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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Polymorphism in Self-Assembly of Short Peptoid Sequences

Due to various applications enabled by diverse morphologies of self-assembled sequence-defined polymers, controlling the self-assembly of synthetic peptidomimetics into designed morphologies has emerged as a promising route for the development of bioinspired functional materials. Herein, we report morphological control over the assembly of a series of short peptoids, or poly-N-substituted glycines, that contain asymmetric hydrophobic domains. We demonstrate that the inherent flexibility of amphiphilic peptoid bilayers drives assembly polymorphism, resulting in the coexistence of nanosheets, twisted ribbons, and nanofibers three distinct morphologies. By tuning peptoid molecular interactions through variations in sequence design, solution pH, and temperature, we demonstrate precise control over the twisting and folding of peptoid bilayers, enabling the formation of well-defined nanosheets and nanohelices. Molecular dynamics simulations further unravel how the introduction of asymmetric hydrophobic domains enables the flexibility of peptoid bilayers and results in peptoid assembly polymorphism. By tuning peptoid molecular interactions through heating, we further demonstrate the transformation of nanosheets into nanohelices. We envision that our mechanistic investigation of peptoid assembly polymorphism provides a strong foundation for leveraging peptoid sequences and chemistries to achieve controlled molecular interactions, driving the creation of biomimetic materials with tailored morphologies and functionalities.

assembly polymorphism↗
DOE OSTI2026

Realization of fermionic Laughlin state on a quantum processor

Strongly correlated topological phases of matter are central to modern condensed matter physics and quantum information technology but often challenging to probe and control in material systems. The experimental difficulty of accessing these phases has motivated the use of engineered quantum platforms for simulation and manipulation of exotic topological states. Among these, the Laughlin state stands as a cornerstone for topological matter, embodying fractionalization, anyonic excitations, and incompressibility. Although its bosonic analogs have been realized on programmable quantum simulators, a genuine fermionic Laughlin state has yet to be demonstrated on a quantum processor. Here, we realize the ν = 1/3 fermionic Laughlin state on IonQ’s trapped-ion quantum computer using an efficient and scalable Hamiltonian variational ansatz with 369 two-qubit gates on a 16-qubit circuit. Employing symmetry-verification error mitigation, we extract key observables that characterize the Laughlin state, including correlation hole, bulk-edge correspondence, and topological entanglement entropy, with strong agreement to exact diagonalization benchmarks. This work demonstrates an end-to-end workflow to simulate material-intrinsic topological orders and provides a starting point to explore its dynamics and excitations on digital quantum processors.

Shen, Lingnan [Univ. of Washington, Seattle, WA (U↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Changes in sea ice concentration explain half of the winter warming of the Arctic surface

Arctic winter warming is stronger than in summer, but its driving mechanisms remain debated, particularly the roles of local processes, like sea-ice loss, versus remote factors, like atmospheric heat transport. Here we introduce a novel decomposition framework that characterizes Arctic warming as a function of historical atmospheric circulation, sea ice concentration, and carbon dioxide changes using observational and reanalysis data. We show that sea ice changes explain about 55% of the winter Arctic near-surface temperature trend during 1959–2015, after removing the effects directly connected to atmospheric circulation. Dynamically induced warming accounts for about 20% at surface and up to 80% in mid-troposphere. The remaining ~25% is attributed to the increase in carbon dioxide, though it also indirectly affects sea-ice loss and circulation-related warming. These findings highlight the dominant role of sea ice loss and change in atmospheric dynamics in affecting the historical Arctic winter warming.

Arctic Sea Ice change↗
DOE OSTI2026

Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic–inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. Here, to understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31–calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ∼2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31–calcite interactions. While this work provides the first experimental confirmation that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31–calcite interface has advanced our fundamental understanding of the atomic interactions at the organic–inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Close, Emily G. S. [Pacific Northwest National Lab↗
DOE OSTI2026

Dichotomy of flat bands in the van der Waals ferromagnet Fe 5 ⁢GeTe 2

Quantum materials with bands of narrow bandwidth near the Fermi level represent a promising platform for exploring a diverse range of fascinating physical phenomena, as the high density of states within the small energy window often enables the emergence of many-body physics. On one hand, flat bands can arise from strong Coulomb interactions that localize atomic orbitals. On the other hand, quantum destructive interference can quench the electronic kinetic energy. Although both have a narrow bandwidth, the two types of flat bands should exhibit very distinct spectral properties arising from their distinctive origins. So far, the two types of flat bands have only been realized in very different material settings and chemical environments, preventing a direct comparison. Here, in this study, we report the observation of the two types of flat bands within the same material system—an above-room-temperature van der Waals ferromagnet, Fe 5−x GeTe 2 , distinguishable by a switchable iron site order. The contrasting nature of the flat bands is also identified by the remarkably distinctive temperature evolution of the spectral features, indicating that one arises from electron correlations in the Fe(1) site-disordered phase, while the other geometrical frustration in the Fe(1) site-ordered phase. Our results therefore provide a direct juxtaposition of the distinct formation mechanism of flat bands in quantum materials and an avenue for understanding the distinctive roles flat bands play in the presence of magnetism, topology, and lattice geometrical frustration, utilizing sublattice ordering as a key control parameter.

Wu, Han [Rice Univ., Houston, TX (United States)] ↗
DOE OSTI2025

The Arctic

The Arctic environment in 2024 continued on a trajectory that has put it in a state far different from that of the twentieth century. Ongoing accumulation of greenhouse gases in the atmosphere continues to quickly warm the Arctic, resulting in rapid changes in the cryosphere that are driving cascading impacts to climate, ecological, and societal systems. Many weather- and climate-related impacts in the Arctic are the result of compounding change, such as increased riverbank erosion, which is proximately due to increased river discharge from higher seasonal precipitation, yet is also exacerbated by thawing permafrost. However, even individual storms occur within very different ocean and ice conditions than were typically present in the late twentieth century. As a result, the impacts, including high winds, excessive precipitation, and coastal inundation, may be quite different nowadays, as exemplified by the October 2024 storm in northwest Alaska that produced severe coastal flooding in several communities. To share some of these impacts with a wider audience, select extreme weather impacts around the greater Arctic have been highlighted through the inclusion of sidebars in recent State of the Climate Arctic chapters (e.g., Benestad et al. 2023; Thoman et al. 2024).

Thoman, Richard L. [Univ. of Alaska, Fairbanks, AK↗
DOE OSTI2025

Revisiting the Role of Ocean Circulation Changes in Polar Ocean Heat Transport Anomalies under Global Warming

In response to greenhouse gas forcing, climate models predict that poleward ocean heat transport (OHT) weakens in the Southern Ocean but increases in the Arctic. The role of ocean circulation changes in this OHT response has been evaluated by decomposing OHT anomalies into a dynamic component (holding ocean temperature fixed while circulation evolves) and a thermodynamic component (holding ocean circulation fixed while temperature evolves). However, ocean temperature changes are themselves shaped by circulation changes through redistribution of the existing heat reservoir and subsequent effects on air–sea heat fluxes. The thermodynamic component can therefore be influenced by circulation changes, making the standard thermodynamic–dynamic decomposition incomplete for isolating the role of circulation changes in OHT anomalies. To address this issue, we use a passive–active decomposition to assess the relative contributions of ocean circulation and passive ocean temperature changes to polar OHT anomalies in a fully coupled climate model. Passive temperature changes are defined as those thermally forced by the atmosphere in the absence of circulation changes. In this passive–active decomposition, an advective term involving both circulation and passive temperature changes remains ambiguous—classifying it as active implies circulation changes dominate Southern Ocean OHT anomalies, whereas classifying it as passive implies temperature changes dominate. However, both interpretations imply that ocean circulation changes have a much weaker effect on polar OHT anomalies than inferred from the standard decomposition. In conclusion, these results help reconcile conclusions from studies using the standard decomposition with those using passive tracer methods to assess the role of circulation changes in polar OHT anomalies.

Arctic↗
DOE OSTI2025

Expedition UT-GOM2-2 Summary

In the summer and fall of 2023, the University of Texas (UT) Deepwater Hydrate Coring Expedition (UT-GOM2-2) drilled, cored, made downhole measurements, and analyzed samples from the seafloor to the base of the gas hydrate stability zone at Site H, in the Walker Ridge Protracted Area Block 313 (Site H, WR313), in the Terrebonne Basin, deepwater Gulf of America (Gulf of Mexico). Analyses of data and samples from the expedition will inform biological, geochemical, and geomechanical models to constrain the role of gas hydrates in the carbon cycle and the potential for gas hydrates as an energy resource.

03 NATURAL GAS↗
DOE OSTI2025

Ecobuoys for Scalable Oceanography

An approach to scalable surface-drifting buoys is needed to enable the high spatial and temporal resolution of oceanographic data that the science and meteorological communities are asking for. With the number of active buoys predicted to increase by a factor of 100 or more, the impact on the environment becomes even more important. Here, we present a pathway to a scalable and sustainable generation of buoys. We identify the main criteria to be used when developing such buoys to be low cost, with reliable data and neutral or even positive environmental impact. For each buoy subsystem—hull, electronics, energy generation and storage, sensors, and communication system—cutting-edge technological solutions are presented, many of them from emerging research in marine or other disciplines. We then assess the potential solutions against the design criteria and plot a path toward small, environmentally friendly, low-cost, and low-power buoys.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Anisotropic Adsorption of De Novo Allosteric Two‐Component Protein Fibers on Mica Surfaces

Protein adsorption at solid–liquid interfaces underlies many biomedical and materials applications, yet the mechanisms governing adsorption of proteins and their assemblies remain poorly understood. Here we investigate de novo–designed proteins that self-assemble into three fibrillar morphologies — small (S), large (L), and helical (H)—on muscovite mica. S-fibers are metastable, forming first but diminishing as L- and H-fibers develop and deposit. Adsorption of both fibers and monomers depends on fiber morphology and solvent environment, which is modulated by the substrate. The anisotropic surface features of the fiber types—long axis of S- and L-fibers and helical grooves of H-fibers—correlate with specific crystallographic directions on mica (001). S- and L-fibers align along the unique lattice axis, while the substrate-facing groove of H-fibers preferentially aligns along the remaining symmetry-related directions. Increasing potassium chloride (KCl) concentrations to molar levels alters adsorption, decreasing monomer coverage relative to fibers. These observations, interpreted through the effect of interfacial interface, indicate that ion-mediated modulation of hydration layers governs electrostatic interactions and alignment. This study reveals how coupling between protein topography, substrate crystallography, and hydration structure dictates selective adsorption and orientation of protein assemblies, offering insights for rational biomolecular material design.

AFM↗
DOE OSTI2025

Spatial mapping of dissolved methane using an in situ sensor in Puget Sound

Release of methane, as gas bubbles or in the dissolved phase, from the seafloor has been observed in coastal waters (< 200 m) and deep ocean basins (> 1000 m). Methane dissolution within the water column affects the geochemistry of the surrounding water, leading to localized oxygen loss and potential escape to the atmosphere, particularly from shallower sites. Traditional methods for detecting and quantifying dissolved methane rely on collecting discrete water samples for ship- or land-based ex situ analysis and post processing. Here, we report on the use of a reduced response time, in situ methane sensor, the Sensor for Aqueous Gases in the Environment (SAGE), for detecting and quantifying dissolved methane concentrations in a wide range of seafloor environments. During a Fall 2022 research cruise on the R/V Thomas G. Thompson in Puget Sound, SAGE was integrated onto a towed conductivity/temperature/depth rosette and deep-sea camera system with live-stream 1 Hz telemetry and used to spatially map the concentration of methane approximately 1 m above the seafloor. The site had been previously identified as an active methane plume field characterized by gas bubbles, fluid venting, and a faulted seabed. The widespread background dissolved concentration of methane measured by SAGE was 83 nM, and a range of 78–670 nM was observed throughout the survey. The results highlight the capacity of SAGE to map the spatial and temporal variability of dissolved methane concentrations in situ and to identify and localize sites of variable methane emissions from the seafloor.

Padilla, Alexandra M. [Woods Hole Oceanographic In↗
DOE OSTI2025

Predicting multi-nodal in-nozzle particle interactions in high-viscosity fluid mediums for acoustophoretic direct-ink writing of line-patterned composites

Patterned functional materials offer improved properties (electrical, thermal, etc.) over their bulk counterparts in many applications, including energy storage, flexible electronics, and sensors. However, manufacturing approaches for patterning materials over large areas with features on the order of hundreds of microns or less are limited. Acoustophoresis, which uses acoustic forces to control particle arrangement in a fluid medium, is a pathway to address this challenge. This process is dependent on particle and fluid properties and enables patterning of a broad range of materials. Herein, a model with experimental validation is presented to demonstrate that acoustophoresis can be combined with direct-ink writing (DIW) to fabricate line patterns over large cm-scale areas. An in-nozzle particle interaction model was developed to investigate the impact of processing conditions on multi-nodal acoustophoretic DIW. The model predicts patterned line widths within a factor of two relative to experimental results for a high viscosity case study. Here, the model was used to investigate the impact of frequency, particle loading, particle radius, and acoustic pressure on line width and patterning time, providing critical feedback regarding the processing conditions suitable for a target application. Model results illustrate that frequency has the greatest impact on line patterns: increasing from 1 to 3 MHz resulted in a greater than 65% reduction in line width and a greater than 85% reduction in patterning time. Additionally, experiments were conducted with an alumina-epoxy ink and a ~21 cm 2 area pattern was rastered in ~5.5 minutes, demonstrating a path towards large-area line-patterned composite fabrication.

25 ENERGY STORAGE↗
DOE OSTI2025

Design of light- and chemically responsive protein assemblies through host-guest interactions

Host-guest (HG) interactions have been widely used to build responsive materials and molecular machines owing to their inherently dynamic nature, interaction specificity, and responsiveness to diverse stimuli. Here, in this work, we have set out to exploit these advantages of HG chemistry in the design of dynamic protein assemblies, using a C 4 symmetric protein, C98 RhuA, as a building block. We show that a C98 RhuA variant individually modified with β-cyclodextrin (βCD) (host) or azobenzene (guest) functionalities can specifically pair with each other to form highly ordered 1D and 2D assemblies. Association and dissociation of βCD RhuA- azo RhuA assemblies can be controlled by UV and visible light as well as by small-molecule modulators of βCD-azobenzene interactions. Kinetics analyses reveal that βCD RhuA- azo RhuA nanotubes assemble without a nucleation barrier, a highly unusual occurrence for helical supramolecular systems. Taken together, our findings provide a compelling example for achieving complex structural and dynamic outcomes in protein assembly through simple chemical design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗
DOE OSTI2025

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Definitive Assessment of the Accuracy, Variationality, and Convergence of Relativistic Coupled Cluster and Density Matrix Renormalization Group in 100-Orbital Space

Accuracy, variationality, and convergence underpin the reliability of modern electronic structure methods, yet definitive benchmarks in the relativistic regime remain elusive due to the absence of numerically exact full configuration interaction (CI) references. Recent algorithmic advances in the CI framework, enabled by the small-tensor-product (STP) decomposition approach, have dramatically extended the tractable size of the configuration space, making numerically exact CI calculations feasible in large active spaces previously beyond reach. In this paper, we employ the recently developed STP-CI framework to perform large-scale numerically exact CI calculations and directly benchmark relativistic coupled cluster and density matrix renormalization group methods. Definitive benchmarking of approximate relativistic electronic structure methods is ensured through the application of the gap theorem, which provides rigorous error bounds on the CI reference and establishes a controlled standard for assessing accuracy, variationality, and convergence.

Chemical calculations↗