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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Water-induced surface ordering facilitating the microcutting of ductile metals

Metal cutting is a crucial process in modern manufacturing. Enhancing the machinability of metals can significantly improve their production efficiency and surface integrity. Coating surface-active media (SAM) on the free surface of the metals before cutting is an easy method to improve machinability, which usually pertains to the category of the renowned Rehbinder effect. However, the existing SAM is usually hazardous and complex materials. Besides, the effect of SAM on the local structure of the metal surface remains unclear. In this study, water is employed as a simple yet often overlooked SAM in the microcutting of copper. Using water as SAM also allows the employment of X-ray absorption fine structure spectroscopy (XAFS) to study the local structure of copper with and without water coating. Results show that water coating on the free surface of copper can significantly reduce the cutting force and chip thickness, and improve the surface finish. Interestingly, removing the water coating enables the recovery of the cutting force, demonstrating a reversible effect. Based on the XAFS results and molecular dynamics simulation, a water-induced surface ordering mechanism is proposed to explain the findings from the microcutting experiments. This mechanism suggests that water molecules can induce surface ordering in copper, resulting in reduced surface energy and fracture toughness of copper, thus enhancing machinability. In conclusion, this work provides valuable insights into the comprehension of the Rehbinder effect and shows that picometer-scale modifications of the surface atom arrangement can considerably alter the deformation mode of metals, paving the way for the development of new manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting chemical reaction equilibria in molten carbonate fuel cells via molecular simulations

It has been recently suggested that hydroxide ions can be formed in the electrolyte of molten carbonate fuel cells when water vapor is present. The hydroxide can replace carbonate in transporting electrons across the electrolyte, thereby reducing the CO 2 separation efficiency of the fuel cell although still producing electricity. In this work, we obtain the equilibrium concentration of hydroxide in five molten alkali carbonate salts from molecular simulations. The results reveal that there can be a substantial amount of hydroxide in the electrolyte at low partial pressures of CO 2 . In addition, we find that the equilibrium concentration of molecular water dissolved in the electrolyte is over two orders of magnitude higher than that of CO 2 . Increasing the size and polarizability (or in other words reducing the “hardness”) of the cations present in the electrolyte can reduce the hydroxide fraction, but at the cost of lowering ionic conductivity.

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

Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.

13 HYDRO ENERGY↗
DOE OSTI2020

Survey of Technologies to Meet PAG limits for Detection of Cesium-137 in Water

The goal of this report is to evaluate the process of adding a sorbent to the sampling process to preconcentrate Cs-137 and then analyze the sorbent to provide a rapid assessment of results to guide decisions on drinking water sources and the protection of the public. Multiple unit design variables were considered: sample configuration/geometry, sorbent efficiency, sample volume. Model simulations demonstrated through these unit design efficiencies that 10 L of sample volume processed through a sorbent provides nearly two orders of magnitude improvement in sample counting time to provide results to a decision maker than the current process. Over 60 publications and reports concerning Cs-137 and sorbents were evaluated. The key attributes were readiness of sorbent to be deployed in a mobile laboratory environment, and minimum sample preparation and conditioning. Examples of sorbents not considered further included nanomaterials, which have not been evaluated at a commercial scale and are limited in availability. The recommended sorbents for further consideration include: ferrocyanide salts, zeolite, and chemically modified granular activated carbon.

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

Separating Oil-Water Mixtures Using Bump Arrays

Particle separation is an important process step across many fields. One technique being applied for separating solids such as blood components or sand particles from carrier fluids is the use of arrays of aligned posts called deterministic lateral arrays to bump particles to one side in the flow stream to enhance separation. This technique may be useful for separation of deformable particles. The ability to efficiently separate two-phase industrial (oil/water) mixtures is key for future use of valuable resources. Over 1 trillion gallons of petroleum production water could be reclaimed annually for reuse in the drought-ridden western US states. The ability to reclaim this petroleum production water may be critical for the Central High Plains (Colorado, Kansas, Oklahoma, Texas, and New Mexico). Trends in just the High Plains area already lost 20 to 25% of the irrigated farming area due to insufficient ground water storage to irrigate, and farmland losses are expected to grow to 40%. Proving this technology is key to reuse of petroleum production water for crop irrigation or to replace water from currently failing aquifers in rich agricultural lands of the Central High Plains. We conducted experiments applying mesofluidic separation for flowing two-phase (oil/water) mixtures. Experiments were conducted using oils of differing viscosities with water as the carrier fluid; separation was achieved over a range of oil-water concentrations. We describe the results of these experiments in this paper.

oil-water separation, micelle, droplet separation,↗
DOE OSTI2025

From Obsolete to Optimal (ATR Demineralized Water System)

My project was migrating a Human-Machine Interface (HMI) and Programmable Logic Controller (PLC) program from legacy software to a modern platform, enhancing operational efficiency and eliminating unsupported, obsolete equipment. Initially, I used a migration tool to transfer the programs to the new software, then manually updated variables to align with the new PLC. I optimized the PLC code by leveraging new scaling features in the I/O cards, removing over 45 obsolete rungs, and enhancing clarity with functional tag aliases. Next, I modernized the HMI's visuals with an updated color scheme and 3D buttons. I developed multiple interface versions iteratively refining them based on operator feedback. I also designed and created a dedicated "Rounds" screen incorporating insights from a previous intern’s project to streamline daily rounds. To improve clarity, consistency, and efficiency I redesigned the entire interface. Adding visual indicators to enhance operational awareness: red is used for values outside normal specifications, green for normal operating modes, yellow for manual mode, and grey for offline units. Additionally, I added a dynamic visual representation of tank levels, creating PLC logic to show the level in inches as well as inches and feet. I then incorporated a navigation sidebar to facilitate efficient screen transitions. Risk of human error was mitigated by defining narrow input ranges for tank level shutoff and password protecting setpoint changes. I also fixed issues with datatypes that caused inaccuracies in the original code. Overall, this comprehensive upgrade significantly enhanced the HMI's functionality, user experience, and operational reliability.

47 - OTHER INSTRUMENTATION↗
DOE OSTI2024

Optimization strategies for produced water networks with integrated desalination facilities

Optimal management and desalination of produced water is a major challenge for U.S. oil and gas development. Integrating rigorous desalination models into multi-period produced water network optimization problems presents several hurdles, which need to be tackled using advanced optimization strategies. Here, in this work, a novel multi-period produced water network formulation with separate solid and liquid flows is introduced to avoid singularities at zero flows. Rigorous steady state desalination models based on mechanical vapor recompression are embedded at the desalination sites in the network model. An integrated optimization formulation is developed to co-optimize the design of desalination units along with the operation of the network. Furthermore, a more robust approach based on the trust region filter method is developed to efficiently integrate complex desalination models into the multi-period planning problem. Both optimization approaches are demonstrated on a produced water network from the PARETO library (Drouven et al., 2022) using thermal desalination units. Our results show that while the TRF and integrated approaches have comparable solve times, the TRF approach has better performance reliability in terms of solver convergence. Furthermore, the optimal solution obtained by embedding rigorous models into the network is significantly different than when desalination costs are approximated using simple cost models, which motivates further research in this field.

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

Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m −3 ) and negligible self‐discharge that makes them uniquely suited as compact, stand‐alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi‐cycle efficiency and high‐levelized cost of storage. In this study, a model is developed to predict the pulverization limit or R crit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy‐efficient manufacturing process (solid‐state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of R crit on hydration and dehydration kinetics is also investigated.

25 ENERGY STORAGE↗
DOE OSTI2022

Structural and dynamic properties of solvated hydroxide and hydronium ions in water from ab initio modeling

Predicting the asymmetric structure and dynamics of solvated hydroxide and hydronium in water from ab initio molecular dynamics (AIMD) has been a challenging task. The difficulty mainly comes from a lack of accurate and efficient exchange–correlation functional in elucidating the amphiphilic nature and the ubiquitous proton transfer behaviors of the two ions. By adopting the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation functional in AIMD simulations, we systematically examine the amphiphilic properties, the solvation structures, the electronic structures, and the dynamic properties of the two water ions. In particular, we compare these results to those predicted by the PBE0-TS functional, which is an accurate yet computationally more expensive exchange–correlation functional. We demonstrate that the general-purpose SCAN functional provides a reliable choice for describing the two water ions. Specifically, in the SCAN picture of water ions, the appearance of the fourth and fifth hydrogen bonds near hydroxide stabilizes the pot-like shape solvation structure and suppresses the structural diffusion, while the hydronium stably donates three hydrogen bonds to its neighbors. We apply a detailed analysis of the proton transfer mechanism of the two ions and find the two ions exhibit substantially different proton transfer patterns. In conclusion, our AIMD simulations indicate that hydroxide diffuses more slowly than hydronium in water, which is consistent with the experimental results.

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

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cellulose Nanofibrils Dewatered with Poly(Lactic Acid) for Improved Bio-Polymer Nanocomposite Processing

Cellulose nanofibrils (CNFs) have theoretically ideal properties for bio-based composite applications; however, the incorporation of these materials into polymers is made challenging by the strong binding of water to CNFs and the irreversible agglomeration of CNFs during drying. Previous methods used “contact dewatering”, wherein the addition of wood flour (WF) to CNFs facilitated the mechanical removal of water from the system via cold pressing, which showed potential in producing dried CNF fibrils attached to wood fibers for biocomposite applications. In this work, the viability of contact dewatering with poly(lactic) acid (PLA) powder for PLA/CNF composites was evaluated. The energy efficiency of dewatering, preservation of nanoscale CNF morphology, and mechanical properties were examined by mixing wet CNFs with pulverized PLA at various loading levels, pressing water out of the system, and compression molding and shear mixing composites for testing. The most impressive results from this dewatering method were the preservation of micron-to-nanoscale fibers with high aspect ratios in PLA-CNF composites; increased strength and modulus of 1.7% and 4.2%, respectively, compared to neat PLA; equivalent or better properties than spray-dried nanocellulose at similar loading levels; and an 11-194x reduction in drying energy compared to spray-drying CNFs.

Chemistry↗
DOE OSTI2020

Iowa’s agriculture is losing its Goldilocks climate

The Iowa landscape is endowed with rich, deep, dark soils that have high water-holding capacity. Because most of the state’s land is flat or gently rolling, agriculture can be practiced with large, efficient machinery. Historically, Iowa’s average climate is characterized by a growing season of about five to six months with favorable sunshine and warm temperatures. Its crop-dormant season has low enough temperatures to prevent overwintering of detrimental pests and pathogens. The seasonal cycle of precipitation has a spring–summer maximum and a winter minimum that generally provide a sufficient and timely supply of water to support high crop densities without the need for irrigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Beneficiation of coal using supercritical water and carbon dioxide extraction: sulfur removal

Abstract This work explores the use of carbon dioxide, water, and their mixtures as solvent for the precombustion beneficiation of raw coal without using any toxic mineral acids in the temperature range of 200–400 °C. The fluid polarity, ionic constant, and supercritical point can be adjusted by H 2 O/CO 2 ratio and temperature. Adding carbon dioxide to hydrothermal fluid also increases the ionization by forming carbonic acid. Extractions with supercritical fluids have several benefits including enhanced mass transport, ease of separation and recycle, wide range of extractive capability and tunability, better inherent safety, and in the case of carbon dioxide and water–low cost. A semi-continuous extraction system was designed and built in which pressure, temperature and the relative flow rates of CO 2 and H 2 O can be controlled. Coal powder is kept in a packed bed and the extraction is carried out at 143 bar pressure. Using sulfur as a model heteroatom, extractive efficiency is examined as a function of the temperature, fluid composition, fluid flow, and extraction time. The results indicate that carbon dioxide, water, and supercritical water-carbon dioxide (ScWC) all can effectively extract about 50% of total sulfur from bituminous coal in 1 h. Extraction above 350 °C decreased effectiveness, and extraction above the supercritical point of pure water caused hydrothermal carbonization. ScWC extraction may provide necessary control to prevent organic dissolution while removing sulfur.

DeCuir, Matthew J.↗
DOE OSTI2025

Informing electrification strategies of residential neighborhoods with urban building energy modeling

Electrifying end uses is a key strategy to reducing GHG emissions in buildings. However, it may increase peak electricity demand that triggers the need to upgrade the existing power distribution system, leading to delays in electrification and needs of significant investment. There is also concern that building electrification may cause an increase of energy costs, leading to further energy burden for low-income communities. This study uses the urban scale building modeling tool CityBES to assess the electrification impacts of more than 43,000 residential buildings in a neighborhood of Portland, Oregon, USA. Energy efficiency upgrades were investigated on their potential to mitigate the increase of peak electricity demand and energy burden. Simulation results from the calibrated EnergyPlus models show that electrification with heat pumps for space heating and cooling as well as for domestic water heating can reduce CO2e emissions by 38%, but increase peak electricity demand by about 9% from the baseline building stock. Combining electrification measures and energy efficiency upgrades can reduce CO2e emissions by 48% while reducing peak electricity demand by 6% and saving the median household energy costs by 28%. City and utility decision makers should consider integrating energy efficiency upgrades with electrification measures as an effective residential building electrification strategy, which significantly reduces carbon emissions, caps or even decreases peak demand while reducing energy burden of residents.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Selective leaching and solvent extraction of Lithium from spent batteries

Pre-extracting Li from spent lithium-ion batteries (LIBs) is crucial because the recovery efficiency of Li is low after other critical metals have been extracted. Traditional methods involving black mass roasting followed by water leaching have resulted in the extraction of 76 % Li and 61 % Al. However, pre-leaching Li from pretreated black mass using an oxalic acid solution at both ambient and elevated temperatures significantly improved results, achieving 98.1 % Li, 99.5 % Al, and 100 % Fe extraction while leaving Ni, Co, Mn, and Cu behind under optimal conditions. Oxalic acid crystals were recovered by refrigerating the leach solution at temperatures below 5 °C and were reused with nearly identical leaching efficiency. Selective extraction of Li from the oxalate leach solution was achieved using Cyanex® 936P under optimal conditions. Here, due to its extremely low Li extraction efficiency, Dichloromethane proved unsuitable as a diluent. Comparative extraction tests using Cyanex® 936P, Cyanex® 272, and DEHPA in kerosene demonstrated that Cyanex® 936P is an excellent extractant for Li, effectively separating it from other impurities. Under optimal conditions, 98.8 % of available Li was extracted using 20 % Cyanex® 936P, compared to 51.1 % with Cyanex® 272 and 39.9 % with DEHPA in kerosene. Additionally, stripping Li from Cyanex® 936P using H 2 SO 4 and HCl was explored, with HCl yielding the best performance.

Black mass↗
DOE OSTI2022

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

In this work, we present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO 2 . The deep-learning models were trained using 3D datasets describing the pressure plume, CO 2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO 2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

58 GEOSCIENCES↗
DOE OSTI2024

Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions

This research provides a valuable tool that streamlines the optimization process while significantly increasing its accuracy. This study creates a robust framework for reactor design optimization by incorporating comprehensive modeling using the Comprehensive Reactor Analysis Bundle, or BlueCRAB, within the Multiphysics Object-Oriented Simulation Environment (MOOSE). BlueCRAB is the United States Nuclear Regulatory Commission's code suite for non-light water reactor analysis and includes the Griffin, Pronghorn, and Bison applications. This not only improves the efficiency of the optimization process but also enhances the reliability of the results. Such a tool is essential for advancing the state-of-the-art in pebble-bed reactor technology and is critical for achieving the goals of Generation IV reactors, which aim for safe, sustainable, and economically viable nuclear energy solutions. This work presents and applies this workflow on pebble-bed reactors while considering both normal and off-normal conditions. A representative gas-cooled pebble-bed reactor at equilibrium core conditions serves as the nominal design specification for normal operation and is based on previous research. The depressurized loss-of-forced-cooling accident is deployed for off-normal conditions in this work. After defining design-related parameters and quantities of interest regarding reactor safety and performance, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of surrogate models. Subsequently, the dataset and surrogate models are employed in two optimization studies aimed at maximizing fuel utilization and economic profit while adhering to safety and operational constraints. Performing the optimization process with fuel utilization as the metric leads to an improvement of approximately 10%, compared to engineering-judgment-based nominal conditions. The optimization on economic profit leads to an estimated increase of ~300 million USD over the lifetime of the reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗