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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Exploring an ‘ideal hill': how lithology and transport mechanisms affect the possibility of a steady state during weathering and erosion

We introduce a model of chemical reaction within hills to explore how evolving porosity (and by inference, permeability) affects flow pathways and weathering. The model consists of hydrologic and reactive-transport equations that describe alteration of ferrous minerals and feldspar. These reactions were chosen because previous work emphasized that oxygen- and acid-driven weathering affects porosity differently in felsic and mafic rocks. A parameter controlling the order of the fronts is presented. In the absence of erosion, the two reaction fronts move at different velocities and the relative depths depend on geochemical conditions and starting composition. In turn, the fronts and associated changes in porosity drastically affect both the vertical and lateral velocities of water flow. For these instances, estimates of weathering advance rates based on simple models that posit unidirectional constant-velocity advection do not apply. In the model hills, weathering advance rates diminish with time as the Darcy velocities decrease with depth. The system can thus attain a dynamical steady state at any erosion rate where the regolith thickness is constant in time and velocities of both fronts become equal to one another and to the erosion rate. The slower the advection velocities in a system, the faster it attains a steady state. For example, a massive rock with relatively fast-dissolving minerals such as diabase -- where solute transport across the reaction front mainly occurs by diffusion -- can reach a steady state more quickly than granitoid rocks in which advection contributes to solute transport. The attainment of a steady state is controlled by coupling between weathering and hydrologic processes that force water to flow horizontally above reaction fronts where permeability changes rapidly with depth and acts as a partial barrier to fluid flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Prediction of Probabilistic Detonation Threshold via Millimeter-Scale Microstructure-Explicit and Void-Explicit Simulations

We present an approach and relevant models for predicting the probabilistic shoc-to-detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure-explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro-1,3,5,7-tetranitro-1,2,3,5-tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical-thermal-chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank-ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run-distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

PtCoO 2 for Scaled Interconnects

Copper (Cu) interconnects are an increasingly important bottleneck in integrated circuits due to energy consumption and latency caused by the notable increase in Cu resistivity as dimensions decrease, primarily due to electron scattering at surfaces. Herein, the potential of a directional conductor, PtCoO 2 , which has a low bulk resistivity and a distinctive anisotropic structure that mitigates electron surface scattering is showcased. Thin films of PtCoO 2 of various thicknesses are synthesized by molecular beam epitaxy (MBE) coupled with a postdeposition annealing process and the superior quality of PtCoO 2 films is demonstrated by multiple characterization techniques. The thickness‐dependent resistivity curve illustrates that PtCoO 2 significantly outperforms effective Cu (Cu with TaN barriers) and Ru in resistivity below 20.0 nm with a more than 6x reduction compared to effective Cu below 6.0 nm, having a value of only 6.32 μΩ cm at 3.3 nm. It is determined that grain boundary scattering can still be improved for even lower resistivities in this material system through a combination of experiments and theoretical simulations. PtCoO 2 is therefore a highly promising alternative material for future interconnect technologies promising lower resistivities, better stability, and significant improvements in energy efficiency and latency for advanced integrated circuits.

Li, Yansong [Department of Electrical Engineering ↗
DOE OSTI2026

Towards gradient multimaterial toolpath generation for direct ink writing with connected fermat spirals

This work describes advances towards a reproducible, parametrically defined algorithm for generating graded multimaterial toolpaths for direct ink writing. Expanding on the existing Fermat space-filling algorithm and coupling with image-driven processing techniques, we demonstrate the fabrication of multimaterial structures. Here, material composition is encoded within toolpaths by parsing hue values from a multi-colored image. By performing dynamic velocity compensation based on local curvature and Euclidean distance filtering, internal voids are mitigated while optimizing print fidelity. Here, the work opens new avenues for designing complex toolpaths with locally programmable composition.

3D Printing↗
DOE OSTI2023

Activity gradient mass transport accelerated corrosion of stainless steel in molten salt

Advanced energy systems based on molten salt technologies have gained increasing interest, and their design and construction are likely going to involve the use of materials of dissimilar chemistries. With dissimilar materials being used, galvanic coupling induced corrosion acceleration is one of the mechanisms believed to be an issue for the deployment of molten salt systems. However, non-galvanic interaction mechanisms such as activity gradient mass transport have also been theorized to represent a potential challenge. Unfortunately, the two effects have often been compounded in the literature, such that it is still unclear which degradation mechanisms are at play in these systems. In the following study, electrochemical measurements are used to predict the effect that galvanic coupling would have on dissimilar materials submerged in the same molten salt medium. Dissimilar material salt exposure tests are then performed to investigate whether galvanic coupling or activity gradient driven processes account for the levels of materials degradation observed. Finally, these separate effect electrochemical and corrosion experiments uniquely elucidate the degradation mechanisms in dissimilar materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On the validity and limitations of 1D model for heat and mass transfer performance evaluation in a multilayer binder-free desiccant dehumidifier: isothermal dehumidification with internal cooling

Efficient humidity control is essential for maintaining indoor thermal comfort, yet conventional vapor-compression-based dehumidifiers are energy-intensive. Employing separate sensible and latent cooling through desiccant-coated heat exchangers (DCHEs) combined with evaporative coolers offers energy savings of up to 80 % compared to conventional systems. However, the dehumidification performance of DCHEs remains limited due to the use of polymer binders for coating desiccant materials onto heat exchange surfaces. In our previous study, we developed a multilayer fixed-bed binder-free desiccant dehumidifier (MFBDD) that demonstrated high dehumidification capacity and low pressure drop compared to rotary desiccant wheels. Nevertheless, its potential for further enhancement through internal cooling and the use of step-shaped adsorption isotherms has not been explored. In this study, a physics-based one-dimensional (1D) transient model is developed and validated to capture the coupled heat and mass transfer processes in the MFBDD and extended to simulate internal cooling using a high-capacity composite metal–organic framework, MIL-101/GO-6 (water uptake ≈1.6 g/g within 35–47 % RH). The model enables detailed analysis of local air and bed temperature dynamics and quantifies how internal cooling affects the dehumidification performance under a wide range of operating conditions. Results show that integrating internal cooling and using MIL-101/GO-6 enhance mass adsorbed, moisture removal capacity, and dehumidification effectiveness by 50 %–99 % compared with the M.S. Gel baseline. The study further reveals that achieving near-isothermal operation requires simultaneous enhancement of the convective heat transfer coefficient and heat exchange surface area. In conclusion, this work provides the first detailed physical insight into the interplay between internal cooling and step-shaped isotherms in a binder-free desiccant device and establishes a validated modeling framework for scaling up and system-level performance evaluation of next-generation energy-efficient dehumidification systems.

Heat and mass transfer↗
DOE OSTI2025

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗
DOE OSTI2021

Materials Fingerprinting Classification

Significant progress in many classes of materials could be made with the availability of experimentally-derived large datasets composed of atomic identities and three-dimensional coordinates. Methods for visualizing the local atomic structure, such as atom probe tomography (APT), which routinely generate datasets comprised of millions of atoms, are an important step in realizing this goal. However, state-of-the-art APT instruments generate noisy and sparse datasets that provide information about elemental type, but obscure atomic structures, thus limiting their subsequent value for materials discovery. The application of a materials fingerprinting process, a machine learning algorithm coupled with topological data analysis, provides an avenue by which here-to-fore unprecedented structural information can be extracted from an APT dataset. As a proof of concept, the material fingerprint is applied to high-entropy alloy APT datasets containing body-centered cubic (BCC) and face-centered cubic (FCC) crystal structures. A local atomic configuration centered on an arbitrary atom is assigned a topological descriptor, with which it can be characterized as a BCC or FCC lattice with near perfect accuracy, despite the inherent noise in the dataset. Finally, this successful identification of a fingerprint is a crucial first step in the development of algorithms which can extract more nuanced information, such as chemical ordering, from existing datasets of complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heat and mass transfer during a sudden loss of vacuum in a liquid helium cooled tube - Part III: Heat deposition in He II

A sudden loss of vacuum can be catastrophic for superconducting particle accelerators. In such an event, air leaks into the liquid-helium-cooled accelerator beamline tube and condenses on its inner surface, causing rapid boiling of the helium and dangerous pressure build-up. Understanding the coupled heat and mass transfer processes is important for the design of the beamline cryogenic system. Our past experimental study on nitrogen gas propagating in a copper tube cooled by normal liquid helium (He I) has revealed a nearly exponential slowing down of the gas front. A theoretical model that accounts for the interplay of the gas dynamics and the condensation was developed, which successfully reproduced various key observations. However, since many accelerator beamlines are actually cooled by superfluid helium (He II) in which the heat transfer is via a non-classical thermal counterflow mode, we need to extend our work to the He II cooled tube. This paper reports our systematic measurements using He II and the numerical simulations based on a modified model that accounts for the He II heat-transfer characteristics. By tuning the He II peak heat-flux parameter in our model, we have reproduced the observed gas dynamics in all experimental runs. The fine-tuned model is then utilized to reliably evaluate the heat deposition in He II. Finallly, this work not only advances our understanding of condensing gas dynamics but also has practical implications to the design codes for beamline safety.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

High capacity Li/Ni rich Ni-Ti-Mo oxide cathode for Li-ion batteries

With the rising cost and insufficient supply of cobalt, the thrust for cobalt-free cathode materials with the high specific capacity to build Li-ion batteries has increased significantly. Using nickel as the prime electrochemical active species, we have synthesized a new-class of materials with the combination of ordered and disordered phases. To obtain high capacity and electrical charge neutrality, stoichiometry of cations designed in a way that it forms Li/Ni rich Ni-Ti-Mo oxide materials. In addition to conventional capacity from redox activity of transition metals, partially reversible oxygen redox reaction also contributes to electrochemical activity and thus results in unusual high capacity. The resultant cathode materials of LiNi 0.5 Ti 0.5 O 2 -(Li 4 MoO 5 ) 0.8 and LiNiO 2 mixture phases reach the specific capacity of 240 mAh/g. Detailed soft X-ray absorption spectroscopy and electron microscopy are used to reveal the crystal phases in this system and trace changes in the Ni 2+ /Ni 4+ redox couple during charge-discharge processes. Finally, such comprehensive analysis of ordered-disordered oxides suggesting potentiality to develop high-capacity cobalt-free cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Investigation of Low-Energy Lattice Dynamics and Their Role in Superionic Na Diffusion and Ultralow Thermal Conductivity of Na 3 PSe 4 as a Solid-State Electrolyte

The atomic dynamics of Na 3 PSe 4 were investigated using a combination of neutron scattering experiments and ab initio and machine-learned molecular dynamics simulations to probe the interplay of fast ionic diffusion with atomic vibrations (phonons) of the host lattice. Our results reveal the existence of low-energy vibrational modes, simultaneously involving motions of Na + ions and framework polyanion subunits, and show that these modes become strongly overdamped in the superionic regime as they couple with the Na + hopping process. In particular, the Na+ migration energy landscape is strongly impacted by low-energy phonons derived from a soft acoustic branch of the host lattice, which modulates the diameter of the Na + diffusion channel at the bottleneck. We find that an additional factor for the enhanced Na + conductivity in Na 3 PSe 4 is the presence of Na-vacancies, which also affect the low-frequency dynamics and thermal vibration amplitudes, pointing to an interplay between Na + vacancies and host dynamics, jointly enhancing ionic diffusivity. Finally, we investigate the origin of ultralow thermal conductivities in Na 3 PSe 4 and Na 3 PS 4 using Green–Kubo simulations and find that low-energy acoustic phonon modes of the overall crystal framework provide a dominant contribution to the thermal conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Mechanism and Reaction Energy Landscape for Apiose Cross-Linking by Boric Acid in Rhamnogalacturonan II

Rhamnogalacturonan II (RG-II)—the most complex polysaccharide known in nature—exists as a borate cross-linked dimer in the plant primary cell wall. Boric acid facilitates the formation of this cross-link on the apiosyl residues of RG-II’s side chain A. Here, we detail the reaction mechanism for the cross-linking process with ab initio calculations coupled with transition state theory. We determine the formation of the first ester linkage to be the rate-limiting step of the mechanism. Our findings demonstrate that the regio- and stereospecific nature of subsequent steps in the reaction itinerary presents four distinct energetically plausible reaction pathways. This has significant implications for the overall structure of the cross-linked RG-II dimer assembly. Finally, our transition state and reaction path analyses reveal key geometric insights that corroborate previous experimental hypotheses on borate ester formation reactions.

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

Modulating Poly(oligocyclobutane) Properties Through Backbone Modifications

Poly(1,n′-divinyl)oligocyclobutane (pDVOCB) has emerged as a class of poly(cycloolefin) that is amenable to chemical recycling and demonstrates promising thermomechanical properties. However, their high melting temperatures coupled with insolubility makes melt processing challenging due to thermo-oxidation of internal alkenes. To address these issues, we describe a series of polymers incorporating modifications to the pDVOCB backbone and analyze the effects on material stability and processability. Intentional migration of the internal 1,2-disubstituted alkenes to an exocyclic trisubstituted position yields isomerized pDVOCB (IpDVOCB) which exhibits a depression of thermal transitions by up to 50 °C. Conversely, elimination of stereoirregularity between enchained DVOCB oligomers through alkene saturation yields hydrogenated pDVOCB (HpDVOCB), resulting in elevated thermal transitions by up to 30 °C. Furthermore, these shifts are attributed to changes in crystal defect density which is strongly influenced by chain stereoregularity. Understanding these behaviors guides future polymer design and expands the control and use of this new class of recyclable poly(cycloolefin)s.

Differential scanning calorimetry↗
DOE OSTI2023

Reaction Current Heterogeneity at the Interface between a Lithium Electrode and Polymer/Ceramic Composite Electrolytes

Although lithium metal anodes are expected to increase the energy density of next-generation batteries, dendrite growth during charge remains a major bottleneck preventing widespread implementation. Composite solid electrolytes with ceramic particles embedded in a polymer matrix have the potential to prevent dendrites owing to the higher mechanical stiffness while also possessing the flexibility to maintain contact with the electrode. However, microscopically, the different mechanical and electrochemical properties of the polymer and ceramic domains can cause inhomogeneous charge transfer at the Li/electrolyte interface, which can lead to nonuniform Li deposition and propagation of dendrites. Here, we computationally examine the coupled electrochemical, transport, and mechanical processes at the interface to determine the propensity for dendrite formation and possible approaches to mitigate this issue. Predictions of two possible microstructures at the interface, namely, (i) where both the polymer and ceramic come in contact with Li metal and (ii) when only the polymer comes in contact with Li metal, suggest that the former has a greater tendency for nonuniform plating. In addition, predictions suggest that minimizing the interfacial resistance between polymers and ceramics and incorporating interlayers between the electrode and electrolyte help mitigate current heterogeneity. In conclusion, these predictions provide guidance for experimental approaches to prevent dendrites in composite electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2024

Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning

Recently, rainfall-runoff simulations in small headwater basins have been improved by methodological advances such as deep neural networks (NNs) and hybrid physics-NN models—particularly, a genre called differentiable modeling that intermingles NNs with physics to learn relationships between variables. However, hydrologic routing simulations, necessary for simulating floods in stem rivers downstream of large heterogeneous basins, had not yet benefited from these advances and it was unclear if the routing process could be improved via coupled NNs. We present a novel differentiable routing method (δMC-Juniata-hydroDL2) that mimics the classical Muskingum-Cunge routing model over a river network but embeds an NN to infer parameterizations for Manning's roughness (n) and channel geometries from raw reach-scale attributes like catchment areas and sinuosity. The NN was trained solely on downstream hydrographs. Synthetic experiments show that while the channel geometry parameter was unidentifiable, n can be identified with moderate precision. With real-world data, the trained differentiable routing model produced more accurate long-term routing results for both the training gage and untrained inner gages for larger subbasins (>2,000 km2) than either a machine learning model assuming homogeneity, or simply using the sum of runoff from subbasins. The n parameterization trained on short periods gave high performance in other periods, despite significant errors in runoff inputs. The learned n pattern was consistent with literature expectations, demonstrating the framework's potential for knowledge discovery, but the absolute values can vary depending on training periods. The trained n parameterization can be coupled with traditional models to improve national-scale hydrologic flood simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities

Abstract Viruses are abundant yet understudied members of soil environments that influence terrestrial biogeochemical cycles. Here, we characterized the dsDNA viral diversity in biochar-amended agricultural soils at the preplanting and harvesting stages of a tomato growing season via paired total metagenomes and viral size fraction metagenomes (viromes). Size fractionation prior to DNA extraction reduced sources of nonviral DNA in viromes, enabling the recovery of a vaster richness of viral populations (vOTUs), greater viral taxonomic diversity, broader range of predicted hosts, and better access to the rare virosphere, relative to total metagenomes, which tended to recover only the most persistent and abundant vOTUs. Of 2961 detected vOTUs, 2684 were recovered exclusively from viromes, while only three were recovered from total metagenomes alone. Both viral and microbial communities differed significantly over time, suggesting a coupled response to rhizosphere recruitment processes and/or nitrogen amendments. Viral communities alone were also structured along an 18 m spatial gradient. Overall, our results highlight the utility of soil viromics and reveal similarities between viral and microbial community dynamics throughout the tomato growing season yet suggest a partial decoupling of the processes driving their spatial distributions, potentially due to differences in dispersal, decay rates, and/or sensitivities to soil heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Demonstration of a MOT in a sub-millimeter membrane hole

Abstract We demonstrate the generation of a cold-atom ensemble within a sub-millimeter diameter hole in a transparent membrane, a so-called “membrane MOT”. With a sub-Doppler cooling process, the atoms trapped by the membrane MOT are cooled down to 10 $$\upmu$$ μ K. The atom number inside the unbridged/bridged membrane hole is about $$10^4$$ 10 4 to $$10^5$$ 10 5 , and the $$1/e^2$$ 1 / e 2 -diameter of the MOT cloud is about 180 $$\upmu$$ μ m for a 400 $$\upmu$$ μ m-diameter membrane hole. Such a membrane device can, in principle, efficiently load cold atoms into the evanescent-field optical trap generated by the suspended membrane waveguide for strong atom-light interaction and provide the capability of sufficient heat dissipation at the waveguide. This represents a key step toward the photonic atom trap integrated platform (ATIP).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Investigations of the stability of GaAs for photoelectrochemical H 2 evolution in acidic or alkaline aqueous electrolytes

The long-term stability of p-GaAs photocathodes has been investigated for the hydrogen-evolution reaction (HER) in contact with either 1.0 M H 2 SO 4 (aq) or 1.0 M KOH(aq). Stability for the HER was evaluated using p-GaAs electrodes that were either etched or coated with active HER catalysts (Pt and CoP). Changes in surface characteristics of GaAs after exposure to electrochemical conditions were monitored by X-ray photoelectron spectroscopy (XPS), and electrode dissolution processes were evaluated by inductively coupled plasma mass spectrometry (ICP-MS). Consistent with thermodynamic predictions, after operation of the HER at pH 0 or pH 14, illuminated etched p-GaAs electrodes exhibited minimal dissolution while preserving a nearly stoichiometric surface. Electrodeposition or sputtering of Pt on the p-GaAs surface promoted the formation of excess As 0 via an interfacial reaction during the HER. The resulting non-stoichiometric As 0 -rich surface of p-GaAs/Pt electrodes caused a loss in photoactivity as well as substantial cathodic dark current. In contrast, p-GaAs electrodes coated with thin-film CoP catalysts did not display an increase in surficial As 0 after operation of the HER in acidic electrolytes. Minimization of deleterious interfacial reactions is thus critical to obtain extended stability in conjunction with high performance from p-GaAs photocathodes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗