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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Colloidal Quantum Shells: An Emerging 2D Semiconductor for Energy Applications

Low-dimensional semiconductors hold strong promise for future energy applications. These nanomaterials are inexpensive to process and offer a broad spectrum of attractive quantum-mechanical properties. The notorious problem of low-dimensional nanostructures, however, lies in their limited performance under high energetic loads, when more than one exciton per particle is created. Multiple excitons undergo fast annihilation, causing efficiently roll-off in energy-intensive applications, including high-brightness LEDs, X-ray scintillators, and solar cells. In this prospective, we will highlight an emerging type of low-dimensional semiconductors that allows avoiding such multi-exciton (MX) energy losses. Recently demonstrated colloidal quantum shells benefit from the spatial separation of multiple excitons, which leads to extraordinary improvements to MX lifetimes and MX quantum yield. This makes quantum shell morphology an attractive candidate for solution-processed optical and electrical devices. In this Focus Review, we compare the optoelectronic properties of quantum shells against other low-dimensional semiconductors and discuss their emerging opportunities in solid-state lighting and energy-harvesting applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Recent Advances in Synthesis and Application of Lignin Nanoparticles

The ability to engineer material at its nanoscale has shown great potentials in overcoming significant obstacles in numerous fields. Because of its abundance, biodegradability, renewability, and eco-friendliness nature, lignin has become an ideal precursor for producing nanoscale materials from both research and industrial communities. Nanolignin, also known as colloidal lignin particle (CLP) or lignin nanoparticle (LNP), has received significant interest in recent years and its production and application in numerous fields represent an important aspect of lignin valorization. LNPs could be produced via several techniques including sonication, solvent exchange, and precipitation, which could be divided into wet and dry methods. Applications of LNPs in UV protection, cosmetics, food package, coatings, and drug delivery have been reported in the literature. Despite being extensively studied, LNPs as well as their derived materials with controlled shape and architecture are still largely underexploited. This book chapter mainly covers recent advances in the preparation of LNPs and their use in the novel and advanced applications in different areas.

Meng, Xianzhi↗
DOE OSTI2024

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

Abstract Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve andQ‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Geochemistry & Geophysics↗
DOE OSTI2025

Enhanced Weathering May Benefit From Co‐Application With Organic Amendments

Abstract Enhanced weathering has emerged as a promising natural climate solution that has the potential to remove billions of tons of carbon from the atmosphere if widely adopted in agricultural settings. Despite this potential, few field trials have been published that verify the carbon dioxide removal (CDR) potential of enhanced weathering in croplands and, until now, none had been published in grazing lands. Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) conducted the first trial of enhanced weathering in a California rangeland and showed weathering of ground silicate rocks despite drought conditions in an already dry climate. Co‐application of inorganic (silicate rocks) with organic (biochar and compost) amendments revealed not just additive, but synergistic effects whereby organic amendments increased rates of weathering. This is important because field CDR rates were <10% of the theoretical maximum (i.e., the rate if basalt was completely weathered); thus, methods to improve weathering rates will be necessary for this practice to scale in a meaningful way. Multi‐carbon pool measurements revealed not only how co‐application of soil amendments heightened net carbon benefits, but also how soil amendments complemented each other to produce net benefits for soil carbon, biomass growth, and greenhouse gas emission reductions. Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) produce new insights toward our understanding of enhanced weathering as well as introduce paths for future research concerning combined amendment applications, synergistic mechanisms for carbon storage, and deployment in various agricultural contexts. While questions remain about the fate of weathering products in arid regions, Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) present novel findings on the potential for significant weathering to occur even under suboptimal conditions.

Almaraz, Maya [Yale Center for Natural Carbon Capt↗
DOE OSTI2022

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2024

eReaxFF force field development for BaZr 0.8 Y 0.2 O 3-δ solid oxide electrolysis cells applications

The use of solid-oxide materials in electrocatalysis applications, especially in hydrogen-evolution reactions, is promising. However, further improvements are warranted to overcome the fundamental bottlenecks to enhancing the performance of solid-oxide electrolysis cells (SOECs), which is directly linked to the more-refined fundamental understanding of complex physical and chemical phenomena and mass exchanges that take place at the surfaces and in the bulk of electrocatalysis materials. Here, we developed an eReaxFF force field for barium zirconate doped with 20 mol% of yttrium, BaZr 0.8 Y 0.2 O 3-δ (BZY20) to enable a systematic, large-length-scale, and longer-timescale atomistic simulation of solid-oxide electrocatalysis for hydrogen generation. All parameters for the eReaxFF were optimized to reproduce quantum-mechanical (QM) calculations on relevant condensed phase and cluster systems describing oxygen vacancies, vacancy migrations, electron localization, water adsorption, water splitting, and hydrogen generation on the surfaces of the BZY20 solid oxide. Using the developed force field, we performed both zero-voltage (excess electrons absent) and non-zero-voltage (excess electrons present) molecular dynamics simulations to observe water adsorption, water splitting, proton migration, oxygen-vacancy migrations, and eventual hydrogen-production reactions. Based on investigations offered in the present study, we conclude that the eReaxFF force field-based approach can enable computationally efficient simulations for electron conductivity, electron leakage, and other non-zero-voltage effects on the solid oxide materials using the explicit-electron concept. Moreover, we demonstrate how the eReaxFF force field-based atomistic-simulation approach can enhance our understanding of processes in SOEC applications and potentially other renewable-energy applications.

08 HYDROGEN↗
DOE OSTI2025

Imaging and spatially resolved mass spectrometry applications in nephrology

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. Further, the complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States

Abstract Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A new generation of direct X-ray detectors for medical and synchrotron imaging applications

Abstract Large-area X-ray imaging is one of the most widely used imaging modalities that spans several scientific and technological fields. Currently, the direct X-ray conversion materials that are being commercially used for large-area (> 8 cm × 4 cm without tiling) flat panel applications, such as amorphous selenium (a-Se), have usable sensitivities of up to only 30 keV. Although there have been many promising candidates (such as polycrystalline HgI 2 and CdTe), none of the semiconductors were able to assuage the requirement for high energy (> 40 keV) large-area X-ray imaging applications due to inadequate cost, manufacturability, and long-term performance metrics. In this study, we successfully demonstrate the potential of the hybrid Methylammonium lead iodide (MAPbI 3 ) perovskite-based semiconductor detectors in satisfying all the requirements for its successful commercialization in synchrotron and medical imaging. This new generation of hybrid detectors demonstrates low dark current under electric fields needed for high sensitivity X-ray imaging applications. The detectors have a linear response to X-ray energy and applied bias, no polarization effects at a moderate bias, and signal stability over long usage durations. Also, these detectors have demonstrated a stable detection response under BNL’s National Synchrotron Light Source II (NSLS-II) 70 keV monochromatic synchrotron beamline.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Enabling deeper learning on big data for materials informatics applications

Abstract The application of machine learning (ML) techniques in materials science has attracted significant attention in recent years, due to their impressive ability to efficiently extract data-driven linkages from various input materials representations to their output properties. While the application of traditional ML techniques has become quite ubiquitous, there have been limited applications of more advanced deep learning (DL) techniques, primarily because big materials datasets are relatively rare. Given the demonstrated potential and advantages of DL and the increasing availability of big materials datasets, it is attractive to go for deeper neural networks in a bid to boost model performance, but in reality, it leads to performance degradation due to the vanishing gradient problem. In this paper, we address the question of how to enable deeper learning for cases where big materials data is available. Here, we present a general deep learning framework based on Individual Residual learning (IRNet) composed of very deep neural networks that can work with any vector-based materials representation as input to build accurate property prediction models. We find that the proposed IRNet models can not only successfully alleviate the vanishing gradient problem and enable deeper learning, but also lead to significantly (up to 47%) better model accuracy as compared to plain deep neural networks and traditional ML techniques for a given input materials representation in the presence of big data.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High flux novel polymeric membrane for renal applications

Biocompatibility and the ability to mediate the appropriate flux of ions, urea, and uremic toxins between blood and dialysate components are key parameters for membranes used in dialysis. Oxone-mediated TEMPO-oxidized cellulose nanomaterials have been demonstrated to be excellent additives in the production and tunability of ultrafiltration and dialysis membranes. In the present study, nanocellulose ionic liquid membranes (NC-ILMs) were tested in vitro and ex vivo. An increase in flux of up to two orders of magnitude was observed with increased rejection (about 99.6%) of key proteins compared to that of polysulfone (PSf) and other commercial membranes. NC-ILMs have a sharper molecular weight cut-off than other phase inversion polymeric membranes, allowing for high throughput of urea and a uremic toxin surrogate and limited passage of proteins in dialysis applications. Superior anti-fouling properties were also observed for the NC-ILMs, including a > 5-h operation time with no systemic anticoagulation in blood samples. Finally, NC-ILMs were found to be biocompatible in rat ultrafiltration and dialysis experiments, indicating their potential clinical utility in dialysis and other blood filtration applications. These superior properties may allow for a new class of membranes for use in a wide variety of industrial applications, including the treatment of patients suffering from renal disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

ToF-SIMS evaluation of PEG-related mass peaks and applications in PEG detection in cosmetic products

Polyethylene glycols (PEGs) are used in industrial, medical, health care, and personal care applications. The cycling and disposal of synthetic polymers like PEGs pose significant environmental concerns. Detecting and monitoring PEGs in the real world calls for immediate attention. This study unveils the efficacy of time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a reliable approach for precise analysis and identification of reference PEGs and PEGs used in cosmetic products. By comparing SIMS spectra, we show remarkable sensitivity in pinpointing distinctive ion peaks inherent to various PEG compounds. Moreover, the employment of principal component analysis effectively discriminates compositions among different samples. Notably, the application of SIMS two-dimensional image analysis visually portrays the spatial distribution of various PEGs as reference materials. The same is observed in authentic cosmetic products. The application of ToF-SIMS underscores its potential in distinguishing PEGs within intricate environmental context. ToF-SIMS provides an effective solution to studying emerging environmental challenges, offering straightforward sample preparation and superior detection of synthetic organics in mass spectral analysis. These features show that SIMS can serve as a promising alternative for evaluation and assessment of PEGs in terms of the source, emission, and transport of anthropogenic organics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unravelling the room temperature growth of two-dimensional h-BN nanosheets for multifunctional applications

The room temperature growth of two-dimensional van der Waals (2D-vdW) materials is indispensable for state-of-the-art nanotechnology. Low temperature growth supersedes the requirement of elevated growth temperatures accompanied with high thermal budgets. Moreover, for electronic applications, low or room temperature growth reduces the possibility of intrinsic film-substrate interfacial thermal diffusion related deterioration of the functional properties and the consequent deterioration of the device performance. Here, we demonstrated the growth of ultrawide-bandgap boron nitride (BN) at room temperature by using the pulsed laser deposition (PLD) process, which exhibited various functional properties for potential applications. Comprehensive chemical, spectroscopic and microscopic characterizations confirmed the growth of ordered nanosheet-like hexagonal BN (h-BN). Functionally, the nanosheets show hydrophobicity, high lubricity (low coefficient of friction), and a low refractive index within the visible to near-infrared wavelength range, and room temperature single-photon quantum emission. In conclusion, our work unveils an important step that brings a plethora of potential applications for these room temperature grown h-BN nanosheets as the synthesis can be feasible on any given substrate, thus creating a scenario for “h-BN on demand” under a frugal thermal budget.

2D h-BN↗
DOE OSTI2025

Epoxy-based vitrimeric semi-interpenetrating network/MXene nanocomposites for hydrogen gas barrier applications

Herein, we report MXene-filled epoxy-based vitrimeric nanocomposites featuring a semi-interpenetrating network (S-IPN) to develop a hydrogen gas (H 2 ) barrier coating with self-healing characteristics for compressed H 2 storage applications. The reversible epoxy network was formed by synthesizing linear epoxy chains with pendent bis-hydroxyl groups using amino diol, which were then crosslinked with 1,4-benzenediboronic acid to generate dynamic boronic ester linkages. To achieve the S-IPN-type molecular arrangement, the epoxy chains were in situ crosslinked in the presence of poly(ethylene-co-vinyl alcohol) (EVOH), giving rise to a self-healing network (EEP) with a healing efficiency of 87%. Into the S-IPN vitrimer (EEP), a 2D platelet-type nanofiller MXene was incorporated to introduce a tortuous path for H 2 gas diffusion along with improved mechanical properties. The nanocomposite coating was applied to nylon 6 liner material, which is conventionally used in all-composite H 2 storage vessels. Further, the application of a 2 wt% MXene/EEP nanocomposite coating showed a permeability coefficient of 0.062 cm 3 mm m -2 d -1 atm -1 exhibiting ~96% reduction in gas permeability compared to uncoated nylon 6. The same nanocomposite exhibited a healing efficiency of 79%. Increasing the MXene loading to 10 wt% further reduced the permeability coefficient to 0.002 cm 3 mm m -2 d -1 atm -1 ; however, the healing efficiency decreased due to restricted chain mobility. In essence, the current work highlights the potential of vitrimeric S-IPN nanocomposite coatings for H 2 gas-barrier applications, enhancing safety and performance.

42 ENGINEERING↗
DOE OSTI2025

Bandgap engineering of SrZrS 3 chalcogenide perovskite via substitutional doping for photovoltaic applications: a first-principles DFT study

Strontium zirconium sulfide (SrZrS 3 ) has garnered significant attention for photovoltaic (PV) applications due to its excellent optoelectronic properties, high chemical and moisture stability, and non-toxicity. However, the bandgaps of both the α- and β-phases lie outside the optimum ranges for both single-junction solar cells (SJSCs) and tandem solar cells (TSCs), thereby limiting their applications in PV technologies. In this study, we employed hybrid density functional theory to engineer the band gaps of α- and β-SrZrS 3 through substitutional doping. We considered three dopants (Hf, Sn, and Ti) at the Zr site of SrZrS 3 with varying doping concentrations and investigated their effects on the structural, electronic, and optical properties of the materials. We found that Sn and Ti doping effectively lowers the band gaps of both α- and β-SrZrS 3 , whereas Hf doping increases them. For x values up to 0.25, the band gaps of the α-SrZr 1−x Sn x S 3 and α-SrZr 1−x Ti x S 3 are within the optimum range for SJSCs, and those of β-SrZr 1−x Sn x S 3 and β-SrZr 1−x Ti x S 3 lie within the optimum range for Si/perovskite as well as perovskite/perovskite TSCs. The three dopants exhibited significant effects on the optical properties of both α- and β-SrZrS 3 , including the absorption coefficient, energy-loss functions, reflectivity, and refractivity spectra. Thermodynamic stability analysis revealed that for both phases, SrZr 1−x Hf x S 3 can be synthesized via exothermic processes, whereas the formation of SrZr 1−x Ti x S 3 and SrZr1−xSn x S 3 is endothermic and hence, not thermodynamically favorable. Further analysis showed that SrZr 1−x Ti x S 3 in both α- and β-phases are stable under thermodynamic equilibrium conditions, whereas SrZr 1−x Sn x S 3 is prone to dissociation into ternary phases (SrZrS 3 and SrSnS 3 ), especially at higher doping concentrations. These results show that Ti doping is effective in tuning the band gaps of α- and β-SrZrS 3 toward the optimal values for PV applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Investigation of electrode passivation during oxidation of a nitroxide radical relevant for flow battery applications

Nitroxide-radicals such as 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) and their derivatives have gained interest as redox-active organic molecules for applications in grid-scale energy storage. In particular, the higher solubility of 4-hydroxy-TEMPO in aqueous media greatly improves its energy density, but unusual kinetics associated with its surface-mediated electrooxidation have limited further development. Here, the apparent passivation behavior of species formed during 4-hydroxy-TEMPO electrooxidation in concentrated electrolytes is investigated. A combination of surface microscopy, X-ray photoelectron spectroscopy, and quartz-crystal gravimetry confirms the formation of a polymeric-type layer over the electrode surface composed of 4-hydroxy-TEMPO-like subunits, which is otherwise not observed with TEMPO. This study indicates that the design of high energy density and stable TEMPO-based redox molecules must also consider the reactivity that may occur due to the molecular characteristics of solubility-enhancing moieties. It is found that the extent of passivation is dependent on the voltage scan rate and 4-hydroxy-TEMPO concentration, underscoring the importance of studying materials at conditions relevant for their proposed applications. Evidence of incomplete passivation and an electrode self-cleaning process is presented, suggesting a materials design strategy to mitigate surface passivation from side reactions that may occur in redox active materials for energy storage applications.

Buchanan, Cailin [Argonne National Laboratory (ANL↗
DOE OSTI2026

Hydrogen applications in airport operations: a review using the Port Authority of New York and New Jersey as an illustrative airport system

Airports combine aircraft propulsion, ground operations, stationary power systems, and fuel logistics in ways that make emissions reduction technically and operationally complex. Existing studies often assess hydrogen applications in these areas separately, limiting understanding of the shared infrastructure, safety, and operational constraints that shape airport deployment. This review evaluates hydrogen across three airport-relevant operational domains: aviation propulsion, ground support equipment and vehicles, and stationary power systems. Within aviation propulsion, the review examines sustainable aviation fuel production and hydrogen-powered aircraft as two distinct hydrogen-relevant pathways. The Port Authority of New York and New Jersey is used as an illustrative airport system to relate the literature to a real operating context. Drawing on peer-reviewed studies, technical reports, demonstration projects, and public operational information, the review also includes screening-level calculations of hydrogen demand and potential CO 2 e reductions for selected applications. The findings show that hydrogen's role is highly application-specific. Near-term opportunities are strongest where hydrogen serves as a low-carbon process input, supports selected high-utilization ground equipment, or contributes to resilient stationary power-system configurations. Hydrogen-powered aircraft remain a longer-term option because storage, fueling infrastructure, certification, cost, and NO x management continue to constrain deployment. Across all domains, infrastructure readiness, fuel logistics, safety requirements, and leakage management emerge as recurring determinants of viability. Future research should focus on cross-domain infrastructure planning, comparative assessment of hydrogen against alternative pathways, improved treatment of leakage and non-CO 2 effects, and clearer safety and regulatory frameworks for airport deployment.

08 HYDROGEN↗
DOE OSTI2020

Four-phase interleaved TCM DC-DC buck converter with matrix inductor in battery charging application

In this paper, a 1-kW DC-DC buck converter with a four-phase interleaved matrix inductor is proposed for battery charging applications. It is well-known that the DC bias on the inductor will cause high core loss as it changes the B–H characteristic. Typically, the transient conduction mode employed in high voltage applications for zero-voltageswitching of devices would cause higher inductor current ripple. The conventional approach to reduce the effect of DC bias and inductor current ripple is employing multi-phases. However, the cost and size of the converter will increase significantly. This paper proposes the matrix inductor which has a small volume and reduces the effect of the DC bias by flux sharing and flux cancellation at the same time, results in low inductor core loss. With the interleaved operations the output current ripple can be lower which is suitable for battery charging application. Besides, the comparison of the synchronous and interleaved operation is presented. A 1-kW prototype is built and the experimental results show that the peak efficiency is 99.1% and 99.2% for synchronous and interleaved control, respectively. Additionally, the output current ripple of the interleaved operation is reduced by 85% in comparison with the synchronous operation.

14 SOLAR ENERGY↗