Bridging Molecular Dynamics and Microstructure Evolution with Interpretable Machine-Learning – the case of spinodal decomposition in Lennard-Jones binary liquid
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The formation of a solid electrolyte interphase (SEI) at the electrode/electrolyte interface substantially affects the stability and lifetime of lithium-ion batteries (LIBs). One of the methods to improve the lifetime of LIBs is by the inclusion of additive molecules to stabilize the SEI. To understand the effect of additive molecules on the initial stage of SEI formation, in this work we compare the decomposition and oligomerization reactions of a fluoroethylene carbonate (FEC) additive on a range of oxygen-functionalized graphitic anodes to those of an ethylene carbonate (EC) organic electrolyte. A series of density functional theory (DFT) calculations augmented by ab initio molecular dynamics (AIMD) simulations reveal that EC decomposition on an oxygen-functionalized graphitic ($11\bar{2}0$) edge facet through a nucleophilic attack on an ethylene carbon site (C E ) of an EC molecule (S2 mechanism) is spontaneous during the initial charging process of LIBs. However, decomposition of EC through a nucleophilic attack on a carbonyl carbon (C C ) site (S1 mechanism) results in alkoxide species regeneration that is responsible for continual oligomerization along the graphitic surface. In contrast, FEC prefers to decompose through an S1 pathway, which does not promote alkoxide regeneration. Including FEC as an additive is thus able to suppress alkoxide regeneration and results in a smaller and thinner SEI layer that is more flexible toward lithium intercalation during the charging/discharging process. In addition, we find that the presence of different oxygen functional groups at the surface of graphite dictates the oligomerization products and the LiF formation mechanism in the SEI.
As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. Here, the Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.
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Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.
Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs) decomposes the interaction energy between molecules into physically interpretable components like geometry distortion, frozen interactions, polarization, and charge transfer (CT, also sometimes called charge delocalization) interactions. In this work, a numerically exact scheme to decompose the CT interaction energy into pairwise additive terms is introduced for the ALMO-EDA using density functional theory. Unlike perturbative pairwise charge-decomposition analysis, the new approach does not break down for strongly interacting systems, or show significant exchange–correlation functional dependence in the decomposed energy components. Both the energy lowering and the charge flow associated with CT can be decomposed. Complementary occupied–virtual orbital pairs (COVPs) that capture the dominant donor and acceptor CT orbitals are obtained for the new decomposition. It is applied to systems with different types of interactions including DNA base-pairs, borane-ammonia adducts, and transition metal hexacarbonyls. While consistent with most existing understanding of the nature of CT in these systems, we report the results also reveal some new insights into the origin of trends in donor–acceptor interactions.
1. To evaluate how increased anthropogenic nutrient inputs alter carbon cycling in grasslands, we conducted a litter decomposition study across 20 temperate grasslands on three continents within the Nutrient Network, a globally distributed nutrient enrichment experiment 2. We determined the effects of addition of experimental nitrogen (N), phosphorus (P) and potassium plus micronutrient (K μ ) on decomposition of a common tree leaf litter in a long-term study (maximum of 7 years; exact deployment period varied across sites). The use of higher order decomposition models allowed us to distinguish between the effects of nutrients on early- versus late-stage decomposition. 3. Across continents, the addition of N (but not other nutrients) accelerated early-stage decomposition and slowed late-stage decomposition, increasing the slowly decomposing fraction by 28% and the overall litter mean residence time by 58%. 4. Synthesis. Using a novel, long-term cross-site experiment, we found widespread evidence that N enhances the early stages of above-ground plant litter decomposition across diverse and widespread temperate grassland sites but slows late-stage decomposition. These findings were corroborated by fitting the data to multiple decomposition models and have implications for N effects on soil organic matter formation. For example, following N enrichment, increased microbial processing of litter substrates early in decomposition could promote the production and transfer of low molecular weight compounds to soils and potentially enhance the stabilization of mineral-associated organic matter. By contrast, by slowing late-stage decomposition, N enrichment could promote particulate organic matter (POM) accumulation. Such hypotheses deserve further testing.
The high proclivity of x rays to destabilize and distort molecular structures has been previously utilized in the synthesis of novel compounds. Here, we show that x-ray induced decomposition of cadmium oxalate induces chemical and structural transformations only at 0.5 and 1 GPa. Using x-ray diffraction and Raman spectroscopy, the synthesized product is identified as cadmium carbonate with cadmium oxalate remnants, which is stable under ambient conditions. At ambient and >1 GPa pressures, only degradation of the electronic density distribution is observed. The transformation kinetics are examined in terms of Avrami’s model, which demonstrates that despite the necessity of high pressure for efficient x-ray induced synthesis of cadmium carbonate, the rate and geometry of structural synthesis in the 0.5–1 GPa pressure range do not depend on the applied pressure. In addition, the possible role of intermolecular distance and molecular mobility in transformation yield is also discussed. Our experimental results indicate that x-ray induced photochemical synthetic pathways can be modulated and optimized by specific parameter selection such as high pressure.
This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data. A beta visualization tool is available for some data types at https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback. Data completed include: Geochemistry, texture, respiration, and enzyme activities FTICR-MS organic matter chemistry Microbial biomass C and N TOC/TDN of water-extractable OM X-ray computed tomography (derived metrics available here, raw data available upon request) Metagenomes; a variety of data formats are available upon request Soil hydraulic properties Data in progress: LC-MS/MS in development, timeline TBD, inquire for status 1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and 1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography. icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates. 1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information. Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information. Readme File_v4.xlsx is the readme file. Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions. The following file and all raw data are available upon request: icr_by_mass_for_single_sample_analysis_only.csv contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs. For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet Acknowledgment: Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at https://sc-data.emsl.pnnl.gov/.
The relative stability of reactive intermediates and reactants on a surface, which dictates the rate and selectivity of catalytic reactions in both gas and liquid phases, is dependent on numerous factors. One well-established example is secondary interactions, such as van der Waals interactions between the catalyst surface and the pendant group of the intermediate, which can govern reaction selectivity for coupling reactions. In this work, we directly show that interactions between adsorbed reaction intermediates and reactant molecules increase the binding energy and affects the geometrical arrangement of coadsorbed reactant/solvent molecules. Evidence for this effect is demonstrated for the oxidative coupling reaction of methanol on a single crystal gold (Au(110)) surface. The rate-limiting reaction intermediate for methanol selfcoupling, methoxy, stabilizes excess adsorbed methanol, which desorbs as a result of beta-hydride decomposition of the adsorbed methoxy. Direct molecular-scale imaging by scanning tunneling microscopy, supplemented by density functional theory, revealed interactive structures formed by methoxy and coadsorbed methanol. Interactions between the methoxy intermediate and coadsorbed methanol stabilizes a hydrogen-bonded network comprising methoxy and methanol by a minimum of 0.13 eV per methanol molecule. Inclusion of such interactions between reaction intermediates and coadsorbed reactants and solvents in kinetic models is important for microkinetic analysis of the rates and selectivities of catalytic reactions in both the gas and liquid phases whenever appreciable coverages of species from the ambient phase exist.
Transition metal nitrides are reactive intermediates in biological and industrial processes. Chemists have synthesized molecular model complexes of such reactive species to understand their function and electronic requirements for new applications. However, molecular chemistry can suffer from intra- and intermolecular decomposition pathways, which preclude further discovery of unknown reactive species. Metal-organic frameworks offer an opportunity for creating long-lived forms of such species with the vacuum of the pore suppressing degradation while simultaneously enabling substrate access for controlled reactivity studies. Here, in this study, we report the characterization of an elusive terminal cobalt nitride species generated through photolysis or thermolysis of a site-isolated cobalt azide within the evacuated metal-organic framework CoN 3 -MFU-4l. The first crystal structure of such a species is presented, with vibrational, X-ray absorption, and electron paramagnetic resonance spectroscopies providing further direct evidence for its formation while elucidating its electronic structure. The system additionally enables subsequent reactivity studies with selected substrates, revealing a unique ambiphilic behavior for a metal nitride species.
We report the spin decomposition of a spin-contaminated different-orbitals-for-different-spins (DODS) wave function is formulated in terms of the Krylov space of the $\hat{S}^2$ ||operator. The number of determinants that contribute to the various projected spin eigenfunctions vertical | $\psi ; S, M \rangle$ depends on the sparsity of the orbital overlap matrix X between the α and β spatial orbitals. The cosine-sine decomposition (CSD) procedure may be applied to this overlap matrix, and the resulting redundant orbital transformations may be applied to the α and β spatial orbitals. This produces a sparse X' matrix in the transformed basis in which each row or column has either one or two nonzero elements. This sparse X' matrix simplifies the spin-decomposition procedure in three ways:1) it reduces the number of contributing determinants within the Krylov basis functions and within the projected spin functions, 2) it reduces the effective orbital dimension through elimination of the frozen core and frozen virtual orbitals, and 3) it simplifies the spin-decomposition procedure in both the original and transformed bases by limiting the Krylov space dimension. These simplifications all reduce the computational effort for the spin-decomposition process. This procedure is implemented within a string-based DODS determinant formulation and applied to spin projection of unrestricted Hartree-Fock determinants.
Single-site catalysts have drawn broad attention in catalysis because of their maximum atomic utilization and unique catalytic performance. Early work in our group has shown a 40-fold higher activity of methanol decomposition over single-site Pt 1 /CeO 2 catalyst than CeO 2 supported 2.5 nm Pt nanoparticles, while a molecular-level understanding of such enhancement is lacking. Herein, the reaction mechanism of methanol decomposition over Pt 1 /CeO 2 was carefully investigated using in situ DRIFTS, and a reaction pathway was proposed. Methanol molecules were dissociatively adsorbed on nanoceria support first, followed by the diffusion of as-formed methoxy species onto Pt single sites where the dehydrogenation occurs and results in the weakly bonded CO. The ease of methanol dissociative adsorption on nanoceria support and the tailored electronic property of Pt 1 via the metal-support interaction are believed to be strongly correlated with the high activity of Pt 1 /CeO 2 .
Various studies have shown associations between molecular features and phenotypes of biological samples. These studies, however, focus on a single phenotype per study and are not applicable to repository scale metabolomics data. Here we report MetSummarizer, a method for predicting (i) the biological phenotypes of environmental and host-oriented samples, and (ii) the raw ingredient composition of complex mixtures. We show that the aggregation of various metabolomic datasets can improve the accuracy of predictions. Since these datasets have been collected using different standards at various laboratories, in order to get unbiased results it is crucial to detect and discard standard-specific features during the classification step. We further report high accuracy in prediction of the raw ingredient composition of complex foods from the Global Foodomics Project.
Solvent-based CO 2 capture consumes significant amounts of energy for solvent regeneration. To improve energy efficiency, this study investigates CO 2 fixation in a solid form through solvation, followed by ionic self-assembly-aided precipitation. Based on the hypothesis that CO 3 2- ions may bind with monovalent metal ions, we introduced Na + into an aqueous hexane-1,6-diamine solution where CO 2 forms carbamate and bicarbonate. Then, Na + ions in the solvent act as a seed for ionic self-assembly with diamine carbamate to form an intermediate ionic complex. The recurring chemical reactions lead to the formation of an ionic solid from a mixture of organic carbamate/carbonate and inorganic sodium bicarbonate (NaHCO 3 ), which can be easily removed from the aqueous solvent through sedimentation or centrifugation and heated to release the captured CO 2 . Mild-temperature heating of the solids at 80–150 °C causes decomposition of the solid CO 2 -diamine-Na molecular aggregates and discharge of CO 2 . This sorbent regeneration process requires 6.5–8.6 GJ/t CO 2 . It was also found that the organic carbamate/carbonate solid, without NaHCO 3 , contains a significant amount of CO 2 , up to 6.2 mmol CO 2 /g-sorbent, requiring as low as 2.9–5.8 GJ/t CO 2 . In conclusion, molecular dynamic simulations support the hypothesis of using Na + to form relatively less stable, yet sufficiently solid, complexes for the least energy-intensive recovery of diamine solvents compared to bivalent carbonate–forming ions.
Interaction analysis techniques, including the many-body expansion (MBE), symmetry-adapted perturbation theory, and energy decomposition analysis, allow for an intuitive understanding of complex molecular interactions. We review these methods by first providing a historical context for the study of many-body interactions and discussing how nonadditivities emerge from Hamiltonians containing strictly pairwise-additive interactions. We then elaborate on the synergy between these interaction analysis techniques and the development of advanced force fields aimed at accurately reproducing the Born–Oppenheimer potential energy surface. In particular, we focus on ab initio–based force fields that aim to explicitly reproduce many-body terms and are fitted to high-level electronic structure results. These force fields generally incorporate many-body effects through ( a) parameterization of distributed multipoles, ( b) explicit fitting of the MBE, ( c) inclusion of many-atom features in a neural network, and ( d) coarse-graining of many-body terms into an effective two-body term. We also discuss the emerging use of the MBE to improve the accuracy and speed of ab initio molecular dynamics.
The accumulation of unmanaged plastic waste in the environment has a devastating impact upon marine life and human health. Catalytic and thermal pyrolysis are promising technologies toward the efficient utilization of plastic waste. Yet, the processing of polymers, such as polyvinyl chloride (PVC), that decompose into corrosive compounds remains a major challenge. In this work, we employ density functional theory (DFT) and thermogravimetric analysis (TGA) to explore the elementary chemical steps that underpin the thermal decomposition of PVC. We determine that the dehydrochlorination reaction (i.e., 1 st stage of thermal decomposition) begins in tertiary chloride defects and propagates via HCl–mediated autocatalysis of internal allylic (IA) chloride groups. The latter groups, when in the vicinity of π–conjugated polymer segments, release HCl in a facile manner. We predict that other compounds, including hydrogen halides and H 2 O could also catalyze PVC’s dehydrochlorination. We suggest that hydrogen halides are the most efficient catalysts for this process, while other compounds like H 2 O may slow down the dehydrochlorination compared to purely HCl-catalyzed process, because of the dilution of the produced HCl. This result is corroborated by TGA experiments. Additionally, we study the thermochemistry and kinetics of polyene chain crosslinking and the formation of aromatics. The former reaction proceeds in parallel with the dehydrochlorination process (i.e., during the 1st stage of thermal decomposition), whilst the latter may occur at high temperatures (i.e., during the 2 nd stage of thermal decomposition). Furthermore, this work contributes to the fundamental understanding of molecular scale phenomena that take place during PVC pyrolysis.
Solid-state lithium ion batteries have enhanced thermal stability compared to batteries using liquid electrolytes. Although their practical implementation is limited by undesired side reactions between the electrode and electrolyte, different modification strategies have been proposed to stabilize these reactive interfaces. These approaches have been primarily based upon bulk materials properties, however, which may not necessarily be representative of the chemistry at the solid/solid interface. In this work, first principles calculations and X-ray scattering experiments are used to elucidate molecular-level reactivity and develop design principles for tailored interfaces based on surface and interfacial properties. Because of its well-known instability, the interface between the Li metal anode and the lithium lanthanum titanate (LLTO) solid electrolyte is applied as a model system. Density functional theory calculations are used to describe bulk, surface, and interfacial thermochemistry of the Li/LLTO system, and interfacial reconstruction is probed using ab initio molecular dynamics. These simulations of the Li/LLTO interface demonstrate facile decomposition concomitant with reduction of Ti 4+ ions. Based on further insights from computational analysis of the surface band edge positions, La 2 O 3 is proposed as an interlayer coating and is shown to provide an energetic barrier for interfacial charge transfer and decomposition reactions from X-ray reflectivity measurements and theoretical calculations. The findings in this work suggest that design strategies based on surface and interfacial properties can be used to kinetically stabilize electrode/electrolyte interfaces in solid-state batteries.