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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Versatile tape-drive target for high-repetition-rate laser-driven proton acceleration

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ( > kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Simulations of radiatively cooled magnetic reconnection driven by pulsed power

Magnetic reconnection is an important process in astrophysical environments, as it reconfigures magnetic field topology and converts magnetic energy into thermal and kinetic energy. In extreme astrophysical systems, such as black hole coronae and pulsar magnetospheres, radiative cooling modifies the energy partition by radiating away internal energy, which can lead to the radiative collapse of the reconnection layer. In this paper, we perform two- and three-dimensional simulations to model the MARZ (Magnetic Reconnection on Z) experiments, which are designed to access cooling rates in the laboratory necessary to investigate reconnection in a previously unexplored radiatively cooled regime. These simulations are performed in GORGON, an Eulerian two-temperature resistive magnetohydrodynamic code, which models the experimental geometry comprising two exploding wire arrays driven by 20 MA of current on the Z machine (Sandia National Laboratories). Radiative losses are implemented using non-local thermodynamic equilibrium tables computed using the atomic code Spk, and we probe the effects of radiation transport by implementing both a local radiation loss model and P 1/3 multi-group radiation transport. The load produces highly collisional, super-Alfvénic (Alfvén Mach number M A ≈ 1.5), supersonic (Sonic Mach number M S ≈ 4–5) strongly driven plasma flows which generate an elongated reconnection layer (Aspect Ratio L/δ≈100 , Lundquist number S L ≈ 400). The reconnection layer undergoes radiative collapse when the radiative losses exceed the rates of ohmic and compressional heating (cooling rate/hydrodynamic transit rate = τ$^{–1}_{cool}$/τ$^{–1}_{H}$ ≈100); this generates a cold strongly compressed current sheet, leading to an accelerated reconnection rate, consistent with theoretical predictions. Lastly, the current sheet is also unstable to the plasmoid instability, but the magnetic islands are extinguished by strong radiative cooling before ejection from the layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Toward Machine Learning-Driven Mass Spectrometric Identification of Trichothecenes in the Absence of Standard Reference Materials

While a significant body of work exists on the detection of commonly known trichothecene toxins, biological, environmental, and other transformational processes can generate many under-characterized and unknown modified trichothecenes. Lacking both analytical reference standards and associated mass spectral databases, identification of these modified compounds reflects both a challenge and a critical gap from forensic and public health perspectives. Here we report here the application of machine learning (ML) techniques toward identification of discriminative fragment ions from mass spectrometric data that can be exploited to detect evidence of type A and B trichothecenes. The goal of this work is to establish a new method for the identification of unknown, though structurally similar trichothecenes, by leveraging objective ML techniques. Discriminative fragments derived from a series of gradient-boosted machine learners are then used to develop ML-driven precursor ion scan (PIS) methods on a triple quadrupole mass spectrometer (QQQ) for screening of “unknown unknown” trichothecenes. Specifically, we apply the PIS method to a laboratory-synthesized trichothecene, a first step in demonstrating the power of alternative, machine learning-driven mass spectrometric methods.

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

Synthesis and Characterization of [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ) for Light-Driven Quantum Dot-Catalyst Hydrogen Evolution

Light-driven hydrogen generation from water is a route to carbon-neutral fuels. However, the integrated light absorbers and catalysts must be compatible and functional under the same conditions. A sulfate-functionalized complex, [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ), where P Ph 2 N ArSO3 = 4-(3,6-diphenyl-1,3,6-azadiphosphepan-1-yl)benzenesulfonate), was synthesized and characterized. A solid-state structure from single-crystal X-ray crystallography is also reported. The electrocatalytic activity for hydrogen evolution of this complex in 7:3 H 2 O:CH 3 CN was characterized by cyclic voltammetry and controlled potential electrolysis, with a maximum observed rate of 83 s –1 . Density functional theory was used to characterize the favorable binding of the sulfate functionalities to cadmium sulfide quantum dots. Experimental assembly of these catalysts onto cadmium sulfide quantum dots was successful. In conclusion, both fast electron transfer and light-driven pH-dependent hydrogen evolution were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Solvent-Driven Transformation of Zn/Cd 2+ -Deoxycholate Assemblies

Deoxycholic acid (DOC) is a unique, biologically derived surfactant with facial amphiphilicity that has been exploited, albeit minimally, in supramolecular assembly of materials. Here, we present the synthesis and structural characterization of three hybrid metal (Zn 2+ and Cd 2+ )-DOC compounds. Analysis by single-crystal Xray diffraction reveals the many interactions that are possible between these facial surfactants and the influence of solvent molecules that drive the assembly of materials. These structures are the first metal- DOC complexes besides those obtained from alkali and alkaline earth metals. We isolated polymeric chains of both Cd and Zn (Zn poly -DOC and Cd poly -DOC) from water. Major interactions between DOC molecules in these phases are hydrophobic in nature. Cd poly -DOC exhibits unique P1 symmetry, with complete interdigitation of the amphiphiles between neighboring polymeric chains. Zn 4 -DOC, obtained from methanol dissolution of Zn poly -DOC, features the OZn 4 tetrahedron, widely known in basic zinc acetate and MOF-5 (metal organic framework). We document a solvent-driven, roomtemperature transition between Zn poly -DOC and Zn 4 -DOC (in both directions) by scanning and transmission electron microscopies in addition to small-angle X-ray scattering, powder X-ray diffraction, and infrared spectroscopy. These studies show the methanoldriven transition of Zn poly -DOC to Zn 4 -DOC occurs via an intermediate with no long-range order of the Zn 4 clusters, indicating the strongest interactions driving assembly are intramolecular. On the contrary, water-driven solid-to-solid transformation from Zn 4 -DOC to Zn poly -DOC exhibits crystal-to-crystal transformation. Zn poly -DOC is robust, easy to synthesize, and comprised of biologically benign components, so we demonstrate dye absorption as a proxy for water treatment applications. It favors absorption of positively charged dyes. These studies advance molecular level knowledge of the supramolecular assembly of facial surfactants that can be exploited in the design of organic-inorganic hybrid materials. This research also highlights the potential of solvent for tuning supramolecular assembly processes, leading to new hybrid materials featuring facial surfactants.

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

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

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

Using Density-Corrected DFT to Understand Density-Driven and Functional-Dependent Errors in Ab Initio Simulations of the Hydrated Electron

The hydrated electron, an excess electron in liquid water, plays a crucial role in a plethora of chemical processes, motivating extensive research efforts to characterize its structure, dynamics, and reactivity in solution. Recent theoretical approaches to understanding this intriguing object have involved ab initio simulations based on density functional theory (DFT). Although DFT allows for the study of hydrated electron reactivity and quantum mechanical behavior, it is well-known that anionic systems can suffer from significant density-driven errors (DDEs). Density-corrected DFT (DC-DFT) provides a framework to mitigate such errors; the method reduces DDEs by replacing the self-consistent (SC) density associated with a given density functional with the Hartree–Fock (HF) density. Since HF densities tend to be more localized than DFT SC densities, the DC-DFT scheme significantly improves errors in calculations where the SC density is spuriously delocalized. Here, we investigate how the use of density correction affects the calculated properties of the DFT-simulated (PBEh) hydrated electron, a particularly challenging diffuse anionic system to simulate. First, we analyze charge delocalization in a system consisting of a model octahedral hydrated electron water cluster (the so-called Kevan structure) along with a spatially separated sulfur atom. We show that the use of density correction indeed reduces DDEs in comparison to a standard DFT global hybrid functional. We then propagate molecular dynamics trajectories of the hydrated electron using DC-DFT, where we find that DC further localizes electron density in the cavity region, a signature of reduced charge delocalization. Unfortunately, the decreased radius of gyration of the spin density and corresponding tightening of the local solvation structure from density correction causes predicted observables to deviate further from experimental measurements than when density correction is not employed. Here, we argue that DC’s worse agreement with experiment results from the removal of a fortuitous cancellation of errors that is intrinsic to the PBEh functional. This indicates that the difficulties with DFT to simulate hydrated electrons are primarily due to the inherent approximations in DFT rather than to density-driven errors.

Density functional theory↗
DOE OSTI2024

Entropy-Driven Charge Separation: A Potential Explanation for the Low Energy Loss Found in OPVs with Non-fullerene Acceptors

The recent development of non-fullerene acceptors (NFA) has led to an abrupt increase in the organic photovoltaic (OPV) efficiency from ~12% to ~20%. NFA OPVs can generate photocurrent efficiently without much energy loss, which contrasts with the large energy loss often needed for generating free charges from excitons in fullerene OPVs. Here, we argue that entropy-driven charge separation, which allows excitons to spontaneously gain heat from the environment, is responsible for the exceptionally low energy loss found in NFA OPVs. The entropic driving force is maximized when the delocalized electron and hole wave functions in the CT exciton intersect each other via pointlike junctions. Furthermore, these pointlike junctions are abundant in the polymer/NFA bulk heterojunction which consists of intertwined, stringlike donor and acceptor domains in which electron delocalizes anisotropically. Such microstructure favors entropy-driven charge separation, which can enable charge separation with a minimal energy loss.

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

Defect-Driven Configurational Entropy in the High-Entropy Oxide Li 1.5 MO 3-δ

Layered lithiated oxides are promising materials for next generation Li-ion battery cathode materials; however, instability during cycling results in poor performance over time compared to the high capacities theoretically possible with these materials. Here, in this paper, we report the characterizations of a Li 1.47 Mn 0.57 Al 0.13 Fe 0.095 Co 0.105 Ni 0.095 O 2.49 high-entropy layered oxide (HELO) with the Li 2 MO 3 structure where M = Mn, Al, Fe, Co, and Ni. Using electron microscopy and X-ray spectroscopy, we identify a homogeneous Li 2 MO 3 structure stabilized by the entropic contribution of oxygen vacancies. This defect-driven entropy would not be attainable in the LiMO 2 structure sometimes observed in similar materials as a secondary phase owing to the presence of fewer O sites and a 3+ oxidation state for the metal site; instead, a Li 2-γ MO 3-δ is produced. Beyond Li 2 MO 3 , this defect-driven entropy approach to stabilizing novel compositions and phases can be applied to a wide array of future cathode materials including spinel and rock salt structures.

25 ENERGY STORAGE↗
DOE OSTI2025

Red-Light-Driven Biophotochemical Diode Based on a Microorganism–Silicon Nanowire Interface for Stable and Efficient Bias-Free CO 2 Reduction

Artificial photosynthesis offers a promising route for sustainable liquid fuel and feedstock production, yet integrating efficient CO 2 reduction catalysts with light-harvesting systems remains challenging. Here, in this study, we present a biophotochemical diode that couples microorganism-driven CO 2 reduction with glycerol oxidation, enabled by silicon nanowire photoelectrodes under varying red-light intensities. Tuning the biotic-abiotic interface─by increasing biocatalyst loading and adjusting the catholyte pH to mitigate local alkalization─significantly improves performance and stability. The enhanced-loading biocathode maintains a high faradaic efficiency across a wide potential range, even under elevated light intensities. At 60 mW/cm 2 , the system achieves a bias-free current density of 3.5 mA/cm 2 . Long-term stability testing at 40 mW/cm 2 demonstrates stable operation for over 100 h. The photoanode generates valuable C 3 products, primarily glycerate and lactate, enhancing the economic viability. This work showcases the importance of microenvironmental control at the biotic-abiotic interface and establishes a scalable platform for light-driven CO 2 reduction using earth-abundant silicon.

Artificial Photosynthesis↗
DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗
DOE OSTI2025

Antielectrophoretic Response-Driven Bending–Tilting Deformation of Cationic Polyelectrolyte Brushes Drives Nonlinear Electroosmotic Transport in Brush-Grafted Nanochannels

In this paper, we use all-atom molecular dynamics (MD) simulations to describe a non-linearly enhanced electroosmotic (EOS) flow, where, in a nanochannel grafted with cationic PMETAC ([Poly(2-(Methacryloyloxy)Ethyl) Trimethylammonium Chloride]) brushes, a two-fold increase in the electric field strength leads to a several-fold (more than two-fold) increase in the EOS flow strength and volume flow rate. The electric field enforces the PMETAC brushes to undergo a bending-tilting driven deformation with a significant portion of the brush layer becoming parallel to the grafting surface. In response, a substantial fraction of the counterions leave the brush layer (hence become more mobile), but instead of going into the bulk, accumulate at the brush-bulk interface, i.e., stay in proximity of the brush segments aligned parallel to the grafting surface. This creates an interesting situation, where the counterions are not completely within the brush layer, yet they fully screen the brush charges. Such “freer” conditions enable the counterions to achieve very high velocity, thereby ensuring that the water solvating the counterions themselves move very fast triggering the significantly augmented EOS transport. Probing deeper we can identify that the bending-tilting driven brush deformation, enforcing the brushes to align parallel to the substrate, results from the anti-electrophoretic behavior of the brushes, where despite being positively charged, the brushes move against the electric field direction. Such an anti-electrophoretic behavior of the PE brushes, which has not been reported before, can be associated with the very fast velocities of the negatively charged counterions and the electrostatic and hydrodynamic coupling of the counterions with the positive functional groups of the brushes. Here, we anticipate that the findings of this paper will shed light on strategies for nanochannel flow, the anti-electrophoretic response of charged polymer chains, and the significance of capturing the detailed chemical architecture of polyelectrolytes in nanoscale science and engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Self-Assembly Driven Microlithography via Near-Infrared Light Activation

Current vat photopolymerization (VP) relies on UV or visible light to start the rapid crosslinking of liquid photocurable resins into 3D-printed structures. Here, we develop a self-assembly-driven photopatterning approach to photothermally generate polymeric solids by combining thermoplasmonic nanoparticles and thermoresponsive polymers, in which near-infrared (NIR) light activates thermoplasmonic heating of nanoparticles, triggering the irreversible self-assembly of thermoresponsive polymers into insoluble mesoglobules. A small amount of thermal initiator and crosslinker leads to irreversible self-assembly of polymer nanocomposites. NIR light offers deeper penetration and reduced scattering compared to UV, enabling more uniform curing of thicker or filled materials and expanded process control for composites or opaque systems. Thermoplasmonic heat generation is achieved using surface-modified gold nanorods (AuNRs) with a longitudinal localized surface plasmon resonance peak in the NIR region. Key variables such as polymer composition, molecular weight, physical interactions at the nanoparticle–polymer interface, which can be tuned by surface functionalization, AuNR concentration, and pH can be used to tailor the assembly behavior of these systems, including photothermal effect, flocculation, and cloud point temperature, and the mechanical properties of the final structures. Collectively, these results highlight a platform for photothermally-driven microlithography of polymer solids with diverse, tunable macroscopic properties, enabled by low-energy NIR light-activated self-assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Light-Driven Depolymerization of Native Lignin Enabled by Proton-Coupled Electron Transfer

In this work, we report a catalytic, light-driven method for the redox-neutral depolymerization of native lignin biomass at ambient temperature. This transformation proceeds via a proton-coupled electron-transfer (PCET) activation of an alcohol O–H bond to generate a key alkoxy radical intermediate, which then facilitates the β-scission of a vicinal C–C bond. Of significance, this single-step depolymerization is driven solely by visible-light irradiation, requires no stoichiometric chemical reagents, and produces no stoichiometric waste. This method exhibits good efficiency and excellent selectivity for the activation and fragmentation of the β-O-4 linkage in the polymer backbone, even in the presence of numerous other PCET-active functional groups. The feasibility of this protocol in enabling the cleavage of the β-1 linkage in model lignin dimers was also demonstrated. These results provide further evidence that visible-light photocatalysis can serve as a viable method for the direct conversion of lignin biomass into valuable arene feedstocks.

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

Development of Data-Driven Models for Performance Prediction and Chemical Dosing of a Full-Scale Controlled Phosphorus Precipitation Reactor

This study evaluated the use of data-driven models to improve control of a struvite precipitation reactor that removes phosphorus from wastewater while producing a fertilizer product. The researchers developed predictive models for influent orthophosphate concentration, effluent orthophosphate concentration, and phosphorus removal using operational data from a full-scale MagPrex™ reactor at a water resource recovery facility in Denver, Colorado. Model predictions were used to recommend magnesium chloride dosing adjustments needed to achieve a target effluent phosphorus concentration. Several machine learning approaches were tested, with ridge regression providing the best predictions for influent orthophosphate concentration and phosphorus removal, and XGBoost providing the best predictions for effluent orthophosphate concentration. Simulation results indicated that the decision-support approach could correctly identify dosing adjustments in most cases and reduce chemical use. Full-scale implementation achieved lower accuracy due to changing operating conditions and limited historical data in some operating ranges. Here, the results demonstrate the potential of data-driven tools to support phosphorus recovery process control while also identifying practical limitations that affect deployment in full-scale systems.

42 ENGINEERING↗
DOE OSTI2025

Reversible Physical Gelation of Thermotropic Liquid Crystals Driven by Nanoplate Self-Assembly

Physically gelled soft materials, driven by the self-assembly of low-molecular-mass gelators (LMGs), have emerged as a platform for designing advanced gels that exhibit reversible gelation and property tunability. Liquid crystal (LC) gels are of great interest due to their supramolecular orderings as gel hosts and their enhanced electro-optical properties. In this study, we demonstrate the physical gelation of a nematic LC driven by nanoplate self-assembly, expanding the concept of gelators from small molecules to nanoparticles. These nanoplates are functionalized with promesogenic ligands and form a fibrillar network in LCs with face-to-face interplate stacking, resembling LMGs. The critical gelation volume fraction in the tilt test is only 0.14 v %, comparable to values reported for LMGs. Rheological analyses confirm viscoelastic properties characteristic of gelation. In situ small-angle X-ray scattering (SAXS) characterizes the formation of nanoplate networks in the LC with decreasing temperature, wherein LC mesogens become trapped in pores. Molecular dynamics (MD) simulations reveal that the interaction between ligand-coated nanoplates and LC-forming mesogens induces a multidomain LC structure, increasing friction between LC domains and stabilizing the gel. This study establishes direct relationships among molecular interactions, nanostructures, and mechanical properties in physically gelled LCs. In conclusion, the findings inspire the future gelator design of both LMGs and nanoplates, with potential applicability in bioscaffold engineering and liquid crystalline nanocomposites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Artificial Z-Scheme Constructed from Dye-Sensitized Metal Oxide Nanosheets for Visible Light-Driven Overall Water Splitting

Sensitization of a wide-gap oxide semiconductor with a visible-light-absorbing dye has been studied for decades as a means of producing H 2 from water. However, efficient overall water splitting using a dye-sensitized oxide photocatalyst has remained an unmet challenge. Here in this paper we demonstrate visible-light-driven overall water splitting into H 2 and O 2 using HCa 2 Nb 3 O 10 nanosheets sensitized by a Ru(II) tris-diimine type photosensitizer, in combination with a WO 3 -based water oxidation photocatalyst and a triiodide/iodide redox couple. With the use of Pt-intercalated HCa 2 Nb 3 O 10 nanosheets further modified with amorphous Al 2 O 3 clusters as the H 2 evolution component, the dye-based turnover number and frequency for H 2 evolution reached 4580 and 1960 h –1 , respectively. The apparent quantum yield for overall water splitting using 420 nm light was 2.4%, by far the highest among dye- sensitized overall water splitting systems reported to date. The present work clearly shows that a carefully designed dye/oxide hybrid has great potential for photocatalytic H 2 production, and represents a significant leap forward in the development of solar-driven water splitting systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network

Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH 2 )O-C(=O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗