Foundation machine learning interatomic potentials (MLIPs) have enabled atomistic simulations across broad regions of chemical and materials space, but many remain computationally expensive and lack explicit electrostatics, limiting their use for systems governed by long-range interactions and electrical response. Previously, we introduced Latent Ewald Summation (LES), which learns latent atomic charges and long-range electrostatics from density functional theory (DFT) energy and force labels alone. Here, we use LES to extract electrostatics that are latent in foundation models: energies and forces predicted by a teacher model are used to train a lightweight LES-augmented student MLIP, with optional fine-tuning on additional DFT data. The resulting models reduce computational cost while providing access to Born effective charge tensors, and infrared spectra. We benchmark student models distilled from a broad set of foundation MLIPs, including UMA, MACE, Orb, eSEN, GemNet-OC, PET, and EquiformerV2-based models, against experimental infrared spectra for liquid water, concentrated hydrochloric acid, and the anatase TiO2(101)-water interface. Across these systems, electrostatic response can be extracted from most foundation MLIPs. The benchmark further shows that the underlying DFT level and dataset used to train the teacher model play a larger role than architecture in determining electrostatic and spectroscopic accuracy. For the TiO2-water interface, fine-tuning with a modest amount of higher-level DFT data improves structural and infrared predictions. LES-based distillation therefore provides a practical route for converting foundation MLIPs into efficient, electrically responsive models, while also testing the physical fidelity encoded in foundation models.

Two-dimensional materials have garnered significant attention in recent years due to their remarkable electronhole transfer capability. However, the advancement of convenient and rapid synthesis techniques remains crucial for further research in this field. In this study, lamellar anatase/rutile-TiO2 phase heterojunctions with a favorable phase interface was synthesized through a fast annealing route using glucose as the template and titanium tetrachloride. The sample synthesized at 600 degrees C with a holding time of 20 min exhibited the most significant levels of H2 evolution activity (53.22 mmol g- 1 h-1) with a low loading of 0.05 wt% Pt co-catalyst, which is significantly higher than the commercial P25 sample. The characterization reveals that the anatase/ rutile-TiO2 phase heterojunction in the two-dimensional sheet exhibits excellent phase interface contact and possesses a large specific surface area with an appropriate pore size. These characteristics are advantageous for facilitating the separation and migration of carriers, thereby enhancing the efficiency of the H2 production reaction through hydrolysis. This study presents a novel approach towards the advancement of highly effective two-dimensional photocatalysts.

Structural, thermal, and dynamic properties of four deep eutectic solvents comprising choline chloride paired with ortho-phenolic derivative hydrogen-bond donors were probed using experiments and molecular simulations. The hydrogen-bond donors include phenol, catechol, o-chlorophenol, and o-cresol, in a 3:1 mixture with the hydrogen-bond acceptor choline chloride. Density, viscosity, and pulsed-field gradient NMR diffusivity measurements were conducted over a range of temperatures. Classical and ab initio molecular dynamics simulation results match experimental data reasonably well. The simulation results were then used to perform a more detailed analysis of the local structure and dynamics of these systems.

Extractant design in liquid-liquid extraction (LLE) is a research frontier of metal ion separations that typically focuses on the direct extractant-metal interactions. However, a more detailed understanding of energetic drivers of separations beyond primary metal coordination is often lacking, including the role of solvent in the extractant phase. In this work, we propose a new mechanism for enhancing metal-complexant energetics with nanostructured solvents. Using molecular dynamics simulations with umbrella sampling, we find that the organic solvent can reshape the energetics of the extractant's intramolecular conformational landscape. We calculate free energy profiles of different conformations of a representative bidentate extractant, n-octyl(phenyl)-N,N-diisobutyl carbamoyl methyl phosphinoxide (CMPO), in four different solvents: dodecane, tributyl phosphate (TBP), and dry and wet ionic liquid (IL) 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2N]). By promoting reorganization of the extractant molecule into its binding conformation, our findings reveal how particular solvents can ameliorate this unfavorable step of the metal separation process. In particular, the charge alternating nanodomains formed in ILs substantially reduce the free energy penalty associated with extractant reorganization. Importantly, using alchemical free energy calculations, we find that this stabilization persists even when we explicitly include the extracted cation. These findings provide insight into the energetic drivers of metal ion separations and potentially suggest a new approach to designing effective separations using a molecular-level understanding of solvent effects.

Lanthanide ion solvation chemistry in nonaqueous phases is key to understanding and developing effective separation processes for these critical materials. Due to the complexity and inherent disorder of the solution phase, a comprehensive picture of the solvated metal ion is often difficult to generate solely from conventional spectroscopic approaches and electronic structure calculations, particularly in the extractant phase. In this work, we use classical molecular dynamics (MD) simulation with an advanced sampling technique, metadynamics, supplemented by experimental spectroscopy and speciation analysis, to measure lanthanide solvation free energy landscapes. We define coordination-based collective variables to probe the entire range of solvation configurations in the organic phase of lanthanum (La), europium (Eu), and lutetium (Lu) nitrate salts bound with a commonly used extractant, N,N'-dimethyl, N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). The known lanthanide extraction trend of La ≈ Eu > Lu is readily explained by the measured free energy surfaces, which show consistent DMDOHEMA coordination from La to Eu, followed by loss of DMDOHEMA coordination from Eu to Lu. These simulations suggest how ligand crowding at the metal center can control selectivity, in this case resulting in the opposite extraction trend as observed with other conventional extractants, where the enthalpic contribution from increasing lanthanide charge density across the series dominates the extraction energetics. We also find that the presence of inner-sphere water, verified by time-resolved fluorescence, diversifies the accessible solvation structures. As a result, understanding solvation requires consideration of an entire thermodynamic ensemble, rather than the single dominant lowest-energy structure, as is often considered out of necessity in interpretation of spectroscopic data or in electronic structure-based ligand design approaches. In general, we demonstrate how metadynamics uniquely enables investigation of complex, multidimensional solvation energetic landscapes, and how it can explain selectivity trends where extraction is controlled by more complex mechanisms than simple charge density-based selectivity.

An azeotrope is a constant boiling point mixture, and its behavior is important for fluid separation processes. Predicting azeotropes from atomistic simulations is difficult due to the complexities and convergence problems of Monte Carlo and free-energy perturbation techniques. Here, we present a methodology for predicting the azeotropes of binary mixtures, which computes the compositional dependence of chemical potentials from molecular dynamics simulations using the S0 method and employs experimental boiling point and vaporization enthalpy data. Using this methodology, we reproduce the azeotropes, or lack thereof, in five case studies, including ethanol/water, ethanol/isooctane, methanol/water, hydrazine/water, and acetone/chloroform mixtures. We find that it is crucial to use the experimental boiling point and vaporization enthalpy for reliable azeotrope predictions, as empirical force fields are not accurate enough for these quantities. Finally, we use regular solution models to rationalize the azeotropes and reveal that they tend to form when the mixture components have similar boiling points and strong interactions.

Fundamental understanding of coordination chemistry across the lanthanide series is essential for explaining chemical behavior of rare-earth metals in complex liquid-liquid extraction processes, which in turn affects the distribution ratios and efficacy of separations as a whole. In this work, we explore the structural trends between the lanthanides and a neutral N,N,N′,N′-tetramethylmalonamide (TMMA) ligand within four isolated families of solid-state compounds: Ln(trans-TMMA)2(NO3)3 Ln = La-Nd, Sm; Ln(cis-TMMA)2(NO3)3 Ln = Eu-Tb, Er; [Ln(TMMA)3(NO3)2][Ln(TMMA)(NO3)4] Ln = Dy-Tm; Ln(Κ2-TMMA)(iPrOH)(NO3)3 and Ln(Κ1-TMMA)(Κ2-TMMA)(NO3)3 Ln = Yb, Lu. Moving across the lanthanide series, we note the formation of both discrete charge-neutral complexes, as well as charged molecular anion-cation pairs, with variations in spatial ligand arrangement, coordination numbers, and ligand denticities. IR and Raman spectroscopy paired with DFT frequency calculations were used for an in-depth investigation of vibrational modes unique to each structural family. The collection of isolated model compounds was also discussed in the context of liquid-liquid separations based on reported distribution ratios from malonamide extraction.

Confinement of solvents and solutes within nanoporous materials frequently leads to the emergence of unique mass transport behaviors that, once fully understood, may lead to improved chemical separations. Here, the diffusion of Rhodamine B (RhB) dye within 10 and 20 nm diameter anodic aluminum oxide (AAO) nanopores filled with binary ethanol/water mixtures is investigated. Mixture compositions spanning from pure ethanol to pure water are employed. The results of confocal fluorescence correlation spectroscopy studies reveal that RhB diffusion occurs by a two-component mechanism comprising composition-dependent fast and slow motions, characterized by diffusion coefficients D-f and D-s. The results are consistent with those of previous studies performed under more limited conditions [J. Phys. Chem. C, 2023, 127, 411-420]. The fast component scales with mixture viscosity and is assigned to hindered bulk-like diffusion in central pore regions. Slow diffusion likely involves adsorption of RhB to the pore surface and may be described by a desorption-mediated mechanism. The occurrence of RhB adsorption to the AAO surface is verified at the single-molecule level by wide-field fluorescence imaging of membrane cross-sectional surfaces. Unique composition-dependent trends in the autocorrelation amplitude and in D-s that mimic bulk RhB solubility are revealed. D-s is found to be smallest in pure ethanol and pure water and largest in intermediate mixtures. These results suggest that RhB surface adsorption is strongest in the pure liquids and weakest in mixtures of intermediate composition, where the dye is least soluble, and most soluble, respectively. Molecular dynamics simulations reveal that a water layer appears on the pore surface under most conditions, while RhB is solvated primarily by ethanol. The composition dependence of RhB diffusion is concluded to reflect its solvation-dependent interactions with the pore walls.

This study highlights the importance of combining distribution ratio measurements with multiple spectroscopic techniques to provide a more comprehensive understanding of organic phase Ln coordination chemistry. Solvent extraction investigations with N,N,N',N'-tetraoctyldiglycolamide (TODGA) in n-heptane reveal the sensitivity of Ln complexation to the HNO3 concentration. Distribution ratio measurements in tandem with UV-Vis demonstrated that increasing the concentration of HNO3 above 0.5 M with a constant NO3- of 1 M increases the number of coordinating TODGA molecules, from a 1:2 to a 1:3 Ln:TODGA complex. At each concentration of HNO3 considered herein (from 0.01 to 1 M), Eu lifetime analysis demonstrated no evidence of H2O coordination. Results from Fourier transform infrared investigations suggest the presence of inner-sphere NO3- under low concentrations of HNO3 when the 1:2 Ln:TODGA complex is present. Increasing the HNO3 concentration above 0.5 M increases the propensity for outer-sphere interactions by removing the coordinated NO3- and saturating the Ln coordination sphere with three TODGA molecules, resulting in the well-established cationic, trischelate homoleptic [Ln(TODGA)3]3+ complex. This work demonstrates the importance in considering the NO3- source for solvent extraction systems. In particular, for systems with an affinity for outer-sphere interactions with molar concentrations of HNO3, changing the NO3- source can change the inner-sphere coordination of the Ln complex, which, in turn, affects the separation efficacy.

Molecular Dynamics (MD) simulation is often used to study properties of various chemical interactions in domains such as drug discovery and development, particularly when executing real experimental studies is costly and/or unsafe. Studying the motion of trajectories of molecules/atoms generated from MD simulations provides a detailed atomic level spatial location of every atom for every time frame in the experiment. The analysis of this data leads to an atomic and molecular level understanding of interactions among the constituents of the system of interest. However, the data is extremely large and poses storage and processing challenges in the querying and analysis of associated atom level motion trajectories. We take a first step towards applying domain-specific generalization techniques for the data representation, subsequently used for applying trajectory compression algorithms towards reducing the storage requirements and speeding up the processing of within-distance queries over MD simulation data. We demonstrate that this generalization-aware compression, when applied to the dataset used in this case study, yields significant improvements in terms of data reduction and processing time without sacrificing the effectiveness of within-distance queries for threshold-based detection of molecular events of interest, such as the formation of Hydrogen Bonds (H-Bonds).

Understanding the impact of extractant functionalization on metal-binding energetics in liquid-liquid extraction is essential to guide the development of better separation processes. Traditionally, computational extractant design uses electronic structure calculations on metal-ligand clusters to determine the metal-binding energy of the lowest energy state. Although highly accurate, this approach does not account for all of the relevant physics encountered under experimental conditions. Such methodologies often neglect entropic contributions such as temperature effects and ligand flexibility, in addition to approximating solvent-extractant interactions with implicit solvent models. In this study, we use classical molecular dynamics simulations with an advanced sampling method, metadynamics, to map out extractant molecule conformational free energies in the condensed phase. We generate the complete conformational landscape in solution for a family of bidentate malonamide-based extractants with different functionalizations of the headgroup and the side chains. In particular, we show how such alkyl functionalization reshapes the free energy landscape, affecting the free energy penalty of organizing the extractant into the cis-like metal-binding conformation from the trans-like conformation of the free extractant in solution. Specifically, functionalizing alkyl tails to the center of the headgroup has a greater influence on increasing molecular rigidity and disfavoring the binding conformation than functionalizing side chains. These findings are consistent with trends in metal-binding energetics based on experimentally reported distribution ratios. We also consider a different bidentate extractant molecule, carbamoylmethylphosphine oxide, and show how the choice of solvent can further reshape the conformational energetic landscape. This study demonstrates the feasibility of using molecular dynamics simulations with advanced sampling techniques to investigate extractant conformational energetics in solution, which, more broadly, will enable extractant design that accounts for entropic effects and explicit solvation.

Constructing high-quality zeolite membrane by regulating solely the kinetics of zeolite nucleation and growth is desired because of its simplicity and potential industrial viability. Herein, a high-performance mordenite membrane was prepared without using organic template successfully on a macroporous tubular & alpha;-alumina support using a novel and simple intermittent hydrothermal synthesis (IHS) method. We aimed at regulating membrane synthesis kinetics by adjusting the concentration of the synthetic gel by introducing an unheated period of the oven in the middle stage of the synthesis process. In the proposed IHS method, the power supply of the oven can be switched off and on with the aid of a smart socket without manual operation, ensuring its feasibility and convenience. A thin and dense membrane layer was formed via the appropriate adjustment of presynthesis time, unheated time, and resynthesis time. The effects of each duration on the morphologies, microstructures, and pervaporation performances of the prepared mordenite membranes were investigated. Under optimized conditions, the as-synthesized mordenite membrane showed high pervaporation performance with a permeation flux and separation factor of 5.57 kg m- 2 h-1 and >10000, respectively, in the dehydration of 90 wt % isopropanol/water mixture at 75 degrees C. This work provides a novel, simple, and feasible method for the preparation of high-performance zeolite membrane.

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid-liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid-liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

Recent experimental work has shown zeolite membrane-based separation as a promising potential technology for Kr/Xe gas mixtures due to its much lower energy requirements in comparison to cryogenic distillation, the conventional separation method for such mixtures. Such a separation is also economically rewarding because Xe is in high demand, as a valuable product for many applications/processes. In this work, we have used Molecular Dynamics (MD) simulations to study the effects of different conditions, i.e., temperature, pressure, and gas feed composition, on Kr/Xe separation performance via DD3R zeolite membranes. We provide a comprehensive study of the permeation of the different gas species, density profiles, and diffusion coefficients. Molecular simulations show that if the feed is changed from pure Kr/Xe to an equimolar mixture, the Kr/Xe separation factor increases, which agrees with experiments. In addition, when Ar is introduced as a sweep gas, the adsorption of both Kr and Xe increases, while the permeation of pure Kr increases. A similar behavior is observed with equimolar mixtures of Kr/Xe with Ar as the sweep gas. High-separation Kr/Xe selectivity is observed at 50 atm and 425 K but with low total permeation rates. Changing pressure and temperature are found to have profound effects on optimizing the separation selectivity and the permeation throughput.

Usnic acid is an antibiotic metabolite produced by a wide variety of lichenized fungal lineages. The enantiomers of usnic acid have been shown to display contrasting bioactivities, and hence it is important to determine their spatial distribution, amounts and enantiomeric ratios in lichens to understand their roles in nature and grasp their pharmaceutical potential. The overall aim of the study was to characterise the spatial distribution of the predominant usnic acid enantiomer in lichens by combining spatial imaging and chiral chromatography. Specifically, separation and quantification of usnic acid enantiomers in four common lichens in Iceland was performed using a validated chiral chromatographic method. Molecular dynamics simulation was carried out to rationalize the chiral separation mechanism. Spatial distribution of usnic acid in the lichen thallus cross-sections were analysed using Desorption Electrospray Ionization-Imaging Mass Spectrometry (DESI-IMS) and fluorescence microscopy. DESI-IMS confirmed usnic acid as a cortical compound, and revealed that usnic acid can be more concentrated around the algal vicinity. Fluorescence microscopy complemented DESI-IMS by providing more detailed distribution information. By combining results from spatial imaging and chiral separation, we were able to visualize the distribution of the predominant usnic acid enantiomer in lichen cross-sections: (+)-usnic acid in Cladonia arbuscula and Ramalina siliquosa, and (-)-usnic acid in Alectoria ochroleuca and Flavocetraria nivalis. This study provides an analytical foundation for future environmental and functional studies of usnic acid enantiomers in lichens.

While organic structure directing agents (OSDAs) are well known to have a directional influence on the topology of a crystallizing zeolite, the relationship between OSDA charge and siting of aliovalent ions on a primarily siliceous framework is unclear. Here, we explore the relationship between OSDA orientation, Al3+ siting, and lattice energy, taking as a model system CHA zeolite occluded with N,N,N-trimethyl-1-adamantyl ammonium (TMAda+) at an Si/Al ratio of 11/1. We use density functional theory calculations to parametrize a fixed-charge classical model describing van der Waals and electrostatic interactions between framework and OSDA. We enumerate and explore all possible combinations of OSDA orientation and Al location (attending to Lowenstein's rule) within a 36 T-site supercell. We find that interaction energies vary over 60 kJ/double-six-ring-unit (d6r). Further, analysis of configurations reveals that energies are sensitive to Al-Al proximity, such that low energies are associated with Al3+ pairs in 8-membered rings and higher energies associated with Al3+ pairs in smaller 6- and 4-membered rings. Comparisons with Al siting inferred from CHA zeolite crystallized with TMAda+ suggests that these computed interaction energies are useful reporters of observed Al siting in CHA synthesized with TMAda+.

The solvation structure and transport properties of Li+ in ionic liquid (IL) electrolytes based on n-methyl-nbutylpyrrolidinium cyano(trifluoromethanesulfonyl)imide [PYR14] [CTFSI] and [Li] [CTFSI] (0 <= x(Li) <= 0.7) were studied by Raman and Nuclear Magnetic Resonance (NMR) diffusometry, and molecular dynamics (MD) simulations. At x(Li) < 0.3, Li+ coordination is dominated by the cyano group. As x(Li) is increased, free cyano-sites become limited, resulting in increased coordination via the sulfonyl group. The 1:1 mixture of the symmetric anions bis(trifluoromethanesulfonyeimide ([TFSI]) and dicyanamide ( [DCA]) results in similar physical properties as the IL with [CTFSI]. However, anion asymmetry is shown to increase Li-salt solubility and promote Li+ transference. The lifetimes of Litcyano coordination for [CTFSI] are calculated to be shorter than those for [DCA], indicating that the competition from the sulfonyl group weakens its solvation with Li+. This resulted in higher Li+ transference for the electrolyte with [CTFSI]. In relation to the utility of these electrolytes in energy storage, the Li-LiFePO4 half cells assembled with IL electrolyte (x(Li) = 0.3, 0.5, and 0.7) demonstrated a nominal capacity of 140 mAh/g at 0.1C rate and 90 'C where the cell with x(Li) = 0.7 IL electrolyte demonstrated 61% capacity retention after 100 cycles and superior rate capability owing to increased electrochemical stability.

Molecular Dynamics (MD) simulation is often used to study properties of various chemical interactions in domains such as drug development when executing real experimental studies are costly and/or unsafe. Studying trajectories generated from MD simulations provides detailed atomic level location data of every atom in the experiment. The analysis of this data leads to an atomic and molecular level understanding of interactions among the constituents of the system-of-interest, however, the data is extremely large and poses formidable storage and processing challenges in the analyses and querying of associated atom level motion trajectories. We take a first step towards applying domain-specific generalization techniques for trajectory compression algorithms towards reducing the storage requirements and speeding up the processing of within-distance queries over MD simulation data. We demonstrate that this generalization-aware compression, when applied to the dataset used in this case study yields significant efficiency improvements, without sacrificing the effectiveness of within-distance queries for threshold-based detection of molecular events of interest, such as the formation of hydrogen-bonds (H-Bonds).

Noble gas fission byproducts, such as Kr and Xe, are generated within nuclear power reactors are currently being discharged into the atmosphere. This practice has a major economic drawback because of the high value associated with some of these gases. The separations of these gases are economically prohibitive because of the high energy requirement associated with cryogenic distillation. Zeolites, nanoporous materials suitable for gas separation processes, have exhibited high selectivity for such separations. We have used nonequilibrium molecular dynamics (MD) to investigate the separation performance of DD3R framework zeolitic membrane. The effects of pressure, temperature, and pure vs. mixture gas feed conditions are studied in this work to understand and explain, at the molecular level, the mechanisms of these (Kr/Xe) separations. Our studies have shown that the DD3R membrane shows promise for high selectivity ratios of Kr over Xe. MD runs show agreement with experimental trends of the permeation of Kr/Xe pure and mixed gases using DD3R zeolite with high separation factor. Despite the absence of Xe complete permeation through the membrane because of MD timescale limitations, our results are sufficient to describe the mechanisms of these separations.