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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Nuclear Resonance Vibrational Spectroscopy Definition of O 2 Intermediates in an Extradiol Dioxygenase: Correlation to Crystallography and Reactivity

The extradiol dioxygenases are a large subclass of mononuclear nonheme Fe enzymes that catalyze the oxidative cleavage of catechols distal to their OH groups. These enzymes are important in bioremediation, and there has been significant interest in understanding how they activate O 2 . The extradiol dioxygenase homoprotocatechuate 2,3-dioxygenase (HPCD) provides an opportunity to study this process, as two O 2 intermediates have been trapped and crystallographically defined using the slow substrate 4-nitrocatechol (4NC): a side-on Fe–O 2 –4NC species and a Fe–O 2 –4NC peroxy bridged species. Also with 4NC, two solution intermediates have been trapped in the H200N variant, where H200 provides a second-sphere hydrogen bond in the wild-type enzyme. While the electronic structure of these solution intermediates has been defined previously as Fe III -superoxo-catecholate and Fe III -peroxy-semiquinone, their geometric structures are unknown. Nuclear resonance vibrational spectroscopy (NRVS) is an important tool for structural definition of nonheme Fe–O 2 intermediates, as all normal modes with Fe displacement have intensity in the NRVS spectrum. In this study, NRVS is used to define the geometric structure of the H200N–4NC solution intermediates in HPCD as an end-on Fe III -superoxo-catecholate and an end-on Fe III -hydroperoxo-semiquinone. Parallel calculations are performed to define the electronic structures and protonation states of the crystallographically defined wild-type HPCD–4NC intermediates, where the side-on intermediate is found to be a Fe III -hydroperoxo-semiquinone. The assignment of this crystallographic intermediate is validated by correlation to the NRVS data through computational removal of H200. While the side-on hydroperoxo semiquinone intermediate is computationally found to be nonreactive in peroxide bridge formation, it is isoenergetic with a superoxo catecholate species that is competent in performing this reaction. In conclusion, this study provides insight into the relative reactivities of Fe III -superoxo and Fe III -hydroperoxo intermediates in nonheme Fe enzymes and into the role H200 plays in facilitating extradiol catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Structural and functional consequences of the STAT5B N642H driver mutation

Hyper-activated STAT5B variants are high value oncology targets for pharmacologic intervention. STAT5B N642H , a frequently-occurring oncogenic driver mutation, promotes aggressive T-cell leukemia/lymphoma in patient carriers, although the molecular origins remain unclear. Herein, we emphasize the aggressive nature of STAT5B N642H in driving T-cell neoplasia upon hematopoietic expression in transgenic mice, revealing evidence of multiple T-cell subset organ infiltration. Notably, we demonstrate STAT5B N642H -driven transformation of γδ T-cells in in vivo syngeneic transplant models, comparable to STAT5B N642H patient γδ T-cell entities. Importantly, we present human STAT5B and STAT5B N642H crystal structures, which propose alternative mutation-mediated SH2 domain conformations. Our biophysical data suggests STAT5B N642H can adopt a hyper-activated and hyper-inactivated state with resistance to dephosphorylation. MD simulations support sustained interchain cross-domain interactions in STAT5B N642H , conferring kinetic stability to the mutant anti-parallel dimer. This study provides a molecular explanation for the STAT5B N642H activating potential, and insights into pre-clinical models for targeted intervention of hyper-activated STAT5B.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Thermal Scattering Law Data Development for Paraffin Wax

Paraffin wax is often used as a nuclear moderator to slow down the fast neutrons in experimental critical assemblies [1]. It is a colorless and soft solid material that consists primarily of straight-chain alkanes (n-alkanes), which are hydrocarbons with the general formula CnH2n+2 [2-3]. The length of the hydrocarbon chain ranges from C20 to C30 and higher [2]. It is distinguished by its solid state at room temperature and begins to melt above approximately 310 K [4]. Paraffin wax is a commonly employed substance in the manufacture of shielding. One of its noteworthy characteristics is its ability to effectively absorb the neutrons. Also, it possesses a high macroscopic cross section, which enables it to efficiently moderate neutrons. As a result, paraffin wax is extensively utilized in various applications where moderation and shielding of neutrons are needed. For simulations, it is necessary to evaluate its thermal scattering law (TSL) and cross sections. Computationally, classical molecular dynamics (CMD) simulations provide the capability of simulating atomic details. For example, several unary, binary, and few multi component mixtures have been investigated of the paraffin model by using molecular dynamics simulations [5-12]. An assessment of thermal neutron scattering in a heavy paraffinic oil treated both as a solid and a viscous fluid containing 25% linear branched paraffin (C30H62), 35% one ring cycloalkane (C30H60), 15% two rings cycloalkane (C30H58), and 25% aromatic (C30H60) chains has been studied using CMD simulations for producing TSL data [13]. Nevertheless, there is lack of TSL and cross section data for paraffin wax as most of the reported analyses focus on the unary and binary mixture of n-alkanes, which is not consistent with actual paraffin wax [2]. In this work, we applied the equilibrium CMD simulations technique to explore the structure and dynamical properties of wax, which are fundamental input to calculate the TSL. A paraffin wax system was modeled using the CMD code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) [14-15] with the semi-empirical COMPASS [16] force field. The density of state (DOS) was calculated from the normalized velocity autocorrelation function (VACF), which is the Fourier transform of the normalized VACF. The DOS was used for the calculation of the TSL and thermal scattering cross sections. The paraffin wax atomic system was constructed by using the MedeA material design platform [17], and was benchmarked using available properties (i.e., density, bond lengths, angles, diffusivity, and viscosity).

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2020

Crystal structure of an Escherichia coli Hfq Core (residues 2–69)–DNA complex reveals multifunctional nucleic acid binding sites

Hfq regulates bacterial gene expression post-transcriptionally by binding small RNAs and their target mRNAs, facilitating sRNA-mRNA annealing, typically resulting in translation inhibition and RNA turnover. Hfq is also found in the nucleoid and binds double-stranded (ds) DNA with a slight preference for A-tracts. Here, we present the crystal structure of the Escherichia coli Hfq Core bound to a 30 bp DNA, containing three 6 bp A-tracts. Although previously postulated to bind to the ‘distal’ face, three statistically disordered double stranded DNA molecules bind across the proximal face of the Hfq hexamer as parallel, straight rods with B-DNA like conformational properties. One DNA duplex spans the diameter of the hexamer and passes over the uridine-binding proximal-face pore, whereas the remaining DNA duplexes interact with the rims and serve as bridges between adjacent hexamers. Binding is sequence-independent with residues N13, R16, R17 and Q41 interacting exclusively with the DNA backbone. Atomic force microscopy data support the sequence-independent nature of the Hfq-DNA interaction and a role for Hfq in DNA compaction and nucleoid architecture. Our structure and nucleic acid-binding studies also provide insight into the mechanism of sequence-independent binding of Hfq to dsRNA stems, a function that is critical for proper riboregulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Simultaneous 10 kHz three-dimensional CH 2 O and tomographic PIV measurements in a lifted partially-premixed jet flame

High-speed, three-dimensional (3D) scalar-velocity field measurements are demonstrated in a lifted partially-premixed dimethyl-ether/air jet flame using simultaneous laser-induced fluorescence (LIF) of formaldehyde (CH 2 O) and tomographic particle image velocimetry (TPIV). The 3D LIF measurements are performed by raster scanning the laser beam from a 100 kHz pulse-burst laser across the probe volume using an acousto-optic deflector. The volumetric reconstruction of the LIF signal from ten parallel planes provides quasi-instantaneous 3D LIF measurements that are synchronized with 10 kHz TPIV measurements. Here, the temporally resolved CH 2 O-LIF and velocity field data are used to analyze Lagrangian particle trajectories and displacement speeds at the base of the lifted flame. The particle trajectories reveal flow structures that are difficult to observe in an Eulerian reference frame. Positive and negative displacement speeds are observed at the CH 2 O-LIF surfaces at the inner and outer regions of the jet flame with a maximum displacement speed of approximately eight times the laminar flame speed of a stoichiometric dimethyl-ether/air mixture. The observations in present study support formation of lean premixed flames near the flame base whose role in flame stabilization should be investigated in more detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Transferring predictions of formation energy across lattices of increasing size*

In this study, we show the transferability of graph convolutional neural network (GCNN) predictions of the formation energy of the nickel-platinum solid solution alloy across atomic structures of increasing sizes. The original dataset was generated with the large-scale atomic/molecular massively parallel simulator using the second nearest-neighbor modified embedded-atom method empirical interatomic potential. Geometry optimization was performed on the initially randomly generated face centered cubic crystal structures and the formation energy has been calculated at each step of the geometry optimization, with configurations spanning the whole compositional range. Using data from various steps of the geometry optimization, we first trained our open-source, scalable implementation of GCNN called HydraGNN on a lattice of 256 atoms, which accounts well for the short-range interactions. Using this data, we predicted the formation energy for lattices of 864 atoms and 2048 atoms, which resulted in lower-than-expected accuracy due to the long-range interactions present in these larger lattices. We accounted for the long-range interactions by including a small amount of training data representative for those two larger sizes, whereupon the predictions of HydraGNN scaled linearly with the size of the lattice. Therefore, our strategy ensured scalability while reducing significantly the computational cost of training on larger lattice sizes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Scalable Computation of Topological Abstractions for Scalar Data

Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigation of Benchmark $k$ eff Sensitivity and Uncertainty for 239 Pu fission in Specific Energy Ranges

Nuclear data at intermediate energies (from 1 to 100s of keV) are evaluated based on scarce differential data and theory unable to capture physics’ expected structure. There is also a lack of integral data. This is a known deficiency and is challenging to address. Calculated effective multiplication factor, k eff , values for intermediate energy experiments are ~25× further from experiment than for fast energies and are often well outside the experimental uncertainties. The goal of the PARADIGM (PARallel Approach of Differential and InteGral Measurements) project is to significantly re duce the uncertainties of intermediate energy nuclear data for 239 Pu. To this end, PARADIGM simultaneously optimizes experiments at both the Los Alamos Neutron Science Center (LANSCE) and National Criticality Experiments Research Center (NCERC). The combined set of data will inform new intermediate-energy nuclear data. By execution of differential and integral experiments, establishment of new theory, and undertaking nuclear data evaluation in parallel, the timeline to deliver improved nuclear data to users will be reduced significantly that is to three years. For the PARADIGM project, it was decided to optimize an integral experiment for two neutron energy ranges, within the full intermediate energy range. The low energy range goes from 1 to 30 keV, while the higher energy range goes from 30 to 600 keV. This work focuses on nuclear data sensitivities and uncertainties for 239 Pu fission for existing experiments in the International Criticality Safety Benchmark Evaluation Project (ICSBEP). When designing new experiments, it is important to understand what benchmarks currently exist. For a more traditional experiment design (in which a specific application model(s) exists), comparisons would be made between the application model(s) and existing benchmarks. For PARADIGM, there is no specific application model, but instead the specific nuclear data reaction and energy ranges of interest can be explored for existing benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

HIF-dependent and reversible nucleosome disassembly in hypoxia-inducible gene promoters

Highlights: • Nucleosome-free regions (NFRs) are established in some gene promoters in a hypoxia-dependent manner. • Hypoxia-inducible NFR (iNFR) formation requires hypoxia-inducible transcription factor (HIF) activity. • Reoxygenation induces the reassembly of nucleosome structures in iNFRs. • Nucleosome reassembly in iNFRs requires SIN3A. Hypoxia causes dramatic changes in gene expression profiles, and the mechanism of hypoxia-inducible transcription has been analyzed for use as a model system of stress-inducible gene regulation. In this study, changes in chromatin organization in promoters of hypoxia-inducible genes were investigated during hypoxia-reoxygenation conditions. Most of the hypoxia-inducible gene promoters were hypersensitive to DNase I under both normal and hypoxic conditions, and our data indicate an immediate recruitment of transcription factors under hypoxic conditions. In some of the hypoxia-inducible promoters, nucleosome-free DNA regions (NFRs) were established in parallel with hypoxia-induced transcription. We also show that the hypoxia-inducible formation of NFRs requires that hypoxia-inducible transcription factors (HIFs) bind to the promoters together with the transcriptional coactivator CBP. Within 1 h after the hypoxia exposure was ended (reoxygenation), HIF complexes were dissociated from the promoter regions. Within 24 h of reoxygenation, the hypoxia-induced transcription returned to basal levels and the nucleosome structure was reassembled in the hypoxia-inducible NFRs. Nucleosome reassembly required the function of the transcriptional coregulator SIN3A. Thus, reversible changes in nucleosome organization mediated by transcription factors are notable features of stress-inducible gene regulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Large-Scale Welding Process Simulation by GPU Parallelized Computing

The computational design of industrially relevant welded structures is extremely time consuming due to coupled physics and high nonlinearity. Previously, most welding distortion and residual stress simulations have been limited to small coupons and reduced order (from three-dimensional [3D] to two-dimensional [2D]), or inherent strain approximations were used for large structures. In this current study, an explicit finite element code based on a graphics processing unit was utilized to perform 3D transient thermomechanical simulation of structural components during welding. Laser brazing of aluminum alloy panels as representative of automotive manufacturing scenarios was simulated to predict out-of-plane distortion under different clamping conditions. The predicted deformation pattern and magnitude were validated by laser scanning data of physical assemblies. In addition, the code was used to investigate residual stresses developed during multipass arc welding of a nuclear industry pressurizer surge nozzle and subsequent welding repair where a 3D simulation was necessary. Taking the experimental data as reference, the 3D model predicted better residual stress distribution than a typical 2D asymmetrical model. Stress evolution in welding repair was also presented and discussed in this study. Furthermore, the efficient numerical model made it feasible to use integrated computational welding engineering to simulate welding processes for large-scale structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Pursuing Heteroleptic Ligand Design Principles for Photoactive Fe Complexes with Ultrafast X-ray Emission and Variable-Temperature Optical Spectroscopies

Understanding the key parameters that govern the photophysical and photochemical properties of transition metal complexes is essential for the development of efficient photosensitizers for photocatalytic applications. Achieving this objective necessitates clear and detailed investigations of their electronic excited states, for which time-resolved metal Kβ X-ray emission spectroscopy (XES) has proven highly effective. Here, we present a time-resolved Fe Kβ XES study of a heteroleptic Fe(II) polypyridyl carbene complex, [Fe(phen) 2 (C 4 H 10 N 4 )] 2+ (1; phen = 1,10-phenanthroline), utilizing both the valence-to-core and Kβ mainline spectral regions, complemented by variable-temperature transient optical absorption (VT-TA) spectroscopy. Detailed analysis of the time-resolved Kβ XES data, supported by density functional theory (DFT) calculations and an Eyring analysis of the VT-TA data, reveals parallel excited state relaxation dynamics that support an assignment of the long-lived excited state to a triplet metal-centered state. Placing these results in the context of prior studies of heteroleptic Fe(II) polypyridyl cyanide complexes motivated a series of DFT calculations to investigate the effects of ligand structural flexibility and arrangement. These calculations reinforce the experimentally derived conclusion that constraining structural flexibility with multidentate ligands significantly impacts the excited state relaxation dynamics. Furthermore, our study emphasizes that the arrangement of strong field ligands in heteroleptic complexes substantially affects the energy of Jahn–Teller active triplet metal-centered states in low-spin d 6 metal complexes. Together, these findings provide synthetic design principles for extending metal-to-ligand charge transfer excited state lifetimes of heteroleptic Fe complexes.

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

Crystal Structure of Borrelia turicatae protein, BTA121, a differentially regulated gene in the tick-mammalian transmission cycle of relapsing fever spirochetes

Tick-borne relapsing fever (RF) borreliosis is a neglected disease that is often misdiagnosed. RF species circulating in the United States include Borrelia turicatae, which is transmitted by argasid ticks. Environmental adaptation by RF Borrelia is poorly understood, however our previous studies indicated differential regulation of B. turicatae genes localized on the 150 kb linear megaplasmid during the tick-mammalian transmission cycle, including bta121. This gene is up-regulated by B. turicatae in the tick versus the mammal, and the encoded protein (BTA121) is predicted to be surface localized. The structure of BTA121 was solved by single-wavelength anomalous dispersion (SAD) using selenomethionine-derivative protein. The topology of BTA121 is unique with four helical domains organized into two helical bundles. Due to the sequence similarity of several genes on the megaplasmid, BTA121 can serve as a model for their tertiary structures. BTA121 has large interconnected tunnels and cavities that can accommodate ligands, notably long parallel helices, which have a large hydrophobic central pocket. Preliminary in-vitro studies suggest that BTA121 binds lipids, notably palmitate with a similar order of binding affinity as tablysin-15, a known palmitate-binding protein. The reported data will guide mechanistic studies to determine the role of BTA121 in the tick-mammalian transmission cycle of B. turicatae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

mesoflow [SWR-22-56]

Mesoflow is a continuum scale simulation tool developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex surface morphologies (of catalysts/biomass particles among others) directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPU) compared to a single processor for representative problem sizes (2 million cell mesh).

Sitaraman, Hariswaran↗
DOE OSTI2025

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Eu(III) and Cm(III) Complexation by the Aminocarboxylates NTA, EDTA, and EGTA Studied with NMR, TRLFS, and ITC—An Improved Approach to More Robust Thermodynamics

The complex formation of Eu(III) and Cm(III) was studied via tetradentate, hexadentate, and octadentate coordinating ligands of the aminopolycarboxylate family, viz., nitrilotriacetate (NTA 3- ), ethylenediaminetetraacetate (EDTA 4- ), and ethylene glycol-bis(2-aminoethyl ether)-N,N,N',N'-tetraacetate (EGTA 4- ), respectively. Based on the complexones’ pK a values obtained from 1 H nuclear magnetic resonance (NMR) spectroscopic pH titration, complex formation constants were determined by means of the parallel-factor-analysis-assisted evaluation of Eu(III) and Cm(III) time-resolved laser-induced fluorescence spectroscopy (TRLFS). This was complemented by isothermal titration calorimetry (ITC), providing the enthalpy and entropy of the complex formation. This allowed us to obtain genuine species along with their molecular structures and corresponding reliable thermodynamic data. The three investigated complexones formed 1:1 complexes with both Eu(III) and Cm(III). Besides the established Eu(III)–NTA 1:1 and 1:2 complexes, we observed, for the first time, the existence of a Eu(III)–NTA 2:2 complex of millimolar metal and ligand concentrations. Demonstrated for thermodynamic studies on Eu(III) and Cm(III) interaction with complexones, the utilized approach is commonly applicable to many other metal–ligand systems, even to high-affinity ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗