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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Handling Iterative Solvers in an Algorithmic Differentiation Framework Using Implicit Methods

Differentiable programming is a powerful concept as it enables the seemly propagation of gradients through functions, algorithms, and/or whole physics simulations. These gradients are useful for a wide variety of applications, including sensitivity studies and machine learning, but one of particular interest is optimization. Gradient-based optimization, enabled through automatic/algorithmic differentiation (AD), can be used on predictive physical models to efficiently optimize a set of design variables. AD methods are a particularly promising approach to complex physics simulations because they can be shown to scale well with an increasing number of design variables; however, care must be taken when coupling between different models or different states of a single model.

algorithmic differentiation↗
DOE OSTI2020

Analytical integration of the tractions induced by non-singular dislocations on an arbitrary shaped triangular quadratic element

Here, an analytical model is proposed to evaluate the nodal force induced by a segment of dislocation upon an arbitrary shaped triangular element. This calculation is required in hybrid methods that associate dislocation dynamics to boundary or finite element to solve simultaneously the evolution of large ensembles of dislocations with complex boundary conditions. Nodal forces are defined as the triple integration of the unbalanced traction field induced by a straight dislocation upon the surface of the element. Following our previous approach (Queyreau et al 2014 Modelling Simul. Mater. Sci. Eng. 22 035004) on a simpler geometry and in the case of linear isotropic elasticity, triple integrals are solved by sequences of integration by parts that exhibit recurrence relations. The traction field is defined and finite everywhere even at the core of dislocations, thanks to the use of the non-singular stress expression formulated by Cai et al (2006 J. Mech. Phys. Solids 54 561–587). The nodal force expressions can be used when considering both a single convolution or double convolution of the Green's function with the core distribution. A solution is also proposed for the case of a semi-infinite segment through the study of the asymptotic behavior of the analytical expressions. The proposed approach is exact and very computationally efficient. The choice of an arbitrary shaped triangular element and quadratic shape functions allow the consideration of complex geometries and comply with automatic meshing procedures. These analytical expressions could also be employed to estimate dislocation interactions with interfaces.

42 ENGINEERING↗
DOE OSTI2024

Investigating Cu-Site Doped Cu–Sb–S Nanoparticles Using Photoelectron and Electron Paramagnetic Resonance Spectroscopy

Tetrahedrite (Cu 12 Sb 4 S 13 ) and famatinite (Cu 3 SbS 4 ) are good candidates for green energy applications because they possess promising thermoelectric and photovoltaic properties as well as contain earth-abundant and nontoxic constituents. Herein, X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), and electron paramagnetic resonance spectroscopy (EPR) methods examined inherent electronic properties and interatomic magnetic interactions of Cu-site doped tetrahedrite and famatinite nanomaterials. An energy-efficient modified polyol method was utilized for the synthesis of tetrahedrite and famatinite nanoparticles doped on the Cu-site with Zn, Fe, Ni, Mn, and Co. This is the first parallel study of tetrahedrite and famatinite nanomaterials with XPS, UPS, and EPR methods alongside a systematic analysis of dopant-dependent effects on the electronic structure and magnetic interactions for each material. XPS showed that the Cu and Sb species in tetrahedrite and famatinite possess different oxidation states, while UPS characterization reveals larger dopant-dependent shifts in the work function for tetrahedrite nanoparticles (4.21 to 4.79 eV) than for famatinite nanoparticles (4.57 to 4.77 eV). Finally, all famatinite nanoparticles display an EPR signal, indicating trace amounts of paramagnetic Cu(II) present below the detection limit of XPS. For tetrahedrite, EPR signatures were observed only for the Zn-doped and Mn-doped nanoparticles, suggesting signal broadening from Cu–Cu spin exchange or spin–lattice relaxation. This study demonstrates the complementary nature of XPS and EPR techniques for studying the oxidation states of metals in solid-state nanomaterials. Comparing the electronic and magnetic properties of tetrahedrite and famatinite while studying the impact of dopant incorporation will guide future endeavors in designing sustainable, high-performance materials for renewable energy applications.

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

Complex Adsorption Behavior of Neodymium and Ytterbium on Structurally-Distinct Alumina Surfaces

New sources of rare earth elements (REEs) are needed to support a green energy transition. REEs adsorbed to aluminum-rich clays in weathering deposits represent important resources but the mechanisms responsible for their retention and ease of extraction are unresolved. Disordered coordination and co-occurrence of multiple species pose challenges to investigating REE adsorption processes via established spectroscopic methods. In this study, we applied element-specific surface crystallography methods to obtain a new perspective on the complexity of REE adsorption mechanisms and affinities. Alumina (001) and (012) crystal surfaces were utilized to evaluate surface-specific controls on Nd(III) and Yb(III) adsorption behavior. The REEs displayed similar total adsorption to alumina (001) as a mixture of inner- and outer-sphere complexes, but Nd displayed a greater proportion of inner-sphere binding. Adsorption of ordered inner- and outer-sphere REE species was substantially lower on alumina (012). These distinct behaviors reflect differences in the surface functional group charging and topography of the two surfaces. However, alumina (012) also hosted a substantial population of disordered adsorbed species, especially for Nd, potentially associated with Al vacancy surface defects. Here, the accumulation of light versus heavy REEs via adsorption in weathering deposits likely results from multiple, competing reactions affected by clay particle morphology. Leaching procedures for resource recovery should account for differential rates of desorption by coexisting inner- and outer-sphere REE surface complexes.

58 GEOSCIENCES↗
DOE OSTI2024

Phosphonate functionalized magnetic mesoporous silica for rare earth element recovery from citrate assisted solid waste extracts

The growing high demand of rare earth elements (REEs) has prompted extensive research on REE recovery from waste streams. This study reports the synthesis and evaluation of phosphonate-functionalized magnetic mesoporous silica (MMS-PP) for REE recovery from the acidic extracts of solid wastes. MMS-PP was synthesized using surfactant template and post-synthesis methods, and tested using simulated and real extraction solutions from citrate-assisted REE extracts from municipal solid waste incineration (MSWI) ash. The organic-inorganic hybrid MMS-PP was evaluated for La recovery from 50 mM simulated citrate extract, with the adsorption capacity of 13.5 mg/g compared to ∼2.5 mg/g for non-functionalized MMS. The MMS-PP material exhibited fast adsorption within 10 min, good La selectivity against competing Na + and Ca 2+ , moderate selectivity against Al 3+ and Fe 3+ , high recyclability over multiple adsorption-desorption cycles, and equivalent efficiency for La, Ce, Nd, and Y recovery. Furthermore, the MMS-PP material also demonstrated 70–95% REE recovery from real citrate extracts of MSWI ash, and the spent MMS-PP material can be regenerated and reused for multiple cycles. Functionalized mesoporous materials in combination with organic-ligand assisted extraction can potentially provide a green, effective, and tunable solid-liquid separation platform for REE recovery from complex solid waste streams.

REE recovery↗
DOE OSTI2020

Optimization of Energy Flow through Synthetic Metabolic Modules and Regulatory Networks in a Model Photosynthetic Eukaryotic Microbe

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methods, coupled with functional and synthetic genomics, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require a detailed systems biology understanding of photosynthetic processes and cellular metabolism. Genome-scale metabolic models (GEMs) are at the core of systems analysis of cellular processes and form a common organizational framework for analyses of data resulting from functional genomics experimental work and computational studies. Therefore, there is a clear demand for high quality photosynthetic model organisms and the appropriate computational tools that enable systems analysis of light-driven metabolism. Through research conducted we expanded the currently available repertoire of photosynthetic GEMs to include the commercially valuable model diatom Phaeoctylum tricornutum. Diatoms have a peculiar and distinct evolutionary footprint and represent a major eukaryotic lineage that is taxonomically and functionally distinct from green and red algae and vascular plants. Therefore, the true potential for light-driven metabolism aimed at biofuel production remains poorly understood at a systems level for a large subset of the global diversity of photosynthetic organisms. The metabolic capabilities of P. tricornutum were comparatively modeled with those from other photosynthetic groups in order to elucidate the occurrence of metabolic traits within and between phototrophs. Additionally, this research resulted in significant extension of the COnstraints Based Reconstruction and Analysis (COBRA) Toolbox to accommodate the crucial need for infrastructure required for ‘omics data integration and analysis in the context of genome-scale models. Therefore, the proposed research achieved two important goals. First, within the broad scope of photosynthetic organisms, we functionally compared and, as a result, identified cellular processes that require optimization in order to enable deployment as biofuel feedstock. Second, the proposed research resulted in development of key computational infrastructure, which can be further extended to other biological systems, that is currently lacking but necessary for multiple ‘omics data integration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Crucial role of thermal fluctuations and vertex corrections for the magnetic pseudogap

It is generally believed that in a two-dimensional metal, whose ground state is antiferromagnetically ordered with Q = (π,π), thermal (static) magnetic fluctuations give rise to precursor behavior above TN in which the spectral function of a hot fermion (the one for which k and k + Q are Fermi surface points) contains two peaks, separated by roughly the same energy as in the antiferromagnetically ordered state. The two peaks persist in some range of T > T N and eventually merge into a single peak at zero frequency. This behavior is obtained theoretically by departing from free fermions in a paramagnet and evaluating the dressed fermionic Green's function by summing up infinite series of diagrams with contributions from thermal magnetic fluctuations. We show, following that keeping vertex renormalization diagrams in these series is crucial as other terms only broaden the spectral function of a hot fermion but do not shift its maximum away from zero frequency. As the consequence, the magnetic pseudogap should be treated as an input for theories that neglect vertex corrections, such as, e.g., Eliashberg theory for magnetically mediated superconductivity. We also analyze the potential pseudogap behavior at T = 0. Here, we argue that it may exist, but only at a finite correlation length, and not as a precursor to antiferromagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Light Energy Transduction in Green Sulfur Bacteria

Green sulfur bacteria (GSB) are exquisitely adapted for growth at extraordinarily low light intensities. They are important primary producers of biomass in many anoxic environments, and they contribute significantly to the biogeochemical cycling of carbon, nitrogen, and sulfur on Earth. Green bacteria more generally share the property of using chlorosomes for light-harvesting, and these unusual organelles have many unique features. These include the presence of a monolayer lipid-protein envelope, self-assembling bacteriochlorophylls (BChl) in which pigment-pigment interactions predominate, and the presence of redox components ([2Fe-2S] ferredoxins and quinones) that play a role in regulating excitation energy transfer to the type-1 homodimeric reaction centers. The reaction centers of GSB are related to Photosystem I of cyanobacteria and higher plants but also exhibit several unique structural and functional features. The long-term objectives of this research program are to understand the structure, functions, and biogenesis of the chlorosomes, reaction centers, and electron transport chains that carry out the photochemical transduction of light energy into chemical energy in the model green sulfur bacterium, Chlorobaculum (formerly Chlorobium) tepidum. Over a period of 26 years, we characterized chlorosomes in detail. We identified the proteins in the chlorosome envelopes of diverse organisms, identified the nearest neighbors of those proteins, and characterized the chlorosomes of mutant strains lacking one to five of these proteins. After the genome sequence of Cba. tepidum became available, we identified all genes encoding enzymes for BChl a , BChl c/d/e/ƒ , and Chl a biosynthesis Cba. tepidum . We additionally identified all genes encoding enzymes for carotenoid biosynthesis. By constructing a bchQRU mutant strain that produces [Et, Me]-BChl d , together with collaborators who are specialists in solid-state NMR and cryo-electron microscopy, we solved the structure of the BChls in chlorosomes. Using similar methods and chlorosomes containing [Et, Me]-BChl c , we then showed that alternative structures were possible using the same syn-anti BChl dimer. The structures were refined by introducing spectroscopic data from single-chlorosome measurements. Over the course of this project, we sequenced the genomes of approximately twenty GSB strains, which provided important information for comparative analyses. Through analyses of metagenomic data from Mushroom and Octopus Springs in Yellowstone National Park, we identified a novel chlorophototroph belonging to the phylum Acidobacteriota. We successfully isolated an axenic culture of this organism. We characterized the photosynthetic apparatus of this bacterium, named Chloracidobacterium thermophilum, in significant detail, in particular its type-1, homodimeric reaction centers. Surprisingly, these reaction centers contain three types of Chls, BChl a , Chl a , and Zn-BChl a' . We showed that a dimer of Zn-BChl a' is the primary donor and Chl a the primary acceptor of electrons in this reaction center by using advanced spectroscopic techniques. We isolated eight additional strains of Chloracidobacterium spp. from Mushroom Spring and Rupite hot springs in Bulgaria. Comparative genomes showed that these represent three species, Cab. thermophilum , Cab. aggregatum , and Cab. validum . By applying comparative genomics, genetic, biochemical biophysical and physiological approaches to study green bacteria, we produced a wealth of new information about the remarkable light-harvesting and energy transduction capabilities of these poorly characterized microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Third moments of nucleon unpolarized, polarized, and transversity parton distribution functions from physical-point lattice QCD

Using forward matrix elements of local leading-twist operators, we present a determination of the isovector third Mellin moments ⟨𝑥 2 ⟩ of nucleon unpolarized, polarized, and transversity parton distribution functions. Two lattice QCD ensembles at the physical pion mass are used, which were generated using a tree-level Symanzik-improved gauge action and 2+1 flavor tree-level improved Wilson Clover fermions coupling via 2-level HEX-smearing. Leveraging a wide set of operators, two extraction methods for the matrix elements, and the automatic inclusion of model uncertainties via bootstrapped model averages, we extract values of the third Mellin moments. Furthermore, this is the first direct calculation of these observables performed at the physical pion mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Microgrid energy scheduling under uncertain extreme weather: Adaptation from parallelized reinforcement learning agents

Microgrids are useful solutions for integrating renewable energy resources and providing seamless green electricity to minimize carbon footprint. In recent years, extreme weather events happened often worldwide and caused significant economic and societal losses. Such events bring uncertainties to the microgrid energy scheduling problems and increase the challenges of microgrid operation. Traditional optimization approaches suffer from the inaccuracy of the uncertain microgrid model and the unseen events. Existing reinforcement learning (RL) - based approaches are also hampered by the limited generalization and the increasing computational burden when stochastic formulations are required to accommodate the uncertainties. This paper proposes a new parallelized reinforcement learning (PRL) method based on the probabilistic events to handle the microgrid energy uncertainties. Specifically, several local learning agents are employed to interact with pertinent microgrid environments in a distributed manner and report outcomes to the global agent, which will optimize microgrid energy resources online during extreme events. The stochastic microgrid energy optimization problem is reformulated to include all possible scenarios with probabilities. The advantage estimate functions of learning agents are designed with a backward sweep to transfer the outcomes to the value function updating process. Two simulation studies, stochastic optimization and online testing, are performed to compare with several existing RL approaches. Results substantiate that the proposed PRL method can achieve up to 20% optimization performance improvement with 4 and 28 times less computation cost than Q-learning with experience replay and multi-agent Q-learning approaches, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Innovation and Winemaking By-Product Valorization: An Ohmic Heating Approach

The by-products of the winemaking process can represent chances for the development of new products. This study focused on the “zero waste” strategy development for by-products generated within winemaking from white and red grape varieties cultivated in the north of Portugal. The phytochemical properties of by-products were identified and characterized. Ohmic heating (OH) as a green extraction method was also applied to grape pomace due to their unknown effects on centesimal and phytochemical compositions. Both protein and carbohydrates were shown to be higher in grape bagasse than in stems. Additionally, red bagasse is richer in bioactive compounds (BC) than white bagasse. The sugar content was 21.91 and 11.01 g/100 g of DW in red and white grape bagasse, respectively. The amount of protein was 12.46 g/100 g of DW for red grape bagasse and 13.18 g/100 g of DW for white. Regarding the extraction methods, two fractions were obtained, a liquid fraction and solid (the remainder after the methodology application). OH presented a higher antioxidant capacity than a conventional (CONV) method. In addition, both extracts presented similar contents of anthocyanins, e.g., delphinidin-3-O-glucoside, petunidin-3-O-glucoside, and peonidin-3-O-glucoside. The solid fraction presented higher amounts of protein and phenols bound to fiber than CONV, which allows its use as a functional ingredient. In conclusion, OH can be an alternative extraction method compared with CONV methods, avoiding non-food grade solvents, thus contributing to circular economy implementation.

Coelho, Marta C. (ORCID:000000026542175X)↗
DOE OSTI2026

Engineering Anti-Microbial Peptide Production in Fungi and Bioprocess Development (CRADA 502)

Crop Protection, specifically controlling agricultural diseases and pests, is essential for crop production at every agricultural scale. Biologics hold enormous potential in this equation to decrease use of more toxic pesticides. Currently, the widespread use of biologics in crop protection is severely hampered by the lack of available tools for their mass production. To ensure biologics are regulated under EPA Biopesticide regulations, the following must be true: The biopesticide is a naturally occurring substance or structurally similar and functionally identical to a naturally occurring substance with a history of exposure to humans and the environment demonstrating minimal toxicity. Since this pertains to the marketed product it is also essential that fermentation hosts have a history of exposure and safe use by humans This research focuses on developing a novel platform for the production and delivery of the cghSAMP peptide using the filamentous fungus Aspergillus niger. A. niger is a well-established industrial microorganism, widely recognized for its strong protein secretion capabilities, high-yield production of enzymes, and classification as a generally recognized as safe (GRAS) organism. By genetically modifying A. niger to express the cghSAMP peptide transgene, we aim to leverage the fungus's robust fermentation system to produce a high volume of the antimicrobial agent. This engineered system represents a potential breakthrough in sustainable disease management, offering an environmentally friendly method for localized application or large-scale production of a biopesticide designed to mitigate the effects of citrus greening disease. The main objectives of this project were: 1. Developing a high-yield and cost-efficient bioprocess to produce an AMP in a current ABF host or readily onboarded hosts. 2. Scale up the process in stirred tank reactors and produce at least 100 grams of AMP at 1- 5g/L

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Designing Catalysts for Dehydrogenation of Methane for Reducing Greenhouse Gas during Natural Gas Extraction

Catalytic conversion of methane (CH 4 ) into useful products is critical for maximizing the utility of natural gas output and for reducing green house gas release associated with flaring (burning off CH 4 at natural gas extraction sites). One particular useful technique is methane dry reforming (DRM), which involves the chemical reaction of CH 4 with carbon dioxide (CO 2 ) to generate carbon monoxide (CO), hydrogen gas (H 2 ), and subsequently other useful products. New and improved catalysts are required to facilitate efficient dry methane reforming. In this report, we apply the Density Functional Theory (DFT) computational technique to investigate a catalyst consisting of small nickel clusters (Ni n , n < 10) on ceria (Ce0 2 (111) surfaces) support. One main thrust of this project is to study the initial CH 4 and CO 2 reactions with the catalyst. We find that CH 4 exhibits barrierless reactive adsorption on to the catalyst. In order words, this step is likely not the rate-determining step. A second thrust is to perform detailed studies of the catalyst itself and examine the role of oxygen vacancies. Using a specific DFT method and a hypothesis about the absence of the Ce(III) redox state, we obtain predictions about oxygen vacancies in good agreement with experimental observations.

03 NATURAL GAS↗
DOE OSTI2023

Influence of aluminum incorporation and aqueous conditions on metal ion release of high-Ni transition metal oxide nanomaterials

Developing a materials perspective of how to control the degradation and negative impact of complex metal oxides requires an integrated understanding of how these nanomaterials transform in the environment and interact with biological systems. Doping with aluminum is known to stabilize oxide materials, but has not been assessed cohesively from synthesis to environmental fate and biological impact. In the present study, the influence of aluminum doping on metal ion release from transition metal oxides was investigated by comparing aqueous transformations of lithium nickel cobalt aluminum oxide (LiNi 0.82 Co 0.15 Al 0.03 O 2 ; NCA) and lithium nickel cobalt oxide (LiNi 0.80 Co 0.20 O 2 ; NC) nanoparticles and by calculating the energetics of metal release using a density functional theory (DFT) and thermodynamics method. Two model environmental organisms were used to assess biological impact, and metal ion release was compared for NCA and NC nanoparticles incubated in their respective growth media: moderately hard reconstituted water (MHRW) for the freshwater invertebrate Daphnia magna (D. magna) and minimal growth medium for the Gram-negative bacterium Shewanella oneidensis MR-1 (S. oneidensis). Further, the amount of metal ions released was reduced for NCA compared to NC in MHRW, which correlated to changes in the modeled energetics of release upon Al substitution in the lattice. In minimal medium, metal ion release was approximately an order of magnitude higher compared to MHRW and was similar to the stoichiometry of the bulk nanoparticles for both NCA and NC. Interpretation of the release profiles and modeling indicated that the increase in total metal ion release and the reduced influence of Al doping arises from lactate complexation of metal ions in solution. The relative biological impacts of NC and NCA exposure for both S. oneidensis and D. magna were consistent with the metal release trends observed for minimal medium and MHRW, respectively. Together, these results demonstrate how a combined experimental and computational approach provides valuable insight into the aqueous transformations and biological impacts of complex metal oxide nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a ‘living data resource.’ Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Membrane Contactor Enabling Energy-Efficient CO 2 Capture from Point Sources with Deep Eutectic Solvents

We demonstrate a scalable and energy-efficient hollow fiber membrane contactor (HFMC)-based process using a green solvent for CO 2 capture. This process uses a deep eutectic solvent (DES) in an HFMC to provide close interfacial interactions and contact between the DES and CO 2 . This approach overcomes disadvantages associated with direct absorption in DES and could potentially be applied to a variety of solvent-based CO 2 capture methods. Commercial low-cost polymer hollow fiber membranes (e.g., microporous polypropylene) were evaluated for CO 2 capture with reline, a prototypical DES. Single-gas measurements showed that the DES-based polypropylene HFMC can capture and separate CO 2 while rejecting N2. From a mixed gas containing 50 mol % N 2 and 50 mol % CO ν , the DES-based HFMC separated CO 2 with a purity of 96.9 mol %. The effect of several process parameters including solvent flow rate, pressure, and temperature on the CO 2 separation performance was studied. The flux of the recovered CO 2 was 67.43 mmole/m 2 /h at a feed pressure of 4 bar. In situ Fourier transform infrared (FTIR) measurements combined with density functional theory (DFT)-based molecular dynamics simulations revealed that reline absorbs CO 2 by physical absorption without forming a new chemical compound, and CO 2 separation by reline occurs via the pressure swing mechanism. This research provides fundamental insights about physical solvent-based separation processes and a pathway toward practical deployment.

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

Galerkin formulation of path integrals in lattice field theory

We present a mathematical framework for Galerkin formulations of path integrals in lattice field theory. The framework is based on using the degrees of freedom (DOFs) associated to a Galerkin discretization as the fundamental lattice variables. We formulate standard concepts in lattice field theory, such as the partition function and correlation functions, in terms of the DOFs. For example, using continuous finite element spaces, we show that the two-point spatial correlation function can be defined between any two points on the domain (as opposed to at just lattice sites) and furthermore, this two-point function satisfies a weak propagator (or Green’s function) identity, in analogy to the continuum case, as well as a convergence estimate obtained from the standard finite element techniques. Furthermore, this framework leads naturally to higher-order formulations of lattice field theories by considering higher-order finite element spaces for the Galerkin discretization. We consider analytical and numerical examples of scalar field theory to investigate how increasing the order of piecewise polynomial finite element spaces affect the approximation of lattice observables. Finally, we sketch an outline of this Galerkin framework in the context of gauge field theories.

97 MATHEMATICS AND COMPUTING↗