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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
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
DOE OSTI2024

Robust Dissimilar Metal Friction Welded Spool for Enhanced Capability for Steam Power Components (Final Program Report)

This project successfully demonstrated the feasibility and advantages of producing durable, friction-welded dissimilar-metal spools, both with and without transition pieces, as well as the use of advanced oxidation-protective coatings for steam power applications. The work encompassed the optimization and full-scale production of NFA tubing, overcoming manufacturing and processing challenges to achieve enhanced strength, creep, and fatigue properties validated by extensive microstructural characterization. Optimized welding techniques were developed and refined for joining dissimilar materials, resulting in defect-free welds optimized for both low- and high-pressure boiler circuits. Systematic evaluation of welding parameters, coupled with heat treatments, ensured reliable performance and minimized weld defects such as banding and cracking. Comprehensive mechanical and non-destructive testing, including tensile, bend, fatigue, and CT scanning, confirmed the superior integrity and durability of the friction-welded joints under representative service conditions. To address oxidation-related degradation, a range of protective alloy coatings—such as IN625, APMT, Duplex 2507, and FeCrAlY—were selected and evaluated for their ability to counteract oxide notch formation at dissimilar metal interfaces. These coatings demonstrated improved oxidation resistance and long-term stability under thermal cycling, thereby extending weld service life. Thermal cyclic testing and long-term studies captured the phase stability and diffusion behavior of coated and uncoated configurations. Validated models for low-cycle fatigue (LCF), creep, and thermal mechanical fatigue (TMF) were developed to predict component life and failure modes. These models confirmed that friction-welded configurations exhibited significantly enhanced performance compared to conventional gas-tungsten arc welding (GTAW), with up to 7× improvement in creep resistance and at least 2× enhancement in fatigue properties. The introduction of a tailored transition piece further reduced thermally induced strains, enhancing fatigue life. The results demonstrate a robust pathway for retrofitting existing steam fleet components and upgrading future equipment to deliver substantially improved cold-start cycling behavior and reduction of unplanned outages due to premature weld failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Bridging particle and reactor scales in the simulation of biomass fast pyrolysis by coupling particle resolved simulation and coarse grained CFD-DEM

Efficient utilization of biomass is challenging due to the complexity of the feedstock at molecular, particle, and reactor scales. Direct coupling of particle scale model and reactor scale simulation is computationally infeasible. In this work, the results from a particle resolved simulation were used to calibrate the heat transfer and reaction kinetics of particles. A hybrid drag model was used to consider the different fluidization properties of sands and biomass particles. The computation cost was reduced using a coarse-grained Discrete Element Method (DEM). The simulated conversion rate, char yield, tar yield, and pyrolysis gas yield compare well with experiment. The residence time and axial distributions of biomass were also analyzed. This novel multi-scale method provides an efficient and accurate tool for the modeling of biomass pyrolysis reactors.

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

A Process Intensification Approach for CO 2 Absorption Using Amino Acid Solutions and a Guanidine Compound

Environmentally friendly amino-acid salt solutions are used for the absorption of carbon dioxide from concentrated flue-gas streams via chemical absorption. Process intensification reduces operating and capital costs by combining chemical reactions and separation operations. Here, we present a new process-intensification approach that combines the CO 2 capture and the amino-acid regeneration steps into a single process carried out in a slurry three-phase reactor. The absorbed CO 2 precipitates as a solid carbonated guanidine compound. The cycle is completed by separation of the solid precipitate to strip the CO 2 and regenerate the guanidine compound, while the liquid solution is recycled to the slurry reactor. The process was studied by modifying a model developed by the authors for a gas-liquid bubble column without the presence of the guanidine compound. The guanidine precipitation reaction was accounted for using kinetic parameters calculated by the authors in another study. The proposed model was implemented by modifying an existing computer code used for the simulation of gas-liquid bubble columns. The calculated results showed that the proposed cycle can significantly reduce energy, equipment, and operating costs and can make an important contribution to developing a competitive cost-effective large-scale process for CO 2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Coupled Roles of Surface Chemistry and Hydrogen-Assisted Cycling in Ruthenium Atomic Layer Deposition on Silicon Oxides

Ruthenium (Ru) is a promising interconnect material for advanced semiconductor technologies due to its favorable scaling characteristics, including a short electron mean free path and strong electromigration resistance. In semiconductor integration, silicon oxide-based dielectrics serve as dominant insulating materials and constitute ubiquitous interfaces for metallization; however, their formation-dependent surface chemistry and its impact on Ru growth remain insufficiently explored. Here, we investigate Ru ALD on native oxide SiO x (N-SiO x ) and thermally grown SiO 2 (T-SiO 2 ) as model substrates using bis(ethylcyclopentadienyl)ruthenium(II) [Ru(EtCp) 2 ] under two distinct reactant-sequence environments: AB-type (Ru(EtCp) 2 /O 2 ) and hydrogenassisted ABC-type (Ru(EtCp) 2 /O 2 /H 2 ). Under the AB-type process, both N-SiO x and T-SiO 2 exhibit pronounced nucleation delay. N-SiO x shows earlier nucleation and higher nucleation density than T-SiO 2 , plausibly attributed to differences in surface hydroxyl populations. Similar temperature-dependent phase evolution is observed on both substrates, with mixed Ru and RuO 2 phases at 250 °C and predominantly metallic Ru at 300 °C accompanied by increased morphological roughening. In contrast, incorporating an H 2 subpulse (ABC-type) mitigates nucleation delay, particularly on hydroxyl-deficient T-SiO 2 , thereby reducing the substratedependent disparity observed under AB cycling. Moreover, RuO 2 formation is suppressed even at 250 °C on both substrates, shifting growth toward more metallic Ru with reduced resistivity (∼20 μΩ·cm at ∼ 20 nm on N-SiO x ). These trends suggest that H 2 influences the surface reaction pathway, contributing to enhanced metallic stabilization and altered early stage growth kinetics. Overall, this work clarifies the coupled roles of substrate chemistry and reactant-sequence design in governing Ru nucleation and early stage film evolution, providing insight relevant to next-generation interconnect integration and future area-selective deposition strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Breaking C-C Bonds via Electrochemically Mediated Hydrogen Atom Transfer Reactions

Cleaving inert SP3-SP3 carbon-carbon (C-C) bonds selectively remains a major challenge in organic chemistry and a main bottleneck in the chemical upcycling of recalcitrant polyolefin waste. Here, we present an electrochemical strategy using redox mediators to activate and break C-C bonds at room temperature and ambient pressure. Specifically, we use N-hydroxyphthalimide (NHPI) as a redox mediator that undergoes electrochemical oxidation to form the phthalimide-N-oxyl (PINO) radical to initiate hydrogen atom transfer (HAT) reactions with benzylic C-H bonds. The resulting benzylic carbon radical is readily captured by molecular oxygen to form a peroxy radical that decomposes into oxygenated C-C bond-scission fragments. This indirect, mediated approach for Csp3-Csp3 bond cleavage reduces the oxidation potential by > 1.2 V compared to the direct oxidation of the substrate, thereby eliminating deleterious side reactions, such as solvent oxidation, that may occur at high potentials. Studies with a bibenzyl model compound revealed a bifurcated reaction pathway following the initial HAT step. At a bibenzyl conversion of 61.0%, the C-C bond cleavage pathway generates benzaldehyde and benzoic acid products at 38.4% selectivity, and the C-H bond oxygenation pathway leads to 1,2-diphenylethanone and benzil products at 39.2% selectivity. Changes in reaction selectivity were investigated with various model compounds, including bibenzyl, 1,3-diphe-nylpropane, 1,4-diphenylbutane, and their derivatives. Product selectivity is correlated with the C-C bond strength of the reactant, with weaker C-C bonds favoring the C-C bond cleavage pathway. We also evaluated the mediated oxidation of oligo-meric styrene (Mn= 510 Da, OS510) which were converted into oxygenated products. Lastly, proof-of-concept depolymeriza-tion of polystyrene (PS, ~10,000 Da) into oxygenated monomers, dimers, and oligomers was demonstrated using NHPI-mediated oxidation.

benzoic acid↗
DOE OSTI2020

Wintertime particulate matter decrease buffered by unfavorable chemical processes despite emissions reductions in China

Extreme and persistent haze events frequently occur during wintertime China. While recent emissions reductions reduced annual mean fine particulate matter (PM2.5) concentrations over eastern China, their effectiveness on wintertime PM2.5 trend remains uncertain. We use observations and model simulations to quantify seasonal differences in PM2.5 trends and investigate the underlying chemical mechanisms driving such differences. We find a much slower decrease in observed wintertime PM2.5 (–3.2% yr-1) since 2014, in contrast to a drastic summertime decrease (–10.3% yr-1). Simulations show two previously underappreciated mechanisms buffering wintertime PM2.5 decrease, including an increase in oxidation capacity due to nitrogen oxides (NOx) reductions under wintertime volatile organic compound (VOC)- limited chemistry, and an enhanced conversion of nitric acid to nitrate by ammonia due to sulfur dioxide reductions. Our findings suggest that control policies targeting VOC and deep NOx reductions are needed to improve wintertime PM2.5 air quality over China.

Leung, Danny M.↗
DOE OSTI2025

Multi-scale computational screening and mechanistic insights of cyclic amines as solvents for improved lignocellulosic biomass processing

A computational screening workflow for the efficient deconstruction of cellulose, lignin and hemicellulose fractions of lignocellulosic biomass using cyclic amines as solvents. Lignocellulosic biomass is a promising feedstock for production of affordable fuels and chemicals from renewable resources. Effective solubilization and subsequent deconstruction of its cellulose, hemicellulose, and lignin fractions is essential for the viability of future biorefineries. This study used quantum chemistry-based equilibrium thermodynamics methods to evaluate the potential of 650 cyclic amines to solubilize cellulose, hemicellulose, and lignin. The activity coefficients of solvent - biopolymer interactions were predicted using the COSMO-RS (COnductor-like Screening MOdel for Real Solvents) method and used to identify cyclic amines that can efficiently dissolve and extract selective fractions of biopolymers during biomass pretreatment. Among the 650 cyclic amines, 1-piperazineethanmaine was predicted to be an effective solvent for extracting all three polymers and was experimentally shown to achieve the highest lignin removal (97.1%). Non-covalent interaction, reduced density gradient and quantum chemical calculations were performed to elucidate the dissolution mechanism of lignin, cellulose and hemicellulose and gain further molecular level insights into the interactions between the cyclic amines and biomass polymers that promote efficient solubilization and extraction. These analyses indicated that 1-piperazineethanmaine and 1-methylimidazole make noncovalent van der Waals, electrostatic interactions and hydrogen bonding with lignin, leading to enhanced lignin removal, while the strong intramolecular hydrogen bonding interactions in cellulose and hemicellulose result in weaker solvent-biopolymer interactions. Overall, the computational approach provided an efficient method for identifying cyclic amines tailored for optimal biomass pretreatment and resulted in the identification of a potential new class of solvents for effective biomass pretreatment.

Kumar, Nikhil↗
NASA NTRS1984

Gravitational effects on flames spreading over thick solid surfaces

A theoretical model for the downward spread of a flame in the gas over a semi-infinitely thick fuel bed is presented. Gas-phase chemistry is assumed to proceed at an infinite rate while the fuel bed is taken to pyrolyze at the surface in an Arrhenius fashion. Spread rates and flame shapes are computed for two different ambient oxygen concentrations for gravitational accelerations both below and above that of the earth. Predicted spread rates decrease and actual flame size increases with decreasing gravity. Results agree favorably with available, experimental results and expected results from reduced gravity experimentation.

Vedha-Nayagam, M.↗
DOE OSTI2022

Experiments and modeling to evaluate global reaction kinetics of three-way catalyst light off for net-zero carbon fuels and selected fuel blends

Internal combustion engine exhaust composition can have a significant impact on the light-off characteristics of CO, NO, and organics in the three-way-catalyst during cold-start. The U.S. Department of Energy’s Co-Optimization of Fuels and Engines initiative was aimed at developing new high-performance fuels, which raises the question of how current three-way-catalysts will perform if the exhaust composition is significantly changed. This work is aimed at quantifying the performance of the catalyst under a variety of different fuel components and mixtures. To this end, a reduced-order model is developed wherein the set of organics examined are placed into molecular groups based on their reactivities and to model each organic within that group with a common kinetic expression. In conclusion, this strategy allows for a first approximation to the light-off characteristics of all organics that fall within that group and to make predictions for fuel blends.

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

A Machine Learning Model for Predicting Composition of Catalytic Coprocessing Products from Molecular Beam Mass Spectra

Demand for the development of an automated and integrated refining process for biofuels has increased in recent years due to the lack of generalized process inspection tools. In bio-oil upgrading processes, all process variables are maintained based on the offline specification of intermediates and products. A lack of real-time product specifications in batch-wise monitoring can cause process failure and wasted resources. Therefore, there is a need for a fast and accurate intermediates/product specification tool that can be used for real-time specification to reduce waste and mitigate the risk of process failure. Here, to address this gap, we developed a machine learning (ML) model for predicting speciated bio-oil composition, including paraffin, iso-paraffins, olefins, naphthene, and aromatics. The model is trained using the mass spectra from upgraded products collected in the vapor phase before condensation and predicts the composition of the condensed product. Training ML models using raw mass spectra is challenging due to numerous overlapped peaks originating from different parent compounds. With this in mind, we propose a protocol that (i) transforms raw mass spectra to chemistry-inspired predefined features and (ii) trains decision tree-based models using these features. Our results show that the random forest model was robust against overfitting and had the highest accuracy compared to other models. Moreover, a stochastic ablation method determined the eight most significant features while maximizing the accuracy. Our protocol facilitates real-time compositional analysis of upgraded bio-oils and thus real-time process monitoring. Additionally, this protocol enables the rational design of efficient catalysts and the determination of optimal process conditions.

09 BIOMASS FUELS↗
NASA NTRS2001

Quantitative Species Measurements in Microgravity Combustion Flames

Flame-vortex interactions are canonical configurations that can be used to study the underlying processes occurring in complicated turbulent reacting flows. The elegant simplicity of the flame-vortex interaction permits the study of these complex interactions under relatively controllable experimental configurations, in contrast to direct measurements in turbulent flames. The ability to measure and model the fundamental phenomena that occur in a turbulent flame, but with time and spatial scales which are amenable to our diagnostics, permits significant improvements in the understanding of turbulent combustion under both normal and reduced gravity conditions. In this paper, we report absolute mole fraction measurements of methane in a reacting vortex ring. These microgravity experiments are performed in the 2.2-sec drop tower at NASA Glenn Research Center. In collaboration with Drs. Chen and Dahm at the University of Michigan, measured methane absorbances are incorporated into a new model from which the temperature and concentrations of all major gases in the flame can be determined at all positions and times in the development of the vortex ring. This is the first demonstration of the ITAC (Iterative Temperature with Assumed Chemistry) approach, and the results of these computations and analyses are presented in a companion paper by Dahm and Chen at this Workshop. We believe that the ITAC approach will become a powerful tool in understanding a wide variety of combustion flames under both equilibrium and non-equilibrium conditions.

Silver, Joel A.↗
NASA NTRS2010

Variability of Springtime Transpacific Pollution Transport During 2000-2006: The INTEX-5 Mission in the Context of Previous Years

We analyze the transport of pollution across the Pacific during the NASA INTEX-B (Intercontinental Chemical Transport Experiment Part 8) campaign in spring 2006 and examine how this year compares to the time period for 2000 through 2006. In addition to aircraft measurements of carbon monoxide (CO) collected during INTEX-B, we include in this study multi-year satellite retrievals of CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument and simulations from the chemistry transport model MOZART-4. Model tracers are used to examine the contributions of different source regions and source types to pollution levels over the Pacific. Additional modeling studies are performed to separate the impacts of inter-annual variability in meteorology and .dynamics from changes in source strength. interannual variability in the tropospheric CO burden over the Pacific and the US as estimated from the MOPITT data range up to 7% and a somewhat smaller estimate (5%) is derived from the model. When keeping the emissions in the model constant between years, the year-to-year changes are reduced (2%), but show that in addition to changes in emissions, variable meteorological conditions also impact transpacific pollution transport. We estimate that about 113 of the variability in the tropospheric CO loading over the contiguous US is explained by changes in emissions and about 213 by changes in meteorology and transport. Biomass burning sources are found to be a larger driver for inter-annual variability in the CO loading compared to fossil and biofuel sources or photochemical CO production even though their absolute contributions are smaller. Source contribution analysis shows that the aircraft sampling during INTEX-B was fairly representative of the larger scale region, but with a slight bias towards higher influence from Asian contributions.

Pfister, G. G.↗
NASA NTRS2017

Creating Aerosol Types Form CHemistry (CATCH): a New Algorithm to Extend the Link Between Remote Sensing and Models

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

K W Dawson↗
DOE OSTI2022

Degradation mechanism of blended cement pastes in sulfate-bearing environments under applied electric fields: Sulfate attack vs. decalcification

Applied electric fields, the reason behind stray currents, accelerate the ingress of sulfate into cementitious materials. To identify mitigation approaches, this study investigates the effects of slag and fly ash on sodium sulfate attacks of cement pastes under a constant electric current. The mineralogical alterations induced by the attacks were analyzed using X-ray diffractometry, thermogravimetric analysis, scanning electron microscopy, and thermodynamic modeling. The dissolution of aluminates in the slag and fly ash induced a monosulfate-rich area (>~20 mm from the cathode surface) to form next to the ettringite-rich area on the sample surface (<~20 mm). This effect reduced the availability of SO 4 2– in the pore solution, thereby hindering the penetration of sulfate. Meanwhile, the consumption of portlandite by the pozzolanic reaction lowered the decalcification resistance of the materials. This produced a wide area that endured the decomposition of portlandite and carbonate-AFm. Altogether, blending 30% fly ash did not improve the resistance of the material to either sulfate attacks or decalcification; blending 50% slag can effectively mitigate sulfate ingress, though decalcification may become a governing mechanism in the degradation process.

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

A Tracer Study on sCO2 Corrosion with Multiple Oxygen-Bearing Impurities

Abstract Several modern power production systems utilize supercritical CO 2 (sCO 2 ), which can contain O 2 and H 2 O as impurities. These impurities may degrade the compatibility of structural alloys through accelerated oxidation. However, it remains unclear which of these impurities plays a bigger role in high-temperature reactions taking place in sCO 2 . In this study, various model and commercial Fe‐ and Ni‐based alloys were exposed in 300 bar sCO 2 at 750 °C to low levels (50 ppm) of O 2 and H 2 O for 1,000 h. 18 O-enriched water was used to enable the identification of the oxygen source in the post-exposure characterization of the samples. However, oxygen from the water did not accumulate in the scale, which consisted of Cr 2 O 3 in the cases where a protective oxide formed. A 2wt.% Ti addition to a Ni-22%Cr model alloy resulted in the formation of thicker oxides in sCO 2 , while a 1wt.% Al addition reduced the scale thickness. A synergistic effect of both Al and Ti additions resulted in an even thicker oxide than what was formed solely by Ti, similar to observations for Ni-based alloy 282.

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

Enhancement of van der Waals Interlayer Coupling through Polar Janus MoSSe

Interlayer coupling plays essential roles in the quantum transport, polaritonic, and electrochemical properties of stacked van der Waals (vdW) materials. In this work, we report the unconventional interlayer coupling in vdW heterostructures (HSs) by utilizing an emerging 2D material, Janus transition metal dichalcogenides (TMDs). In contrast to conventional TMDs, monolayer Janus TMDs have two different chalcogen layers sandwiching the transition metal and thus exhibit broken mirror symmetry and an intrinsic vertical dipole moment. Such a broken symmetry is found to strongly enhance the vdW interlayer coupling by as much as 13.2% when forming MoSSe/MoS 2 HS as compared to the pristine MoS 2 counterparts. Our noncontact ultralow-frequency Raman probe, linear chain model, and density functional theory calculations confirm the enhancement and reveal the origins as charge redistribution in Janus MoSSe and reduced interlayer distance. Furthermore, our results uncover the potential of tuning interlayer coupling strength through Janus heterostacking.

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

Machine learning a molecular Hamiltonian for predicting electron dynamics

We develop a computational method to learn a molecular Hamiltonian matrix from matrix-valued time series of the electron density. As we demonstrate for three small molecules, the resulting Hamiltonians can be used for electron density evolution, producing highly accurate results even when propagating 1,000 time steps beyond the training data. As a more rigorous test, we use the learned Hamiltonians to simulate electron dynamics in the presence of an applied electric field, extrapolating to a problem that is beyond the field-free training data. We find that the resulting electron dynamics predicted by our learned Hamiltonian are in close quantitative agreement with the ground truth. Our method relies on combining a reduced-dimensional, linear statistical model of the Hamiltonian with a time-discretization of the quantum Liouville equation within time-dependent Hartree Fock theory. In conclusion, we train the model using a least-squares solver, avoiding numerous, CPU-intensive optimization steps. For both field-free and field-on problems, we quantify training and propagation errors, highlighting areas for future development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗