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At least 73 records · Page 4

Oil in Alaska North Slope Gas Hydrate Reservoir: Micro-CT and Flow Simulation Insights into Permeability

Gas hydrate-bearing sands on the Alaska North Slope (ANS) host minor volumes of crude oil whose impact on formation permeability has never been quantified relative to a gas hydrate reservoir system. Here, we combine in situ pressure-core microcomputed-tomography (μ-CT), thermogravimetric analysis (TGA), gas-chromatography–mass-spectrometry (GC–MS), scanning-electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Stokes-flow simulation to (i) quantify oil saturation, (ii) infer its source, and (iii) evaluate its influence on permeability after gas-hydrate dissociation. μ-CT and SEM-EDS imaging identify the host sediment as silty, with some grain-coating clay present. Eight representative 3003-voxel subvolumes extracted from a preserved pressure core (Core 15P-3c, from the B1 sand (unit B), HYDRATE 02 Geo Data Well (GDW), 886.96–887.29 m measured depth, MD) exhibit porosities of 0.34–0.37 and an average oil saturation of 0.09 ± 0.03, in comparison to an independent TGA-based estimate of 0.16. GC-MS fingerprints obtained from an adjacent depressurized core (Core 17P-1, 891.37–891.44 m MD), together with oil pore habit revealed by μ-CT, suggest that the oil is partly native but also includes contributions from mineral oil-based drilling fluid contamination. Further analysis of oil–porewater interactions and flushing tests confirms that native oil saturation in the analyzed samples ranges from 0.04 to 0.08 with an average of approximately 0.06, and the oil is highly immobile. Flow simulations demonstrate that the native oil saturation of ≈0.06 reduces permeability by approximately 50% due to both pore blockage and increased flow-path tortuosity. These findings reveal the potential presence of native oil within the ANS gas hydrate reservoir and suggest that future simulation models may need to account for its impact on permeability to improve long-term performance predictions of gas and water production.

02 PETROLEUM↗

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as $\sqrt{T/N}$. When only K$\ll$T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to $\sqrt{K/N}$. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

97 MATHEMATICS AND COMPUTING↗

Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pb dimerization greatly accelerates charge losses in MAPbI 3 : Time-domain ab initio analysis

Metal halide perovskites constitute a new type of semiconducting materials with long charge carrier lifetimes and efficient light-harvesting. The performance of perovskite solar cells and related devices is limited by nonradiative charge and energy losses, facilitated by defects. Combining nonadiabatic molecular dynamics and time-domain density functional theory, we demonstrate that charge losses depend strongly on the defect chemical state. By considering an extra Pb atom in CH 3 NH 3 PbI 3 , which is a common defect in lead halide perovskites, we investigate its influence on charge trapping and recombination. In a chemically inert form as a Pb interstitial, the extra Pb atom has only a mild influence on charge recombination. However, if the extra Pb atom binds to a native Pb atom to form a dimer, the charge trapping and recombination are greatly accelerated because the Pb-dimer creates a localized midgap trap state that couples strongly to the perovskite valence band edge. Holes disappear from the valence band two orders of magnitude faster than in the pristine perovskite and recombine with conduction band electrons one order of magnitude faster. The simulations identify the phonon modes involved in the nonradiative charge trapping and recombination and highlight the importance of rapid decoherence within the electronic subsystem for long carrier lifetimes. The detailed atomistic analysis of the charge trapping and recombination mechanisms enriches the understanding of defect properties and provides theoretical guidance for improving perovskite performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗

Development of energetic and enzymatic limitations on microbial carbon cycling in soils

Soil organic carbon (SOC) constitutes an important reservoir in the global carbon cycle that is vulnerable to transformation and loss from land use and climate change. Anoxic conditions protect SOC from microbial degradation through limiting the energetics of respiration and inhibiting extracellular oxidative enzymes. Given growing evidence of prevalent anaerobic microsites in upland soils, we designed an experiment testing the development of dissolved organic carbon (DOC) signatures of energetic and enzymatic limitations on microbial carbon utilization across simulated soil aggregates or peds. Reactors comprised a soil column “aggregate” underlying an advective “macropore” channel. Soils received downward diffusive inputs of aerated porewater media with added nitrate, sulfate, or no amendment—where native ferrihydrite served as dominant anaerobic terminal electron acceptor (TEA). After 40 days, added nitrate resulted in highest bulk respiration and DOC production while sulfate did not differ from the control. Nominal oxidation state of carbon (NOSC) was higher (more favorable) with added TEAs at soil surfaces and decreased with depth, while NOSC in the non-amended soil remained lower and constant with depth. DOC generally increased with depth, which along with decreasing NOSC values indicates joint electron-donor and acceptor control over respiration energetics. Of all organic compound classes, only the relative abundance of phenolics increased between 0 and 0.5 cm depth, which aligns with the oxic-anoxic transition and suggests oxidative enzyme inhibition. Furthermore, our results suggest that oxygen limitation within upland soil aggregates may preserve SOC via both energetic and enzymatic C protection mechanisms, which are vulnerable upon exposure to oxygen.

54 ENVIRONMENTAL SCIENCES↗

String-Like Transport in Superionic Conductors

Superionic or fast-ion conductors are multicomponent solid-state systems in which one sublattice becomes mobile and exhibits extraordinarily high ionic conductivity before the melting within the solid state. Uranium dioxide (UO{sub 2}) - the fuel material of choice in most nuclear reactors - shows superionic behavior, although the mechanism of fast ion transport of the mobile oxygen ions, and its implication, is not well-understood. UO{sub 2} belongs to the category of Type II superionics wherein the conductivity rises gradually with increasing temperature, without an attendant phase change. In a recent work, using atomistic simulations and available neutron and x-ray scattering data, we have shown that all Type II superionic conductors exhibit a well-defined onset of dynamic disorder at a characteristic temperature T{sub α} = (∼2000 K for UO{sub 2}). Unlike the familiar superionic or Bredig transition temperature T{sub α} (∼2650 K for UO{sub 2}) that is associated with a second-order thermodynamic phase transition, T{sub α} represents an order-disorder (O-D) transition that marks a structural and kinetic crossover from a crystalline state to a semi-ordered state. In the temperature range between T{sub α} and T{sub λ}, the oxygen ions in UO{sub 2} exhibit jammed dynamics even though the mobile oxygen ions favor collective hopping from one native crystalline site to another. This cooperative dynamics manifests as dynamical heterogeneity (DH) - the tendency of highly mobile oxygen ions to form dynamic clusters, and dynamical facilitation (DF) - the mode of system relaxation facilitated solely through the kinetic ions transferring their mobility to neighboring ions. The jammed dynamics portrayed by the oxygen ions is similar to that observed in supercooled liquids and glassy materials, and other disordered systems such as granular media and polymers. In the current work, we probe the ionic dynamics in UO{sub 2} for the presence of another ubiquitous signature of glassy and jammed systems, namely, the one-dimensional string-like motion of the mobile species. Unlike the uncorrelated vacancy exchanges and interstitial migration in defected crystalline states, the string motion is a collective mechanism among the mobile species wherein each member of the string induces the next member to move in a correlated, sequential fashion. Using atomistic simulations, we demonstrate that oxygen ions in UO{sub 2} are transported through a string-like mechanism in the temperature range between T{sub α} and T{sub λ}, and the probability distribution of occurrence of the strings varies exponentially with string length. The discovery of string-like motion of the oxygen ions is somewhat surprising given the crystalline underpinning of the mobile species and the dynamic tendency of the oxygen ions to hop between lattice sites. In addition to dynamical heterogeneity and dynamical facilitation, our work has added one more entry, namely the occurrence of string-like transport, to the list of phenomenological similarities between superionic conductors and jammed systems. Using atomistic simulations, we have established the occurrence of string-like ionic motion among the oxygen ions in UO{sub 2} between temperatures T{sub α} - the order-disorder (O-D) transition temperature, and T{sub λ} - the Bredig transition temperature. As observed in other jammed systems, the length of the strings is observed to have an exponential distribution implying that the probability of occurrence of a smaller string is much higher than that of a longer string. Interestingly, using Temperature-Accelerated Dynamics (TAD) we have also established that string-like hopping takes place at temperatures lower than T{sub α}; these results will be published elsewhere. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tracking the protein conformational motions driving HIV-1 membrane fusion

HIV-1 Env (trimeric gp120/gp41) is the surface protein responsible for membrane fusion. The Env binds to the receptor proteins, which induces gp120 shedding leading to conformational changes of gp41 from the pre-fusion to post-fusion state, allowing its fusion peptide to embed in the host cell membrane and bringing the viral and host cell membranes together. The gp41 refolding is a target of several peptide inhibitors. Yet, the molecular mechanism of this dynamic process is still not well understood. In this study, we successfully simulate the conformational change of gp41 from pre-fusion to post-fusion state in atomistic resolution using all-atom structure-based models. We reveal that maintaining the directionality of protomer interactions in both pre-fusion and post-fusion states is crucial for gp41 refolding. Additionally, we find that HR1 inherently extends as a three-helical bundle toward the host-cell membrane without any bias. Importantly, we identify native contacts in the pre-fusion state that are critical for the proper refolding of gp41 towards the post-fusion state. Lastly, by incorporating the membrane-fusion inhibitors, T20 and SFT, we identify the most vulnerable stage in the fusion pathway that exhibits the greatest sensitivity to these drugs, which could aid in a better understanding of drug resistance mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Electrostatic Influence on Photoisomerization in Bacteriorhodopsin and Halorhodopsin

Bacteriorhodopsin (bR) and halorhodopsin (hR) are mutual membrane proteins that transport ions across the cell membrane in halobacteria. Their ion transport function is triggered by photoactivated isomerization of the retinal protonated Schiff base (RPSB) chromophore. In spite of their similar structures, bR and hR exhibit widely differing RPSB isomerization rates and quantum yields (with bR being both faster and more efficient than hR). Previous simulations of photoisomerization in bR and hR using ab initio multiple spawning (AIMS) with QM/MM have successfully reproduced the experimentally observed ordering of quantum yields and isomerization rates, but the origin of these differences remains elusive. In this work, we discover the role of electrostatic interactions in the protein pocket surrounding RPSB. We probe the influence of protein electrostatics by modifying the charge of the complex counterion in bR/hR to be more/less negative than the native state. We find that such modifications lead to bR-like behavior in hR and vice versa. This demonstrates the crucial role of electrostatic interactions in controlling the outcome of RPSB photoisomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DTK C/Fortran Interface Development for NEAMS FSI Simulations

This report documents the development of DataTransferKit (DTK) C and Fortran interfaces for fluid-structure-interaction (FSI) simulations in NEAMS. In these simulations, the codes Nek5000 and Diablo are being coupled within the SHARP framework to study flow-induced vibration (FIV) in reactor steam generators. We will review the current Nek5000/Diablo coupling algorithm in SHARP and the current state of the solution transfer scheme used in this implementation. We will then present existing DTK algorithms which may be used instead to provide an improvement in both flexibility and scalability of the current SHARP implementation. We will show how these can be used within the current FSI scheme using a new set of interfaces to the algorithms developed by this work. These new interfaces currently expose the mesh-free solution transfer algorithms in DTK, a C++ library, and are written in C and Fortran to enable coupling of both Nek5000 and Diablo in their native Fortran language. They have been compiled and tested on Cooley, the test-bed machine for Mira at ALCF.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Metallic support films reduce optical heating in cryogenic correlative light and electron tomography

Super-resolved cryogenic correlative light and electron tomography is an emerging method that provides both the single-molecule sensitivity and specificity of fluorescence imaging, and the molecular scale resolution and detailed cellular context of tomography, all in vitrified cells preserved in their native hydrated state. Technical hurdles that limit these correlative experiments need to be overcome for the full potential of this approach to be realized. Chief among these is sample heating due to optical excitation which leads to devitrification, a phase transition from amorphous to crystalline ice. Here, in this work, we show that much of this heating is due to the material properties of the support film of the electron microscopy grid, specifically the absorptivity and thermal conductivity. We demonstrate through experiment and simulation that the properties of the standard holey carbon electron microscopy grid lead to substantial heating under optical excitation. In order to avoid devitrification, optical excitation intensities must be kept orders of magnitude lower than the intensities commonly employed in room temperature super-resolution experiments. We further show that the use of metallic films, either holey gold grids, or custom made holey silver grids, alleviate much of this heating. For example, the holey silver grids permit 20× the optical intensities used on the standard holey carbon grids. Super-resolution correlative experiments conducted on holey silver grids under these increased optical excitation intensities have a corresponding increase in the rate of single-molecule fluorescence localizations. This results in an increased density of localizations and improved correlative imaging without deleterious effects from sample heating.

59 BASIC BIOLOGICAL SCIENCES↗

Thermal unfolding of barstar and the properties of interfacial water around the unfolded forms

Identification of the intermediates along the folding-unfolding pathways and probing their interactions with surrounding solvent are two important but relatively unexplored issues in protein folding. In this work, we have carried out atomistic molecular dynamics simulations to study the thermal unfolding of barstar in aqueous solution from its folded native form at two different temperatures (400 K and 450 K). The calculations at 400 K reveal partial unfolding of two α-helices (helix-1 and helix-2) and their interconnecting loop. At 450 K, on the other hand, the entire protein attains an expanded flexible conformation due to disruption of a large fraction of tertiary contacts and breaking of almost all the secondary structures. These two disordered structures obtained at such high temperatures are then studied around room temperature to probe their influence on the properties of surrounding solvent. It is found that though the unfolding of the protein in general leads to increasingly hydrated interface, but new structural motifs with locally dehydrated interface may also form during the structural transition. Additionally, independent of the conformational state of the protein, its influence on surrounding solvent has been found to be restricted to the first hydration layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Matrix Approach to Accelerate Spin-Up of CLM5

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin-up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi-Analytical Spin-Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin-up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up on site and globally in comparison with other spin-up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

54 ENVIRONMENTAL SCIENCES↗

On the analysis and comparison of conformer-specific essential dynamics upon ligand binding to a protein

The native state of a protein consists of an equilibrium of conformational states on an energy landscape rather than existing as a single static state. The co-existence of conformers with different ligand-affinities in a dynamical equilibrium is the basis for the conformational selection model for ligand binding. In this context, the development of theoretical methods that allow us to analyze not only the structural changes but also changes in the fluctuation patterns between conformers will contribute to elucidate the differential properties acquired upon ligand binding. Molecular dynamics simulations can provide the required information to explore these features. Its use in combination with subsequent essential dynamics analysis allows separating large concerted conformational rearrangements from irrelevant fluctuations. We present a novel procedure to define the size and composition of essential dynamics subspaces associated with ligand-bound and ligand-free conformations. These definitions allow us to compare essential dynamics subspaces between different conformers. Our procedure attempts to emphasize the main similarities and differences between the different essential dynamics in an unbiased way. Essential dynamics subspaces associated to conformational transitions can also be analyzed. As a test case, we study the glutaminase interacting protein (GIP), composed of a single PDZ domain. Both GIP ligand-free state and glutaminase L peptide-bound states are analyzed. Our findings concerning the relative changes in the flexibility pattern upon binding are in good agreement with experimental Nuclear Magnetic Resonance data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single-Molecule Detection of the Encounter and Productive Electron Transfer Complexes of a Photosynthetic Reaction Center

Small, diffusible redox proteins play an essential role in electron transfer (ET) in respiration and photosynthesis, sustaining life on Earth by shuttling electrons between membrane-bound complexes via finely tuned and reversible interactions. Ensemble kinetic studies show transient ET complexes form in two distinct stages: an “encounter” complex largely mediated by electrostatic interactions, which subsequently, through subtle reorganization of the binding interface, forms a “productive” ET complex stabilized by additional hydrophobic interactions around the redox-active cofactors. Here, using single-molecule force spectroscopy (SMFS) we dissected the transient ET complexes formed between the photosynthetic reaction center-light harvesting complex 1 (RC-LH1) of Rhodobacter sphaeroides and its native electron donor cytochrome c 2 (cyt c 2 ). Importantly, SMFS resolves the distribution of interaction forces into low (~150 pN) and high (~330 pN) components, with the former more susceptible to salt concentration and to alteration of key charged residues on the RC. Thus, the low force component is suggested to reflect the contribution of electrostatic interactions in forming the initial encounter complex, whereas the high force component reflects the additional stabilization provided by hydrophobic interactions to the productive ET complex. Employing molecular dynamics simulations, we resolve five intermediate states that comprise the encounter, productive ET and leaving complexes, predicting a weak interaction between cyt c 2 and the LH1 ring near the RC-L subunit that could lie along the exit path for oxidized cyt c 2 . The multimodal nature of the interactions of ET complexes captured here may have wider implications for ET in all domains of life.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗

First-Principles Characterization of the Elusive I Fluorescent State and the Structural Evolution of Retinal Protonated Schiff Base in Bacteriorhodopsin

The conversion of light energy into work is essential to life on earth. Bacteriorhodopsin (bR), a light-activated proton pump in Archae, has served for many years as a model system for the study of this process in photoactive proteins. Upon absorption of a photon, its chromophore, the retinal protonated Schiff base (RPSB), isomerizes from its native all-trans form to a 13-cis form and pumps a proton out of the cell in a process that is coupled to eventual ATP synthesis. Despite numerous time-resolved spectroscopic studies over the years, the details of the photodynamics of bR on the excited state, particularly the characterization of the I fluorescent state, the time-resolved reaction mechanism, and the role of the counterion cluster of RPSB, remain uncertain. Here, in this work, we use ab initio multiple spawning (AIMS) with spin-restricted ensemble Kohn–Sham (REKS) theory to simulate the nonadiabatic dynamics of the ultrafast photoreaction in bR. The excited state dynamics can be partitioned into three distinct phases: (1) relaxation away from the Franck–Condon region dominated by changes in retinal bond length alternation, (2) dwell time on the excited state in the I fluorescent state featuring an untwisted, bond length inverted RPSB, and (3) rapid torsional evolution to the conical intersection after overcoming a small excited state barrier. We fully characterize the I fluorescent state and the excited state barrier that hinders direct evolution to the conical intersection following photoexcitation. We also find that photoisomerization is accompanied by weakening of the interaction between RPSB and its counterion cluster. However, in contradiction with a recent time-resolved X-ray experiment, hydrogen bond cleavage is not necessary to reproduce the observed photoisomerization dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗