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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Extended thermodynamic model for high salinity produced waters

To support the development of desalination processes for high salinity produced waters, we developed a comprehensive thermodynamic model that reliably predicts the thermodynamic properties and phase behavior of produced water. Here this study extends a previously developed thermodynamic model for the aqueous hexary oceanic salt system by incorporating the Sr 2+ and Ba 2+ ions. Based on the electrolyte nonrandom two-liquid theory, the model requires two adjustable binary interaction parameters for each water-electrolyte and electrolyte-electrolyte pair that has a common ion. The binary interaction parameters for the electrolyte-electrolyte pairs involving Sr 2+ and Ba 2+ ions were identified using thermodynamic and salt solubility data. The model was validated for temperatures from 273.15 K to 473.15 K and electrolyte concentrations from infinite dilution to salt saturation. Extension of the model to include HCO 3 − , CO 3 2− , and CO 2 is currently in progress.

42 ENGINEERING↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
DOE OSTI2022

Hilbert space fragmentation in a 2D quantum spin system with subsystem symmetries

We consider a 2D quantum spin model with ring-exchange interaction that has subsystem symmetries associated to conserved magnetization along rows and columns of a square lattice, which implies the conservation of the global dipole moment. The model is not integrable, but violates the eigenstate thermalization hypothesis through an extensive Hilbert space fragmentation, including an exponential number of inert subsectors with trivial dynamics, arising from kinetic constraints. While subsystem symmetries are quite restrictive for the dynamics, we show that they alone cannot account for such a number of inert states, even with infinite-range interactions. We present a procedure for constructing shielding structures that can separate and disentangle dynamically active regions from each other. Notably, subsystem symmetries allow the thickness of the shields to be dependent only on the interaction range rather than on the size of the active regions, unlike in the case of generic dipole-conserving systems.

Khudorozhkov, Alexey↗
DOE OSTI2025

Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 With Regional Grid Refinement

The simulation of ice sheet‐climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi‐century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric CO 2 increases by 1% yr -1 until quadrupling the pre‐industrial level and then is held fixed). A variable‐resolution (VR) grid with 1/4° regional refinement over the broader Arctic and 1° resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional 1° lat‐lon grid simulations to investigate the impact of grid refinement. Compared with the 1° runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the 1° runs, respectively.

Earth System Model↗
DOE OSTI2024

Characterizing Supernovae Neutrinos in MARLEY

This summer I worked on characterizing the uncertainties in neutrino-argon interactions due to the optical model potential. Functionally, this was a great deal of new experience coding in C++. I wrote a script using MARLEY(Gardiner 2019) to compute both the branching ratios and exclusive cross sections for a whole host of different decay processes from the unstable Potassium nucleus created by a v+Ar charged current interaction. These decays were computed through MARLEY, governed by a global parametrization of the Optical Model potential(Koning-Delaroche 2003). Helpfully, Pruitt+ 2023 provided public supplemental material outlining 400 separate "universes" for the optical model potential parameters. These "universes" represent uncertainties on the optical potential itself, and I wrote code to incorporate them into the MARLEY framework and quantify their impact on the predictions of neutrino-argon cross sections. This stands as the first computation of nuclear de-excitation systematic errors on cross sections in this energy band for v+Ar interactions, a critical step to understanding the science we can do with DUNE in the tens-of-MeV band.

Abu El-Haj, Luca↗
DOE OSTI2024

Noncentrosymmetric Triangular Magnet CaMnTeO 6 : Strong Quantum Fluctuations and Role of s 0 versus s 2 Electronic States in Competing Exchange Interactions

Abstract Noncentrosymmetric triangular magnets offer a unique platform for realizing strong quantum fluctuations. However, designing these quantum materials remains an open challenge attributable to a knowledge gap in the tunability of competing exchange interactions at the atomic level. Here, a new noncentrosymmetric triangular S = 3/2 magnet CaMnTeO 6 is created based on careful chemical and physical considerations. The model material displays competing magnetic interactions and features nonlinear optical responses with the capability of generating coherent photons. The incommensurate magnetic ground state of CaMnTeO 6 with an unusually large spin rotation angle of 127°(1) indicates that the anisotropic interlayer exchange is strong and competing with the isotropic interlayer Heisenberg interaction. The moment of 1.39(1) µB , extracted from low‐temperature heat capacity and neutron diffraction measurements, is only 46% of the expected value of the static moment 3 µB . This reduction indicates the presence of strong quantum fluctuations in the half‐integer spin S = 3/2 CaMnTeO 6 magnet, which is rare. By comparing the spin‐polarized band structure, chemical bonding, and physical properties of AMnTeO 6 ( A = Ca, Sr, Pb), how quantum‐chemical interpretation can illuminate insights into the fundamentals of magnetic exchange interactions, providing a powerful tool for modulating spin dynamics with atomically precise control is demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Shear-induced lift force on spheres in a viscous linear shear flow at finite volume fractions

Several studies have shown a significant increase in drag on a distribution of solid spherical particles within a fluid with increasing particle volume fraction. As a result, many empirical drag laws accounting for the dependence on the Reynolds number and volume fraction can be found in the literature. This study investigates the possibility of a similar effect of the particle volume fraction on the mean hydrodynamic lift force on randomly distributed spherical particles in a linear shear flow. Particle-resolved direct numerical simulations are performed to evaluate the mean lift force, and the results are compared with the case of an isolated particle in a linear shear flow for the same Reynolds number and shear rate. The mean lift force acting on the particles appears to remain nearly the same as that on an isolated particle. However, due to the influence of neighboring particles, there is a substantial force variation in transverse directions on each individual particle, whose magnitude is comparable to the mean drag force. The distribution of drag force in a linear shear flow is shown to be nearly the same as in a uniform flow at the same volume fraction and Reynolds number. A simple stochastic model based on a Gaussian distribution is presented for the lift force variation, and its performance is compared to the prediction of the deterministic pairwise interaction extended point-particle model.

42 ENGINEERING↗
DOE OSTI2022

Evaluation of simulations of near-surface variables using the regional climate model CCLM for the MOSAiC winter period

The ship-based experiment MOSAiC 2019/2020 was carried out during a full year in the Arctic and yielded an excellent data set to test the parameterizations of ocean/sea-ice/atmosphere interaction processes in regional climate models (RCMs). In the present paper, near-surface data during MOSAiC are used for the verification of the RCM COnsortium for Small-scale MOdel–Climate Limited area Mode (COSMO-CLM or CCLM). CCLM is used in a forecast mode (nested in ERA5) for the whole Arctic with 15 km resolution and is run with different configurations of sea ice data. These include the standard sea ice concentration taken from passive microwave data with around 6 km resolution, sea ice concentration from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data and MODIS sea ice lead fraction data for the winter period. CCLM simulations show a good agreement with the measurements. Relatively large negative biases for temperature occur for November and December, which are likely associated with a too large ice thickness used by CCLM. The consideration of sea ice leads in the sub-grid parameterization in CCLM yields improved results for the near-surface temperature. ERA5 data show a large warm bias of about 2.5°C and an underestimation of the temperature variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Escalation in the host-pathogen arms race: A host resistance response corresponds to a heightened bacterial virulence response

The zig-zag model of host-pathogen interaction describes the relative strength of defense response across a spectrum of pathogen-induced plant phenotypes. A stronger defense response results in increased resistance. Here, we investigate the strength of pathogen virulence during disease and place these findings in the context of the zig-zag model. Xanthomonas vasicola pv. holcicola ( Xvh ) causes sorghum bacterial leaf streak. Despite being widespread, this disease has not been described in detail at the molecular level. We divided diverse sorghum genotypes into three groups based on disease symptoms: water-soaked lesions, red lesions, and resistance. Bacterial growth assays confirmed that these three phenotypes represent a range of resistance and susceptibility. To simultaneously reveal defense and virulence responses across the spectrum of disease phenotypes, we performed dual RNA-seq on Xvh -infected sorghum. Consistent with the zig-zag model, the expression of plant defense-related genes was strongest in the resistance interaction. Surprisingly, bacterial virulence genes related to the type III secretion system (T3SS) and type III effectors (T3Es) were also most highly expressed in the resistance interaction. This expression pattern was observed at multiple time points within the sorghum- Xvh pathosystem. Further, a similar expression pattern was observed in Arabidopsis infected with Pseudomonas syringae for effector-triggered immunity via AvrRps4 but not AvrRpt2. Specific metabolites were able to repress the Xvh virulence response in vitro and in planta suggesting a possible signaling mechanism. Taken together, these findings reveal multiple permutations of the continually evolving host-pathogen arms race from the perspective of host defense and pathogen virulence responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗
DOE OSTI2024

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Determining Partial Atomic Charges for Liquid Water: Assessing Electronic Structure and Charge Models

Partial atomic charges provide an intuitive and efficient way to describe the charge distribution and the resulting intermolecular electrostatic interactions in liquid water. Many charge models exist and it is unclear which model provides the best assignment of partial atomic charges in response to the local molecular environment. In this work, we systematically scrutinize various electronic structure methods and charge models (Mulliken, natural population analysis, CHelpG, RESP, Hirshfeld, Iterative Hirshfeld, and Bader) by evaluating their performance in predicting the dipole moments of isolated water, water clusters, and liquid water as well as charge transfer in the water dimer and liquid water. Although none of the seven charge models is capable of fully capturing the dipole moment increase from isolated water (1.85 D) to liquid water (about 2.9 D), the Iterative Hirshfeld method performs best for liquid water, reproducing its experimental average molecular dipole moment, yielding a reasonable amount of intermolecular charge transfer, and showing modest sensitivity to the local water environment. The performance of the charge model is dependent on the choice of the density functional and the quantum treatment of the environment. The computed molecular dipole moment of water generally increases with the percentage of the exact Hartree–Fock exchange in the functional, whereas the amount of charge transfer between molecules decreases. For liquid water, including two full solvation shells of surrounding water molecules (within about 5.5 Å of the central water) in the quantum chemical calculation converges the charges of the central water molecule. Furthermore, our final pragmatic quantum chemical charge-assigning protocol for liquid water is the Iterative Hirshfeld method with M06-HF/aug-cc-pVDZ and a quantum region cutoff radius of 5.5 Å.

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

Parity- and Time-Reversal-Violating Nuclear Forces

Parity-violating and time-reversal conserving (PVTC) and parity-violating and time-reversal-violating (PVTV) forces in nuclei form only a tiny component of the total interaction between nucleons. The study of these tiny forces can nevertheless be of extreme interest because they allow one to obtain information on fundamental symmetries using nuclear systems. The PVTC interaction derives from the weak interaction between the quarks inside nucleons and nuclei, therefore the study of PVTC effects opens a window on the quark-quark weak interaction. The PVTV interaction is sensitive to more exotic interactions at the fundamental level, in particular to strong CP violation in the Standard Model Lagrangian, or even to exotic phenomena predicted in various beyond-the-Standard-Model scenarios. The presence of these interactions can be revealed either by studying various asymmetries in polarized scattering of nuclear systems, or by measuring the presence of non-vanishing permanent electric dipole moments of nucleons, nuclei and diamagnetic atoms and molecules. In this contribution, we review the derivation of the nuclear PVTC and PVTV interactions within various frameworks. We focus in particular on the application of chiral effective field theory, which allows for a more strict connection with the fundamental interactions at the quark level. We investigate PVTC and PVTV effects induced by these potentials on several few-nucleon observables, such as the longitudinal asymmetries in proton-proton scattering and the 3 He($\vec{n}$,p) 3 H reaction, the radiative neutron-proton capture, and the electric dipole moments of the deuteron and the trinucleon system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Neutrino-Nucleus Scattering Cross Sections at Medium Energies

The weak interactions of neutrinos with other Standard Model particles are well described within the Standard Model of particle physics. However, modern accelerator-based neutrino experiments employ nuclei as targets, where neutrinos interact with bound nucleons, turning a seemingly simple electroweak process into a complex many-body problem in nuclear physics. At the time of writing this Encyclopedia of Particle Physics chapter, neutrino-nucleus interactions remain one of the leading sources of systematic uncertainty in accelerator-based neutrino oscillation measurements. This chapter provides a pedagogical overview of neutrino interactions with nuclei in the medium-energy regime, spanning a few hundred MeV to several GeV. It introduces the fundamental electroweak formalism, outlines the dominant interaction mechanisms - including quasielastic scattering, resonance production, and deep inelastic scattering - and discusses how nuclear effects such as Fermi motion, nucleon-nucleon correlations, meson-exchange currents, and final-state interactions modify observable cross sections. The chapter also presents a brief survey of the foundational and most widely used theoretical models for neutrino-nucleus cross sections, together with an overview of current and upcoming accelerator-based neutrino oscillation experiments that are shaping the field. Rather than targeting experts, this chapter serves as a primer for advanced undergraduates, graduate students, and early-career researchers entering the field. It provides a concise foundation for understanding neutrino-nucleus scattering, its relevance to oscillation experiments, and its broader connections to both particle and nuclear physics.

Pandey, Vishvas [Fermilab] (ORCID:0000000230827987↗
DOE OSTI2023

Origin of hydroxyl pair formation on reduced anatase TiO 2 (101)

The interaction of water with metal oxide surfaces is of key importance to several research fields and applications. Because of its ability to photo-catalyze water splitting, reducible anatase TiO 2 (a-TiO 2 ) is of particular interest. Here, we combine experiments and theory to study the dissociation of water on bulk-reduced a-TiO 2 (101). Following large water exposures at room temperature, point-like protrusions appear on the a-TiO 2 (101) surface, as shown by scanning tunneling microscopy (STM). These protrusions originate from hydroxyl pairs, consisting of terminal and bridging OH groups, OH t /OH b , as revealed by infrared reflection absorption spectroscopy (IRRAS) and valence band experiments. Utilizing density functional theory (DFT) calculations, we offer a comprehensive model of the water/a-TiO 2 (101) interaction. In conclusion, this model also explains why the hydroxyl pairs are thermally stable up to ~480 K.

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

Three-dimensional modeling of hyphal fusion, branching, and nutrient transport in filamentous fungi

Fungi exhibit behaviors distinct from other microbes. Filamentous fungi grow by extending complex networks of branched filaments collectively referred to as the mycelium. These networks can expand over large distances and traverse low-nutrient areas by translocating nutrients through the filament network. This spatial characteristic makes filamentous fungi crucial for soil ecosystems, supporting stable microbial communities and promoting plant growth. However, simulating these behaviors is complex. The elongated nature of fungal compartments results in different mechanical interactions compared to the commonly modeled spherical bacteria. These detailed hyphal mechanics require specialized consideration and are often excluded from conventional fungal simulation packages. Additionally, the extensive fungal networks in nature demand computationally intensive simulations, necessitating high-performance algorithms. Therefore, realistic fungi simulations require specialized software. Here, we introduce a fungal modeling expansion to the high-performance biological modelling and interface exchange (bmx) software suite. bmx leverages adaptive mesh refinement in AMReX for chemical diffusion and incorporates a full mechanical model for bacterial cells, accelerated by GPUs. By extending bmx to model filamentous particles, we demonstrate the formation of complex filament networks through interactions like hyphal branching and fusion (anastomosis). We show that the networks produced match real-world fungal structures through various metrics. This work supports computational studies of fungal growth dynamics and can be adapted to investigate the growth of other filamentous structures in biology or materials science. The expanded-BMX package is open-sourced and is available online.

Cell mechanics↗
DOE OSTI2024

Toward first principles-based simulations of dense hydrogen

Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g., planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange–correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principles PIMC as well as in DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions that are based on first principles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗