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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Water in Solutions of Chaotropic and Kosmotropic Salts: A Differential Scanning Calorimetry Investigation

We report the use of aqueous phase separations via aqueous biphasic systems (ABS) has been widely explored in the recent decades. For wider and more “intelligent” applications, it is important to look below the surface and study these systems thoroughly at a fundamental level. Two important questions still unsolved are how do polymers and ions of different types organize water (if they in fact they do so) and how does it affect the separation of phases? In the present work, differential scanning calorimetry (DSC) was used to relate ABS phase diagrams and the behavior of water in aqueous solutions containing kosmotropic salts (K 3 PO 4 or (NH 4 ) 2 SO 4 ), a chaotropic ionic liquid ([C 4 mim]Cl), or a polymer (PEG-2000), all of which are reported components of ABS, and their mixtures. Additional DSC transitions were observed for the two classes of salts which could be assigned based on the fundamental differences between their interactions with water, suggesting that it is the differences in the abilities of kosmotropic and chaotropic salts to interact with water which result in the phase separation phenomena observed. The DSC measurements of solutions of PEG-2000 and (NH 4 ) 2 SO 4 indicate that aqueous solutions of PEG-2000 supercool and potentially enter a glassy state that exhibits devitrification upon heating. The devitrified state exhibits a clear eutectic with water. Mixtures of the polymer and salt continue to exhibit all the features observed for the pure components. These results suggest that the mixtures are phase separated and consist of largely separate concentrated solutions of PEG-2000 and (NH 4 ) 2 SO 4 , indicating an entropy-driven phase separation. The DSC analysis of these systems further refines the understanding of kosmotropic and chaotropic solutes into more specific phenomena for each compound. Lastly, this work suggests that DSC can be used to understand the role of each salt/component in ABS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Structural Differentiation between Layered Single (Ni) and Double Metal Hydroxides (Ni–Al LDHs) Using Wavelet Transformation

Layered double hydroxides (LDHs) are anionic clays important in disciplines such as environmental chemistry, geochemistry, and materials science. Developments in signal processing of extended X-ray absorption fine structure (EXAFS) data, such as wavelet transformation (WT), have been used to identify transition metals and Al present in the hydroxide sheets of LDHs. The WT plots of LDHs should be distinct from those of isostructural single metal hydroxides. However, no direct comparison of these minerals appears in the literature using WT. This work systematically analyzes a suite of Ni-rich mineral standards, including Ni–Al LDHs, single metal Ni hydroxides, and Ni-rich silicates using WT. The results illustrate that the WT plots for α-Ni(OH)2 and Ni–Al LDHs are often indistinguishable from each other, with similar two-component plots for the different mineral types. This demonstrates that the WT of the first metal shell often cannot be used to differentiate an LDH from a single metal hydroxide. Interlayer anions adsorbed to the hydroxide sheet of α-Ni(OH)2 affect the EXAFS spectra and are not visible in the FT but are clearly resolved and discrete in the WT.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Differentiating and Quantifying Gas-Phase Conformational Isomers Using Coulomb Explosion Imaging

Conformational isomerism plays a crucial role in defining the physical and chemical properties and biological activity of molecules ranging from simple organic compounds to complex biopolymers. However, it is often a significant challenge to differentiate and separate these isomers experimentally as they can easily interconvert due to their low rotational energy barrier. Here, we use the momentum correlation of fragment ions produced after inner-shell photoionization to distinguish conformational isomers of 1,2-dibromoethane (C 2 H 4 Br 2 ). We demonstrate that the three-body breakup channel, C 2 H 4 + + Br + + Br + , contains signatures of both sequential and concerted breakup, which are decoupled to distinguish the geometries of two conformational isomers and to quantify their relative abundance. The sensitivity of our method to quantify these yields is established by measuring the relative abundance change with sample temperature, which agrees well with calculations. Finally, our study paves the way for using Coulomb explosion imaging to track subtle molecular structural changes.

Photoionization↗
DOE OSTI2017

Calcium and zinc differentially affect the structure of lipid membranes

Interactions of calcium (Ca 2+ ) and zinc (Zn 2+ ) cations with biomimetic membranes made of dipalmitoylphosphatidylcholine (DPPC) were studied by small angle neutron diffraction (SAND). Experiments show that the structure of these lipid bilayers is differentially affected by the two divalent cations. Initially, both Ca 2+ and Zn 2+ cause DPPC bilayers to thicken, while further increases in Ca 2+ concentration result in the bilayer thinning, eventually reverting to having the same thickness as pure DPPC. The binding of Zn 2+ , on the other hand, causes the bilayers to swell to a maximum thickness, and the addition of more Zn 2+ does not result in a further thickening of the membrane. Agreement between our results obtained using oriented planar membranes and those from vesicular samples implies that the effect of cations on bilayer thickness is the result of electrostatic interactions, rather than geometrical constraints due to bilayer curvature. This notion is further reinforced by MD simulations. Lastly, the radial distribution functions reveal a strong interaction between Ca 2+ and the phosphate oxygens, while Zn 2+ shows a much weaker binding specificity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Differential Heat of Adsorption and Isosteres

Heat of adsorption is a basic thermodynamic property extensively used not only for understanding thermal effects and heat management in industrial gas storage and separation processes but also for development and validation of adsorption models and materials force fields. Despite a long history of theoretical studies and a vast experimental literature, controversies often arise in the thermodynamic analysis of heat effects due to various assumptions used to describe gas adsorption and inconsistencies between direct calorimetric measurements and isosteric heat obtained from various adsorption isotherms. Here we present a rigorous theoretical procedure for predicting isosteric heat without any assumption about the geometry of porous adsorbents or operating conditions. Quantitative relations between the differential heat and various isosteres have been established with the grand-canonical Monte Carlo simulation for gas adsorption in amorphous as well as crystalline porous materials. The inconsistencies and practical issues with conventional methods for the analysis of the heat effect have been clarified in the context of the exact results for model systems. Via the resolution of a number of controversies about heat analysis, we hope that the new theoretical procedure will be adopted for both fundamental research and industrial applications of gas adsorption processes.

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

Differentiating Thermal Conductances at Semiconductor Nanocrystal/Ligand and Ligand/Solvent Interfaces in Colloidal Suspensions

Infrared-pump, electronic-probe (IPEP) spectroscopy is used to measure heat flow into and out of CdSe nanocrystals suspended in an organic solvent, where the surface ligands are initially excited with an infrared pump pulse. Subsequently, the heat is transferred from the excited ligands to the nanocrystals and in parallel to the solvent. Parallel heat transfer in opposite directions uniquely enables us to differentiate the thermal conductances at the nanocrystal/ligand and ligand/solvent interfaces. Using a novel solution to the heat diffusion equation, we fit the IPEP data to find that the nanocrystal/ligand conductances range from 88 to 135 MW m –2 K –1 and are approximately 1 order of magnitude higher than the ligand/solvent conductances, which range from 7 to 26 MW m –2 K –1 . Transient nonequilibrium molecular dynamics (MD) simulations of nanocrystal suspensions agree with IPEP data and show that ligands bound to the nanocrystal by bidentate bonds have more than twice the per-ligand conductance as those bound by monodentate bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Differentiation of surface and bulk conductivities in topological insulator via four-probe spectroscopy

Topological insulators, with characteristic topological surface states, have emerged as a new state of matter with rich potentials for both fundamental physics and device applications. However, the experimental detection of the surface transport has been hampered by the unavoidable extrinsic conductivity associated with the bulk crystals. Here we show that a four-probe transport spectroscopy in a multi-probe scanning tunneling microscopy system can be used to differentiate conductivities from the surface states and the coexisting bulk states in topological insulators. We derive a scaling relation of measured resistance with respect to varying inter-probe spacing for two interconnected conduction channels, which allows quantitative determination of conductivities from both channels. Using this method, we demonstrate the separation of 2D and 3D conduction in topological insulators by comparing the conductance scaling of Bi 2 Se 3 , Bi 2 Te 2 Se, and Sb-doped Bi 2 Se 3 with that of a pure 2D conductance of graphene on SiC substrate. We also report the 2D conductance enhancement due to the surface doping effect in topological insulators. This technique can be applied to reveal 2D to 3D crossover of conductance in other complex systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coarse-Grained Modeling Elucidates Differential Metabolism of Saccharomyces cerevisiae under Varied Nutrient Limitations

Microorganisms such as Saccharomyces cerevisiae have a native ability to adapt their metabolism to varying nutrient conditions. Understanding their responses to nutrient limitations is critical for decoding cellular physiology and designing strategies for metabolic engineering. While the influence of carbon availability on yeast metabolism has been extensively studied, the role of nitrogen availability remains relatively underexplored. In this study, we utilized a coarse-grained kinetic model to systematically analyze and compare the effects of carbon and nitrogen limitations on yeast metabolism. Our model successfully revealed the differential metabolic characteristics of S. cerevisiae under carbon- and nitrogen-limited chemostat conditions. It also highlighted the significance of protein activity regulation at varying carbon-to-nitrogen ratios, and elucidated distinct strategies employed to maintain ATP homeostasis. Furthermore, this study provides a computational tool for investigating yeast physiology under nutrient limitations and offers quantitative and mechanistic insights into yeast metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Surface Hydroxyls of Imogolite Nanotubes Drive Distinct Structures and Mobility Differentiation of Nanoconfined Water

Abstract Nanoconfined fluids, particularly water, govern subsurface geochemistry, yet the molecular-level mechanisms by which mineral surfaces dictate confined water structure and mobility remain poorly resolved. Here, we combine solution- and solid-state proton (1H) NMR spectroscopy, NMR relaxometry, modulated-gradient spin–echo (MGSE) NMR diffusometry, infrared spectroscopy, and molecular dynamics simulations to demonstrate that surface hydroxyls drive the structural and dynamic differentiation of water in imogolite nanotubes. In saturated suspensions, we observe the coexistence of distinct water 1H environments, each exhibiting significantly reduced mobility, which we attribute to strong interactions with the imogolite surfaces. As more mobile water is removed, long-range water diffusivity in the fibrous solid samples slows to 1.6 × 10–10 m2·s–1 while local fluctuations increase to 3.4 × 10–8 m2·s–1, indicating a significant increase in molecular restriction through surface interactions. Together, our experiments reveal three coexisting populations with varied structures and mobilities, all distinct from liquid bulk water. We resolve a persistent solid-like interfacial layer strongly bound to surface hydroxyls, characterized by an unusually short T2 (<1 ms), and a very close effective 1H–1H distance of ∼1.55 Å between water and the inner-surface silanol group. An inner-core population occupying the inner cavity exhibits an intermediate dynamic regime with restricted axial diffusion, while outer-surface water associated with aluminum hydroxyls retains relatively higher mobility. These results experimentally substantiate a hierarchy of water populations in imogolite and show how surface chemistry dictates the structures and dynamics of confined water.

Fleming, Xander B. [Earth and Environmental Scienc↗
DOE OSTI2022

A Differentiable Hydrology Approach for Modeling With Time-Varying Parameters

In the analysis of observational data with mathematical models, it is often desirable to let one or more model parameters vary with time to account for changing environmental conditions or to offer more flexibility. A standard approach for dynamic models is to allow for the number of parameters to grow as a function of time, leading to a high-dimensional inference problem for long data records. We propose using Hamiltonian Monte Carlo, a gradient-based Markov chain Monte Carlo (MCMC) method, to perform Bayesian inference for time-varying parameters (TVP) in hydrology models. As derivatives of model error functions with regard to parameters are not available in closed form, we implemented the GR4J rainfall-runoff models in Theano/PyMC3, and Jax/NumPyro, allowing for the application of automatic differentiation techniques. A simulation experiment assessing the viability of these methods for recovering underlying temporal variation in parameters indicates that a discrete Gaussian random walk-based prior appears to be best suited across a range of scenarios while the continuous-time Gaussian process compares relatively poorly. In an analysis of 20 years of daily real-world streamflow records from the Model Parameter Estimation Experiment (MOPEX) hydrology data set with increasing data sparsity and at multiple temporal resolutions, we find that TVP inference with gradient-based MCMC is a flexible and reliable approach for analyzing hydrology models with dynamic parameter sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗
DOE OSTI2021

Observation of current-induced switching in non-collinear antiferromagnetic IrMn 3 by differential voltage measurements

There is accelerating interest in developing memory devices using antiferromagnetic (AFM) materials, motivated by the possibility for electrically controlling AFM order via spin-orbit torques, and its read-out via magnetoresistive effects. Recent studies have shown, however, that high current densities create non-magnetic contributions to resistive switching signals in AFM/heavy metal (AFM/HM) bilayers, complicating their interpretation. Here we introduce an experimental protocol to unambiguously distinguish current-induced magnetic and nonmagnetic switching signals in AFM/HM structures, and demonstrate it in IrMn 3 /Pt devices. A six-terminal double-cross device is constructed, with an IrMn 3 pillar placed on one cross. The differential voltage is measured between the two crosses with and without IrMn 3 after each switching attempt. For a wide range of current densities, reversible switching is observed only when write currents pass through the cross with the IrMn 3 pillar, eliminating any possibility of non-magnetic switching artifacts. Micromagnetic simulations support our findings, indicating a complex domain-mediated switching process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole

Eukaryotic phytoplankton are responsible for at least 20% of annual global carbon fixation. Their diversity and activity are shaped by interactions with prokaryotes as part of complex microbiomes. Although differences in their local species diversity have been estimated, we still have a limited understanding of environmental conditions responsible for compositional differences between local species communities on a large scale from pole to pole. Here, we show, based on pole-to-pole phytoplankton metatranscriptomes and microbial rDNA sequencing, that environmental differences between polar and non-polar upper oceans most strongly impact the large-scale spatial pattern of biodiversity and gene activity in algal microbiomes. The geographic differentiation of co-occurring microbes in algal microbiomes can be well explained by the latitudinal temperature gradient and associated break points in their beta diversity, with an average breakpoint at 14 °C ± 4.3, separating cold and warm upper oceans. As global warming impacts upper ocean temperatures, we project that break points of beta diversity move markedly pole-wards. Hence, abrupt regime shifts in algal microbiomes could be caused by anthropogenic climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The obligate intracellular bacterium Orientia tsutsugamushi differentiates into a developmentally distinct extracellular state

Orientia tsutsugamushi (Ot) is an obligate intracellular bacterium in the family Rickettsiaceae that causes scrub typhus, a severe mite-borne human disease. Its mechanism of cell exit is unusual amongst Rickettsiaceae, as Ot buds off the surface of infected cells enveloped in plasma membrane. Here, we show that Ot bacteria that have budded out of host cells are in a distinct developmental stage compared with intracellular bacteria. We refer to these two stages as intracellular and extracellular bacteria (IB and EB, respectively). These two forms differ in physical properties: IB is both round and elongated, and EB is round. Additionally, IB has higher levels of peptidoglycan and is physically robust compared with EB. The two bacterial forms differentially express proteins involved in bacterial physiology and host-pathogen interactions, specifically those involved in bacterial dormancy and stress response, and outer membrane autotransporter proteins ScaA and ScaC. Whilst both populations are infectious, entry of IB Ot is sensitive to inhibitors of both clathrin-mediated endocytosis and macropinocytosis, whereas entry of EB Ot is only sensitive to a macropinocytosis inhibitor. Our identification and detailed characterization of two developmental forms of Ot significantly advances our understanding of the intracellular lifecycle of an important human pathogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Molecular basis of differential HLA class I-restricted T cell recognition of a highly networked HIV peptide

Cytotoxic-T-lymphocyte (CTL) mediated control of HIV-1 is enhanced by targeting highly networked epitopes in complex with human-leukocyte-antigen-class-I (HLA-I). However, the extent to which the presenting HLA allele contributes to this process is unknown. Here we examine the CTL response to QW9, a highly networked epitope presented by the disease-protective HLA-B57 and disease-neutral HLA-B53. Despite robust targeting of QW9 in persons expressing either allele, T cell receptor (TCR) cross-recognition of the naturally occurring variant QW9_S3T is consistently reduced when presented by HLA-B53 but not by HLA-B57. Crystal structures show substantial conformational changes from QW9-HLA to QW9_S3T-HLA by both alleles. The TCR-QW9-B53 ternary complex structure manifests how the QW9-B53 can elicit effective CTLs and suggests sterically hindered cross-recognition by QW9_S3T-B53. We observe populations of cross-reactive TCRs for B57, but not B53 and also find greater peptide-HLA stability for B57 in comparison to B53. These data demonstrate differential impacts of HLAs on TCR cross-recognition and antigen presentation of a naturally arising variant, with important implications for vaccine design.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗
DOE OSTI2025

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Differential programming enabled functional imaging with Lorentz transmission electron microscopy

Abstract Lorentz transmission electron microscopy is an advanced characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials. Information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during image acquisition. Various methods have been proposed to retrieve the phase of the electron wavefunction using intensities of the acquired images, most of which work only in the small defocus limit. Imaging at strong defoci not only carries more quantitative phase information, but is essential to the study of weak magnetic and electrostatic fields at the nanoscale. In this work we develop a method based on differentiable programming to solve the inverse problem of phase retrieval. We show that our method maintains a high spatial resolution and robustness against noise even at the upper defocus limit of the microscope. More importantly, our proposed method can go beyond recovering just the phase information. We demonstrate this by retrieving the electron-optical parameters of the contrast transfer function alongside the electron exit wavefunction.

97 MATHEMATICS AND COMPUTING↗