Molecular Calculations Research Articles

A Dual Effect Additive Modified Electrolyte Strategy to Improve the Electrochemical Performance of Zinc-Based Prussian Blue Analogs Energy Storage Device.

Prussian blue analogs (PBA) exhibit excellent potential for energy storage due to their unique three-dimensional open framework and abundant redox active sites. However, the dissolution of transition metal ions in water can compromise the structural integrity of PBAs, leading to significant issues such as low cycle life and capacity decay. To address these challenges, we proposed a dual-effect additive-modified electrolyte method to alleviate such issues, introducing sodium ferrocyanide (Na4Fe(CN)6) into aqueous alkaline electrolytes. It could not only capture Zn2+ dissolved on the surface of Na1.86Zn1.46[Fe(CN)6]0.87 (ZnHCF) electrode material during the cycling process but also conduct redox reactions on the electrode surface to provide additional capacitance. Through experiments and molecular simulation calculations, it showed that Na4Fe(CN)6 can restrict the movement of Zn dissolution into the electrolyte on the electrode surface. Based on this, an asymmetric supercapacitor based on ZnHCF//activated carbon was assembled with a modified electrolyte. The assembled supercapacitor displayed a specific capacitance of 1,329.65 mF cm-2, a power density of 2,900 mW cm-2, and an energy density of 388.28 mW h cm-2. This study provides a new idea for the design and construction of stable and efficient PBA energy storage materials by inhibiting the leaching of transition metals in PBA.

Elucidation of Complexation Mechanism of Rosmarinic Acid and Berberine

Polyphenols are known to form complexes with various organic compounds. This ability can may change the chemical or physical properties of the compounds involved and may even affect their efficacy in the case of drugs. Our research revealed that mixing solutions of the polyphenol rosmarinic acid (RA) and berberine (Ber), a widely used and pharmacologically important isoquinoline alkaloid, resulted in the formation of a precipitate of the RA–Ber complex at a molar ratio of 1:1. This was confirmed using 1H NMR and Fourier Transform Infrared Spectroscopy. To elucidate the formation mechanism of the precipitate, the behavior of RA and Ber in an aqueous solution was examined using 1H NMR, indicating the formation of the RA–Ber complex at a molar ratio of 1:1, consistent with the results of precipitation. Additionally, we investigated the steric structure of the RA–Ber complex in an aqueous solution using molecular modeling calculations. These calculations suggested the existence of seven types different steric structures of the RA–Ber complex, primarily stabilized by π–π interactions. Based on these results, we concluded that mixing RA and Ber solutions in an aqueous environment results in the formation of RA–Ber complexes with seven types different steric structures at a molar ratio of 1:1. The precipitate forms because these complexes are less water-soluble than either RA or Ber alone.

ROSHAMBO: Open-Source Molecular Alignment and 3D Similarity Scoring.

Efficient virtual screening techniques are critical in drug discovery for identifying potential drug candidates. We present an open-source package for molecular alignment and 3D similarity calculations optimized for large-scale virtual screening of small molecules. This work parallels widely used proprietary tools and offers an approach complementary to structure-based virtual screening. Our package employs the PAPER software for optimizing molecular alignments based on Gaussian volume overlaps. GPU acceleration is utilized to significantly reduce computational time and resource requirements. After obtaining the optimal alignments between the target and the query molecules, both shape and color (based on pharmacophore features) scores are computed to assess molecular similarity, with aligned molecules optionally being output in sdf format. The package was benchmarked using the DUDE-Z public data sets. Results demonstrated the package's near-state-of-the-art performance and robustness across multiple target classes, with speed that enables many routine ligand-based drug discovery workflows. As an open-source and freely available resource (github.com/molecularinformatics/roshambo) with both a convenient Python API and command line interface, our package also addresses the need for accessible and efficient virtual screening tools in drug discovery.

Enhanced reliability of Cu-Sn bonding through the microstructure evolution of nanotwinned copper

Kirkendall voids are detrimental to the Cu-Sn bonding interface, causing the failure of the high-density package. Herein, the perpendicularly aligned nanotwinned Cu (p-ntCu) and the horizontally aligned nanotwinned Cu (h-ntCu) are prepared by controlling the electrodeposition procedure. The p-ntCu shows advantages both in fast-bonding process and in void suppression through the in-situ microstructure evolution. Compared with h-ntCu, the abundant perpendicularly aligned twin boundaries in p-ntCu provide fast interdiffusion paths to build a bonding interface. In the bonding process, p-ntCu grows to ultra-large-grained Cu with an average grain size of 6.68 μm. The reduced density of normal grain boundaries in p-ntCu lowers the Cu diffusion rate and contributes to more balanced interdiffusion at the bonding interface, which is confirmed by molecular dynamics simulation and kinetic calculations of intermetallic compound (IMC) growth. In addition, the low impurity content in p-ntCu further reduces the diffusion flux imbalance and limits the nucleation of Kirkendall vacancies. Consequently, the p-ntCu/Sn interface keeps void-free during 150 °C long-term thermal aging due to the synergistic effect of reduced grain-boundary diffusion and lower impurity content, which will be beneficial for achieving high-reliability Cu-Sn bonding.

Interaction of graphene oxide with tannic acid: computational modeling and toxicity mitigation in C. elegans.

Graphene oxide (GO) undergoes multiple transformations when introduced to biological and environmental media. GO surface favors the adsorption of biomolecules through different types of interaction mechanisms, modulating the biological effects of the material. In this study, we investigated the interaction of GO with tannic acid (TA) and its consequences for GO toxicity. We focused on understanding how TA interacts with GO, its impact on the material surface chemistry, colloidal stability, as well as, toxicity and biodistribution using the Caenorhabditis elegans model. Employing computational modeling, including reactive classical molecular dynamics and ab initio calculations, we reveal that TA preferentially binds to the most reactive sites on GO surfaces via the oxygen-containing groups or the carbon matrix; van der Waals interaction forces dominate the binding energy. TA exhibits a dose-dependent mitigating effect on the toxicity of GO, which can be attributed not only to the surface interactions between the molecule and the material but also to the inherent biological properties of TA in C. elegans. Our findings contribute to a deeper understanding of GO's environmental behavior and toxicity and highlight the potential of tannic acid for the synthesis and surface functionalization of graphene-based nanomaterials, offering insights into safer nanotechnology development.

Scalar and vectorized implementations of the density functional theory via Geant4 and GeantV project

In this paper, we present the implementation of the Density Functional Theory (DFT) method using the Geant4-DNA framework in the Single Instruction Single Data (SISD) mode. Furthermore, this implementation is improved in terms of execution time within the GeantV project with vectorization techniques such as Single Instruction Multiple Data (SIMD). Within this framework, a set of SIMD strategies in molecular calculation algorithms such as one-electron operators, two-electron operator, quadrature grids, and functionals, was implemented using the VecCore library. The applications developed in this work implement two DFT functionals, the Local Density Approximation (LDA) and the General Gradient Approximation (GGA), to approximate the molecular ground-state energies of small molecules and amino acids. To assess the performance of the implementations, a standard test simulation was performed in multiple CPU platforms. The SIMD vectorization strategy significantly accelerates DFT calculations, leading to time ratios ranging from 1.6 to 5.4 in either individual steps or entire implementations when compared with the scalar process within Geant4.

Pharmacoinformatics, Molecular Dynamics Simulation, and Quantum Mechanics Calculation Based Phytochemical Screening of Croton bonplandianum Against Breast Cancer by Targeting Estrogen Receptor-α (ERα)

Breast cancer progression is strongly influenced by estrogen receptor-α (ERα), a ligand-activated transcription factor that regulates hormone binding, DNA interaction, and transcriptional activation. ERα plays a key role in promoting cell proliferation in breast tissue, and its overexpression is associated with the advancement of breast cancer through estrogen-mediated signaling pathways. Targeting ERα is, therefore, a promising therapeutic strategy for breast cancer. However, there are currently no phytochemical-based drug candidates approved for effectively inhibiting breast cancer progression driven by elevated ERα expression. This study aims to identify phytochemical inhibitors from Croton bonplandianum against ERα using pharmacoinformatics approaches. Eighty-three bioactive compounds from C. bonplandianum were retrieved from the IMPPAT (Indian Medicinal Plants, Phytochemistry, and Therapeutics) database and screened through molecular docking for their binding affinity to ERα. The top candidates were further evaluated through molecular dynamics simulations, ADME analysis, toxicity assessment, and quantum mechanics-based DFT calculations. The thermodynamic properties and HOMO-LUMO energy gap values indicated that the selected compounds were both stable and active. Among them, 2,3-oxidosqualene (CID-5366020) and 5,8,11-eicosatriynoic acid, trimethylsilyl ester (CID-91696396) demonstrated the most potent inhibitory activity against ERα. These findings suggest that these compounds have significant potential as therapeutic agents for breast cancer treatment by targeting ERα.

Molecular and energetic analysis of the interaction and specificity of Maximin 3 with lipid membranes: In vitro and in silico assessments.

In this study, the interaction of antimicrobial peptide Maximin 3 (Max3) with three different lipid bilayer models was investigated to gain insight into its mechanism of action and membrane specificity. Bilayer perturbation assays using liposome calcein leakage dose-response curves revealed that Max3 is a selective membrane-active peptide. Dynamic light scattering recordings suggest that the peptide incorporates into the liposomal structure without producing a detergent effect. Langmuir monolayer compression assays confirmed the membrane inserting capacity of the peptide. Attenuated total reflection-Fourier transform infrared spectroscopy showed that the fingerprint signals of lipid phospholipid hydrophilic head groups and hydrophobic acyl chains are altered due to Max3-membrane interaction. On the other hand, all-atom molecular dynamics simulations (MDS) of the initial interaction with the membrane surface corroborated peptide-membrane selectivity. Peptide transmembrane MDS shed light on how the peptide differentially modifies lipid bilayer properties. Molecular mechanics Poisson-Boltzmann surface area calculations revealed a specific electrostatic interaction fingerprint of the peptide for each membrane model with which they were tested. The data generated from the in silico approach could account for some of the differences observed experimentally in the activity and selectivity of Max3.

Obtaining and Characterizing Thermostable α-Amylases Secreted by Bacillus subtilis, Originating from Bacillus amyloliquefaciens and Bacillus subtilis

The production of recombinant enzymes, primarily used for obtaining pure and functional target molecules, holds significant importance in modern biotechnology. This study aimed to obtain and characterize recombinant, extracellularly expressed α-amylases (Amy3500 and Amy1974), derived from B. amyloliquefaciens MDC1974 and B. subtilis MDC3500, respectively, using the pBE-S shuttle vector. Both α-amylase genes were molecularly cloned into the E. coli/B. subtilis pBE-S shuttle vector, both with (Amy1974sig and Amy3500sig) and without their signal peptides (Amy1974 and Amy3500), along with a signal peptide originating from the plasmid, and tested in flask fermentations. For recombinant Amy3500, the amylase variants resulted in similar levels of volumetric activity (700–750 U/mL). In contrast, the expression of Amy1974 nearly doubled compared to Amy1974sig with double signal peptides, reaching 2000 U/mL. SDS-PAGE estimated the molecular weight of Amy1974 α-amylase to be 54.6 kDa, which is consistent with the theoretical molecular mass calculations. However, the estimated molecular weight of Amy3500 α-amylase was significantly lower upon exiting the producer cells. Ca2⁺ ions exhibit a modest activating effect on the activities of Amy1974 and Amy3500 amylases, likely due to their tight binding to the protein scaffold. Both enzymes exhibited broad activity peaks between 45 and 70 °C, with a maximum at 65 °C. The Amy1974 and Amy3500 α-amylases demonstrated broad pH optima and pH-dependent thermostability, with optimum pH values at 6.5 and 5.8, and thermal stability peaks at pH 7.6 and 5.9, respectively. Both α-amylases displayed high relative activity against various starches, including corn amylopectin and potato amylose, while showing comparatively lower activity towards α-, β-, and γ-cyclodextrins. The Amy1974 amylase is effective in converting starch into dextrins of varying lengths, while Amy3500 primarily converts starch into glucose. These characteristics make them promising candidate enzymes for industrial applications.

Photochemical and Collision-Induced Cross-Linking in Stereochemically Distinct Scaffolds of Peptides and Nitrile Imines in Gas-Phase Ions.

Intramolecular cross-linking between peptides and nitrile-imine intermediates was studied in stereochemically distinct conjugates in which the reacting components were mounted on cis-1,2-cyclohexane and trans-1,4-cyclohexane scaffolds that we call 1,2-s-peptides and 1,4-s-peptides, respectively. The nitrile-imine intermediates were generated by N2 loss from 2,5-diaryltetrazole tags upon UV-photodissociation at 213 and 250 nm or by collision-induced dissociation, and further interrogated by CID and UVPD-MS3. Peptide fragment ion series originating from linear structures and macrocyclic cross-links were distinguished and used to quantify the cross-linking yields. The yields in MS2 varied between 27% for AAAG conjugates to 78% for GAAAK conjugates, depending on the peptide sequence. The CID-MS3 yields were in a 57-97% range, depending on the peptide sequence. Structures of 1,2-s-peptide and 1,4-s-peptide ions as well as several of their nitrile-imine intermediates and cross-links were investigated by high-resolution cyclic ion mobility in combination with Born-Oppenheimer molecular dynamics and density functional theory calculations. Matches between the experimental and calculated collision cross sections and ion relative Gibbs energies were used to assign peptide structures. Peptide conjugates C-terminated with Gly and Lys residues underwent cross-linking by the carboxyl group, as established by MS3 sequencing and corroborated by carboxyl blocking experiments that lowered the cross-linking yields. Peptide conjugates C-terminated with Arg also cross-linked via the side-chain guanidine group. A notable feature of the 1,4-s-peptide ions was the participation of low-energy twist-boat cyclohexane conformers that was enforced by strong hydrogen bonds between the peptide and nitrile imine.

A study on the coupling of Li+ and H3BO3 extraction and their mutual promotion mechanism

Efficient extraction of lithium and boron resources from salt-lakes is a prominent topic of research among scholars. In this study, a process route for the simultaneous extraction of lithium and boric acid was employed, followed by their separation through stepwise stripping. During the experiments, a coupling effect in the extraction of Li+ and H3BO3 was found, leading to an in-depth investigation of their mutual promotion mechanisms. Three significant patterns have been clearly verified through experiments, molecular dynamics simulations and quantum chemical calculations: First, the acidic extractant N221 can not only extract Li+, but also enhance the extraction of H3BO3; Second, mono-fatty alcohol R-OH as dilute can effectively extract H3BO3 while also promoting the extraction of Li+. Lastly, Li+ and H3BO3 can mutually promote each other's extraction. Using the Qinghai old brine, N221 system achieved a 99 % extraction efficiency for H3BO3, with an initial lithium extraction of 97 %, around 80 % in subsequent rounds. This paper proposes an effective method for the extraction of Li+ and boric acid, and thoroughly studied the mechanism of their mutual promotion of extraction. This research offers new insights into the comprehensive utilization of salt-lake resources.

Modulation of ABCG2 Transporter Activity by Ko143 Derivatives.

ABCG2 is a multidrug transporter that protects tissues from xenobiotics, affects drug pharmacokinetics, and contributes to multidrug resistance of cancer cells. Here, we present tetracyclic fumitremorgin C analog Ko143 derivatives, evaluate their in vitro modulation of purified ABCG2, and report four high-resolution cryo-EM structures and computational analyses to elucidate their interactions with ABCG2. We found that Ko143 derivatives that are based on a ring-opened scaffold no longer inhibit ABCG2-mediated transport activity. In contrast, closed-ring, tetracyclic analogs were highly potent inhibitors. Strikingly, the least potent of these compounds, MZ82, bound deeper into the central ABCG2 cavity than the other inhibitors and it led to partial closure of the transmembrane domains and increased flexibility of the nucleotide-binding domains. Minor structural modifications can thus convert a potent inhibitor into a compound that induces conformational changes in ABCG2 similar to those observed during binding of a substrate. Molecular dynamics simulations and free energy binding calculations further supported the correlation between reduced potency and distinct binding pose of the compounds. We introduce the highly potent inhibitor AZ99 that may exhibit improved in vivo stability.

Artemisia campestris L. as a promising source of potential antiviral drugs for SARS-CoV-2: Docking and dynamic simulation studies

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been considered as global public health security threats. Due to its rapid spread, high mortality rate and unavailability of treatment, we need to find a potent drug against SARS-CoV-2. Natural products are useful agents for the discovery of new potential drugs to combat coronavirus. Artemisia campestris, an aromatic plant widely used in traditional medicine, particularly in southern region of Algeria, is recognized for its essential oils and phenolics compounds possessing a wide range of biological activities. This study selected sixty-nine compounds from this plant to determine their binding interactions with the SARS-CoV-2 main protease (Mpro) and receptor-binding domain of the spike (S-RBD) protein, by using computational methods. Rutin, isoquercetin, and quercetin-3-O-glucuronide were shown to be the most potent inhibitors for Mpro and S-RBD with docking scores and Ki values ranging from -16.06 to -10.67 Kcal/mol and 0.005 to 30.01 nM, respectively. Evaluation of ADMET pharmacokinetic properties and the drug likeness in silico revealed that only 3,5-dicaffeoylquinic acid, 3–4–5-tricaffeoylquinic acid, isorhamnetin-3-O-glucoside, and rubescensin A could be more effective drugs against COVID-19. Molecular dynamics (MD) simulations (100 ns) and MM-GBSA calculations confirmed the stability of ligand-protein complexes via hydrogen bonding interactions with crucial residues. The analysis of structural parameters (RMSD, RMSF, H-bonds, Rg, and SASA) indicates that 3,4,5-tricaffeoylquinic acid and rubescensin A compounds have good stability and significant binding affinity with the Mpro and S-RBD protein. Taken together, our findings confirm that Artemisia campestris as a plausible source of anti-SARS-COV-2 phytochemicals and suggest that may play important role in this activity.

An optimal global biochar application strategy based on matching biochar and soil properties to reduce global cropland greenhouse gas emissions: findings from a global meta-analysis and density functional theory calculation

Biochar has been extensively utilized to amend soil and mitigate greenhouse gas (GHG) emissions from croplands. However, the effectiveness of biochar application in reducing cropland GHG emissions remains uncertain due to variations in soil properties and environmental conditions across regions. In this study, the impact of biochar surface functional groups on soil GHG emissions was investigated using molecular model calculation. Machine learning (ML) technology was applied to predict the responses of soil GHG emissions and crop yields under different biochar feedstocks and application rates, aiming to determine the optimum biochar application strategies based on specific soil properties and environmental conditions on a global scale. The findings suggest that the functional groups play an essential role in determining biochar surface activity and the soil’s capacity for adsorbing GHGs. ML was an effective method in predicting the changes in soil GHG emissions and crop yield following biochar application. Moreover, poor-fertility soils exhibited greater changes in GHG emissions compared to fertile soil. Implementing an optimized global strategy for biochar application may result in a substantial reduction of 684.25 Tg year−1 CO2 equivalent (equivalent to 7.87% of global cropland GHG emissions) while simultaneously improving crop yields. This study improves our understanding of the interaction between biochar surface properties and soil GHG, confirming the potential of global biochar application strategies in mitigating cropland GHG emissions and addressing global climate degradation. Further research efforts are required to optimize such strategies.Graphical

The potential of supramolecular synthon to develop coamorphous systems with tailored physical stability: Mechanistic insights integrating kinetics and thermodynamics

Coamorphous drug delivery systems have received increasing interest owing to their potential to improve the solubility, dissolution and bioavailability of poorly water-soluble drugs. However, the crystallization risk is one of major limitations in their application. It has been widely recognized that the coformer plays a vital role in physical stability of coamorphous formulation. Unfortunately, the screen of optimal coformer still adopts a trial-and-error method, which is time-consuming and expensive. Herein, a supramolecular synthon approach based on the interaction between functional groups, was exploited to design coamorphous systems (CMs) consisting of lurasidone hydrochloride (LH) and three coformers, saccharin (SAC), L-tryptophan (TRP), and L-cysteine hydrochloride (CYS). X-ray powder diffraction suggested the order of physical stability of the coamorphous systems was ranked as LH-CYS CM > LH-TRP CM > LH-SAC CM. The charge-assisted hydrogen bond between LH and coformer was confirmed by infrared spectroscopy and solid-state 13C NMR. Moreover, structural, electronic, and molecular interaction information, especially hydrogen bonding interactions, were quantified by theoretical calculations, including miscibility calculations, molecular dynamics simulations and quantum chemical calculations. It was revealed that LH-CYS CM exhibited the best miscibility, strongest binding energy and strongest H-bond with partially covalent character, demonstrating the significant role of supramolecular synthon in stabilizing coamorphous formulations. Interestingly, LH-TRP CM, not LH-CYS CM, exhibited the lowest molecular mobility among three coamorphous systems, which was inconsistent with their physical stability. But from thermodynamic perspective, the order of configurational entropy and physical stability of coamorphous systems was completely consistent. We shed light on the comprehensive effects of molecular mobility and configurational entropy on physical stability of coamorphous systems. Importantly, the relationship between supramolecular synthon and kinetic/thermodynamic mechanisms was also discussed, and the positive correlation between configurational entropy and intermolecular interactions was proposed in this paper. Our findings demonstrated the great potential of supramolecular synthon in designing coamorphous systems with tailored physical stability, and further provided a deeper insight into the mechanisms of physical stability of coamorphous systems.

Fast Color Image Encryption Algorithm Based on DNA Coding and Multi-Chaotic Systems

At present, there is a growing emphasis on safeguarding image data, yet conventional encryption methods are full of numerous limitations. In order to tackle the limitations of conventional color image encryption methodologies, such as inefficiency and insufficient security, this paper designs an expedited encryption method for color images that uses DNA coding in conjunction with multiple chaotic systems. The encryption algorithm proposed in this paper is based on three-dimensional permutation, global scrambling, one-dimensional diffusion and DNA coding. First of all, the encryption algorithm uses three-dimensional permutation algorithms to scramble the image, which disrupts the high correlation among the image pixels. Second, the RSA algorithm and the SHA-256 hashing algorithm are utilized to derive the starting value necessary for the chaotic system to produce the key. Third, the image is encrypted by using global scrambling and one-dimensional diffusion. Finally, DNA coding rules are used to perform DNA computing. The experimental results indicate that the encryption scheme exhibits a relatively weak inter-pixel correlation, uniform histogram distribution, and an information entropy value approaching eight. This shows that the proposed algorithm is able to protect the image safely and efficiently.

Engineering the Substrate Specificity of UDP-Glycosyltransferases for Synthesizing Triterpenoid Glycosides with a Linear Trisaccharide as Aided by Ancestral Sequence Reconstruction.

Triterpenoids have wide applications in the pharmaceutical and agricultural industries. The glycosylation of triterpenoids catalyzed by UDP-glycosyltransferases (UGTs) is a crucial method for producing valuable derivatives with enhanced functions. However, only a few UDP-glucosyltransferases have been reported to synthesize the rare triterpenoids with linear-chain trisaccharide at C3-OH. This study revealed that the UGT91H subfamily primarily contributed to the 2"-O-glycosylation of triterpenoids with high regioselectivity, then the substrate scope was further expanded by ancestral sequence reconstruction (ASR). With ancestral enzyme UGT91H_A1 as a model, the sequence-structure-function relationship was explored. A RTAS loop (R212/T213/A214/S215) was identified to affect the substrate specificity of UGT91H_A1. Transferring this RTAS loop to the corresponding position of UGT91H enzymes successfully expanded their substrate spectra. The functional role of RTAS loop was further elucidated by molecular dynamics simulation and quantum mechanical computation. UGT91H_A1 was applied to the low-cost synthesis of terpenoid rhamnosides with a linear trisaccharide in combining with a self-sufficient UDP-rhamnose regeneration system. Finally, we developed a phylogeny-based platform to efficiently mining new UGT91Hs from plant genomic data. This study provided robust biocatalysts for synthesizing various triterpenoid glycosides with a linear trisaccharide and demonstrated ASR as an efficient tool in engineering the function of UDP-glycosyltransferases.

Probing the performance of DFT in the structural characterization of [FeFe] hydrogenase models.

In this work, a series of DFT and DFT-D methods is combined with double-ζ basis sets to benchmark their performance in predicting the structures of five newly synthesized hexacarbonyl diiron complexes with a bridging ligand featuring a μ-S2C3 motif in a ring-containing unit functionalized with aromatic groups. Such complexes have been considered as [FeFe] hydrogenase catalytic site models with potential for eco-friendly energetic applications. According to this assessment, r2SCAN is identified as the density functional recommended for the reliable description of the molecular and crystal structures of the herein studied models. However, the butterfly (μ-S)2Fe2 core of the models demonstrates a minor deformation of its optimized geometry obtained from both molecular and periodic calculations. The FeFe bond length is slightly underestimated while the FeS bonds tend to be too long. Adding the D3(BJ) correction to r2SCAN does not lead to any improvement in the calculated structures.

Computational Multiscale Study of the Interaction Between the PDMS Polymer and Sunscreen-Related Pollutant Molecules

Sunscreen molecules play a critical role in protecting skin from ultraviolet radiation, yet their efficient detection and separation pose challenges in environmental and analytical contexts. In this work, we employ a multilevel modeling approach to investigate the molecular interactions between representative sunscreen molecules and the polydimethylsiloxane (PDMS) polymer, a material widely recognized for its sorbent properties. Our goal is to explore how these interactions can be fine-tuned to facilitate the effective separation of sunscreen molecules in portable membrane inlet mass spectrometry (MIMS) systems, potentially leading to the development of new membrane materials. Using a combination of advanced computational techniques—force field molecular dynamics simulations, semiempirical GFN2-xTB, and density functional theory calculations—we assess the interaction strength and noncovalent interactions of sunscreen molecules, namely oxybenzone, naphthalene, benzo[a]anthracene, avobenzone, and 1,3,5-trichlorobenzene, with PDMS. Additionally, the effect of temperature on the interaction dynamics is evaluated, with the aim of extending the sorbent capacities of PDMS beyond light polar molecules to larger, polar sunscreen compounds. This study provides critical insights into the molecular-level interactions that may guide the design of novel membrane materials for efficient molecular separation.

Maximum entropy method for valence quark distributions in exotic hadrons: a study of the Zc(3900)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z_c(3900)$$\\end{document} case

In this study we demonstrate the application of the maximum entropy method (MEM) to determine the valence quark distribution of exotic hadrons. Our investigation yields three key findings. Firstly, we observe a significant shift towards smaller Bjorken scale x in the peak position of the valence quark distribution for hadrons with an increasing number of valence quarks, consistent with previous results by Kawamura and Kumano. Secondly, assuming that the Zc(3900)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z_c(3900)$$\\end{document} initially consists of four valence quarks, we employ MEM to determine its initial valence quark distribution, estimating a radius of rc=1.276\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$r_c=1.276$$\\end{document} fm at an extremely low resolution scale Q2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Q^2$$\\end{document}. Furthermore, we identify a notable discrepancy between our computed charge form factor Gc(q)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G_c(q)$$\\end{document} at leading order and the outcomes of hadron molecular state calculations. We propose that this form factor can be extracted from the QCD counting rule cross-section, which is grounded in generalized distribution amplitudes (GDA) linked to the multi-quark states.