PACMAN: A Robust Partial Atomic Charge Predicter for Nanoporous Materials Based on Crystal Graph Convolution Networks

We report a fast and easy method (PACMAN) to assign partial atomic charges on metal-organic framework (MOF) and covalent-organic framework (COF) crystal structures based on graph convolution networks (GCNs) trained on >1.8 million high-fidelity partial atomic charge data obtained from the Quantum Metal-Organic Framework (QMOF) database. The developed model shows outstanding performance, achieving a mean absolute error (MAE) of 0.0055 e (test set performance) while maintaining consistency with DDEC6, Bader, and CM5 charges across diverse chemistry and topologies of MOFs and COFs. We find that the new method accurately assigns partial atomic charges for ion-containing nanoporous materials, which has not been possible in previous machine learning (ML) models. Grand canonical Monte Carlo (GCMC) simulation results for CO2 and N2 uptakes and the Widom particle insertion calculation for Henry's law constant of water results based on PACMAN and the original DDEC6 charges show excellent agreements compared to other ML models reported in the literature. The runtime analysis of the new method demonstrates that the partial atomic charges of MOF and COF structures with up to 500 atoms can be obtained in less than 10 s. An easy-to-use web interface has been developed to facilitate the adoption of the developed model.

Radiation-Induced Defects in Uranyl Trinitrate Solids

Actinides are inherently radioactive; thus, ionizing radiation is emitted by these elements can have profound effects on its surrounding chemical environment through the formation of free radical species. While previous work has noted that the presence of free radicals in the system impacts the redox state of the actinides, there is little atomistic understanding of how these metal cations interact with free radicals. Herein, we explore the effects of radiation (UV and γ) on three U(VI) trinitrate complexes, M[UO2(NO3)3] (where M=K+, Rb+, Cs+), and their respective nitrate salts in the solid state via electron paramagnetic resonance (EPR) and Raman spectroscopy paired with Density Functional Theory (DFT) methods. We find that the alkali salts form nitrate radicals under UV and γ irradiation, but also note the presence of additional degradation products. M[UO2(NO3)3] solids also form nitrate radicals and additional DFT calculations indicate the species corresponds to a change from the bidentate bound nitrate anion into a monodentate NO3 • radical. Computational studies also highlight the need to include the second sphere coordination environment around the [UO2(NO3)3]0,1 species to gain agreement between the experimental and predicted EPR signatures.

Multispecies-coadsorption-induced rapid preparation of graphene glass fiber fabric and applications in flexible pressure sensor

Direct chemical vapor deposition (CVD) growth of graphene on dielectric/insulating materials is a promising strategy for subsequent transfer-free applications of graphene. However, graphene growth on noncatalytic substrates is faced with thorny issues, especially the limited growth rate, which severely hinders mass production and practical applications. Herein, graphene glass fiber fabric (GGFF) is developed by graphene CVD growth on glass fiber fabric. Dichloromethane is applied as a carbon precursor to accelerate graphene growth, which has a low decomposition energy barrier, and more importantly, the produced high-electronegativity Cl radical can enhance adsorption of active carbon species by Cl-CH2 coadsorption and facilitate H detachment from graphene edges. Consequently, the growth rate is increased by ~3 orders of magnitude and carbon utilization by ~960-fold, compared with conventional methane precursor. The advantageous hierarchical conductive configuration of lightweight, flexible GGFF makes it an ultrasensitive pressure sensor for human motion and physiological monitoring, such as pulse and vocal signals.

Atomic-scale insights in the interplay of chemical composition and chirality in two-dimensional chiral perovskites

The incorporation of chiral molecules (A) in materials based on hybrid ABX3 perovskites has opened new paths to tune the optoelectronic properties of perovskites through the transfer of chirality to the inorganic BX framework. However, our atomistic understanding of the role of chemical BX composition in the magnitude of the chirality transfer is far from complete. In this study, we use density functional theory calculations and the experimental Ruddlesden-Popper chiral (R-/S-NEA)2PbBr4 structure (R-/S-NEA = R-/S-1-(1-naphthyl)ethylammonium) to investigate the effects induced by chemical substitution of Pb by Ge or Sn and Br by Cl or I on the transfer of chirality and physical-chemical properties. We have observed that different enantiomers result in opposing orientations of octahedral tiltings within the inorganic framework, thus transferring chirality to the inorganic structure. The tilts are greater in perovskites based on Pb and decrease in the sequence of Cl to Br to I, as a consequence of the decrease in the halide electronegativity that weakens the interactions between X and the -N+H3 group of the NEA chiral cation. The chirality transfer is also evident in the Rashba-Dresselhaus effects on the electronic band structure, in which we found magnitudes directly correlated to the trends of octahedra tilting. The band offsets of substitutions B and X are predominantly influenced by their natural atomic energy levels, while organic molecules play a pivotal role in modulating the ionic potential and electron affinity in systems containing light atoms. The band gap values range from 1.91 up to 3.77 eV, with chirality and anion electronegativity providing significant tuning effects on whether the band gaps are direct or indirect.

Quantifying the Uncertainty of Force Field Selection on Adsorption Predictions in MOFs

Comparisons between simulated and experimental adsorption isotherms in MOFs are fraught with challenges. On the experimental side, there is significant variation between isotherms measured on the same system, with a significant percentage (∼20%) of published data being considered outliers. On the simulation side, force fields are often chosen "off-the-shelf" with little or no validation. The effect of this choice on the reliability of simulated adsorption predictions has not yet been rigorously quantified. In this work, we fill this gap by systematically quantifying the uncertainty arising from force field selection on adsorption isotherm predictions. We choose methane adsorption, where electrostatic interactions are negligible, to independently study the effect of the framework Lennard-Jones parameters on a series of prototypical materials that represent the most widely studied MOF "families". Using this information, we compute an adsorption "consensus isotherm" from simulations, including a quantification of uncertainty, and compare it against a manually curated set of experimental data from the literature. By considering many experimental isotherms measured by different groups and eliminating outliers in the data using statistical analysis, we conduct a rigorous comparison that avoids the pitfalls of the standard approach of comparing simulation predictions to a single experimental data set. Our results show that (1) the uncertainty in simulated isotherms can be as large as 15% and (2) standard force fields can provide reliable predictions for some systems but can fail dramatically for others, highlighting systematic shortcomings in those models. Based on this, we offer recommendations for future simulation studies of adsorption, including high-throughput computational screening of MOFs.

Coordinate-Free and Low-Order Scaling Machine Learning Model for Atomic Partial Charge Prediction for Any Size of Molecules

The atomic partial charge is of great importance in many fields, such as chemistry and drug-target recognition. However, conventional quantum-based computing of atomic charges is relatively slow, limiting further applications of atomic charge analysis. With the help of machine learning methods, various kinds of models appear to speed up atomic charge calculations. However, there are still some concerning problems. Some models based on geometric coordinates require high-accuracy geometry optimization as a preprocess, while other models have a limitation on the size of input molecules that narrow the applications of the model. Here, we propose a machine learning atomic charge model based on a message-passing featurizer. This preprocessing featurizer can quickly extract atomic environment information from a molecule according to the connectivity inside the molecule. The resulting descriptor can be used with a neural network to quickly predict the atomic partial charge. The model is able to automatically adapt to any size of molecule while remaining efficient and achieves a root-mean-square error in the Hirshfeld charge prediction of 0.018e, with an overall time complexity of O(n2). Thus, this model could enlarge the range of applications of atomic partial charge to more fields and cases.

Unravelling CO Activation on Flat and Stepped Co Surfaces: A Molecular Orbital Analysis

Structure sensitivity in heterogeneous catalysis dictates the overall activity and selectivity of a catalyst whose origins lie in the atomic configurations of the active sites. We explored the influence of the active site geometry on the dissociation activity of CO by investigating the electronic structure of CO adsorbed on 12 different Co sites and correlating its electronic structure features to the corresponding C-O dissociation barrier. By including the electronic structure analyses of CO adsorbed on step-edge sites, we expand upon the current models that primarily pertain to flat sites. The most important descriptors for activation of the C-O bond are the decrease in electron density in CO's 1π orbital , the occupation of 2π anti-bonding orbitals and the redistribution of electrons in the 3σ orbital. The enhanced weakening of the C-O bond that occurs when CO adsorbs on sites with a step-edge motif as compared to flat sites is caused by a distancing of the 1π orbital with respect to Co. This distancing reduces the electron-electron repulsion with the Co d-band. These results deepen our understanding of the electronic phenomena that enable the breaking of a molecular bond on a metal surface.

pyCOFBuilder: A Python Package for Automated Creation of Covalent Organic Framework Models Based on the Reticular Approach

Covalent organic frameworks (COFs) have gained significant popularity in recent years due to their unique ability to provide a high surface area and customizable pore geometry and chemistry, making them an ideal choice for a wide range of applications. However, exploring COFs experimentally can be arduous and time-consuming due to their immense number of potential structures. As a result, computational high-throughput studies have become an attractive option. Nevertheless, generating COF structures can also be a challenging and time-consuming task. To address this challenge, here, we introduce the pyCOFBuilder, an open-source Python package designed to facilitate the generation of COF structures for computational studies. The pyCOFBuilder software provides an easy-to-use set of functionalities to generate COF structures following the reticular approach. In this paper, we describe the implementation, main features, and capabilities of the pyCOFBuilder, demonstrating its utility for generating COF structures with varying topologies and chemical properties. pyCOFBuilder is freely available on GitHub at https://github.com/lipelopesoliveira/pyCOFBuilder.

Ultralow Glassy Thermal Conductivity and Controllable, Promising Thermoelectric Properties in Crystalline o-CsCu5S3

We thoroughly investigated the anharmonic lattice dynamics and microscopic mechanisms of the thermal and electronic transport characteristics in orthorhombic o-CsCu5S3 at the atomic level. Taking into account the phonon energy shifts and the wave-like tunneling phonon channel, we predict an ultralow κL of 0.42 w/mK at 300 K with an extremely weak temperature dependence following ∼T-0.33. These findings agree well with experimental values along with the parallel to the Bridgman growth direction. The κL in o-CsCu5S3 is suppressed down to the amorphous limit, primarily due to the unconventional Cu-S bonding induced by the p-d hybridization antibonding state coupled with the stochastic oscillation of Cs atoms. The nonstandard temperature dependence of κL can be traced back to the critical or dominant role of wave-like tunneling of phonon contributions in thermal transport. Moreover, the p-d hybridization of Cu(3)-S bonding results in the formation of a valence band with "pudding-mold" and high-degeneracy valleys, ensuring highly efficient electron transport characteristics. By properly adjusting the carrier concentration, excellent thermoelectric performance is achieved with a maximum thermoelectric conversion efficiency of 18.4% observed at 800 K in p-type o-CsCu5S3. Our work not only elucidates the anomalous electronic and thermal transport behavior in the copper-based chalcogenide o-CsCu5S3 but also provides insights for manipulating its thermal and electronic properties for potential thermoelectric applications.

Chemically tuned intermediate band states in atomically thin CuxGeSe/SnS quantum material for photovoltaic applications

A new generation of quantum material derived from intercalating zerovalent atoms such as Cu into the intrinsic van der Waals gap at the interface of atomically thin two-dimensional GeSe/SnS heterostructure is designed, and their optoelectronic features are explored for next-generation photovoltaic applications. Advanced ab initio modeling reveals that many-body effects induce intermediate band (IB) states, with subband gaps (~0.78 and 1.26 electron volts) ideal for next-generation solar devices, which promise efficiency greater than the Shockley-Queisser limit of ~32%. The charge carriers across the heterojunction are both energetically and spontaneously spatially confined, reducing nonradiative recombination and boosting quantum efficiency. Using this IB material in a solar cell prototype enhances absorption and carrier generation in the near-infrared to visible light range. Tuning the active layer's thickness increases optical activity at wavelengths greater than 600 nm, achieving ~190% external quantum efficiency over a broad solar wavelength range, underscoring its potential in advanced photovoltaic technology.

Study of CHF3/CH2F2 Adsorption Separation in TIFSIX-2-Cu-i

Hydrofluorocarbons (HFCs) have important applications in different industries; however, they are environmentally unfriendly due to their high global warming potential (GWP). Hence, reclamation of used hydrofluorocarbons via energy-efficient adsorption-based separation will greatly contribute to reducing their impact on the environment. In particular, the separation of azeotropic refrigerants remains challenging, such as typical mixtures of CH2F2 (HFC-23) and CHF3 (HFC-32), due to a lack of adsorptive mechanisms. Metal-organic frameworks (MOFs) can provide a promising solution for the separation of CHF3-CH2F2 mixtures. In this study, the adsorption mechanism of CHF3-CH2F2 mixtures in TIFSIX-2-Cu-i was revealed at the microscopic level by combining static pure-component adsorption experiments, molecular simulations, and density-functional theory (DFT) calculations. The adsorption separation selectivity of CH2F2/CHF3 in TIFSIX-2-Cu-i is 3.17 at 3 bar under 308 K. The existence of similar TiF62- binding sites for CH2F2 or CHF3 was revealed in TIFSIX-2-Cu-i. Interactions between the fluorine atom of the framework and the hydrogen atom of the guest molecule were found to be responsible for determining the high adsorption separation selectivity of CH2F2/CHF3. This exploration is important for the design of highly selective adsorbents for the separation of azeotropic refrigerants.

Repulsive Lateral Interaction of Water Molecules at the Initial Stages of Adsorption in Microporous AlPO4-11 According to 27Al NMR and DFT

Lateral (adsorbate-adsorbate) interactions between adsorbed molecules affect various physical and chemical properties of microporous adsorbents and catalysts, influencing their functional properties. In this work, we studied the hydration of microporous AlPO4-11 aluminophosphate, which has an unusually ordered structure upon adsorption of water vapor, and according to 27Al NMR data, only tetrahedrally or octahedrally coordinated Al sites are present in the AlPO4-11. These 27Al NMR data are consistent with the results of density functional theory (DFT) calculations of hydrated AlPO4-11, which revealed the presence of a strong repulsive lateral interaction at the initial stage of adsorption, suppressing the adsorption of water on neighboring (separated by one -O-P-O- bridge) Al crystallographic sites. As a result, of all the different aluminum sites, only half of the Al1 sites adsorb two water molecules and acquire octahedral coordination.

Predicted Separation of Acid Gases from Gas Mixtures by Functionalized Porous Aromatic Frameworks

The selective adsorption of target acid gas molecules from binary gas mixtures by porous aromatic frameworks (PAFs) with two identical functional groups per aromatic ring (PAF-R2) was computationally investigated using grand canonical Monte Carlo simulations. PAF-R2 adsorption was considered for three binary mixtures of small molecular concentrations of acid gas and abundant nitrogen gas (CO2/N2, SO2/N2, and H2S/N2). The results indicate that additional functional groups enhance acid gas loadings and selectivity, compared with pristine PAF and single-functionalized PAFs. Low pressures yield linearly increasing gas loadings and constant selectivity, while high pressures yield much higher adsorption and selectivity. In particular, SO2 loading and selectivity under high pressures are heavily influenced by the PAF's maximum adsorption limit, which can be linked back to the functional groups and their configuration. In summary, PAF-(3,5)-(COOH)2 (nomenclature of PAFs is provided in the Appendix in the Supporting Information) and many other PAF with the same two electron-withdrawing groups are predicted to have great acid gas adsorption and selectivity from gas mixtures, while PAF-(3,5)-(OH)2 (one of PAFs with two identical electron-donating groups) is predicted to have good adsorption and selectivity, especially under elevated pressures. The results of this work can provide insights into various types of PAFs with great selective adsorption ability and their corresponding conditions. The simulation procedures and results may inspire the exploration and screening of other types of PAFs or porous materials, for acid gas absorption.

When Polymorphism in Metal-Organic Frameworks Enables Water Sorption Profile Tunability for Enhancing Heat Allocation and Water Harvesting Performance

The development of thermally driven water-sorption-based technologies relies on high-performing water vapor adsorbents. Here, polymorphism in Al-metal-organic frameworks is disclosed as a new strategy to tune the hydrophilicity of MOFs. This involves the formation of MOFs built from chains of either trans- or cis- µ-OH-connected corner-sharing AlO4(OH)2 octahedra. Specifically, [Al(OH)(muc)] or MIP-211, is made of trans, trans-muconate linkers, and cis-µ-OH-connected corner-sharing AlO4(OH)2 octahedra giving a 3D network with sinusoidal channels. The polymorph MIL-53-muc has a tiny change in the chain structure that results in a shift of the step position of the water isotherm from P/P0 ≈ 0.5 in MIL-53-muc, to P/P0 ≈ 0.3 in MIP-211. Solid-state NMR and Grand Canonical Monte Carlo reveal that the adsorption occurs initially between two hydroxyl groups of the chains, favored by the cis-positioning in MIP-211, resulting in a more hydrophilic behavior. Finally, theoretical evaluations show that MIP-211 would allow achieving a coefficient of performance for cooling (COPc) of 0.63 with an ultralow driving temperature of 60 °C, outperforming benchmark sorbents for small temperature lifts. Combined with its high stability, easy regeneration, huge water uptake capacity, green synthesis, MIP-211 is among the best adsorbents for adsorption-driven air conditioning and water harvesting from the air.

High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures

In this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10 Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.

Synthesis, characterization, and density functional theory investigation of (CH6N3)2[NpO2Cl3] and Rb[NpO2Cl2(H2O)] chain structures

The actinyl tetrachloro complex [An(V/VI)O2Cl4]2-/3- tends to form discrete molecular units in both solution and solid state materials, but related aquachloro complexes have been observed as both discrete coordination compounds and 1-D chain topologies. Subtle differences in the inner sphere coordination significantly influence the formation of structural topologies in the actinyl chloride system, but the exact reasoning for these variations has not been delineated. In the current study, we present the synthesis, structural characterization, and vibrational analysis of two 1-D neptunyl(V) chain compounds: (CH6N3)2[NpO2Cl3] (Np-Gua) and Rb[NpO2Cl2(H2O)] (Np-Rb). Bonding and non-covalent interactions (NCIs) in the systems were evaluated using periodic Density Functional Theory (DFT) to link these properties to related phases. We observed ∼6.5% and ∼3.9% weakening of NpO bonds in Np-Gua and Np-Rb compared to the reference Cs3[NpO2Cl4]. NCI analysis distinguished specific assembly modes, where Np-Gua was connected via hydrogen bonding (N-H⋯Cleq and N-H⋯Oyl) and Np-Rb contained both cation interactions (Rb+⋯Oyl and Rb+⋯Cleq) and hydrogen bonding (Oeq-H⋯Oyl) networks. Thermodynamically viable formation pathways for both compounds were explored using DFT methodology. The [NpO2Cl4](aq)3- and [NpO2Cl3(H2O)](aq)2- substructures were identified as precursors to Np-Gua and [NpO2Cl3(H2O)](aq)2- and [NpO2Cl2(H2O)2](aq)- were isolated as the primary building units of Np-Rb. Finally, we utilized DFT to analyze the vibrational modes for Np-Gua and Np-Rb, where we found evidence of the NpO bond weakening within the Np(V) chain structures compared to [NpO2Cl4]3-.

Hierarchical Computational Screening of Quantum Metal-Organic Framework Database to Identify Metal-Organic Frameworks for Volatile Organic-Compound Capture from Air

The design and discovery of novel porous materials that can efficiently capture volatile organic compounds (VOCs) from air are critical to address one of the most important challenges of our world, air pollution. In this work, we studied a recently introduced metal-organic framework (MOF) database, namely, quantum MOF (QMOF) database, to unlock the potential of both experimentally synthesized and hypothetically generated structures for adsorption-based n-butane (C4H10) capture from air. Configurational Bias Monte Carlo (CBMC) simulations were used to study the adsorption of a quaternary gas mixture of N2, O2, Ar, and C4H10 in QMOFs for two different processes, pressure swing adsorption (PSA) and vacuum-swing adsorption (VSA). Several adsorbent performance evaluation metrics, such as C4H10 selectivity, working capacity, the adsorbent performance score, and percent regenerability, were used to identify the best adsorbent candidates, which were then further studied by molecular simulations for C4H10 capture from a more realistic seven-component air mixture consisting of N2, O2, Ar, C4H10, C3H8, C3H6, and C2H6. Results showed that the top five QMOFs have C4H10 selectivities between 6.3 × 103 and 9 × 103 (3.8 × 103 and 5 × 103) at 1 bar (10 bar). Detailed analysis of the structure-performance relations showed that low/mediocre porosity (0.4-0.6) and narrow pore sizes (6-9 Å) of QMOFs lead to high C4H10 selectivities. Radial distribution function analyses of the top materials revealed that C4H10 molecules tend to confine close to the organic parts of MOFs. Our results provided the first information in the literature about the VOC capture potential of a large variety and number of MOFs, which will be useful to direct the experimental efforts to the most promising adsorbent materials for C4H10 capture from air.

Understanding Carbon Monoxide Binding and Interactions in M-MOF-74 (M = Mg, Mn, Ni, Zn)

Small molecules may adsorb strongly in metal-organic frameworks (MOFs) through interactions with under-coordinated open metal sites (OMS) that often exist within these structures. Among adsorbates, CO is attractive to study both for its relevance in energy-related applications and for its ability to engage in both σ-donation and π-backbonding interactions with the OMS in MOFs. Concomitant with strong adsorption, structural changes arise due to modifications of the electronic structure of both the adsorbate and adsorbent. These structural changes affect the separation performance of materials, and accurately capturing these changes and the resulting energetics is critical for accurate predictive modeling of adsorption. Traditional approaches to modeling using classical force fields typically do not capture or account for changes at the electronic level. To characterize the structural and energetic effects of the local structural changes, we employed density functional theory (DFT) to study CO adsorption in M-MOF-74s. M-MOF-74s feature OMS at which CO is known to adsorb strongly and can be synthesized with a variety of divalent metal cations with distinct performance in adsorption. We considered M-MOF-74s with a range of metals of varied d-band occupations (Mg (3d0), Mn (3d5), Ni (3d8), and Zn (3d10)) with various structural constraints ranging from geometrically constrained adsorbent and adsorbate ions to fully optimized geometries to deconvolute the relative contributions of various structural effects to the adsorption energetics and binding distances observed. Our data indicate that the most significant structural changes during adsorption correlate with the greatest π-backbonding behaviors and commensurately result in a sizable binding energy change observed for CO adsorption. The insights built from this work are relevant to two longstanding research challenges within the MOF community: rational design of materials for separations and the design of force fields capable of accurately modeling adsorption.

Atomistic-Level Effects of Noncovalent Interactions and Crystalline Packing for Organic Material Structural Integrity upon Exposure to Gamma Radiation

Developing an atomistic understanding of ionizing radiation induced changes to organic materials is necessary for intentional design of greener and more sustainable materials for radiation shielding and detection. Cocrystals are promising for these purposes, but a detailed understanding of how the specific intermolecular interactions within the lattice upon exposure to radiation affect the structural stability of the organic crystalline material is unknown. This study evaluates atomistic-level effects of γ radiation on both single- and multicomponent organic crystalline materials and how specific noncovalent interactions and packing within the crystalline lattice enhance structural stability. Dose studies were performed on all crystalline systems and evaluated via experimental and computational methods. Changes in crystallinity were evaluated by p-XRD and free radical formation was analyzed via EPR spectroscopy. Type of intermolecular interactions and packing within the crystal lattice was delineated and related to the specific free radical species formed and the structural integrity of each material. Periodic DFT and HOMO-LUMO surface mapping calculations provided atomistic-level identifications of the most probable sites for the radicals formed upon exposure to γ radiation and relate intermolecular interactions and molecular packing within the crystalline lattice to experimental results.

Enhanced CO2 capture in partially interpenetrated MOFs: Synergistic effects from functional group, pore size, and steric-hindrance

Excessive CO2 emissions have contributed to global environmental issues, driving the development of CO2 capture adsorbents. Among various candidates, metal-organic frameworks (MOFs) are considered the most promising due to their unique microporous structure. Herein, a series of partially interpenetrated MOFs named UPC-XX were built to investigate the continuous enhancement in CO2 capture performance via synergistic effects from functional group, pore size, and steric-hindrance using theoretical calculations. It's showed that the introduction of functional groups improved the structure polarity and created more adsorption sites, thus, enhanced CO2 capture capacity. The pore size modification augments the exposure of adsorption sites to mitigate the negative impact of pore space and surface area reduction caused by the introduction of functional groups, thereby further increasing the CO2 capture capacity. The steric-hindrance effect optimized the adsorption sites distribution, which hasn't been considered in the previous two regulation strategies, thus, further increased the CO2 capture capacity. The results underscore UPC-MOFs as outstanding adsorbent materials, among the UPC-MOFs, UPC-OSO3-steric exhibited the highest CO2 capture capacity of 12.69 mmol/g with selectivities of 1142.41 (CO2 over N2) and 507.42 (CO2 over CH4) at 1.0 bar, 298 K. And the synergistic effect mechanisms of functional group, structure size, and steric hindrance were elucidated through theoretical calculations analyzing pore characteristics, gas distribution, isosteric heat, and van der Waals/Coulomb interactions.

Three-Dimensional Noncovalent Interaction Network within [NpO2Cl4]2- Coordination Compounds: Influence on Thermochemical and Vibrational Properties

Noncovalent interactions (NCIs) can influence the stability and chemical properties of pentavalent and hexavalent actinyl (AnO2+/2+) compounds. In this work, the impact of NCIs (actinyl-hydrogen and actinyl-cation interactions) on the enthalpy of formation (ΔHf) and vibrational features was evaluated using Np(VI) tetrachloro compounds as the model system. We calculated the ΔHf values of these solid-state compounds through density functional theory+ thermodynamics (DFT+ T) and validated the results against experimental ΔHf values obtained through isothermal acid calorimetry. Three structural descriptors were evaluated to develop predictors for ΔHf, finding a strong link between ΔHf and hydrogen bond energy (EHtotal) for neptunyl-hydrogen interactions and total electrostatic attraction energy (Eelectrostatictotal) for neptunyl-cation interactions. Finally, we used Raman spectroscopy together with bond order analysis to probe Np=O bond perturbation due to NCIs. Our results showed a strong correlation between the degree of NCIs by axial oxygen and red-shifting of Np=O symmetrical stretch (ν1) wavenumbers and quantitatively demonstrated that NCIs can weaken the Np=O bond. These properties were then compared to those of related U(VI) and Np(V) phases to evaluate the effects of subtle differences in the NCIs and overall properties. In general, the outcomes of our study demonstrated the role of NCIs in stabilizing actinyl solid materials, which consequently governs their thermochemical behaviors and vibrational signatures.

Synthesis, Characterization, and Density Functional Theory Investigation of the Solid-State [UO2Cl4(H2O)]2- Complex

A significant number of solid-state [UO2Cl4]2- coordination compounds have been synthesized and structurally characterized. Yet, despite their purposive relative abundance in aqueous solutions, characterization of aquachlorouranium(VI) complexes remain rare. In the current study, a solid-state uranyl aqua chloro complex ((C4H12N2)2[UO2Cl4(H2O)]Cl2) was synthesized using piperazinium as a charge-balancing ligand, and the structure was determined using single-crystal X-ray diffraction. Using periodic density functional theory, the electronic structure of the [UO2Cl4(H2O)]2- complex was compared to [UO2Cl4]2- to uncover the strengthening of the U═O bond in [UO2Cl4(H2O)]2-. Changes in the strength of the U═O bond were validated further with Raman and IR spectroscopy, where uranyl symmetrical (ν1) and asymmetrical (ν3) stretches were blue-shifted compared to the reference [UO2Cl4]2- complex. Furthermore, the formation energy of the solid-state (C4H12N2)2[UO2Cl4(H2O)]Cl2 complex was calculated to be -287.60 ± 1.75 kJ mol-1 using isothermal acid calorimetry. The demonstrated higher stability relative to the related [UO2Cl4]2- complex was related to the relative stoichiometry of the counterions.

The influence of force fields on the structure and dynamics of water confined in ZIF-8 from atomistic simulations

The complexity of modeling flexible crystals, such as ZIF-8, mainly stems from the handling of intramolecular interactions. Numerous force fields have been proposed in the literature to describe the interactions between atoms in ZIF-8. We employ seven force fields to examine the structure and dynamic behavior of water molecules confined in ZIF-8, with the aim of investigating the impact of force fields on simulation results. Various structural characterization methods consistently indicate that the choice of different force fields has quantitative effects but no qualitative effects on the structural characteristics of confined water. Additionally, the force fields do not impact the qualitative description of the diffusion mechanism. Both mean-square displacement and van Hove autocorrelation function reveal two characteristic movements of water molecules diffusing in ZIF-8: a short-time intra-cavity hopping process and a long-time inter-cavity hopping process. However, the framework flexibility is found to play a crucial role in determining the order of spatial arrangement and local structure, self-diffusion coefficient and reorientational dynamics of confined water. Specifically, the DREIDING force field gives rise to an unrealistic stiff framework, enhancing the order of spatial arrangement and diminishing the local ordered structure of confined water. Meanwhile, it results in much slower translational and reorientational dynamics. Hence, the general DREIDING force field cannot be considered for providing a quantitative description of the water structure and dynamics.

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non-Covalent Interactions in a Uranyl Tetrahalide Model System

Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO2 X4 ]2- (X=Cl- and Br- ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔHf ) and observed vibrational signatures. ΔHf values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [E H , norm total ${{E}_{H,{\rm { norm}}}^{{\rm { total}}}}$ ]) were assessed as descriptors for trends in ΔHf . Results demonstrated a strong correlation betweenE H , norm total ${E_{{\rm{H}},{\rm{norm}}}^{{\rm{total}}} }$ and ΔHf , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid-state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid-state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red-shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular-level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

The Influence of Ni Addition in the Mechanism of CO2 Electroreduction on Cu Crystals-Mechanistic Insight from DFT Simulations

We present a DFT analysis of the role of the Cu-Ni synergistic effect for the CO₂ reduction to C₂H₄, in comparison to the pure Cu catalyst. The analysis is focused on the thermodynamic stability of reactive intermediates along the proposed pathway of C₂ species formation. We have observed that the potential needed for the reaction decreases with the addition of Ni in the investigated model. In addition, we have observed the differences in the preferred pathway based on the significant differences in stability of the reactive intermediates depending on th Cu:Ni ratio. The results suggest that despite the fact the Cu surface is always exposed, and it is the only one that is able to directly interact with the intermediates, the presence of the Ni in the underlying sections of the crystal is significant enough to change the mechanism of the reaction.

Soft corrugated channel with synergistic exclusive discrimination gating for CO2 recognition in gas mixture

Developing artificial porous systems with high molecular recognition performance is critical but very challenging to achieve selective uptake of a particular component from a mixture of many similar species, regardless of the size and affinity of these competing species. A porous platform that integrates multiple recognition mechanisms working cooperatively for highly efficient guest identification is desired. Here, we designed a flexible porous coordination polymer (PCP) and realised a corrugated channel system that cooperatively responds to only target gas molecules by taking advantage of its stereochemical shape, location of binding sites, and structural softness. The binding sites and structural deformation act synergistically, exhibiting exclusive discrimination gating (EDG) effect for selective gate-opening adsorption of CO₂ over nine similar gas molecules, including N₂, CH₄, CO, O₂, H₂, Ar, C₂H₆, and even higher-affinity gases such as C₂H₂ and C₂H₄. Combining in-situ crystallographic experiments with theoretical studies, it is clear that this unparalleled ability to decipher the CO₂ molecule is achieved through the coordination of framework dynamics, guest diffusion, and interaction energetics. Furthermore, the gas co-adsorption and breakthrough separation performance render the obtained PCP an efficient adsorbent for CO₂ capture from various gas mixtures.

Preferential perovskite surface-termination induced high piezoresponse in lead-free in situ fabricated Cs3Bi2Br9-PVDF nanocomposites promotes biomechanical energy harvesting

Lead-free halide perovskites have gained immense popularity in photovoltaic and energy harvesting applications because of their excellent optical and electrical attributes with minimal toxicity. We synthesized composite films of lead-free Cs₃Bi₂Br₉ perovskite embedded in the polyvinylidene fluoride (PVDF) matrix and have investigated their piezoelectric energy harvesting. Five PVDF@Cs₃Bi₂Br₉ composite films were fabricated with varying wt% of the perovskite in the PVDF. The composite with a 4 wt% of the perovskite shows 85% activation of the electroactive β-phase of PVDF. Additionally, this composite exhibits a maximum polarisation of ∼0.1 μC cm^-2 and the best energy storage density of ∼0.8 mJ cm^-3 at an applied field of ∼16 kV cm^-1 among all the synthesized composites. A nanogenerator fabricated using 4 wt% loading in the composite film produced an instantaneous output voltage of ∼40 V, an instantaneous current of ∼4.1 μA, and a power density of ∼17.8 μW cm^-2 across 10 MΩ resistance when repeatedly hammered by the human hand. The nanogenerator is further employed to light up several LEDs and to charge capacitors with a small active area demonstrating significant promise for prospective wearables and portable devices and paving the way for high-performance nanogenerators using lead-free halide perovskites. Density functional theory calculations were performed to understand the interaction of the electroactive phase of the PVDF with different perovskite surface terminations to unravel the various interaction mechanisms and their ensuing charge transfer properties.

Machine Learning Electron Density Prediction Using Weighted Smooth Overlap of Atomic Positions

Having access to accurate electron densities in chemical systems, especially for dynamical systems involving chemical reactions, ion transport, and other charge transfer processes, is crucial for numerous applications in materials chemistry. Traditional methods for computationally predicting electron density data for such systems include quantum mechanical (QM) techniques, such as density functional theory. However, poor scaling of these QM methods restricts their use to relatively small system sizes and short dynamic time scales. To overcome this limitation, we have developed a deep neural network machine learning formalism, which we call deep charge density prediction (DeepCDP), for predicting charge densities by only using atomic positions for molecules and condensed phase (periodic) systems. Our method uses the weighted smooth overlap of atomic positions to fingerprint environments on a grid-point basis and map it to electron density data generated from QM simulations. We trained models for bulk systems of copper, LiF, and silicon; for a molecular system, water; and for two-dimensional charged and uncharged systems, hydroxyl-functionalized graphane, with and without an added proton. We showed that DeepCDP achieves prediction R2 values greater than 0.99 and mean squared error values on the order of 10-5e2 Å-6 for most systems. DeepCDP scales linearly with system size, is highly parallelizable, and is capable of accurately predicting the excess charge in protonated hydroxyl-functionalized graphane. We demonstrate how DeepCDP can be used to accurately track the location of charges (protons) by computing electron densities at a few selected grid points in the materials, thus significantly reducing the computational cost. We also show that our models can be transferable, allowing prediction of electron densities for systems on which it has not been trained but that contain a subset of atomic species on which it has been trained. Our approach can be used to develop models that span different chemical systems and train them for the study of large-scale charge transport and chemical reactions.

Calculation of Self, Corrected, and Transport Diffusivities of Isopropyl Alcohol in UiO-66

The UiO-6x family of metal-organic frameworks has been extensively studied for applications in chemical warfare agent (CWA) capture and destruction. An understanding of intrinsic transport phenomena, such as diffusion, is key to understanding experimental results and designing effective materials for CWA capture. However, the relatively large size of CWAs and their simulants makes diffusion in the small-pored pristine UiO-66 very slow and hence impractical to study directly with direct molecular simulations because of the time scales required. We used isopropanol (IPA) as a surrogate for CWAs to investigate the fundamental diffusion mechanisms of a polar molecule within pristine UiO-66. IPA can form hydrogen bonds with the μ3-OH groups bound to the metal oxide clusters in UiO-66, similar to some CWAs, and can be studied by direct molecular dynamics simulations. We report self, corrected, and transport diffusivities of IPA in pristine UiO-66 as a function of loading. Our calculations highlight the importance of the accurate modeling of the hydrogen bonding interactions on diffusivities, with about an order of magnitude decrease in diffusion coefficients when the hydrogen bonding between IPA and the μ3-OH groups is included. We found that a fraction of the IPA molecules have very low mobility during the course of a simulation, while a small fraction are highly mobile, exhibiting mean square displacements far greater than the ensemble average.

High-Throughput Screening of the CoRE-MOF-2019 Database for CO2 Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy

Stabilizing the escalating CO₂ levels in the atmosphere is a grand challenge in view of the increasing global demand for energy, the majority of which currently comes from the burning of fossil fuels. Capturing CO₂ from point source emissions using solid adsorbents may play a part in meeting this challenge, and metal-organic frameworks (MOFs) are considered to be a promising class of materials for this purpose. It is important to consider the co-adsorption of water when designing materials for CO₂ capture from post-combustion flue gases. Computational high-throughput screening (HTS) is a powerful tool to identify top-performing candidates for a particular application from a large material database. Using a multi-scale modeling strategy that includes a machine learning model, density functional theory (DFT) calculations, force field (FF) optimization, and grand canonical Monte Carlo (GCMC) simulations, we carried out a systematic computational HTS of the all-solvent-removed version of the computation-ready experimental metal-organic framework (CoRE-MOF-2019) database for selective adsorption of CO₂ from a wet flue gas mixture. After initial screening based on the pore diameters, a total of 3703 unique MOFs from the database were considered for screening based on the FF interaction energies of CO₂, N₂, and H₂O molecules with the MOFs. MOFs showing stronger interactions with CO₂ compared to that with H₂O and N₂ were considered for the next level of screening based on the interaction energies calculated from DFT. CO₂-selective MOFs from DFT screening were further screened using two-component (CO₂ and N₂) and finally three-component (CO₂, N₂, and H₂O) GCMC simulations to predict the CO₂ capacity and CO₂/N₂ selectivity. Our screening study identified MOFs that show selective CO₂ adsorption under wet flue gas conditions with significant CO₂ uptake capacity and CO₂/N₂ selectivity in the presence of water vapor. We also analyzed the nature of pore confinements responsible for the observed CO₂ selectivity.

Theoretical investigation of CO2 capture in the MIL-88 series: effects of organic linker modification

CO₂ capture is a crucial strategy to mitigate global warming and protect a sustainable environment. Metal-organic frameworks with large surface area, high flexibility, and reversible adsorption and desorption of gases are good candidates for CO₂ capture. Among the synthesized metal-organic frameworks, the MIL-88 series has attracted our attention due to their excellent stability. However, a systematic investigation of CO₂ capture in the MIL-88 series with different organic linkers is not available. Therefore, we clarified the topic via two sections: (1) elucidate physical insights into the CO₂@MIL-88 interaction by van der Waals-dispersion correction density functional theory calculations, and (2) quantitatively study the CO₂ capture capacity by grand canonical Monte Carlo simulations. We found that the 1π_g, 2σ_u/1π_u, and 2σ_g peaks of the CO₂ molecule and the C and O p orbitals of the MIL-88 series are the predominant contributors to the CO₂@MIL-88 interaction. The MIL-88 series, i.e., MIL-88A, B, C, and D, has the same metal oxide node but different organic linkers: fumarate (MIL-88A), 1,4-benzene-dicarboxylate (MIL-88B), 2,6-naphthalene-dicarboxylate (MIL-88C), and 4,4'-biphenyl-dicarboxylate (MIL-88D). The results exhibited that fumarate should be the best replacement for both the gravimetric and volumetric CO₂ uptakes. We also pointed out a proportional relationship between the capture capacities with electronic properties and other parameters.

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

CRAFTED: An exploratory database of simulated adsorption isotherms of metal-organic frameworks

Grand Canonical Monte Carlo is an important method for performing molecular-level simulations and assisting the study and development of nanoporous materials for gas capture applications. These simulations are based on the use of force fields and partial charges to model the interaction between the adsorbent molecules and the solid framework. The choice of the force field parameters and partial charges can significantly impact the results obtained, however, there are very few databases available to support a comprehensive impact evaluation. Here, we present a database of simulations of CO₂ and N₂ adsorption isotherms on 690 metal-organic frameworks taken from the CoRE MOF 2014 database. We performed simulations with two force fields (UFF and DREIDING), six partial charge schemes (no charges, Qeq, EQeq, MPNN, PACMOF, and DDEC), and three temperatures (273, 298, 323 K). The resulting isotherms compose the Charge-dependent, Reproducible, Accessible, Forcefield-dependent, and Temperature-dependent Exploratory Database (CRAFTED) of adsorption isotherms.

Selective sorption of oxygen and nitrous oxide by an electron donor-incorporated flexible coordination network

Incorporating strong electron donor functionality into flexible coordination networks is intriguing for sorption applications due to a built-in mechanism for electron-withdrawing guests. Here we report a 2D flexible porous coordination network, [Ni₂(4,4'-bipyridine)(VTTF)₂]n(1) (where H₂VTTF = 2,2'-[1,2-bis(4-benzoic acid)-1,2ethanediylidene]bis-1,3-benzodithiole), which exhibits large structural deformation from the as-synthesized or open phase (1α) into the closed phase (1β) after guest removal, as demonstrated by X-ray and electron diffraction. Interestingly, upon exposure to electron-withdrawing species, 1β reversibly undergoes guest accommodation transitions; 1α⊃O₂ (90 K) and 1α⊃N₂O (185 K). Moreover, the 1β phase showed exclusive O₂ sorption over other gases (N₂, Ar, and CO) at 120 K. The phase transformations between the 1α and 1β phases under these gases were carefully investigated by in-situ X-ray diffraction, in-situ spectroscopic studies, and DFT calculations, validating that the unusual sorption was attributed to the combination of flexible frameworks and VTTF (electron-donor) that induces strong interactions with electron-withdrawing species.

Understanding the Reactivity of Supported Late Transition Metals on a Bare Anatase (101) Surface: A Periodic Conceptual DFT Investigation

The rapidly growing interest for new heterogeneous catalytic systems providing high atomic efficiency along with high stability and reactivity triggered an impressive progress in the field of single-atom catalysis. Nevertheless, unravelling the factors governing the interaction strength between the support and the adsorbed metal atoms remains a major challenge. Based on periodic density functional theory (DFT) calculations, this paper provides insight into the adsorption of single late transition metals on a defect-free anatase surface. The obtained adsorption energies fluctuate, with the exception of Pd, between -3.11 and -3.80 eV and are indicative of a strong interaction. Depending on the considered transition metal, we could attribute the strength of this interaction with the support to i) an electron transfer towards anatase (Ru, Rh, Ni), ii) s-d orbital hybridisation effects (Pt), or iii) a synergistic effect between both factors (Fe, Co, Os, Ir). The driving forces behind the adsorption were also found to be strongly related to Klechkowsky's rule for orbital filling. In contrast, the deviating behaviour of Pd is most likely associated with the lower dissociation enthalpy of the Pd-O bond. Additionally, the reactivity of these systems was evaluated using the Fermi weighted density of states approach. The resulting softness values can be clearly related to the electron configuration of the catalytic systems as well as with the net charge on the transition metal. Finally, these indices were used to construct a model that predicts the adsorption strength of CO on these anatase-supported d-metal atoms. The values obtained from this regression model show, within a 95 % probability interval, a correlation of 84 % with the explicitly calculated CO adsorption energies.

Carbon Dioxide Reduction on Transition Metal Dichalcogenides with Ni and Cu Edge Doping: A Density-Functional Theory Study

Transition-metal dichalcogenides (TMDs) have promising properties for their use as catalysts of CO₂ reduction to methane via the Sabatier reaction. In this article we use density-functional theory calculations to gain insight into the energetics of this reaction for Mo/W-based and S/Se-based TMDs with non-, Ni- and Cu-doping. We show that sulfur-based TMDs with Ni/Cu doping exhibit better indicators for catalytic performance of the CO₂ reduction reaction than non-doped and doped TMDs without active sites. In addition, the role of the transition metal was found to a much smaller influence in the reaction than the role of the chalcogen and dopant atoms, which influence the bonding strength and type, respectively.

Giant Tunability of Charge Transport in 2D Inorganic Molecular Crystals by Pressure Engineering

The unique intermolecular van der Waals force in emerging two-dimensional inorganic molecular crystals (2DIMCs) endows them with highly tunable structures and properties upon applying external stimuli. Using high pressure to modulate the intermolecular bonding, here we reveal the highly tunable charge transport behavior in 2DIMCs for the first time, from an insulator to a semiconductor. As pressure increases, 2D α-Sb₂ O₃ molecular crystal undergoes three isostructural transitions, and the intermolecular bonding enhances gradually, which results in a considerably decreased band gap by 25 % and a greatly enhanced charge transport. Impressively, the in situ resistivity measurement of the α-Sb₂ O₃ flake shows a sharp drop by 5 orders of magnitude in 0-3.2 GPa. This work sheds new light on the manipulation of charge transport in 2DIMCs and is of great significance for promoting the fundamental understanding and potential applications of 2DIMCs in advanced modern technologies.

Free-atom-like d states beyond the dilute limit of single-atom alloys

Through a data-mining and high-throughput density functional theory approach, we identify a diverse range of metallic compounds that are predicted to have transition metals with "free-atom-like" d states that are highly localized in terms of their energetic distribution. Design principles that favor the formation of localized d states are uncovered, among which we note that site isolation is often necessary but that the dilute limit, as in most single-atom alloys, is not a pre-requisite. Additionally, the majority of localized d state transition metals identified from the computational screening study exhibit partial anionic character due to charge transfer from neighboring metal species. Using CO as a representative probe molecule, we show that localized d states for Rh, Ir, Pd, and Pt tend to reduce the binding strength of CO compared to their pure elemental analogues, whereas this does not occur as consistently for the Cu binding sites. These trends are rationalized through the d-band model, which suggests that the significantly reduced d-band width results in an increased orthogonalization energy penalty upon CO chemisorption. With the multitude of inorganic solids that are predicted to have highly localized d states, the results of the screening study are likely to result in new avenues for heterogeneous catalyst design from an electronic structure perspective.

Berry Population Analysis: Atomic Charges from the Berry Curvature in a Magnetic Field

The Berry curvature is essential in Born-Oppenheimer molecular dynamics, describing the screening of the nuclei by the electrons in a magnetic field. Parts of the Berry curvature can be understood as the external magnetic field multiplied by an effective charge so that the resulting Berry force behaves like a Lorentz force during the simulations. Here, we investigate whether these effective charges can provide insight into the electronic structure of a given molecule or, in other words, whether we can perform a population analysis based on the Berry curvature. To develop our approach, we first rewrite the Berry curvature in terms of charges that partially capture the effective charges and their dependencies on the nuclear velocities. With these Berry charges and charge fluctuations, we then construct our population analysis yielding atomic charges and overlap populations. Calculations at the Hartree-Fock level reveal that the atomic charges are similar to those obtained from atomic polar tensors. However, since we additionally obtain an estimate for the fluctuations of the charges and a partitioning of the atomic charges into contributions from all atoms, we conclude that the Berry population analysis is a useful alternative tool to analyze the electronic structures of molecules.

Unexpected polarization properties of sub-nanosized magnesium clusters

The isotropic electrostatic polarizability (IEP) of sub-nanosized magnesium clusters Mg₂-Mg₃₂ was studied in an extensive set comprising 1237 structurally unique isomers. These isomers were found in the course of the global search for the potential energy surface minima of the magnesium clusters at the BP86/6-31G(d) level. The calculation of the polarizability at the same DFT level reveals an unexpected property of the IEP: the linear correlation between the polarizability of the most favorable isomers (and only them) and the cluster nuclearity n. Moreover, for each n, the most stable cluster isomer demonstrates nearly minimal IEP value among all found isomers of a given nuclearity. Surprisingly, these observed features are independent of the cluster structures which are quite different. We hypothesize that the energetic favorability of a cluster structure is related to their low polarizability. Apparently, the atoms forming the cluster tend to arrange themselves in such a way as to provide the most compact distribution of the cluster electron density. A possible explanation of the observed trends, their significance for cluster structure prediction, and the practical applications are discussed.

Discovery of Clustered-P1 Borophene and Its Application as the Lightest High-Performance Transistor

The two-dimensional network of boron atoms (borophene) has attracted attention for its ultralow molar mass and remarkable polymorphism. Synthesized polymorphs of borophene (striped, β₁₂, χ₃, and honeycomb), so far, are all found to be metallic. Employing a genetic algorithm-based structure searching technique, here we discover an allotrope, clustered-P1, which is located very close to the global energy minimum. Clustered-P1 exhibits a bulk silicon-like band gap (1.08 eV) with symmetric effective masses (∼0.2 m₀) for electrons and holes along the transport direction. Phonon dispersion and beyond room-temperature ab initio molecular dynamics studies further confirm its excellent dynamic and structural stability. Since two-dimensional semiconductors are promising silicon alternatives for complementary metal-oxide semiconductor (CMOS) technology extension, we further investigate the characteristics of clustered-P1-based transistors using self-consistent quantum transport models for channel lengths of 10-3 nm. The performance of these devices has been found to be balanced for p- and n-type transistors and meets the requirements of the International Roadmap for Devices and Systems (IRDS). Our study may aid in the experimental realization of the lightest high-performance transistor.

Predicting Frequency from the External Chemical Environment: OH Vibrations on Hydrated and Hydroxylated Surfaces

Robust correlation curves are essential to decipher structural information from IR-vibrational spectra. However, for surface-adsorbed water and hydroxides, few such correlations have been presented in the literature. In this paper, OH vibrational frequencies are correlated against 12 structural descriptors representing the quantum mechanical or geometrical environment, focusing on those external to the vibrating molecule. A nonbiased fitting procedure based on Gaussian process regression (GPR) was used alongside simple analytical functional forms. The training data consist of 217 structurally unique OH groups from 38 water/metal oxide interface systems for MgO, CaO and CeO₂, all optimized at the DFT level, and the fully anharmonic and uncoupled OH vibrational signatures were calculated. Among our results, we find the following: (i) The intermolecular R(H···O) hydrogen bond distance is particularly strong, indicating the primary cause of the frequency shift. (ii) Similarly, the electric field along the H-bond vector is also a good descriptor. (iii) Highly detailed machine learning descriptors (ACSF, SOAP) are less intuitive but were found to be more capable descriptors. (iv) Combinations of geometric and QM descriptors give the best predictions, supplying complementary information.

Dehydrogenation versus deprotonation of disaccharide molecules in vacuum: a thorough theoretical investigation

Dehydrogenation and deprotonation of sucrose and trehalose molecules in vacuum is theoretically studied by using ab initio calculations in the framework of the density functional theory. The differences in the structural, electronic, energetic and vibrational properties of dehydrogenated and deprotonated molecules are discussed, depending on the site from which the hydrogen atom or the proton has been removed. The dehydrogenated molecules are found to be stable, regardless of which hydrogen atom is removed. This contrasts with the instability of the deprotonated molecules, where break-ups or structural reorganizations of the molecule are observed in 20-30% of the cases, but only when the hydrogen atom whose proton is removed was bonded to a carbon atom. Considering the stability and possible rearrangements of the hydrogen network of the deprotonated/dehydrogenated molecule, the formation of additional hydrogen-bridge bonds compared with the nominal molecule appears to be more pronounced for the deprotonated molecules than for the dehydrogenated ones. Moreover, our calculations show that the hydrogen-transfer energy barriers are usually larger for the deprotonated molecules than for the dehydrogenated ones. Finally, compared with the nominal molecule, the vibrational frequency spectrum is shifted to lower frequencies for both the dehydrogenated and the deprotonated molecules.