Search NASA⌕ Search

SEARCH · Search NASA

Results for “classical molecular dynamics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Atomistic Insights into Lithium–Glyme Solvate Ionic Liquids: Effects of Chain Length and Anion Coordination

For this study, mixtures of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in diglyme (G2), triglyme (G3) and tetraglyme (G4) at solvate ionic liquid (SIL) concentrations were investigated using classical molecular dynamics (cMD) simulations with a physically motivated force-field specifically developed for modeling these systems. The structural and dynamical properties of the mixtures were computed and analyzed. Lithium solvation shells, radial distribution functions, and X-ray structure factors were studied across the different SIL systems. Translational diffusion and rotational relaxation times were also evaluated, exhibiting similar trends with increasing glyme chain length. The results are consistent with experimental data and in good agreement with previous computational studies on G3 and G4. These findings validate the accuracy of the force field in modeling glyme systems and its use for describing the [Li(G2) 4/3 ][TFSI] mixture. Additionally, the thermal and electrochemical stability of these electrolytes were systematically examined. The thermal stability appears to be governed by cooperative interactions among glyme molecules, while the electrochemical stability is primarily influenced by Li + -anion interactions, which vary significantly with glyme chain length. Overall, the study sheds light on the crucial role of the anion in these glyme-based SILs and offers valuable insights into Li + -glyme systems at SIL concentrations, highlighting their promise as potential Li-ion battery electrolytes.

anions↗
DOE OSTI2022

Water Weakening of Calcium Oxide

Chemomechanical processes such as water weakening can control the permeability and deformation of rocks and manmade materials. Here, atomistic modeling and nanomechanical experiments were used to identify molecular origins of chemomechanical effects in calcium oxide (CaO) and its effect on observed elastic, plastic, and brittle deformation. Classical molecular dynamics simulations with the bond order-based reactive force-field ReaxFF were used to assess brittle fracture. In the presence of water, CaO fractured earlier and more often during quasi-static loading, with a calculated reduction in fracture toughness of ~80% associated with changes in the stress distribution around the crack tip. Experimentally, elastic and plastic deformation of CaO surfaces exposed to water was assessed experimentally using in situ liquid nanoindentation. Nanoindentation showed that following exposure to water, the contact hardness decreased by 1–2 orders of magnitude and decreased the modulus by 2–3 orders of magnitude due to surface hydroxylation. Furthermore, the strong chemomechanical effects on the mechanical processes in CaO suggests that minerals with similar structures may exhibit comparable effects, influencing the stability of cements and geomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effect of Hydrophilicity and Interfacial Water Structure on Particle Attachment

Oriented attachment (OA) of nanoparticles is an important and common crystallization pathway. Efforts to isolate and quantify the interparticle forces that underlie OA have only recently been initiated and the role played by the interfacial solvent structure in the confined region between nanocrystal surfaces in enabling and controlling OA remains an open question. In this work, classical molecular dynamics (MD) simulations were performed to compute the free energy landscape of nanoparticles approaching mineral substrates in both vacuum and pure water. Periclase (MgO), muscovite (KAl 3 Si 3 O 10 (OH) 2 ), and pyrophyllite (Al 2 Si 4 O 10 (OH) 2 ) nanoparticles exposing the (100), (001), and (001) surfaces, respectively, were brought to contact with substrates exposing the same surfaces. These mineral surfaces were selected to investigate a range of hydrophilicities (periclase > muscovite > pyrophyllite). The MD simulations revealed that the interfacial water structure created free energy minima for nanoparticle approach that corresponded to integer numbers of intervening water layers. The depth of the free energy minima and the free energy barriers between minima correlated positively with the hydrophilicity of the mineral surface. While the range of solvent-mediated interactions was predicted to be short (a few intervening water layers at most for MgO), the free energy barriers were calculated to be large (fraction of an eV per nm 2 ) and the effect of misalignment diminished rapidly with the number of intervening water layers. The results help explain the formation of mesocrystals and the observed ability of nanoparticles to rotate before attachment while in a long-lived solvent-separated state.

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

Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation

Classical theories of particle aggregation, such as Derjaguin–Landau–Verwey–Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na + , K + , and NO 3 –) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (~3–4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal–basal surfaces is more favorable than between (001) edge–edge surfaces (~5–6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (~5–10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. Further, the results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Surface Energies and Structure of Salt–Brine Interfaces

Permeability of salt formations is controlled by the equilibrium between the salt–brine and salt–salt interfaces described by the dihedral angle, which can change with the composition of the intergranular brine. In this work, classical molecular dynamics (MD) simulations were used to investigate the structure and properties of the salt–brine interface to provide insight into the stability of salt systems. Mixed NaCl–KCl brines were investigated to explore differences in ion size on the surface energy and interface structure. Nonlinearity was noted in the salt–brine surface energy with increasing KCl concentration, and the addition of 10% KCl increased surface energies by 2–3 times (5.0 M systems). Size differences in Na+ and K+ ions altered the packing of dissolved ions and water molecules at the interface, impacting the surface energy. Additionally, ions at the interface had lower numbers of coordinating water molecules than those in the bulk and increased hydration for ions in systems with 100% NaCl or 100% KCl brines. Ultimately, small changes in brine composition away from pure NaCl altered the structure of the salt–brine interface, impacting the dihedral angle and the predicted equilibrium permeability of salt formations.

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

Electric-Field-Induced Assembly of an Ionic Liquid–Water Interphase Enables Efficient Heavy Metal Electrosorption

Controlling ion desolvation, transport, and charge transfer at the electrode-electrolyte interface (EEI) is critical to enabling the rational design of efficient and selective separation of targeted heavy metals and decontamination of industrial waste water. One challenge is to sufficiently resolve and interrogate the intermediate transformation steps between solvated metal cations and bare cations for electroreduction at the EEI and establish pathways to modulate these steps to achieve efficient energy transfer for targeted reactive separations. Herein, we obtained a predictive understanding of the effect of adding a hydrophobic ionic liquid, 1-ethyl-3-methylimidazolium chloride (EMIMCl), to an aqueous electrolyte on modulating the desolvation and electrosorption of Pb 2+ cations using a combination of experimental and theoretical techniques. Here, we reveal formation of a compact interphase layer consisting of EMIMCl-Pb complex clusters under an applied electric field using operando electrochemical Raman spectroscopy, atomic force microscopy, and electrochemical impedance spectroscopy measurements combined with classical molecular dynamics simulations. The application of a larger negative potential is shown to result in formation of a well oriented layer with the positive imidazolium ring of the EMIMCl lying on the electrode and the long hydrophobic alkyl chain extending into the bulk electrolyte. This oriented layer is demonstrated to facilitate desolvation of incoming solvated Pb 2+ cations and decrease the charge transfer resistance for Pb electrodeposition, which has important implications for selective removal of Pb from contaminated mixtures. Overall, our studies open up new opportunities to modulate ion desolvation using hydrophobic ionic liquids in aqueous electrolytes for efficient heavy metal separation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tuning the Functionalities of Porous Liquids for Emergent Gas-Capture Properties

Type 3 Porous Liquids (PLs) are a class of materials with the potential to revolutionize gas capture, storage, and utilization. These PLs are formed by suspending sorbent nanoparticles (e.g., metal−organic frameworks) in sterically excluded solvents, creating permanent porosity for gas capture in a processable, low-viscosity phase. Herein, a computational study revealed sorbent surface functionalization strategies to enhance CO 2 sorption, and the molecular structural signatures underpinning the enhancements in gas uptake. PLs composed of a ZIF-8 surface functionalized with 3-amino-1,2,4-triazole (Atz) in glyceryl triacetate were targeted for emergent CO 2 capture, exceeding that of the unfunctionalized ZIF-8 PL. ZIF-8 was surface functionalized with Atz at various surface coverage fractions (f), and classical molecular dynamics simulations predicted an increase in CO 2 sorption capacity with increasing f, up to f = 0.75. Additionally, detailed structural analyses revealed that solvent orientational order, derived from the solvent triplet-angle distribution, can identify the gas-capture potential of a PL without requiring computationally expensive direct modeling of the CO 2 sorption. Combined with experimental validation, initial computational screening of PL compositions promises to accelerate the discovery of PL compositions for novel gas separation materials platforms.

gas capture↗
DOE OSTI2023

Unexpected Kinetic Solvent Effects Enhance Activity and Selectivity in Biphasic Systems

Biphasic dehydration of fructose to 5-hydroxymethylfurfural (HMF) has shown unprecedented increases in productivity, but a mechanistic understanding is lacking. Herein, we couple fast experimental reaction kinetics, multiscale modeling (phase behavior, classical molecular dynamics(MD), and quantum mechanics/molecular mechanics MD), in situ sampling, and IR and 13 C-NMR spectroscopy to elucidate the complex effects of nonpolar extracting organic solvents on the kinetics of fructose dehydration. We show that these organic solvents can reach significant mutual solubility with water at reaction temperatures, enabling the partition of the sugar and catalyst into the extracting phase. In the organic-rich environment, the dehydration of fructose proceeds faster and more selectively than in water due to increased relative abundance of the reactive furanose isomer, enhanced water–catalyst–substrate interactions driven by nanophase separation, and higher product stability stemming from preferential solvation. Furthermore, we demonstrate that these solvent effects impact other critical biphasic reactions in biomass upgrading and provide qualitative principles for solvent selection.

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

Water or Anion? Uncovering the Zn 2+ Solvation Environment in Mixed Zn(TFSI) 2 and LiTFSI Water-in-Salt Electrolytes

Applications of aqueous zinc batteries for grid-scale energy storage are limited by their poor reversibility and the competing water splitting reaction. The recent invention of a water-in-salt (WIS) electrolyte concept provides a new route enabling a stable and highly reversible aqueous zinc battery chemistry. In the present work, a mixed zinc bis(trifluoromethane sulfonyl)imide (Zn(TFSI) 2 ) and LiTFSI WIS electrolyte was studied using X-ray total scattering, X-ray absorption, and Fourier transform infrared spectroscopy in conjunction with classical molecular dynamics simulations. It was found that, in the highly concentrated WIS electrolyte consisting of 1 m Zn(TFSI) 2 and 20 m LiTFSI, Zn 2+ cations are mainly solvated by six waters in their first solvation shell, while the TFSI – anions are completely excluded. This ion solvation picture is fundamentally different from the previous understandings. The results suggest that additional studies are needed to fully understand the unusual stability and reversibility of zinc-WIS electrolyte-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Pretreatment with Sodium Methyl Mercaptide Increases Carbohydrate Yield during Kraft Pulping

Kraft pulping is the predominant technology in the pulp and paper industry for removing lignin from wood carbohydrates to produce paper, board, packaging, tissue, and specialty cellulose. However, the kraft process is energy intensive and expensive, and its yield is limited by the degradation of carbohydrates. Pretreatment can increase carbohydrate yield by limiting degradation via primary peeling of reducing end groups. However, protection of galactoglucomannan (GGM), the primary hemicellulose component of softwood, is minimal when conventional pretreatments are used. Here, we investigated the effectiveness of sodium methyl mercaptide pretreatment on southern pine wood chips under a range of experimental conditions. We found that pretreatment of biomass with 4.38% sodium methyl mercaptide at pH 12 and 105 °C for 60 min provided small but significant increases in xylan and cellulose yields relative to control conditions, but preservation of GGM was minimal. Furthermore, to provide insight into molecular-scale details of primary peeling, pretreatment, and alkaline hydrolysis, we performed classical molecular dynamics (MD) simulations under selected process conditions and quantum mechanical (QM) calculations of selected reactions. MD simulations showed that C1 of the GGM reducing end is more readily accessible by HO – and CH 3 S – ions than in cellulose. The free energy barrier for peeling calculated with QM is lower for GGM than for cellulose, indicating increased susceptibility to peeling. In addition, we found that GGM may be more susceptible to internal chain cleavage than cellulose. Thus, even though reducing end groups may be protected initially through pretreatment, new unprotected reducing end groups may be generated through alkaline hydrolysis. Taken together, these findings show the promise of methyl mercaptide as a pretreatment technology for cellulose retention and also provide molecular insight for improving its effectiveness toward GGM.

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

Data-Centric Development of Lignin Structure–Solubility Relationships in Deep Eutectic Solvents Using Molecular Simulations

Lignin is a natural source of aromatic chemicals with significant potential as an abundant, renewable feedstock for value-added products. Deep eutectic solvents (DES)–solvents composed of a hydrogen bond donor (HBD) and acceptor (HBA) in varying ratios–have emerged as a highly tunable class of solvents for lignin solubilization. However, the variety of possible DES compositions and limited molecular-scale understanding of lignin solubility makes solvent selection a challenge without laborious trial-and-error experimentation. To address these challenges, we use classical molecular dynamics (MD) simulations to study the interactions of lignin model compounds with various DES–water systems. Quantitative parameters (descriptors) were calculated by postprocessing the MD results and used to train a regression model that predicts experimentally determined solubilities of lignin model compounds. This approach revealed that the most important descriptors of solubility are the system temperature, solute hydrophilicity, and metrics quantifying hydrogen bonding. Maximizing the interactions between solute–HBD (hydrophobic group), water–HBD (hydrophilic group), and water–HBA molecules led to the highest model compound solubility. Our results support a hydrotropic mechanism in which extensive DES–water hydrogen bonding and favorable HBD interactions with the solute promote high solubility. We applied the regression model derived using model compounds to predict the solubility of representative lignin oligomers. The model predicted lignin oligomers’ solubilities in good agreement with experiments, indicating that the simulations of model compounds can be extended to predict the solubility of larger lignin compounds across a range of solvent compositions and temperatures. Furthermore, these findings provide new molecular-scale insight into lignin solubilization mechanisms and a new method for computationally screening potential solvent systems for lignin valorization.

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

Revitalizing Iron Redox by Anion-Insertion-Assisted Ferro- and Ferri-Hydroxides Conversion at Low Alkalinity

Iron hydroxides are desirable alkaline battery electrodes for low cost and environmental beneficence. However, hydrogen evolution on charging and Fe 3 O 4 formation on discharging cause low storage capacity and poor cycling life. Here, we report that green rust (GR) (Fe 2+ 4 Fe 3+ 2 (HO – ) 12 SO 4 ), formed via sulfate insertion, promotes Fe(OH) 2 /FeOOH conversion and shows a discharge capacity of ~211 mAh g –1 in half-cells and Coulombic efficiency of 93% after 300 cycles in full-cells. Theoretical calculations show that Fe(OH) 2 /FeOOH conversion is facilitated by intercalated sulfate anions. Classical molecular dynamics simulations reveal that electrolyte alkalinity strongly impacts the energetics of sulfate solvation, and low alkalinity ensures fast transport of sulfate ions. Anion-insertion-assisted Fe(OH) 2 /FeOOH conversion, also achieved with Cl – ion, paves a pathway toward efficient utilization of Fe-based electrodes for sustainable applications.

25 ENERGY STORAGE↗
DOE OSTI2023

The Energetic Origins of Pi–Pi Contacts in Proteins

Accurate potential energy models of proteins must describe the many different types of noncovalent interactions that contribute to a protein’s stability and structure. Pi–pi contacts are ubiquitous structural motifs in all proteins, occurring between aromatic and nonaromatic residues and play a nontrivial role in protein folding and in the formation of biomolecular condensates. Guided by a geometric criterion for isolating pi–pi contacts from classical molecular dynamics simulations of proteins, we use quantum mechanical energy decomposition analysis to determine the molecular interactions that stabilize different pi–pi contact motifs. We find that neutral pi–pi interactions in proteins are dominated by Pauli repulsion and London dispersion rather than repulsive quadrupole electrostatics, which is central to the textbook Hunter–Sanders model. This results in a notable lack of variability in the interaction profiles of neutral pi–pi contacts even with extreme changes in the dielectric medium, explaining the prevalence of pi-stacked arrangements in and between proteins. We also find interactions involving pi-containing anions and cations to be extremely malleable, interacting like neutral pi–pi contacts in polar media and like typical ion–pi interactions in nonpolar environments. Like-charged pairs such as arginine–arginine contacts are particularly sensitive to the polarity of their immediate surroundings and exhibit canonical pi–pi stacking behavior only if the interaction is mediated by environmental effects, such as aqueous solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dissociation of salts in water under pressure

The investigation of salts in water at extreme conditions is crucial to understanding the properties of aqueous fluids in the Earth. We report first principles (FP) and classical molecular dynamics simulations of NaCl in the dilute limit, at temperatures and pressures relevant to the Earth's upper mantle. Similar to ambient conditions, we observe two metastable states of the salt: the contact (CIP) and the solvent-shared ion-pair (SIP), which are entropically and enthalpically favored, respectively. We find that the free energy barrier between the CIP and SIP minima increases at extreme conditions, and that the stability of the CIP is enhanced in FP simulations, consistent with the decrease of the dielectric constant of water. The minimum free energy path between the CIP and SIP becomes smoother at high pressure, and the relative stability of the two configurations is affected by water self-dissociation, which can only be described properly by FP simulations.

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

Insights into solvent and surface charge effects on Volmer step kinetics on Pt (111)

Abstract The mechanism of pH-dependent hydrogen oxidation and evolution kinetics is still a matter of significant debate. To make progress, we study the Volmer step kinetics on platinum (111) using classical molecular dynamics simulations with an embedded Anderson-Newns Hamiltonian for the redox process and constant potential electrodes. We investigate how negative electrode electrostatic potential affects Volmer step kinetics. We find that the redox solvent reorganization energy is insensitive to changes in interfacial field strength. The negatively charged surface attracts adsorbed H as well as H + , increasing hydrogen binding energy, but also trapping H + in the double layer. While more negative electrostatic potential in the double layer accelerates the oxidation charge transfer, it becomes difficult for the proton to move to the bulk. Conversely, reduction becomes more difficult because the transition state occurs farther from equilibrium solvation polarization. Our results help to clarify how the charged surface plays a role in hydrogen electrocatalysis kinetics.

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

High-throughput screening of hypothetical metal-organic frameworks for thermal conductivity

Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (> 1.0 g cm -3 ), small pores (< 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (< 0.02 W m -1 K -1 ), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (>10 Wm -1 K -1 ), the structures of which we describe in additional detail.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗