Journal of Molecular Modeling最新文献

{"title":"Molecular dynamics simulations of thermal transport in metals using a two-temperature model.","authors":"B Baer, D G Walker","doi":"10.1007/s00894-025-06433-5","DOIUrl":"10.1007/s00894-025-06433-5","url":null,"abstract":"<p><strong>Context: </strong>In classical molecular dynamics, thermal transport via electrons is typically non-existent. Therefore, thermal property determination in metals or material systems that include metals is inaccessible. We have developed a two-temperature model for use with non-equilibrium molecular dynamics to predict thermal interface resistance across metal-metal and metal-insulator interfaces. Using LAMMPS and a modified module for the diffusion of thermal energy via electrons, we systematically examine the effects of including a second transport pathway through material systems. We found that inclusion of an electronic transport pathway reduces the phonon-only thermal conductivity because of electron-phonon scattering. Moreover, the presence of electrons eliminates temperature jumps at the boundary but still admits interface resistance, which is reduced in some cases by an order of magnitude.</p><p><strong>Method: </strong>We developed a module for LAMMPS that estimates thermal transport via the diffusion equation with a specified electron thermal conductivity. The electronic energy is transferred to/from the atomic system using velocity rescaling with appropriate momentum perturbation. The atomistic motion is governed by the NiU3-EAM potential.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"220"},"PeriodicalIF":2.5,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12296977/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A classification method for fluorescence emission spectra of anionic surfactants with few-shot learning.","authors":"Hanyang Ning, Miao Ma, Zhiwei Shi, Liping Ding","doi":"10.1007/s00894-025-06440-6","DOIUrl":"10.1007/s00894-025-06440-6","url":null,"abstract":"<p><strong>Context: </strong>The unregulated use of anionic surfactants poses significant environmental risks, necessitating methods for their rapid and accurate identification. While fluorescence spectroscopy is a powerful tool, its application faces a critical challenge: existing analytical strategies either rely on complex and costly sensor arrays to acquire rich data, or they apply traditional machine learning to simpler, single-spectrum data, which often requires pre-processing steps like PCA that risk information loss. Furthermore, standard deep learning approaches are often unsuitable due to the high cost and effort required to acquire the large datasets they need for training. To address this gap, we propose an end-to-end, few-shot learning method (CNN-PN) for the classification of anionic surfactant fluorescence emission spectra. Our approach leverages a one-dimensional convolutional neural network (1D-CNN) to automatically extract features from the full, raw spectrum, thus avoiding lossy pre-processing. It then employs a prototypical network to perform robust, similarity-based classification, a strategy highly effective for limited sample sizes. We validated our method on our FESS dataset (53 surfactant categories) and a public metal oxides dataset. In our experiments, the CNN-PN method consistently outperformed traditional techniques like LDA, SVM, and KNN. It achieved 76.36% accuracy when trained with only a single sample per class, 95.90% in a multi-sample scenario on our FESS dataset, and 84.86% on the public dataset. This work provides a powerful and data-efficient framework for spectral analysis, facilitating the development of more accessible and rapid fluorescence sensing technologies, particularly for applications where data collection is expensive or constrained.</p><p><strong>Methods: </strong>A few-shot learning classification method based on prototypical networks was employed. A one-dimensional convolutional neural network (1D-CNN) was utilized to extract spectral features from the full fluorescence emission spectra. Classification was then performed within the prototypical network framework using Euclidean distance as the similarity metric between features in the learned latent space. The Python programming language and the PyTorch library were used for all model implementations and data analysis.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"218"},"PeriodicalIF":2.5,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In depth first-principles investigation of phase stability, structural, vibrational, electronic, elastic, piezoelectric, and magnetic properties in vanadium-based janus dichalcogenide monolayer VBrSe.","authors":"Laichaoui Mahdi Mourad, Rami Mrad, Yuanping Chen, Shibing Chu","doi":"10.1007/s00894-025-06444-2","DOIUrl":"10.1007/s00894-025-06444-2","url":null,"abstract":"<p><strong>Context: </strong>This study presents a comprehensive first-principles investigation of the structural, electronic, vibrational, elastic, and piezoelectric properties of monolayer Janus VBrSe in both 2H and 1 T phases. The 1 T phase is found to be dynamically unstable, whereas the 2H-VBrSe phase is confirmed to be both energetically favorable and dynamically stable, indicating its feasibility for experimental synthesis. The 2H phase exhibits a direct band gap with pronounced strain sensitivity, significant out-of-plane piezoelectric response, and distinct Raman-active vibrational modes, facilitating phase identification. Micromagnetic simulations further reveal robust ferromagnetic ordering. These properties establish 2H-VBrSe as a multifunctional material suitable for next-generation applications in sensors, optoelectronics, flexible devices, and spintronic systems.</p><p><strong>Methods: </strong>Density functional theory (DFT) calculations were performed using the VASP package, incorporating spin-orbit coupling and van der Waals corrections to accurately capture the behavior of layered systems. Electronic structure and geometry were optimized using advanced exchange-correlation functionals to improve band gap accuracy. Phonon dispersion analyses confirmed dynamic stability, while elastic constants and piezoelectric coefficients were computed to assess mechanical and electromechanical performance. Ferromagnetic behavior was evaluated via micromagnetic simulations using MuMax3. The theoretical framework enables further exploration of temperature-dependent phenomena, such as thermal stability and dynamical response, through ab initio molecular dynamics.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"217"},"PeriodicalIF":2.5,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Noncovalent dyads of lanthanide nitride cluster fullerenes Ln₃N@C₈₀ and bisphthalocyanines LnPc₂: Insights from DFT calculations.","authors":"Lina M Bolivar-Pineda, Elena V Basiuk, Vladimir A Basiuk","doi":"10.1007/s00894-025-06415-7","DOIUrl":"10.1007/s00894-025-06415-7","url":null,"abstract":"<p><strong>Context: </strong>Lanthanide-based systems, such as nitride cluster fullerenes Ln₃N@C₈₀ and bipthalocyanines LnPc₂ (Pc = phthalocyanine ligand), are of interest for their magnetic, fluorescent and electronic properties. In this regard, we performed DFT characterization to investigate the changes in structure and electronic properties for noncovalently interacting lanthanide (Ln; where Ln = La, Ce, Gd and Lu) nitride cluster fullerenes and bisphthalocyanines to form Ln₃N@C₈₀ + LnPc₂ dyads. The optimized geometries, formation and frontier orbital energies, HOMO-LUMO plots, charge and spin of Ln and N(NCF) atoms, as well as spin density plots of the dyads were analyzed in comparison with those of isolated Ln₃N@C₈₀ and LnPc₂ components. In addition to LnPc₂ bending distortion, the noncovalent dyad formation alters the geometry of the encapsulated Ln₃N cluster, favoring more planar or pyramidal geometries, depending on the case. The HOMO and LUMO orbitals are found on bisphthalocyanines, being localized on the isoindole units, except for Ce₃N@C₈₀ + CePc₂ dyad, where the LUMO was found on the central metal of CePc₂. The HOMO-LUMO gap energy is lower for the dyads compared to isolated NCFs, being rather close to the gap energy of bisphthalocyanines. The changes in spin density distribution are evident in the dyads containing Ce and Gd atoms, contrary to their La and Lu-derived counterparts. The interaction of Ce₃N@C₈₀ and Gd₃N@C₈₀ with CePc₂ and GdPc₂, respectively, causes redistribution of the spin density, with changes in the orientation of spin-up and spin-down electrons in the encapsulated Ce₃N and Gd₃N clusters.</p><p><strong>Methods: </strong>The geometry optimization and electronic properties calculations based on density functional theory were performed using the DMol³ module of Material Studio 8.0 software package from Accelrys Inc. The computational parameters selected included the general gradient approximation functional PBE, combined with a long-range dispersion correction developed by Grimme (PBE-D2), the double numerical basis set (DN), equivalent to the 6-31G Pople-type basis set along with the DFT semiconductor pseudopotentials. To mitigate the self-consistent field convergence problems, the thermal smearing technique was applied, with a final very small value of 0.0001 Ha (equivalent to 31.6 K temperature), or Fermi orbital occupancy in some cases.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"216"},"PeriodicalIF":2.1,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12287152/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-fidelity neural network-based prediction of tensile strength of high-entropy alloy (FeNiCoCrCu) using molecular dynamics data.","authors":"Nazib E Elahi Khan Chowdhury, Alif Jawad, Anfalur Rahman, Mohammad Jane Alam Khan","doi":"10.1007/s00894-025-06439-z","DOIUrl":"https://doi.org/10.1007/s00894-025-06439-z","url":null,"abstract":"<p><strong>Context: </strong>High-entropy alloys (HEAs) represent a class of advanced materials with superior mechanical, thermal, and chemical properties. FeNiCoCrCu HEA has been of particular interest due to its excellent tensile strength, corrosion resistance, and thermal stability. However, it is a significant challenge to understand and optimize the mechanical properties of such alloys due to the complex structure. Molecular dynamics (MD) is a popular choice in investigating atomic-scale characteristics but is computationally costly for large polycrystal systems. Machine learning approaches have seen growing interest as surrogate models that can produce accurate predictions and lower computational costs. This study demonstrates the first application of Multi-fidelity Physics Informed Neural Network (MPINN) model for predicting the tensile strength of FeNiCoCrCu. This study generates a large dataset of tensile strength for different compositions of FeNiCoCrCu HEA and uses it to train a MPINN model. The MPINN model successfully predicts the tensile strength of FeNiCoCrCu for different compositions and validates the effectiveness of the MD data-enabled MPINN model in making accurate predictions of material properties.</p><p><strong>Methods: </strong>This study uses LAMMPS for the molecular dynamics simulations and TensorFlow for building and running the machine learning models. The low-fidelity (LF) and high-fidelity (HF) data for the machine learning model are obtained from MD simulations of small single crystals and large polycrystals, respectively. MD simulation systems are created using Atomsk, and EAM potential is used for the forcefield. The simulations are visualized using OVITO. The MPINN model utilizes both linear and non-linear relations between LF and HF data. In TensorFlow, the machine learning model is optimized using the Adam optimizer, and L2 regularization is used to prevent overfitting.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"214"},"PeriodicalIF":2.1,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New determination of the thermophysical properties of argon gas considering nuclear spin and symmetry effects.","authors":"F Bouchelaghem, H Boutarfa, M Chicouche, S Lias","doi":"10.1007/s00894-025-06435-3","DOIUrl":"https://doi.org/10.1007/s00894-025-06435-3","url":null,"abstract":"<p><strong>Context: </strong>Since statistical physics and quantum mechanics were first successfully combined thanks in part to the work of Chapman and Cowling and Hirschfelder. Extensive theoretical and experimental research has been dedicated to understanding the kinetics of gases and gas mixtures. This integration has, among other achievements, theoretically established a direct link between the macroscopic properties of gases whether measured or calculated and the quantum characteristics of their constituent particles. This model successfully established straightforward mathematical relationships linking the microscopic interactions between the atomic and/or molecular components of a gas to measurable transport properties, such as diffusion and viscosity coefficients. It also provided explanations for how these properties vary and how they are influenced by thermodynamic parameters like pressure, density, and temperature.</p><p><strong>Methods: </strong>The potential data available to us are either obtained from ab initio calculations or experimental measurements. The ab initio values of the potential V(R) are derived from a quantum-theoretical approach to the molecular problem. Typically, these methods provide the potential energy at discrete values of the internuclear distance R within a specified range. To build the potential energy curve corresponding to the fundamental interactions, we will rely on ab initio data. Knowing this potential allows for the numerical solution of the radial wave equation using Numerov's method, ultimately enabling the calculation of the phase shifts <math><mrow><mi>η</mi> <mfenced><mi>E</mi></mfenced> </mrow> </math> . From the elastic collision phase shifts, we derive the self-diffusion coefficient D, viscosity <math><mi>η</mi></math> , and thermal conductivity <math><mi>λ</mi></math> using the Chapman-Enskog model. For diffusion and viscosity, we perform calculations both with accounting for the symmetry and spin effects associated with the identical nature of the colliding particles. We then examine how these transport coefficients vary with temperature and propose a straightforward computational approach to obtain analytical expressions for D(T), <math><mrow><mi>η</mi> <mo>(</mo> <mi>T</mi> <mo>)</mo></mrow> </math> , and <math><mrow><mi>λ</mi> <mo>(</mo> <mi>T</mi> <mo>)</mo> <mo>.</mo></mrow></math></p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"215"},"PeriodicalIF":2.1,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Density functional theory for nanomaterials: structural and spectroscopic applications-a review.","authors":"Ansa Latif, Anam Latif, Muhammad Mohsin, Ijaz Ahmad Bhatti","doi":"10.1007/s00894-025-06431-7","DOIUrl":"https://doi.org/10.1007/s00894-025-06431-7","url":null,"abstract":"<p><strong>Context: </strong>Nanoparticles (NPs) exhibit unique physical and chemical properties that defy classical mechanics, owing to their quantum nature. These properties are dictated by size, shape, and structure, rendering NPs indispensable across diverse applications, including catalysis, medical imaging, drug delivery, and energy research. Advanced computational tools have become indispensable in unraveling the intricacies of nanomaterial behavior, driving significant progress in theoretical and computational research. Among these tools, the density functional theory (DFT) has emerged as a powerful method for predicting material properties. In this review study, we delve into key aspects of DFT simulations applied to nanomaterials, including Optimal Geometries, Band Gap and Electronic Properties, Density of States (DOS), Natural Bond Orbitals (NBO), and spectroscopic features (Infrared, Raman Spectra, and UV-Visible Spectra). Despite its successes, DFT faces limitations, particularly concerning semiconductor materials. Researchers strive to enhance its accuracy while maintaining computational efficiency. Balancing generically accurate functionals for specific applications remains an ongoing challenge. As nanomaterial continues to play a significant part in a variety of industries, the progress of DFT is of great interest and exploration.</p><p><strong>Methods: </strong>This review discusses DFT-based computational techniques employed for modeling nanomaterials. The calculations are generally done by utilizing generalized gradient approximation (GGA) functionals such as PBE (Perdew-Burke-Ernzerhof), and where necessary, hybrid functionals like B3LYP to enhance band gap accuracy. All calculations are performed using the standard quantum chemistry packages such as VASP, Gaussian, or Quantum ESPRESSO. This combination of methods offers a complete theoretical basis for the study of nanomaterial properties.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"211"},"PeriodicalIF":2.1,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theoretical modeling of interactions of Cr₂O_n and Mn₂O_n clusters with H₂ molecules.","authors":"Konstantin V Bozhenko, Andrey N Utenyshev, Lavrenty G Gutsev, Sergey M Aldoshin, Gennady L Gutsev","doi":"10.1007/s00894-025-06437-1","DOIUrl":"https://doi.org/10.1007/s00894-025-06437-1","url":null,"abstract":"<p><strong>Context: </strong>Gas sensors with high sensitivity and selectivity are essential for industrial safety and environmental monitoring. The ongoing development of more effective sensors relies on two key aspects: the design of novel sensing materials and a deeper understanding of the underlying sensing mechanisms. Among the various materials used for the sensor fabrication, semiconducting metal oxides such as chromium and manganese oxides have garnered much recent attention. Notably, palladium-doped chromium oxide has demonstrated high efficiency in hydrogen sensing. Chromium oxides can function as single-component sensors and also in components of composite systems. Manganese oxides are likewise widely used in sensing applications, especially as electrochemical sensors either alone or in combination with other metal oxides.</p><p><strong>Methods: </strong>All calculations were carried out by using spin-polarized density functional theory with the generalized gradient approximation as implemented in Gaussian 09. Among the numerous exchange-correlation functionals and basis sets, we chose the BPW91 functional and 6-311 + G* basis set of triple-zeta quality. We considered reactions of Cr₂O_n and Mn₂O_n with H₂ and found pathways leading from the reagents to products. All but one reaction pathways were found to have two or three transition states separated by local minima. The search of transition states was performed by using the modified conjugate gradient algorithm and the local minima were determined by applying the intrinsic reaction coordinate algorithm. It was found that some of the pathways are spin-dependent, i.e., the total spin magnetic moments of reagents do not match those of the products.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"213"},"PeriodicalIF":2.1,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microhydration of phenylboronic acid and its hydration free energy.","authors":"Doungous Sale, Alhadji Malloum, Mama Nsangou, Jean Jules Fifen, Jeanet Conradie","doi":"10.1007/s00894-025-06436-2","DOIUrl":"10.1007/s00894-025-06436-2","url":null,"abstract":"<p><strong>Context: </strong>Understanding the interactions of phenylboronic acid with its surrounding water molecules is essential for several applications in solvated systems. In the present work, we investigated the microhydration of the phenylboronic acid (PBA) and calculated its hydration free energy using the cluster continuum solvation model. Microhydration of PBA has not been investigated previously in the literature. It requires the structures of PBA to be surrounded by n explicit water molecules (PBA-W <math><mmultiscripts><mrow></mrow> <mi>n</mi> <mrow></mrow></mmultiscripts> </math> ). The results show that the B(OH) <math><mmultiscripts><mrow></mrow> <mn>2</mn> <mrow></mrow></mmultiscripts> </math> unit of phenylboronic acid forms clusters with water molecules that are similar to those of neutral water clusters. The QTAIM analysis shows that the structures of phenylboronic acid-water clusters are stabilized by strong OH <math><mo>⋯</mo></math> O and weak CH <math><mo>⋯</mo></math> O hydrogen bonds. In addition to QTAIM analysis, NBO analysis was also performed on the most stable configurations to better understand the delocalization of electron density from donor to proper acceptor within the compound. In addition, we found that the most stable structures dominate the population of the clusters for temperatures from 20 to 400 K. Finally, using the structures of the microhydrated phenylboronic acid, we estimated the free energy of hydration and the enthalpy of hydration of PBA. At room temperature, the phenylboronic acid's free energy and enthalpy of hydration are respectively evaluated to be <math><mo>-</mo></math> 72.1 kcal/mol and <math><mo>-</mo></math> 85.5k cal/mol. Assessment of temperature effects on the free energy and the enthalpy of hydration shows that the enthalpy is temperature-independent, while the free energy increases linearly with temperature.</p><p><strong>Methods: </strong>Initial configurations of PBA-W <math><mmultiscripts><mrow></mrow> <mi>n</mi> <mrow></mrow></mmultiscripts> </math> have been generated using classical molecular dynamics and subsequently optimized using the level of theory, <math><mi>ω</mi></math> B97X-D/def2-TZVP. Optimizations, frequency calculations, and NBO analysis are performed using the Gaussian 16 suite of programs. On the most stable configurations, we have performed the quantum theory of atoms in molecules (QTAIM) analysis to get insights into the hydrogen bond network of PBA-W <math><mmultiscripts><mrow></mrow> <mi>n</mi> <mrow></mrow></mmultiscripts> </math> . QTAIM is performed using AIMAll software. Thermodynamic properties as a function of temperature are evaluated using a homemade FORTRAN code-named TEMPO.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"212"},"PeriodicalIF":2.1,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12276122/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential use of deep eutectic solvents based on sugar as green separation media for the acidic gases capture process from the gas mixtures: molecular dynamics simulation and COSMO-RS insights.","authors":"Samaneh Barani Pour, Nasrin Jabbarvand Behrooz, Jaber Jahanbin Sardroodi, Mohammad Sadegh Avestan","doi":"10.1007/s00894-025-06430-8","DOIUrl":"https://doi.org/10.1007/s00894-025-06430-8","url":null,"abstract":"<p><strong>Context: </strong>The global greenhouse gas (GHG) emissions originate from five main economic sectors: energy, industry, construction, transportation, and AFOLU (agriculture, forestry, and other land uses). The emissions of these gases from fossil fuels and land use have reached their highest levels since the nineteenth century. Consequently, urgent actions are required to address this issue worldwide to deal with specific challenges affecting air quality and weather conditions. For this purpose, the reduction of environmental pollutants requires finding methods, including extraction techniques using green solvents (DESs). Understanding the interactions between acid gases (H₂S/CO₂) and the eutectic solvent components (HBA/HBD) determines how much pollutant is absorbed by deep eutectic solvents (DESs). In this regard, to better comprehend the mechanism of H₂S gas absorption, we calculated the combined distribution functions (CDFs) involving the radial distribution functions (RDFs) and the angular distribution functions (ADFs). Additionally, we examined the hydrogen-bonding network, density profiles, spatial distribution functions (SDFs), and the nonbonded energies between H₂S and DES (choline chloride (ChCl)-glucose (Glu)/fructose (Fru) with a molar ratio of 2:1) components were calculated at 333 K. Furthermore, at the pressure between 1 and 15 atm, we obtained the solubility of H₂S/CO₂ gases, solubility selectivity, and diffusivity selectivity parameters as pressure functions to assess the efficacy of sugar-based DES in natural gas sweetening procedures. By analyzing how the interaction of H₂S molecules with the DES components, we concluded that the eutectic solvents based on glucose (Glu)/fructose (Fru) and choline chloride (ChCl) can absorb H₂S molecules.</p><p><strong>Methods: </strong>The molecular graphics program VMD and the PACKMOL package have been used to prepare DES components and simulation boxes. First, initial configurations were minimized under the periodic boundary condition, and then the systems were heated to T = 333 K. Then, a 50 ns NPT simulation was performed at 333 K, while gradually decreasing the distance between the two boxes until reaching equilibrium. The conductor-like screening model (COSMO), as a novel method, has been utilized to predict some properties. The TURBOMOLE program package has been employed to determine the geometries of the electronic density of each HBA and HBD in targeted deep eutectic solvents (optimizing the geometry of DESs components with Becke-Perdew-86 (BP86) functional along with a triple zeta valence potential (TZVP) basis set).</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 8","pages":"210"},"PeriodicalIF":2.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}