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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Diatom influence on the production characteristics of hydrate-bearing sediments: Examples from Ulleung Basin, offshore South Korea

The Ulleung Basin Gas Hydrate field expeditions in 2007 (UBGH1) and 2010 (UBGH2) sought to assess the Basin's gas hydrate resource potential. Coring operations in both expeditions recovered evidence of gas hydrate, primarily as fracture-filling (or vein type) morphologies in mainly silt-sized, fine-grained sediment, but also as pore-occupying hydrate in the coarser-grained layers of interbedded sand and fine-grained systems. A commonality across many of these occurrences is the presence of diatoms in the fine-grained sediment. Here we tested fine-grained sediment (median grain size <12.5 μm) associated with hydrate occurrences at four UBGH2 sites (UBGH2-2-2, UBGH2-3, UBGH2-6 and UBGH2-11) to investigate potential impacts of diatoms on efforts to extract methane from hydrate, or to tap hydrocarbon reservoirs beneath hydrate-bearing sediment. Two key considerations are: the extent to which diatoms control sediment mechanical properties, and the extent to which pore-water freshening, which occurs as gas hydrate breaks down during resource extraction, alters the diatom control on sediment mechanical properties. We conducted experiments to measure sediment index properties, sedimentation behavior and compressibility to address these considerations. We relied on scanning electron microscope (SEM) imagery and X-ray powder diffraction (XRD) to characterize the sediment mineralogy. Our high-level findings are that at the ~20–45% (by volume) diatom concentrations observed at these UBGH2 sites, sediment compressibility increases with diatom content, but diatoms only appear to increase porosity and permeability at the highest diatom concentration (~45%). Our measurements suggest in situ compression indices of 0.35–0.55 and permeabilities on the order of 0.01milliDarcies (1 × 10 -17 m 2 ) can be anticipated at these sites. Importantly, these properties are not expected to vary significantly upon pore water freshening that accompanies gas hydrate dissociation during production.

58 GEOSCIENCES↗
DOE OSTI2021

Non-Loudon-Fleury Raman scattering in spin-orbit coupled Mott insulators

In this work we revisit the theory of magnetic Raman scattering in Mott insulators with strong spin-orbit coupling, with a major focus on Kitaev materials. We show that Kitaev materials with bond-anisotropic interactions are generally expected to show both one- and two-magnon responses. It is further shown that, in order to obtain the correct leading contributions to the Raman vertex operator R, one must take into account the precise, photon-assisted microscopic hopping processes of the electrons and that, in systems with multiple hopping paths, R contains terms beyond those appearing in the traditional Loudon-Fleury theory. Most saliently, a numerical implementation of the revised formalism to the case of the three-dimensional hyperhoneycomb Kitaev material β– Li 2 Ir O 3 reveals that the non-Loudon-Fleury scattering terms actually dominate the Raman intensity. In addition, they induce a qualitative modification of the polarization dependence, including, e.g., the emergence of a sharp one-magnon peak at low energies, which is not expected in the traditional Loudon-Fleury theory. This peak is shown to arise from microscopic photon-assisted tunneling processes that are of similar type with the ones leading to the symmetric off-diagonal interaction Γ (known to be present in many Kitaev materials), but take the form of a bond-directional magnetic dipole term in the Raman vertex. These results are expected to apply across all Kitaev materials and mark a drastic change of paradigm for the understanding of Raman scattering in materials with strong spin-orbit coupling and multiple exchange paths.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Rare Earth and Transition Metal Containing Glasses

Transition metal (TM) and rare earth (RE) ions have been incorporated into many glass systems such as silicate, phosphate, and borosilicate-based oxide glasses, as well as in halide and chalcogenide glasses, that find applications ranging from optical, photonic, and magnetic devices, solid-state battery, to nuclear waste disposal. Understanding the structural role of RE and TM in these glasses can help to develop glass compositions for targeted applications with either high-optical emission efficiency, electrical conductivity, or chemical durability. In this chapter, we first provide a general introduction of the applications and structural features of RE and TM in glasses, then the critical aspects of molecular dynamics (MD) simulations of these glasses such as interatomic potentials, structural analysis tools to study RE and TM ions in glasses and their clustering behaviors, Quantitative Structure–Property Analysis (QSPR), diffusion and dynamic property calculations, and electronic structure calculations to understand electronic defects such as charge trapping and radiation effects are introduced. Three representative case studies are presented: the first one is on MD simulations of erbium- and europium-doped silica and silicate glasses, as well as cerium doped aluminophosphate glasses, that revealed the effect of glass composition on RE ion local structure and clustering behavior. Electronic structure calculations of cerium-doped glass show how the existence of multioxidation states help to mediate radiation-induced damages caused by excited electron–hole pairs was also discussed. The second one focuses on alkali vanadophosphate glasses where the existence of two vanadium oxidation states help to provide electronic conduction in the glasses while alkali ions provide ionic conduction. MD simulations were used to understand vanadium environments and other structural aspects in the phosphate glasses, as well as the ionic transport behaviors of alkali ions. The third case study is on zirconium-containing borosilicate and aluminosilicate glasses that find wide applications in nuclear waste disposal. MD simulations help to provide structural details of zirconium ions that are validated by diffraction and EXAFS spectra. The structural information was used to interpret changes of mechanical properties and chemical durability by using QSPR and other analyses-based MD-generated structure models.

Du, Jincheng↗
DOE OSTI2025

Enabling Low-Temperature (LTP) Ignition Technologies for Multi-Mode Engines through the Development of a Validated High-Fidelity LTP Model for Predicative Simulations Tools

The goal of multi-mode engine architectures is to extend current lean-burn dilution limits with renewable fuels, which requires spark plugs to deposit high energies (hundreds of mJ) in order to initiate ignition and complete combustion. At elevated energy deposition rates, spark plugs experience increased electrode erosion and thermal losses, which ultimately shortens the spark-plug lifetime and lowers ignition efficiency. As such, in order to safeguard the efficiency gains of multi-mode concepts, new and improved ignition technologies are required. Recently, non-equilibrium low-temperature plasmas (LTP) have been shown to promote energy-efficient ignition via quenching and transport of electronically excited atoms and molecules, selective radical production and fast heating of hydrocarbon/air mixtures [1-2]. Thus, LTP is seen as a technology that can potentially improve the energy extraction efficiency of fuels, while enabling kinetically controlled combustion modes towards fuel leaner conditions to realize current DOE VTO goals of improving the sustainability of future mobility [3]. Although many previous studies have demonstrated the efficacy of plasma-assisted ignition to enhance combustion, the detailed enhancement mechanisms remain largely unknown, especially for oxygenated fuels and at elevated pressures that are most relevant to practical engine conditions. These barriers hinder the development of accurate and comprehensive numerical models that seek to describe LTP-based ignition in existing engine design software tools and methods. Current state-of-the-art simulation capabilities for LTP ignition systems are in need of improvements since they deliver qualitative results only due to important limitations of existing approaches. Firstly, validated kinetic models with elementary steps for plasma discharges in oxygenated fuel/air mixtures of relevance to the transportation sector are required. Such kinetic models do not exist at present and will be developed and validated within this project. Secondly, plasma discharges and reactive mixture ignition are multi-scale, unsteady processes requiring high-performance numerical methods and software that execute efficiently on DOE supercomputers. Such software does not exist at present and will be developed and applied to practical LTP ignition scenarios as part of this project. Thirdly, experimental databases that are tailored to serve as benchmark in support of the development of predictive computational models of LTP ignition do not exist and will be part of this project.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Materials challenges for quantum technologies based on color centers in diamond

Emerging quantum technologies require precise control over quantum systems of increasing complexity. Defects in diamond, particularly the negatively charged nitrogen-vacancy center, are a promising platform with the potential to enable technologies ranging from ultra-sensitive nanoscale quantum sensors, to quantum repeaters for long distance quantum networks, to simulators of complex dynamical processes in many-body quantum systems, to scalable quantum computers. While these advances are due in large part to the distinct material properties of diamond, the uniqueness of this material also presents difficulties, and there is a growing need for novel materials science techniques for characterization, growth, defect control, and fabrication dedicated to realizing quantum applications with diamond. In this article we identify and discuss the major materials science challenges and opportunities associated with diamond quantum technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal conductivity of multilayer polymer-nanocomposite thin films

The development of electrical insulators that are thermally conducting is critical for thermal management applications in many advanced electronics and electrical devices. Here, we synthesized polymer nanocomposite (PNC) films composed of polymers [polyethylenimine, poly(vinylamine), poly(acrylic acid), and poly(ethylene oxide)] and dielectric fillers (montmorillonite clay and hexagonal boron nitride) by layer-by-layer technique. The cross-plane thermal conductivity (k⊥) of the film was measured by the 3ω method. The effect of various factors such as film growth, filler type, filler volume fraction, polymer chemical structures, and temperature on the thermal conductivity is reported. The k⊥ of PNCs with thickness from 37 nm to 1.34 μm was found to be in the range of 0.11 to 0.21 ± 0.02 W m−1 K−1. The k⊥ values were found to be lower than the constituent polymer matrix. The experimental result is compared with existing theoretical models of nanocomposite systems to get insight into heat transfer behavior in such layered films composed of dielectrics and polymers.

Physics↗
DOE OSTI2024

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗
DOE OSTI2021

Multimodal imaging of oil-in-water bilgewater emulsion and biofilms

Bilgewater emulsions, consisting of oil and surfactant mixtures in water, affect many aquatic species. Thus development of methods and techniques to treat or mitigate the formation and undesired consequences of shipboard emulsions are urgently needed. This work presents new results of the evolution of the bilgewaer chemical and physical properties using in situ imaging. A Navy O/W emulsion consisting of three oils and a detergent mixture was used as the synthetic bilgewater model [1, 2]. Synthetic oil-in-water (O/W) emulsion droplets were seled in a vacuum compatible microfluidic sample holder and imaged using a suite of tools including scanning electron microscopy (SEM), time-of-flight secondary ion mass spectrometry (ToF-SIMS), confocal laser scanning microscopy, and optical microscopy, highlighting the advantage of multiscale analysis and its applications in waste reduction and treatment in the environment. The transferrable and vacuum compatible microfluidic interface, System for Analysis at the Liquid Vacuum Interface (SALVI), was used in this study. SALVI enabled surface analysis of liquids and liquid-solid interactions using ToF-SIMS and SEM [3, 4]. Its detection window is an aperture of 2 ?m in diameter open to vacuum, permitting direct detection of the liquid surface. Liquid is withheld by surface tension within the aperture. The interface is composed of a silicon nitride membrane and polydimethylsiloxane microchannel [3, 4]. A variety of samples including complex liquid mixtures, ionic liquids, single mammalian cells, live biofilms, and solid-electrolyte interface have been analyzed using in situ imaging [5, 6]. The feasibility of using SALVI for in situ SEM imaging of nanoparticles and colloids in liquid was recently demonstrated [7]. This paper shows new findings of multimodal imaging and analysis of synthesized emulsion particles in water. Figure 1 depicts a schematic of multimodal in situ imaging of bilgewater emulsion using SEM and ToF-SIMS. Furthermore, we study the interactions of microbes and bilgewater emulsion. Microbes play an important role in the ocean. We hypothesize that microbes release organics that can act as surfactants that affect bilgewater formation or weakening. We present the first systematic study of emulsions and biofilms and investigate the effects of biofilms on bilgewater emulsions. Pseudomonas was selected as a model strain. Biofilms were cultured in a microchannel to allow culture [8]. Once a thick layer of biofilms was formed, the medium solution was changed to a mixture consisting of 50 % bilgewater emulsion. Dispersed biofilms were collected at 24 hrs. and 48 hrs. after emulsions were introduced into the channel. Bilgewater emulsions, biofilms, and mixtures of bilgewater emulsions and biofilms were analyzed using multiple in situ and ex situ techniques as described earlier. Our findings indicate that biofilms change the chemical makeup of the emulsion surface compositions and emulsion droplet size distribution, confirming the hypothesis that extracellular polymeric substance (EPS) related components released from biofilms can function as surfactants and change the oil-in-water interfaces.

bilgewater, multimodal imaging, biofilms↗
DOE OSTI2025

A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion

Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. Here, in this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [Phys. Rev. Lett. 2024, 133, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.

Reeves, Cian C. [Univ. of California, Santa Barbar↗
DOE OSTI2023

Amorphous Metal Ribbon (AMR) and Metal Amorphous Nanocomposite (MANC) Materials Enabled High Power Density Vehicle Motor Applications (Final Technical Report)

A collaborative team from Carnegie Mellon Univ. (CMU), North Carolina State Univ. (NCSU) and Metglas, South Carolina have studied new high speed motors (HSMs) with high-power density for traction motor applications. These are enabled by hybrid designs, including Flux Switching with Permanent Magnets (FSWPM) motors, exploiting permanent magnets without heavy rare earths (RE-lean) and high induction/high resistivity soft magnetic materials that allow for high switching frequencies needed to increase power densities. Team members include Michael E. McHenry, Prof. Materials Science & Eng., CMU, with > 30 years experience in magnetic materials development; Subashish Bhattacharya, Prof. Electrical Eng. and Freedom Center Director at NCSU with > 30 years experience in development of power electronic components and systems and Eric Theisen, Director of Research at Metglas, the only US located supplier of AMR and MANC materials. The team offers novel axial motor architectures exploiting soft magnetic materials (SMMs) that switch with low loss at high frequencies and heavy rare earth free permanent magnets that address materials criticality issues, supply chain risks, and high costs for traction motors. Axial-flux permanent magnet motors (APFM), offer efficiency improvements reducing rotor losses and also significantly higher power density. Axial-flux construction requires less core material, high torque-to-weight ratio. Since AFPM machines have thin magnets, they are smaller than radial flux motors making them attractive in space-limited applications. Noise and vibration are less and planar air gaps are easily adjusted. Flexibility in air-gap direction allows many topologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Editorial: Microbial C1 Metabolism and Biotechnology

Archaea and bacteria with the capacity to utilize one-carbon (C1) molecules as carbon and energy sources are widespread across the planet and are important players in many biogeochemical processes. As such, they occupy an array of diverse anaerobic and aerobic niches and perform unique metabolisms that enable the utilization of carbon dioxide (CO 2 ), carbon monoxide (CO), formate (HCOOH), methanol (CH 3 OH), and methane (CH 4 ) for growth. Several industrial processes have been developed that leverage these microbes for the targeted conversion of anthropogenic waste gases that contain C1 molecules, including natural gas (CH 4 ), anaerobic digestion-derived biogas (CH 4 and CO 2 ), industrial flue gas (CO 2 and CO), and syngas (CO 2 , CO, and H 2 ) (Figure 1). Further, there is increasing interest in electrochemical reduction of CO 2 to CO, CH 4 , and intermediates with increased solubility compared to gaseous C1 molecules (formate and methanol) using electrons derived from renewable sources like wind, solar, or hydrothermal systems to mitigate atmospheric greenhouse gas. Thus, C1-utilizing microbes will likely play an integral role in biotechnologies that are part of a sustainable, circular bioeconomy. However, fundamental knowledge gaps into the metabolism and physiology of these microbes exist that limit their utility as biocatalysts for carbon-efficient biomanufacturing. This special topic presents studies focused on the fundamental aspects of C1 metabolism in diverse microbial systems with the ability to convert anthropogenic greenhouse gases into valuable products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Large Propagation-Direction-Dependent Circularly Polarized Emission and Scattering Anisotropies of a Chiral Organic-Inorganic Semiconductor

Chiral materials are important tools for transducing circularly polarized light within many emerging opto-electronic and spin-based technologies. Here, we demonstrate that thin films of a bismuth iodide-based 0D chiral hybrid organic-inorganic semiconductor (HOIS) exhibit large anisotropy values in circularly polarized light emission (CPLE) that approach 50%, with mirror-image responses from front- and back-side measurements. A comprehensive analysis of light-wave propagation, absorption, emission, and scattering is constructed on the basis of a symmetry-derived exciton fine structure model, which accurately describes the direction and polarization dependence of the observed excitonic circular dichroism and CPLE, including contributions from both photoluminescence and resonant Raman scattering. Our analysis indicates that molecular chirality drives preferential film alignment with respect to the out-of-plane lattice vector direction, producing the observed anisotropies. This first demonstration in an HOIS system provides a unique route for enhancing polarization-dependent emission, and circularly polarized light transduction more broadly, in self-assembled HOIS.

14 SOLAR ENERGY↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Stochastic tensor contraction for quantum chemistry

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2024

Nontrivial fusion of Majorana zero modes in interacting quantum-dot arrays

Motivated by recent experimental reports of Majorana zero modes (MZMs) in quantum-dot systems at the “sweet spot,” where the electronic hopping t ℎ is equal to the superconducting coupling Δ, we study the time-dependent spectroscopy corresponding to the nontrivial fusion of MZMs. The term “nontrivial” refers to the fusion of Majoranas from different original pairs of MZMs, each with well-defined parities. We employ an experimentally accessible time-dependent real-space local density-of-states (LDOS) method to investigate the nontrivial MZM fusion outcomes in canonical chains and in a Y-shaped array of interacting electrons. In the case of quantum-dot chains where two pairs of MZMs are initially disconnected, after fusion we find equal-height peaks in the electron and hole components of the LDOS, signaling nontrivial fusion into both the vacuum I and fermion Ψ channels with equal weight. For π-junction quantum-dot chains, where the superconducting phase has opposite signs on the left and right portions of the chain, after the nontrivial fusion we observed the formation of an exotic two-site MZM near the center of the chain, coexisting with another single-site MZM. Furthermore, we also studied the fusion of three MZMs in the Y-shaped geometry. In this case, after the fusion we observed the novel formation of another exotic multisite MZM, with properties depending on the connection and geometry of the central region of the Y-shaped quantum-dot array.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Difficult Measurements of Materials Systems at Cryogenic Temperatures: Cryo-EELS and Cryo-4D-STEM

Scanning/transmission electron microscopy (S/TEM) in materials science has traditionally been accomplished at room temperature due to their solid state in this temperature range and relative insensitivity to radiolysis damage. Cooling to cryogenic temperatures tended to introduce instabilities such as vibration and drift and can lead to the buildup of carbon contamination or ice reducing contrast. The need to expand TEM experimental techniques into new fields such as quantum and battery materials led to new efforts to reduce these instabilities while achieving temperatures at or well below liquid nitrogen (77 K). Further, developments in detector and spectrometer technology brought new capabilities for high resolution electron energy loss spectroscopy (EELS) and scanning nanodiffraction (4D-STEM). These experimental modalities can require even tighter controls of drift, vibration, and exposure time. Here this presentation will discuss accomplishing difficult experiments at cryogenic temperatures in honor of the late Dr. Lena Kourkoutis who inspired and led many such experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pilgrim : A thermal rate constant calculator and a chemical kinetics simulator

Pilgrim is a program written in Python and designed to use direct dynamics in the calculation of thermal rate constants of chemical reactions by the variational transition state theory (VTST), based on electronic structure calculations for the potential energy surface. Pilgrim can also simulate reaction mechanisms using kinetic Monte Carlo (KMC). For reaction processes with many elementary steps, the rate constant of each of these steps can be calculated by means of conventional transition state theory (TST) or by using VTST. In the current version, Pilgrim can evaluate thermal rates using the canonical version of reaction-path VTST, which requires the calculation of the minimum energy path (MEP) associated with each elementary step or transition structure. Multi-dimensional quantum effects can be incorporated through the small-curvature tunneling (SCT) approximation. These methodologies are available both for reactions involving a single structure of the reactants and the transition state and also for reactions involving flexible molecules with multiple conformations of the reactant and/or of the transition state. For systems with many conformers, the program can evaluate each of the elementary reaction rate constants by multipath canonical VTST or multi-structural VTST. Moreover, the reactant can be unimolecular or bimolecular. Torsional anharmonicity can be incorporated through either the MSTor or the Q2DTor programs. Dual-level calculations are also available in Pilgrim: automatic high-level single-point energies can be used to correct the energy of reactants, transition states, products, and MEP points using the interpolated single-point energies (ISPE) algorithm. When the rate constants of all the chemical processes of interest are known, by means of their calculation using Pilgrim or alternatively through analytical fits to the rate constants as functions of temperature, it is possible to simulate a multistep mechanism under specified laboratory conditions using KMC. Finally, this algorithm allows performing a kinetic simulation to monitor the evolution of each chemical species with time and obtain the product yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Exact two-body expansion of the many-particle wave function

Progress toward the solution of the strongly correlated electron problem has been stymied by the exponential complexity of the wave function. Previous work established an exact two-body exponential product expansion for the ground-state wave function. By developing a reduced density-matrix analog of Dalgarno-Lewis perturbation theory, we prove here that (i) the two-body exponential product expansion is rapidly and globally convergent with each operator representing an order of a renormalized perturbation theory, (ii) the energy of the expansion converges quadratically near the solution, and (iii) the expansion is exact for both ground and excited states. The two-body expansion offers a reduced parametrization of the many-particle wave function as well as the two-particle reduced density matrix with potential applications on both conventional and quantum computers for the study of strongly correlated quantum systems. In this work, we demonstrate the result with the exact solution of the contracted Schrödinger equation for the molecular chains H 4 and H 5 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗