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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Gas-driven short disconnection mitigates thermal runaway in Li-ion batteries under mechanical abuse

Mechanical abuse poses a critical safety risk to Li-ion batteries by inducing internal short circuits that initiate thermal runaway. Remarkably, voltage recovery frequently emerges during thermal runaway initiation, a phenomenon that conventional theories fail to explain. Here, our study develops a new multiphysics mechanism to explain voltage recovery, termed gas-driven short disconnection, whereby internal gas pressure mechanically disengages short-circuit contacts and causes the cell voltage to rebound. This mechanism incorporates gas generation and its structural impact on the short circuit. Real-time optical and thermal imaging and X-ray computed tomography reveal fluid-structure interaction between internal gas flow and adjacent shorting contacts. We establish a mechanistic framework linking gas-driven short disconnection to cell-level voltage and temperature responses, elucidating the extension–truncation pattern of voltage recovery. Furthermore, thermal regime maps show that a voltage recovery duration exceeding 5 s correlates with limited temperature rise below 150 °C, indicating that sustained short-circuit disconnection suppresses Joule heating. Additionally, a dimensionless criterion is deduced from scaling analysis for physical plausibility of gas-driven short disconnection in mechanically abused cells. This finding inspires smart venting control, which regulates gas release to maintain the internal pressure while dissipating gas enthalpy, thereby providing a device-level strategy for thermal runaway mitigation.

Gas-driven short disconnection↗
DOE OSTI2021

Bioinspired aligned magnetic features in aerogels for humidity sensing

Many natural plant tissues, such as pinecones, utilize structures to transduce changes in humidity into movement or strain. These often employ layered structures with aligned features in order to create differential stress across the material as different portions swell at different rates. Here, by replicating these types of structures in synthetic materials we can create structures that respond to humidity in a similar manner. Taking these aligned features as inspiration, silica aerogels with tailored humidity reactive properties were created. This behavior was achieved by creating aligned features in these aerogels using a Helmholtz coil to produce a uniform magnetic field that aligned ferrofluid droplets into chains and needle like features. These magnetite-based structures were shown to retain their superparamagnetic properties, allowing them to easily be removed from the aerogels, leaving a large number of aligned channels. Aerogels with the removed needles experienced significantly different strains than both unmodified aerogels and aerogels with the aligned features still in place. Aerogels with these tunable aligned features could be used in humidity sensors that can transduce changes in humidity into strain and could be used in applications such as volatile organic compound capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Closed-loop control of meltpool temperature in directed energy deposition

The objective of this work is to mitigate flaw formation in powder and laser-based directed energy deposition (DED) additive manufacturing process through close-loop control of the meltpool temperature. In this work, the meltpool temperature was controlled by modulating the laser power based on feedback signals from a coaxial two-wavelength imaging pyrometer. The utility of closed-loop control in DED is demonstrated in the context of practically inspired trapezoid-shaped stainlesssteel parts (SS 316L). We demonstrate that parts built under closed-loop control have reduced variation in porosity and uniform microstructure compared to parts built under open-loop conditions. For example, post-process characterization showed that closed-loop processed parts had a volume percent porosity ranging from 0.036% to 0.043%. In comparison, open-loop processed parts had a larger variation in volume percent porosity ranging from 0.032% to 0.068%. Further, parts built with closed-loop processing depicted consistent dendritic microstructure. By contrast, parts built with open-loop processing showed microstructure heterogeneity with the presence of both dendritic and planar grains, which in turn translated to large variation in microhardness

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scalable phononic metamaterials: Tunable bandgap design and multi-scale experimental validation

Phononic metamaterials offer unprecedented control over wave propagation, making them essential for applications such as vibration isolation, waveguiding, and acoustic filtering. However, achieving scalable and precisely tunable bandgap properties across different length scales remains challenging. This study presents a user-friendly design framework for phononic metamaterials, enabling ultra-wide bandgap tunability (B/ω c ratios up to 172 %) across multiple frequency ranges and scales. Using finite element simulations of a Yablonovite-inspired unit cell, we establish a comprehensive parametric design space that illustrates how geometric parameters, such as sphere size and beam diameter, controls bandgap width and frequency. The scalability and robustness of the framework are validated through experimental testing on additively manufactured structures at both macro (10 mm) and micro (80 µm) scales, fabricated using Stereolithography and Two-Photon Polymerization. Transmission loss measurements, conducted with piezoelectric transducers and laser vibrometry, closely match simulations in the kHz and MHz frequency ranges, confirming the reliability and consistency of the bandgap behavior across scales. This work bridges theory and experiments at multiple scales, offering a practical methodology for the rapid design of phononic metamaterials and expanding their potential for diverse applications across a broad range of frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Lifelike behavior of chemically oscillating mobile capsules

Inspired by the self-organization of unicellular species into multicellular organisms, we use theory and simulation to design a system of mobile, active microcapsules that produce chemicals according to a catalytic reaction network (CRN). In solution, the catalytic reactions generate a force that drives the flow of the surrounding fluid. The convective flow, in turn, transports the capsules to new chemical surroundings with each successive translation. Consequently, the chemical signal produced by a cluster of capsules is critically dependent on the proximity and spatial configuration of the neighboring capsules. If all of the capsules and chemical products involved in the CRN lie within sufficient proximity, then the system develops oscillatory behavior that drives the dynamic self-assembly of capsules into larger clusters that are capable of collective action. Finally, these simulations indicate potential chemo-mechanic mechanisms that enable single cellular units, such as ameba, to organize into multicellular life forms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Two-dimensional materials for bio-realistic neuronal computing networks

Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. Here we also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Robust natural nanocomposites realizing unprecedented ultrafast precise molecular separations

Synthetic polymer membranes can potentially reduce the large energy and carbon footprints that are typically associated with traditional chemical separation technologies. Unfortunately, current production protocols negate the green benefits of membrane separation. To address this bottleneck, here we report the use of natural materials monosaccharide – glucose and polydopamine and Zr-based metal organic frameworks (MOFs) to fabricate ultrathin nanocomposite membranes via interfacial polymerization reaction. The synergistic effect of these three materials on angstrom-scale molecular transport both in organic solvent and aqueous environment was elucidated using a series of complementary techniques. We demonstrate such nature-inspired nanocomposite membranes enable structural stability even in polar aprotic solvents, and unparalleled ultra-fast, low-pressure, precise separations in both nanofiltration modes, which easily surpass state-of-the-art membranes relying on unsustainable materials. Finally, the multi-functionality of saccharide nanocomposites was elegantly harnessed to impact separation applications that contribute towards a better living environment.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Functionalized separator for next-generation batteries

Advancements in battery technology have dramatically increased demand for improvements in separator design, as the separator plays a critical role in ensuring the safety and electrochemical performance of the cells. Current separators, either in commercial usage or under investigation, have yet to meet the high stability and lifespan performance standards necessary to prevent deterioration in the efficiency and reliability of the battery technologies. Recently, considerable effort has been devoted to developing functionalized separators, ranging from designing a variety of new materials and modification methods, and increasingly, to optimizing advanced preparation processes. In order to understand how the mechanisms of separator performance are affected by different properties, we will first summarize recent research progress and then have in-depth discussions regarding the separator's significant contribution to enhancing the safety and performance of the cell. Additionally, we then provide our design strategy for future separators, which not only meets the requirements of different type of batteries, but also aims for multifunctionality. We hope such a perspective could provide new inspiration in the development of separator research for future battery technologies.

25 ENERGY STORAGE↗
DOE OSTI2021

Making the most of your electrons: Challenges and opportunities in characterizing hybrid interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated hard-soft interfaces have recently evoked significant interest. Soft matter is typically dominated by structural fluctuations even at room temperature, while hard matter is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices, and metal organic frameworks to name a few, have delivered promising insights into the technologically relevant applications such as catalysis, environmental remediation, optoelectronics, and medicine. The interfacial structure between the hard and soft phases demonstrates features across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing structure–property relationships especially difficult. There are additional considerations at all stages of sample analysis from preparing electron-transparent samples to obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. Here, we discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or molecular-level understanding of these interfaces. These solutions present a host of opportunities for investigating the role interfaces play in this unique class of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Core-shell metallic alloy nanopillars-in-dielectric hybrid metamaterials with magneto-plasmonic coupling

Combining plasmonic and magnetic properties, namely magneto-plasmonic coupling, inspires great research interest and the search for magneto-plasmonic nanostructure becomes considerably critical. In this work, we designed a nanopillar-in-matrix structure with core–shell alloyed nanopillars for both BaTiO 3 (BTO)-Au 0.5 Co 0.5 (AuCo) and BTO-Au 0.25 Cu 0.25 Co 0.25 Ni 0.25 (AuCuCoNi) hybrid systems, i.e., ferromagnetic alloy cores (e.g., Co or CoNi) with plasmonic shells (e.g., Au or Au/Cu). These core–shell alloy nanopillars are uniformly embedded into a dielectric BTO matrix to form a vertically aligned nanocomposite (VAN) structure. Both hybrid systems present excellent epitaxial quality and interesting multi-functionality, e.g., high magnetic anisotropy, magneto-optical coupling response, tailorable plasmonic resonance wavelength, tunable hyperbolic properties and strong optical anisotropy. These alloyed nanopillars-in-matrix designs provide enormous potential for complex hybrid material designs with multi-functionality and demonstrate strong interface enabled magneto-plasmonic coupling along with plasmonic and magnetic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Overall, our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

42 ENGINEERING↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding effects of conductive additives in lithium-sulfur batteries

Since 2009, lithium-sulfur (Li-S) batteries have been attracting much research interest, ascribed to their high energy density and cost-effectiveness. However, their S cathodes are harassed by the poor conductivity, shuttling of lithium polysulfides (LPSs), and large volume change. In improving conductivity of S cathodes, carbon materials are widely used as conductive additives. However, there still lacks a comparative study on their geometric and structural effects in Li-S batteries. To this end, a systematic investigation is conducted on two different typical conductive additives, carbon black (CB) 1 and nitrogen-doped graphene nanosheets (N-GNS) 2 . This work reveals that, compared to the zero-dimensional (0D) CB nanoparticles, the two-dimensional (2D) N-GNS is structurally less defective and has a larger surface area. Furthermore, as a result, the 2D structure of the N-GNS helps achieve higher capacity retention but inhibits Li-ion transportation. In comparison, the 0D structure of the CB facilitates the transportation of Li-ions with a higher initial capacity but exposed to a severer shuttling behavior of LPSs. It is also found that a combination of the CB and N-GNS enables better performance of Li-S batteries, in terms of sustainable capacity, Coulombic efficiency, and rate capability. This study is inspiring for designing better S cathodes for Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Enabling a novel approach to a controlled fabrication of 1D crystalline nanowires on suspended microstructures of arbitrary geometries using two direct-writing technologies

Recent progresses in additive manufacturing have inspired new technologies, such as direct laser writing technique, based on two-photon polymerization (2 PP), which complements and further enriches the nanofabrication tools portfolio. Here, we combine 2 PP and our mask-free scanning probe assisted ‘direct-write patterning’ (DWP) method to allow for: a) the fabrication of micro-bridge structures with sub-micrometer resolution, b) selective synthesis of crystalline ZnO nanowires at predefined locations, respectively. This synergistic approach enables cantilever probe patterning of catalysts directly on suspended micro-bridges for in-situ CVD growth of nanoscale material, in a templated manner. The study reported here represents the first proof-of-concept experiments demonstrating versatile and scalable methodology, which can be applied and straightforwardly extended to grow a variety of other nanomaterials, in a controlled and selective fashion, on freestanding micro/nanoscale structures, whose size and geometry can be conveniently varied via templating of sacrificial 2 PP polymeric scaffolds. Furthermore, the demonstration of the possibility to integrate this new approach with the conventional lithography techniques provides a step forward to the development of the novel class of hybrid polymer-silicon-1D or -2D materials, and systems. The quality of the produced ZnO nanowire assemblies was assessed using several physical characterization methods.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiparametric AFM Insights into Electron Transport Mechanisms in Biomemristors

Biomemristors have attracted significant attention due to their applications in biodegradable and flexible electronic devices, and their prospective functions in information storage, neural synapses, and neuromorphic computation. Hence, understanding biomaterials' resistive switching (RS) mechanism is essential to design novel biomemristors with enhanced performance. In the last decade, various atomic force microscopy (AFM) modes, such as Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (cAFM), in situ/operando visualize the electron transport behaviors within biomemristors at the nanoscale. This review provides a comprehensive discussion of multiparametric AFM techniques to characterize biomemristors and inspire new ideas in developing next-generation consumer electronics. We also summarize the progress of revealing the internal mechanism of biomemristors with functional AFM to visualize and understand the switching behavior. Finally, the opportunities and challenges of further utilizing multiparametric AFM to explore the electron transport mechanisms in biomemristors are presented.

Shi, Chenyang↗
DOE OSTI2024

Superconductivity in CH 4 and BH – 4 containing compounds derived from the high-pressure superhydrides

Inspired by the synthesis of the high-pressure Fm3m LaH 10 superconducting superhydride, systematic density functional theory (DFT) calculations are performed to study ternaries that could be derived from it by replacing two of the hydrogen atoms with boron or carbon and varying the identity of the electropositive element. Though many of the resulting alkali-metal and alkaline-earth MC 2 H 8 phases are predicted to be dynamically stable at mild pressures, their superconducting critical temperatures (T c s) are low because their metallicity results from the filling of an electride-like band. Substitution with a trivalent element leads to phases with substantial metal d- character at the Fermi level whose T c s are typically above 40 K. Here, among the MB 2 H 8 phases examined, KB 2 H 8 , RbB 2 H 8 and CsB 2 H 8 are predicted to be dynamically stable at very mild pressures, and their stability is rationalized by a DFT-Chemical Pressure analysis that elucidates the role of the M atom size. Quantum anharmonic effects strongly affect the properties of KB 2 H 8 , the highest predicted T c compound, near 10 GPa, but molecular dynamics simulations reveal it would decompose below its T c at this pressure. Nonetheless, at ca. 50 GPa KB 2 H 8 is predicted to be thermally stable with a superconducting figure of merit surpassing that of the recently synthesized LaBeH 8 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Potassium Prussian blue-coated Li-rich cathode with enhanced lithium ion storage property

With high specific capacity, the layered Li-rich Mn-based oxide (LRMO) is a promising candidate cathode material for Li-ion batteries. However, the irreversible release of Li-ions during the first charging process, instability of LRMO/electrolyte interface and relatively low ion conductivity of LRMO result in low initial Coulombic efficiency (ICE), poor cycle stability and rate performance, which prohibit its further application. Furthermore, interface engineering via additive coating is expected to effectively address these issues. Herein, we rely on potassium Prussian blue (KPB), a Li + acceptor with good ion conductivity, as a new coating material on LRMO particles. The KPB coating not only forms a protective layer on the surface of LRMO against electrolyte corrosion, but also functions as a host for Li + transport and accommodation, leading to enhanced ion conductivity and ICE of LRMO cathode. Consequently, 2 wt% KPB coated LRMO cathode achieved an initial discharge capacity of up to 281.7 mA h g -1 with an ICE of 85.69% compared to an ICE of 79.52% for the LRMO cathode without coating. The cycling and rate performance are also greatly improved as evidenced by the well maintained capacity of up to 176.8 mA h g -1 after 100 cycles at a current density of 0.5 C, compared to the limited capacity of only 135.3 mA h g -1 for the LRMO cathode without coating. Overall, this work pioneers the use of potassium Prussian blue as additive coating material to enhance performance of LRMO cathode, and we expect it to inspire the battery community with new strategies of material engineering/design toward practical application in high-energy lithium-ion batteries.

25 ENERGY STORAGE↗