prospective validation are needed to integrate AI approaches into routine clinical care and real-time monitoring of novel therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Supported Single‐Atom Manganese Catalysts for the Trimerization of Ethylene

Selective ethylene oligomerization via oxidative cyclization, forming metallacyclic intermediates, is typically catalyzed by molecular titanium and chromium complexes to produce butenes, hexenes, or octenes, depending on the supporting ligand framework. However, this mechanism requires significant electron density at the metal active site and is not known to be generalizable to other first-row transition metals. In this work, we computationally investigate the electronic modulation of five transition metals (Mn, Fe, Co, Ni, and Cu) supported on titania (TiO₂) through reductive lithium intercalation to promote selective oligomerization via oxidative cyclization, using density functional theory (DFT). Our findings predict that Mn/LiTiO₂ exhibits high catalytic activity due to the exergonic nature of oxidative cyclization with two ethylene molecules. Additionally, lithium titanate (LiTiO₂) supports enhance catalytic performance compared to TiO₂. Experimental validation confirms that Mn/LiTiO₂ achieves higher conversion rates and improved selectivity toward hexene (C₄:C₆ = 1:2.6). The enhanced activity is attributed to lithiation, which alters the electronic environment around Mn active sites. Mechanistic studies reveal that the formation of a seven-membered ring, a key intermediate for hexene formation, is more favorable on LiTiO₂ than TiO₂. This work provides the first evidence of Mn catalyzing selective ethylene oligomerization via oxidative cyclization in either homogeneous or heterogeneous catalysis.

Kim, Yu Lim [Argonne National Laboratory (ANL), Ar↗