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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rigorous incorporation of pH effects into ab initio electrochemical models

This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0023410. The theme of this project was to update electronically grand canonical atomistic simulations to properly incorporate pH effects, on a rigorous thermodynamic basis, and to compare this to experimental findings. This project was primarily conducted by PI Andrew Peterson and his group at Brown University, with an unfunded collaboration with the Quantum Simulations Group at Lawrence Livermore National Laboratory with Dr. Joel Varley, who hosted the primary graduate student (Alexander Lackey) funded by this project and contributed to all major intellectual pursuits, utilizing the expertise and capabilities of the national laboratory to advance the project goals. Postdoctoral associate Dr. Juye Kim was also a major contributor to this project, and implementation of the final section included cooperation with several electronic-structure open-source software developers, including Colin Baker (Brown), Sandeep Sharma (CalTech), Georg Kastlunger (DTU), and Jens Jørgen Mortensen (DTU).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

A Multi-Physics Study on High-Specific Power Li-O2 Batteries for Electric Aircraft

Commercialization of lithium-air batteries faces many challenges, such as electrolyte decomposition, short cycle life, low energy and power density, etc. However, commercialization of Li-O2 batteries for aeronautics is much more challenging due to additional safety constraints on cyclability and performance (high specific power and specific energy). For this presentation, we will discuss inter-related aspects of physics-based modeling of a pack: cell and battery model calibration. In addition, we will evaluate and present optimal battery designs for high discharge current density, high discharge time, and low battery mass using simulation-based optimization.The Finite Element Model (FEM) used to simulate a Li-O2 cell is based on the work of Bevara [1]. The different aspects of the model are based on: porous electrode theory and concentrated electrolyte theory; quantum tunneling model for the resistance of conformal layer of discharge product (Li2O2) [1]; Butler-Volmer kinetics for electrochemical reaction; Fick's diffusion for oxygen transport; and an oxygen dissolution model is applied at the air/electrolyte interface [2]. The electrolyte properties such as ion conductivity, ion diffusion, oxygen diffusion, and mass density of the electrolyte were taken from Molecular Dynamics (MD) simulations [3]; while the other model parameters, which includes mass of cell components, were calibrated to match experiments at high discharge current densities. The cell mass includes the anode, cathode, separator, electrolyte, and other components (such as current collector). This calibrated model is used to perform parametric studies on cathode thickness, porosity, tortuosity, carbon particle size, electrolyte transport and material properties, partial pressure of oxygen, discharge time, and discharge current density to study optimal designs for high specific power and energy. References:1. Bevara, V. & Andrei, P. (2014), J. Electrochem. Soc. 161 (14), A2068-A2079.2.Mehta, M. & Andrei, P. (2015), J. Power Sources. 286, 299-308.3.Liyana-Arachchi, T.; Haskins, J.; Burke, C.; Diederichsen, K.; McCloskey, B.; & Lawson, J. (2018), J. Phys. Chem. B. 122 (36), 8548 - 8559.4.Choi, W.; Kikumoto, H.; Choudhary, R. & Ooka, R. (2018), Applied Energy, 209, 306-321.

Mehta, Mohit↗
DOE OSTI2020

Solvation at metal/water interfaces: An ab initio molecular dynamics benchmark of common computational approaches

Determining the influence of the solvent on electrochemical reaction energetics is a central challenge in our understanding of electrochemical interfaces. To date, it is unclear how well existing methods predict solvation energies at solid/liquid interfaces, since they cannot be assessed experimentally. Ab initio molecular dynamics (AIMD) simulations present a physically highly accurate, but also a very costly approach. In this work, we employ extensive AIMD simulations to benchmark solvation at charge-neutral metal/water interfaces against commonly applied continuum solvent models. We consider a variety of adsorbates including *CO, *CHO, *COH, *OCCHO, *OH, and *OOH on Cu, Au, and Pt facets solvated by water. The surfaces and adsorbates considered are relevant, among other reactions, to electrochemical CO 2 reduction and the oxygen redox reactions. We determine directional hydrogen bonds and steric water competition to be critical for a correct description of solvation at the metal/water interfaces. As a consequence, we find that the most frequently applied continuum solvation methods, which do not yet capture these properties, do not presently provide more accurate energetics over simulations in vacuum. We find most of the computed benchmark solvation energies to linearly scale with hydrogen bonding or competitive water adsorption, which strongly differ across surfaces. Furthermore, we determine solvation energies of adsorbates to be non-transferable between metal surfaces, in contrast to standard practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2025

Multi-species electrolyte migration kinetics with directed flow

Here, this paper investigates an electrochemical process designed to control mixing kinetics in liquid electrolytes. The process utilizes an electrochemical cell with anode and cathode chambers connected by a channel without a membrane. This configuration depletes multiple electroactive species in the cathode chamber while selectively replenishing them in the anode chamber. A key application is the removal of impurity species from the cathode chamber electrolyte and the selective replenishment of primary electroactive species in the anode chamber. Aqueous cell experiments were conducted to validate the theoretical model, and simulations were performed for molten salt electrolytes. This approach minimizes waste by reducing the need for additional electrolyte supplies and extends the utilization of anion species, contributing to environmentally sustainable electrochemical materials processing.

Electrochemical Process↗
DOE OSTI2020

Exploring non-adiabaticity to CO reduction reaction through ab initio molecular dynamics simulation

Non-adiabatic chemical reaction refers to the electronic excitation during reactions. This effect cannot be modeled by the ground-state Born-Oppenheimer molecular dynamics (BO-MD), where the electronic structure is at the ground state for every step of ions' movement. Although the non-adiabatic effect has been explored extensively in gas phase reactions, its role in electrochemical reactions, such as water splitting and CO 2 reduction, in electrolyte has been rarely explored. On the other hand, electrochemical reactions usually involve electron transport; thus, a non-adiabatic process can naturally play a significant role. In this work, using one-step CO 2 reduction as an example, we investigated the role of the non-adiabatic effect in the reaction. The reaction barriers were computed by adiabatic BO-MD and non-adiabatic real-time time dependent density functional theory (rt-TDDFT). We found that by including the non-adiabatic effect, rt-TDDFT could increase the reaction barrier up to 6% compared to the BO-MD calculated barrier when the solvent model is used to represent water. Simulations were carried out using explicit water molecules around the reaction site under different overpotentials, and similar non-adiabatic effects were found.

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

Metal dissolution from first principles: Potential-dependent kinetics and charge transfer

Metal dissolution and its inverse process are integral to both corrosion and electrodeposition; however, many mechanistic details regarding the dissolution process are challenging to decipher. These include how ion dissolution kinetics and charge transfer are influenced by the competition between metal and solvent interactions under an electrode potential. Here, in this work, we introduce a computational framework based on density functional theory with grand-canonical treatment of electrons to directly predict the potential energy landscape for metal dissolution at a constant potential. Using aluminum as an example, we demonstrate that dissolution kinetics is governed by competing kinetics between two physical processes associated with metal–metal bond breaking and ion-migration within the electrical double layer, respectively. We identify a kinetic transition between regimes dominated by each of these processes and show that this transition depends on the operating electrode potential, among other key factors. It is further found that kinetics and thermodynamics of these processes can be described with a simple, one-parameter Marcus-theory-type model. Beyond offering new understanding of charge transfer during dissolution, our simulation protocol provides a recipe for directly predicting other important quantities in electrochemical reactions from first principles that are difficult to measure, such as the symmetry factor.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of Electro-chemical Battery Model for Plug-and-Play Eco-system Library

Energy storage components are fundamental to the concept of an Integrated Energy System (IES). They serve to store surplus energy during low-demand periods for later release when other IES components (i.e., Secondary Energy Source, Balance of Plant, etc.) would otherwise have to operate flexibly. This provision for storage avoids high-amplitude power ramps in these components thereby limiting thermal and mechanical stresses to their internals and providing for extended service life. This report describes a dynamic model that has been developed for an electrochemical battery. The lithium-ion (Li-ion) cell was selected as representative technology. The battery model was developed in the Dymola simulation environment and meets the requirements of the ecosystem plug-and-play library. The model accurately describes the electric dynamic response of a Li-ion battery for an imposed charging/discharging power profile. The corresponding physical limitations related to over-power scenarios, and the impact of the residual state of charge are accounted for in the model. A literature review of the major degradation processes affecting Li-ion batteries was performed. Given the purposes of the CTD-IES project, the progressive fade of the installed capacity, the reduction of the round-trip efficiency, and the limits on the number of charging/discharging cycles are aspects that need to be taken into account in techno-economic analyses. The modeling of these degradation phenomena becomes crucial when predictions over long time horizons (capacity expansion) are made. For each one of these phenomena, a brief description is given, and some figures to be implemented in the HERON optimization algorithm are presented.

25 ENERGY STORAGE↗
DOE OSTI2026

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗
DOE OSTI2020

The MPACT 2020 Milestone: Safeguards and Security by Design of Future Nuclear Fuel Cycle Facilities.

The Materials Protection, Accounting, and Control Technologies (MPACT) campaign, within the U.S. Department of Energy Office of Nuclear Energy, has developed a Virtual Facility Distributed Test Bed for safeguards and security design for future nuclear fuel cycle facilities. The purpose of the Virtual Test Bed is to bring together experimental and modeling capabilities across the U.S. national laboratory and university complex to provide a one-stop-shop for advanced Safeguards and Security by Design (SSBD). Experimental testing alone of safeguards and security technologies would be cost prohibitive, but testbeds and laboratory processing facilities with safeguards measurement opportunities, coupled with modeling and simulation, provide the ability to generate modern, efficient safeguards and security systems for new facilities. This Virtual Test Bed concept has been demonstrated using a generic electrochemical reprocessing facility as an example, but the concept can be extended to other facilities. While much of the recent work in the MPACT program has focused on electrochemical safeguards and security technologies, the laboratory capabilities have been applied to other facilities in the past (including aqueous reprocessing, fuel fabrication, and molten salt reactors as examples). This paper provides an overview of the Virtual Test Bed concept, a description of the design process, and a baseline safeguards and security design for the example facility. Parallel papers in this issue go into more detail on the various technologies, experimental testing, modeling capabilities, and performance testing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Formation of LiF Surface Layer During Direct Fluorination of High-Capacity Co-Free Disordered Rocksalt Cathodes

Disordered rocksalt (DRX) cathodes have attracted interest due to their high capacity and compositional flexibility (e.g., Co-free chemistries). However, the sloping voltage profile and gradual capacity fade during cycling have hindered widespread adoption of these materials. Simulations predict that fluorine substitution in DRX cathodes will improve their capacity, rate performance and cyclability. In this study we use a fluidized bed reactor to fluorinate a model Lirich DRX composition (Li1.15Ni0.375Ti0.375Mo0.1O2, NTMO) to investigate how fluorine content impacts the cathode’s structure and electrochemical performance. Instead of substituting O with F to form oxyfluoride phases, direct fluorination of DRX cathodes leads to formation of LiF surface films which improves the specific energy and capacity retention. This study demonstrates the feasibility of direct fluorination to improve the electrochemical performance of high voltage cathodes by tuning the material’s surface chemistry.

Co-free disordered rock-salt cathode, direct fluor↗
DOE OSTI2020

Electro-reduction of organics on metal cathodes: A multiscale-modeling study of benzaldehyde on Au (111)

Here, we present a multiscale modeling study on the electro-reduction of benzaldehyde (BZY) on Au(111) under realistic electrochemical conditions. To model the electrochemical cell, we adopt a capacitor model in which complex solvents are confined between a Au cathode and a carbon anode. Classical molecular dynamics simulations reveal that electrode charge density and the presence of alcohol show strong effects on the density, adsorption geometry and dynamics of benzaldehyde on the Au electrode. Under charging conditions, the surface concentration of benzaldehyde on the Au electrode decreases, while the content of other species increases. Finally, we proposed a scheme that correlates the electric current running through the Au/solvent interface with the applied bias. This study provides a molecular level understanding of how solvent composition, in this case water/alcohol content, controls the activity of electrocatalytic hydrogenation

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

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗
DOE OSTI2024

Topology optimization for the full-cell design of porous electrodes in electrochemical energy storage devices

In this paper, we introduce a density-based topology optimization framework to design porous electrodes for maximum energy storage. We simulate the full cell with a model that incorporates electronic potential, ionic potential, and electrolyte concentration. The system consists of three materials, namely pure liquid electrolyte and the porous solids of the anode and cathode, for which we determine the optimal placement. We use separate electronic potentials to model each electrode, which allows interdigitated designs. As a result, a penalization is required to ensure that the anode and cathode do not touch, i.e., causing a short circuit. We compare multiple 2D designs generated for different fixed conditions, e.g. material properties. A 3D design with complex channel and interlocked structure is also created. All optimized designs are far superior to the traditional monolithic electrode design with respect to energy storage metrics. We observe up to a 750% increase in energy storage for cases with slow effective ionic diffusion within the porous electrode.

25 ENERGY STORAGE↗
DOE OSTI2021

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗
DOE OSTI2022

Thick Electrode Design for Facile Electron and Ion Transport: Architectures, Advanced Characterization, and Modeling

The demand for lithium ion batteries continues to expand for powering applications such as portable electronics, grid-scale energy storage, and electric vehicles. As the application requirements advance, the innovation of lithium ion batteries toward higher energy density and power output is required. Along with the investigation of new materials, an important strategy for increasing battery energy content is to design electrodes with high areal loading to minimize the fraction of nonactive materials such as current collectors, separators, and packaging components, resulting in significant gains in energy content and the reduction of the system-level cost. However, the adoption of thick high areal loading electrodes has been impeded by sluggish charge transport and mechanical instability. With conventional slurry cast electrodes, battery function significantly deteriorates with increases in electrode thickness due to high cell polarization and the incomplete utilization of active materials. Thus, a consideration of approaches that facilitate an understanding and eventual adoption of high-loading electrodes is warranted to enable the deliberate advancement of next-generation batteries. Herein, this Account considers three aspects critical to the science and technology of thick high-loading electrodes. The first discussion covers recent approaches to the design and fabrication of high-loading electrodes. Ensuring electrical contact throughout the electrode is accomplished through the manipulation of conductive additives or using a conductive scaffold within the electrode. Ion transport can be facilitated through electrode design and fabrication approaches that deliberately control the electrode porosity and tortuosity. Second, advanced characterization methodologies are presented as the ability to determine the origins of transport limitations provide the insight needed to deliberately approach future designs. Spectroscopic and diffraction methods have been used to characterize the 2D and 3D pore structure and composition of the electrodes. Furthermore, operando methods that yield spatially and temporally resolved information regarding the progression of the electrochemical reaction are highlighted. The third aspect considered is the utilization of modeling. Physically based continuum models linked with the results of experimental characterization have been demonstrated and then allow the rapid simulation of a variety of deliberate electrode designs and their impacts on functional electrochemistry. Variables relevant to the designs can be tested by the model under a series of use conditions to identify those of most promise for a specific application. Finally, an outlook on future opportunities for high-loading battery electrode research is provided to inform and entice practitioners in the field to pursue these important directions of inquiry.

25 ENERGY STORAGE↗
DOE OSTI2025

Molecular Dynamics Simulations of Supercritical Carbon Dioxide and Water using TraPPE and SWM4-NDP Force Fields

The increased levels of carbon dioxide (CO 2 ) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO 2 capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO 2 applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO 2 is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO 2 is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO 2 and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO 2 model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. In conclusion, we anticipate the development of a compatible polarizable CO 2 model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Simulation of Impedance Changes with Aging in Lithium Titanate-based Cells Using Physics-Based Dimensionless Modeling

Quantifying aging effects in lithium-ion cells with chemistries that have a flat open circuit potential is challenging. We implement a physics-based electrochemical model to track changes in the electrochemical impedance response of lithium titanate-based cells. Frequency domain equations of a pseudo two-dimensional model are made dimensionless, and the corresponding non-dimensional parameters are estimated using a Levenberg-Marquardt routine. The model weighs the relative contributions of changes in diffusion, ionic conduction within the electrolyte phase against solid phase electronic conduction towards cell aging. Solid-phase diffusion, charge transfer resistance and double layer capacitance at the solid-liquid interface are accounted for in the particle impedance. The estimation routine tracks dimensionless parameters using accelerated cycling data from full cells over 1000 cycles. The model can be deployed within a short time for state estimation using physics-based models without requiring prior knowledge of the battery chemistry, format, or capacity.

25 ENERGY STORAGE↗