Pub Date : 2025-12-20DOI: 10.1016/j.chphi.2025.100992
T.S. Balaji, S. Balaji, P. Rathinakumar, S. Karthik
<div><div>Metal oxide (MOX) nanostructures are among the most widely deployed platforms for real-time detection of toxic and greenhouse gases because their surfaces actively mediate charge transfer while remaining compatible with CMOS-scale integration. Yet, classical descriptions often treat surface chemistry and electronic transport as loosely coupled processes, which limits predictive design. This work advances a unified view of sensing in ZnO, SnO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, WO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span>, NiO, and TiO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> nanostructures by coupling non-linear adsorption–desorption kinetics with band bending and depletion-layer dynamics.</div><div>We introduce a compact, physics-grounded model that blends Beer–Lambert attenuation of active sites with Langmuir-like coverage and a Poisson-based surface-potential update. The framework captures transient conductance with a mean absolute deviation <span><math><mo>≤</mo></math></span> <!--> <!-->5% against reported experimental datasets spanning oxidizing (NO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) and reducing (CO, H<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>S) analytes. Quantitatively, optimized ZnO nanorods achieve a response of 152% at 50 ppm NO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and 250 °C with <span><math><mrow><mo>∼</mo><mn>28</mn></mrow></math></span> s recovery, while MOF-derived hollow CuO rods exhibit sub-ppm H<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>S detection near room temperature; the extracted adsorption-limited activation energies fall in the range 0.34–<span><math><mrow><mn>0</mn><mo>.</mo><mn>41</mn><mspace></mspace><mi>eV</mi></mrow></math></span>. Structurally, reducing crystallite size from <span><math><mrow><mo>∼</mo><mn>40</mn><mspace></mspace><mi>nm</mi></mrow></math></span> to <span><math><mrow><mo>∼</mo><mn>25</mn><mspace></mspace><mi>nm</mi></mrow></math></span> increases the usable surface-to-volume ratio by about 1.6-fold (60%), translating to a 35%–70% sensitivity gain under identical operating conditions.</div><div>The novelty lies in treating structural descriptors (grain size, porosity, heterojunctions) and electronic descriptors (donor density <span><math><msub><mrow><mi>N</mi></mrow><mrow><mi>D</mi></mrow></msub></math></span>, surface site density <span><math><msub><mrow><mi>N</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span>) within a single closed-form workflow that is simple enough for on-node implementation yet faithful to semiconductor physics. Beyond aligning with published experimental trends in graphene/WO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> hybrids and noble-metal-decorated TiO<span><math><msub><mrow></mrow
{"title":"Electronic and structural dynamics of metal oxide nanostructures for gas detection","authors":"T.S. Balaji, S. Balaji, P. Rathinakumar, S. Karthik","doi":"10.1016/j.chphi.2025.100992","DOIUrl":"10.1016/j.chphi.2025.100992","url":null,"abstract":"<div><div>Metal oxide (MOX) nanostructures are among the most widely deployed platforms for real-time detection of toxic and greenhouse gases because their surfaces actively mediate charge transfer while remaining compatible with CMOS-scale integration. Yet, classical descriptions often treat surface chemistry and electronic transport as loosely coupled processes, which limits predictive design. This work advances a unified view of sensing in ZnO, SnO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, WO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span>, NiO, and TiO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> nanostructures by coupling non-linear adsorption–desorption kinetics with band bending and depletion-layer dynamics.</div><div>We introduce a compact, physics-grounded model that blends Beer–Lambert attenuation of active sites with Langmuir-like coverage and a Poisson-based surface-potential update. The framework captures transient conductance with a mean absolute deviation <span><math><mo>≤</mo></math></span> <!--> <!-->5% against reported experimental datasets spanning oxidizing (NO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) and reducing (CO, H<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>S) analytes. Quantitatively, optimized ZnO nanorods achieve a response of 152% at 50 ppm NO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and 250 °C with <span><math><mrow><mo>∼</mo><mn>28</mn></mrow></math></span> s recovery, while MOF-derived hollow CuO rods exhibit sub-ppm H<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>S detection near room temperature; the extracted adsorption-limited activation energies fall in the range 0.34–<span><math><mrow><mn>0</mn><mo>.</mo><mn>41</mn><mspace></mspace><mi>eV</mi></mrow></math></span>. Structurally, reducing crystallite size from <span><math><mrow><mo>∼</mo><mn>40</mn><mspace></mspace><mi>nm</mi></mrow></math></span> to <span><math><mrow><mo>∼</mo><mn>25</mn><mspace></mspace><mi>nm</mi></mrow></math></span> increases the usable surface-to-volume ratio by about 1.6-fold (60%), translating to a 35%–70% sensitivity gain under identical operating conditions.</div><div>The novelty lies in treating structural descriptors (grain size, porosity, heterojunctions) and electronic descriptors (donor density <span><math><msub><mrow><mi>N</mi></mrow><mrow><mi>D</mi></mrow></msub></math></span>, surface site density <span><math><msub><mrow><mi>N</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span>) within a single closed-form workflow that is simple enough for on-node implementation yet faithful to semiconductor physics. Beyond aligning with published experimental trends in graphene/WO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> hybrids and noble-metal-decorated TiO<span><math><msub><mrow></mrow","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100992"},"PeriodicalIF":4.3,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-17DOI: 10.1016/j.chphi.2025.100993
Vu Thi Hoa
Arsenic contamination in Vietnamese groundwater threatens millions, with concentrations frequently exceeding 600 μg/L in the Mekong and Red River Deltas. Herein, we report the rational design of a hydroxyl‑enriched two-dimensional Ti₃C₂(OH)₂ MXene nano-assembly that simultaneously achieves ultrahigh arsenic adsorption and ultrasensitive electrochemical detection. Advanced DFT calculations incorporating implicit (PCM) and explicit (AIMD) solvation reveal that surface −OH groups drive the spontaneous formation of highly ordered, self-assembled bidentate arsenate monolayers through a supramolecular-like recognition motif, delivering the strongest aqueous-phase binding energy (−2.15 eV for As(V)) among all terminations (−O, −F) via 0.34 e⁻ interfacial charge transfer and a pronounced 0.32 eV work-function shift. These atomically engineered surface nano-assemblies translate into exceptional experimental performance: adsorption capacities of 58.3 mg/g (As(V)) and 41.7 mg/g (As(III)), ultra-fast kinetics (<30 min), wide pH tolerance (4–9), and robust selectivity in complex natural matrices. The same material enables portable electrochemical sensing with a 1.8 μg/L limit of detection and <5 % deviation from ICP-MS across real Vietnamese groundwater samples. A 60-day decentralized household pilot in An Giang province consistently delivered effluent arsenic below 10 μg/L without electricity or chemicals. This work establishes hydroxylated Ti₃C₂Tₓ MXene as a powerful dual-functional 2D nano-assembly platform, bridging molecular-level supramolecular design with field-deployable arsenic mitigation in resource-limited regions.
{"title":"DFT-guided engineering of hydroxylated Ti₃C₂Tₓ MXene for efficient arsenic removal and electrochemical monitoring in vietnamese groundwater","authors":"Vu Thi Hoa","doi":"10.1016/j.chphi.2025.100993","DOIUrl":"10.1016/j.chphi.2025.100993","url":null,"abstract":"<div><div>Arsenic contamination in Vietnamese groundwater threatens millions, with concentrations frequently exceeding 600 μg/L in the Mekong and Red River Deltas. Herein, we report the rational design of a hydroxyl‑enriched two-dimensional Ti₃C₂(OH)₂ MXene nano-assembly that simultaneously achieves ultrahigh arsenic adsorption and ultrasensitive electrochemical detection. Advanced DFT calculations incorporating implicit (PCM) and explicit (AIMD) solvation reveal that surface −OH groups drive the spontaneous formation of highly ordered, self-assembled bidentate arsenate monolayers through a supramolecular-like recognition motif, delivering the strongest aqueous-phase binding energy (−2.15 eV for As(V)) among all terminations (−<em>O</em>, −<em>F</em>) via 0.34 e⁻ interfacial charge transfer and a pronounced 0.32 eV work-function shift. These atomically engineered surface nano-assemblies translate into exceptional experimental performance: adsorption capacities of 58.3 mg/g (As(V)) and 41.7 mg/g (As(III)), ultra-fast kinetics (<30 min), wide pH tolerance (4–9), and robust selectivity in complex natural matrices. The same material enables portable electrochemical sensing with a 1.8 μg/L limit of detection and <5 % deviation from ICP-MS across real Vietnamese groundwater samples. A 60-day decentralized household pilot in An Giang province consistently delivered effluent arsenic below 10 μg/L without electricity or chemicals. This work establishes hydroxylated Ti₃C₂Tₓ MXene as a powerful dual-functional 2D nano-assembly platform, bridging molecular-level supramolecular design with field-deployable arsenic mitigation in resource-limited regions.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100993"},"PeriodicalIF":4.3,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.chphi.2025.100994
Masoud Salavati , Stanford White IV , Mohammed Majdoub , Mine G. Ucak-Astarlioglu , Ahmed Al-Ostaz , Samrat Choudhury , Sasan Nouranian
Carbonaceous structures can be produced via pyrolysis of polymeric precursors for applications in gas separation membranes, energy storage, flexible electronics, electromagnetic interference shielding foams, etc. Maximizing char yield is a primary objective, determined by precursor chemistry, composition, pyrolysis conditions, and kinetics. The complex, non-linear relationships among these factors favor machine learning (ML) for process design and optimization. A physics-informed, transformer-based ML model was developed to predict char mass evolution (thermal decomposition) of transition-metal-catalyzed polyetherimide (PEI)/graphite (Gr) nanocomposites from thermogravimetric analysis (TGA) data. The dataset included 38 formulations with varying Gr and catalyst (Fe, Ni, Co) contents, heating rates, and pyrolysis temperatures. Additional features captured Gr and catalyst structural and electronic properties (crystal system, d-orbital free electrons, lattice parameters, cohesive energy, carbide formation energy, electrical conductivity at 20 °C) and kinetic parameters from 2D/3D Avrami–Erofeev models (pre-exponential factor, activation energy). Data were split into “seen” catalysts (Fe, Ni) for training/validation and an “unseen” catalyst (Co) for testing. Hyperparameters and feature selection were optimized via the random forest method. The model achieved > 0.98 on unseen data, accurately predicting TGA curves and kinetic trends. Experimental and ML-predicted curves showed close agreement, with successful extrapolation to Co-containing nanocomposites. This study integrates kinetics modeling with advanced ML to enhance prediction of pyrolysis behavior in polymer nanocomposites, providing a practical framework for developing carbonaceous materials with tailored properties.
{"title":"Physics-informed machine learning prediction of char mass evolution in the catalytic pyrolysis of polyetherimide/graphite nanocomposites","authors":"Masoud Salavati , Stanford White IV , Mohammed Majdoub , Mine G. Ucak-Astarlioglu , Ahmed Al-Ostaz , Samrat Choudhury , Sasan Nouranian","doi":"10.1016/j.chphi.2025.100994","DOIUrl":"10.1016/j.chphi.2025.100994","url":null,"abstract":"<div><div>Carbonaceous structures can be produced via pyrolysis of polymeric precursors for applications in gas separation membranes, energy storage, flexible electronics, electromagnetic interference shielding foams, etc. Maximizing char yield is a primary objective, determined by precursor chemistry, composition, pyrolysis conditions, and kinetics. The complex, non-linear relationships among these factors favor machine learning (ML) for process design and optimization. A physics-informed, transformer-based ML model was developed to predict char mass evolution (thermal decomposition) of transition-metal-catalyzed polyetherimide (PEI)/graphite (Gr) nanocomposites from thermogravimetric analysis (TGA) data. The dataset included 38 formulations with varying Gr and catalyst (Fe, Ni, Co) contents, heating rates, and pyrolysis temperatures. Additional features captured Gr and catalyst structural and electronic properties (crystal system, d-orbital free electrons, lattice parameters, cohesive energy, carbide formation energy, electrical conductivity at 20 °C) and kinetic parameters from 2D/3D Avrami–Erofeev models (pre-exponential factor, activation energy). Data were split into “seen” catalysts (Fe, Ni) for training/validation and an “unseen” catalyst (Co) for testing. Hyperparameters and feature selection were optimized via the random forest method. The model achieved <span><math><mrow><mi>R</mi><mi>²</mi></mrow></math></span> > 0.98 on unseen data, accurately predicting TGA curves and kinetic trends. Experimental and ML-predicted curves showed close agreement, with successful extrapolation to Co-containing nanocomposites. This study integrates kinetics modeling with advanced ML to enhance prediction of pyrolysis behavior in polymer nanocomposites, providing a practical framework for developing carbonaceous materials with tailored properties.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100994"},"PeriodicalIF":4.3,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.chphi.2025.100991
Ephrald Jebishkumar H, Sumithraj Premkumar P
Selenium-doped zirconium oxide (ZrO2:Se) nanoparticles were synthesized via a microwave-assisted solution combustion route to develop efficient materials for clean energy storage. Structural and morphological studies confirmed a tetragonal crystal structure with a nanocrystalline size of ∼14 nm, as observed from TEM analysis. XPS analysis confirmed the presence of selenium in mixed oxidation states (Se0/Se2-, Se4+ and Se6+), predominantly existing as surface-adsorbed oxidized species forming Se–O–Zr linkages. Nitrogen adsorption isotherms revealed a high surface area, promoting enhanced electrochemical activity. Electrochemical investigations in 6 M KOH electrolyte demonstrated clear pseudocapacitive behavior, delivering a specific capacitance of 703 F g-1 at 2 A g-1, an energy density of 79.12 Wh kg-1, and a power density of 2000 W kg-1. The electrode exhibited good cycling stability, retaining approximately 83 % capacitance after 4000 cycles. These findings highlight that selenium incorporation improves electrical conductivity, ion transport, and surface redox activity, making selenium-doped zirconium oxide a promising electrode material for high-performance pseudocapacitor and sustainable energy storage applications.
采用微波辅助溶液燃烧的方法合成了硒掺杂氧化锆（ZrO2:Se）纳米颗粒，开发了高效的清洁储能材料。结构和形态学研究证实了一个四方晶体结构，纳米晶体尺寸为~ 14 nm，从TEM分析中观察到。XPS分析证实硒以混合氧化态（Se0/Se2-， Se4+和Se6+）存在，主要以表面吸附的氧化态存在，形成Se-O-Zr键。氮吸附等温线显示出高的表面积，促进了电化学活性的增强。在6 M KOH电解液中的电化学研究显示出明显的假电容行为，在2 a g-1时提供703 F -1的比电容，能量密度为79.12 Wh kg-1，功率密度为2000 W kg-1。该电极表现出良好的循环稳定性，在4000次循环后保持约83%的电容。这些发现突出表明，硒的掺入改善了电导率、离子传输和表面氧化还原活性，使硒掺杂氧化锆成为高性能伪电容器和可持续储能应用的有前途的电极材料。
{"title":"Selenium-doped zirconium oxide nanoparticles as a promising electrode material for high-performance supercapacitors","authors":"Ephrald Jebishkumar H, Sumithraj Premkumar P","doi":"10.1016/j.chphi.2025.100991","DOIUrl":"10.1016/j.chphi.2025.100991","url":null,"abstract":"<div><div>Selenium-doped zirconium oxide (ZrO<sub>2</sub>:Se) nanoparticles were synthesized via a microwave-assisted solution combustion route to develop efficient materials for clean energy storage. Structural and morphological studies confirmed a tetragonal crystal structure with a nanocrystalline size of ∼14 nm, as observed from TEM analysis. XPS analysis confirmed the presence of selenium in mixed oxidation states (Se<sup>0</sup>/Se<sup>2-</sup>, Se<sup>4+</sup> and Se<sup>6+</sup>), predominantly existing as surface-adsorbed oxidized species forming Se–O–Zr linkages. Nitrogen adsorption isotherms revealed a high surface area, promoting enhanced electrochemical activity. Electrochemical investigations in 6 M KOH electrolyte demonstrated clear pseudocapacitive behavior, delivering a specific capacitance of 703 F g<sup>-1</sup> at 2 A g<sup>-1</sup>, an energy density of 79.12 Wh kg<sup>-1</sup>, and a power density of 2000 W kg<sup>-1</sup>. The electrode exhibited good cycling stability, retaining approximately 83 % capacitance after 4000 cycles. These findings highlight that selenium incorporation improves electrical conductivity, ion transport, and surface redox activity, making selenium-doped zirconium oxide a promising electrode material for high-performance pseudocapacitor and sustainable energy storage applications.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100991"},"PeriodicalIF":4.3,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-12DOI: 10.1016/j.chphi.2025.100990
Herlina Rasyid , Muhammad Idham Darussalam Mardjan , Maulidan Firdaus , Nur Asmi , Bahrun Bahrun
Malaria remains a major global health issue due to the emergence of drug-resistant Plasmodium falciparum. The discovery of new compounds targeting essential enzymes such as P. falciparum lactate dehydrogenase (PfLDH) and P. falciparum dihydrofolate reductase-thymidylate synthase (PfDHFR-TS) is a potential strategy for the development of antimalarials. In this study, 30 Isoindolinone-Hydrazide hybrid compounds were designed and evaluated using in silico molecular docking, molecular dynamics simulations, and MM-PBSA analysis. The molecular docking showed that all compounds exhibited stronger interactions than the native ligands of each protein. In PfLDH, the top three compounds (1e, 1l, and 1t) showed binding energies ranging from -8.3 to -8.6 kcal/mol, more favorable than the native ligand (-5.7 kcal/mol). In PfDHFR-TS, compounds 1k and 1l have the best affinity with binding energies of -11.1 and -10.8 kcal/mol, better than the native ligand (-8.1 kcal/mol). Molecular dynamics simulations indicate that the 1l-PfLDH and 1k-PfDHFR-TS complex provides the best stability of protein interactions and structure, characterized by low Rg values, minimal RMSD fluctuations, and stable RMSF patterns in key residues. Physicochemical analysis confirms that all compounds comply with Lipinski's rules, supporting their candidacy as drug-like molecules.
Conclusions
This computational investigation identifies Isoindolinone-Hydrazide hybrids, particularly compounds 1l (for PfLDH) and 1k (for PfDHFR-TS), as promising in silico antimalarial inhibitor candidates. These findings provide a theoretical basis for future experimental validation to confirm their predicted antiplasmodial potential.
{"title":"In Silico Design of Isoindolinone-Hydrazide Hybrid Compounds as Antiplasmodium Through Molecular Docking, Molecular Dynamics Simulation, and MM-PBSA Calculation","authors":"Herlina Rasyid , Muhammad Idham Darussalam Mardjan , Maulidan Firdaus , Nur Asmi , Bahrun Bahrun","doi":"10.1016/j.chphi.2025.100990","DOIUrl":"10.1016/j.chphi.2025.100990","url":null,"abstract":"<div><div>Malaria remains a major global health issue due to the emergence of drug-resistant <em>Plasmodium falciparum</em>. The discovery of new compounds targeting essential enzymes such as <em>P. falciparum</em> lactate dehydrogenase (PfLDH) and <em>P. falciparum</em> dihydrofolate reductase-thymidylate synthase (PfDHFR-TS) is a potential strategy for the development of antimalarials. In this study, 30 Isoindolinone-Hydrazide hybrid compounds were designed and evaluated using <em>in silico</em> molecular docking, molecular dynamics simulations, and MM-PBSA analysis. The molecular docking showed that all compounds exhibited stronger interactions than the native ligands of each protein. In PfLDH, the top three compounds (<strong>1e, 1l</strong>, and <strong>1t</strong>) showed binding energies ranging from -8.3 to -8.6 kcal/mol, more favorable than the native ligand (-5.7 kcal/mol). In PfDHFR-TS, compounds <strong>1k</strong> and <strong>1l</strong> have the best affinity with binding energies of -11.1 and -10.8 kcal/mol, better than the native ligand (-8.1 kcal/mol). Molecular dynamics simulations indicate that the <strong>1l</strong>-PfLDH and <strong>1k</strong>-PfDHFR-TS complex provides the best stability of protein interactions and structure, characterized by low Rg values, minimal RMSD fluctuations, and stable RMSF patterns in key residues. Physicochemical analysis confirms that all compounds comply with Lipinski's rules, supporting their candidacy as drug-like molecules.</div></div><div><h3>Conclusions</h3><div>This computational investigation identifies Isoindolinone-Hydrazide hybrids, particularly compounds <strong>1l</strong> (for PfLDH) and <strong>1k</strong> (for PfDHFR-TS), as promising <em>in silico</em> antimalarial inhibitor candidates. These findings provide a theoretical basis for future experimental validation to confirm their predicted antiplasmodial potential.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100990"},"PeriodicalIF":4.3,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.chphi.2025.100988
Usman Mohammed Saidu , Monika Srivastava , Abubakar Sadiq Umar , Serguei V. Savilov , Markas Diantoro
Perovskites have proved themselves to be the champion material in terms of producing highly efficient solar cells. But due to their instability in ambient condition and toxicity of lead the commercialization of perovskite solar cells has not possible till date. The usage of Artificial Intelligence and Machine learning in photovoltaics have paved new ways which leads to formation of new perovskite compositions and materials, optimized deposition techniques and also the predicted performance of the device. A descriptive review of the research in optimization of the perovskites for its application in solar cells and the various Artificial Intelligence and machine learning models used for these prediction studies has been described here.
{"title":"Artificial Intelligence-Based Applications in Perovskite Photovoltaic Cells","authors":"Usman Mohammed Saidu , Monika Srivastava , Abubakar Sadiq Umar , Serguei V. Savilov , Markas Diantoro","doi":"10.1016/j.chphi.2025.100988","DOIUrl":"10.1016/j.chphi.2025.100988","url":null,"abstract":"<div><div>Perovskites have proved themselves to be the champion material in terms of producing highly efficient solar cells. But due to their instability in ambient condition and toxicity of lead the commercialization of perovskite solar cells has not possible till date. The usage of Artificial Intelligence and Machine learning in photovoltaics have paved new ways which leads to formation of new perovskite compositions and materials, optimized deposition techniques and also the predicted performance of the device. A descriptive review of the research in optimization of the perovskites for its application in solar cells and the various Artificial Intelligence and machine learning models used for these prediction studies has been described here.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100988"},"PeriodicalIF":4.3,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145788323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The present investigation addresses the adsorptive response of octopamine neurotransmitter onto the surface of B12N12 nanocage with density functional theory (DFT) at B3LYP/6–311G(d,p) level of theory. Accordingly, the adsorption behaviour and electronic properties such as HOMO and LUMO energies, chemical potential, Fermi energy, and work function have been explored. The calculations consequences three possible configuration of octopamine@B12N12 nanohybrid offering configuration-(a) as the most favourable configuration with the adsorption energy value of -33.52 kcal/mol. The natural bond orbital (NBO) assessment revealed a charge transfer of 0.382 from octopamine to B12N12 nanocage, indicating the charge transfer direction from drug to cage. Also, the energy gap of considered nanocage shows reduction by 14% upon interaction with octopamine neurotransmitter. The influence of aqueous medium on the adsorption energy and electronic properties have been also considered.
{"title":"Theoretical investigation on interaction of octopamine neurotransmitter with BN nanocage","authors":"Tarun Yadav , Ehsan Shakerzadeh , Vetrivelan Vaithiyanathan , Vaibhav Jaiswal , Dileep Kumar Gupta , Anchit Modi , Pradeep Kumar","doi":"10.1016/j.chphi.2025.100989","DOIUrl":"10.1016/j.chphi.2025.100989","url":null,"abstract":"<div><div>The present investigation addresses the adsorptive response of octopamine neurotransmitter onto the surface of B<sub>12</sub>N<sub>12</sub> nanocage with density functional theory (DFT) at B3LYP/6–311G(d,p) level of theory. Accordingly, the adsorption behaviour and electronic properties such as HOMO and LUMO energies, chemical potential, Fermi energy, and work function have been explored. The calculations consequences three possible configuration of octopamine@B<sub>12</sub>N<sub>12</sub> nanohybrid offering configuration-(a) as the most favourable configuration with the adsorption energy value of -33.52 kcal/mol. The natural bond orbital (NBO) assessment revealed a charge transfer of 0.382<span><math><mrow><mo>|</mo><mi>e</mi><mo>|</mo></mrow></math></span> from octopamine to B<sub>12</sub>N<sub>12</sub> nanocage, indicating the charge transfer direction from drug to cage. Also, the energy gap of considered nanocage shows reduction by 14% upon interaction with octopamine neurotransmitter. The influence of aqueous medium on the adsorption energy and electronic properties have been also considered.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100989"},"PeriodicalIF":4.3,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.chphi.2025.100984
Rahul D. Jawarkar , Rachana Gautre , Shreya Dhakulkar , Abdul Samad , Umang Shah , Prashant K. Deshmukh , Sami AL Hussain , Magdi E.A. Zaki
This study reports the development and validation of a statistically robust Quantitative Structure–Activity Relationship (QSAR) model for predicting the antiproliferative activity of small-molecule compounds against the A549 human lung carcinoma cell line. The work outlines a systematic approach for constructing and evaluating a predictive QSAR framework that identifies key structural determinants governing cytotoxic efficacy. A curated dataset underwent rigorous preprocessing to eliminate redundant entries, salts, and non-human bioassay data, followed by conversion of IC₅₀ values to pIC₅₀ to ensure data uniformity. Molecular descriptors were computed using PyDescriptor and subsequently refined via both objective and subjective feature selection protocols implemented in QSARINS 2.2.4, resulting in the identification of eight optimal descriptors contributing to model performance. Among these, the most significant; com_spChyd_6A, com_Chyd_9A, fOringN3B, and n_sp3C_2B exhibited strong positive correlations with biological activity. These descriptors indicate that sp-hybridized hydrophobic carbon atoms near the molecular center of mass, increased overall hydrophobicity, and appropriately positioned nitrogen atoms enhance membrane permeability and receptor-binding affinity. In contrast, descriptors such as fNH₂B, fsp₂CnotringO₁B, and fspCC₅B were negatively correlated with activity, likely due to steric hindrance, diminished lipophilicity, and suboptimal electronic configurations. Mechanistic validation through matched molecular pair analysis confirmed the interpretability and chemical relevance of the selected descriptors, reinforcing the model’s internal consistency within its defined applicability domain. Residual diagnostics, along with Williams and Insubria plots, further validated the model’s statistical integrity, revealing minimal overfitting and a well-constrained applicability boundary. Collectively, these findings underscore the reliability and translational potential of the QSAR model as a rational design tool to guide future development of potent A549 inhibitors by emphasizing favorable structural motifs and excluding deleterious molecular features.
{"title":"Application of chemoinformatics and molecular simulations in lead optimization targeting A549 cell proliferation for lung cancer therapy","authors":"Rahul D. Jawarkar , Rachana Gautre , Shreya Dhakulkar , Abdul Samad , Umang Shah , Prashant K. Deshmukh , Sami AL Hussain , Magdi E.A. Zaki","doi":"10.1016/j.chphi.2025.100984","DOIUrl":"10.1016/j.chphi.2025.100984","url":null,"abstract":"<div><div>This study reports the development and validation of a statistically robust Quantitative Structure–Activity Relationship (QSAR) model for predicting the antiproliferative activity of small-molecule compounds against the A549 human lung carcinoma cell line. The work outlines a systematic approach for constructing and evaluating a predictive QSAR framework that identifies key structural determinants governing cytotoxic efficacy. A curated dataset underwent rigorous preprocessing to eliminate redundant entries, salts, and non-human bioassay data, followed by conversion of IC₅₀ values to pIC₅₀ to ensure data uniformity. Molecular descriptors were computed using PyDescriptor and subsequently refined via both objective and subjective feature selection protocols implemented in QSARINS 2.2.4, resulting in the identification of eight optimal descriptors contributing to model performance. Among these, the most significant; com_spChyd_6A, com_Chyd_9A, fOringN3B, and n_sp3C_2B exhibited strong positive correlations with biological activity. These descriptors indicate that sp-hybridized hydrophobic carbon atoms near the molecular center of mass, increased overall hydrophobicity, and appropriately positioned nitrogen atoms enhance membrane permeability and receptor-binding affinity. In contrast, descriptors such as fNH₂B, fsp₂CnotringO₁B, and fspCC₅B were negatively correlated with activity, likely due to steric hindrance, diminished lipophilicity, and suboptimal electronic configurations. Mechanistic validation through matched molecular pair analysis confirmed the interpretability and chemical relevance of the selected descriptors, reinforcing the model’s internal consistency within its defined applicability domain. Residual diagnostics, along with Williams and Insubria plots, further validated the model’s statistical integrity, revealing minimal overfitting and a well-constrained applicability boundary. Collectively, these findings underscore the reliability and translational potential of the QSAR model as a rational design tool to guide future development of potent A549 inhibitors by emphasizing favorable structural motifs and excluding deleterious molecular features.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100984"},"PeriodicalIF":4.3,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1016/j.chphi.2025.100987
Yanan Liu , Ji Zheng , Long Bao , Yuke Qi , Qian Zhang , Zhongpeng Wang
Photocatalytic is a promising technology for pollutants treatment, however, the practical application is still hindered by the lack of efficient photocatalysts. Herein, a novel Z-scheme g-C3N4/MoO3 (CN/MO) heterojunction photocatalyst was designed via in-situ calcination method for efficient degrading methylene blue (MB). The introduction of CN can greatly improve the light absorption capacity and accelerate the migration and separation efficiency of photoinduced e--h+ pairs, showing a significant enhancement in photocatalytic activity. Upon visible light irradiation, the optimal CN/MO composites exhibited superior MB removal efficiency (95 % within 25 min), which is 2.0 times and 3.3 times greater than those of pure CN and MO. In addition, the CN/MO composites showed excellent recycling stability. The radical experiments unveiled that the •OH, O2˙− and h+ play major roles in MB removal, then a Z-scheme degradation mechanism was proposed. This work provided new insights into the design of more efficient photocatalysts for environmental degradation applications.
{"title":"A CN/MO heterojunction with high stability for efficient environmental pollution removal","authors":"Yanan Liu , Ji Zheng , Long Bao , Yuke Qi , Qian Zhang , Zhongpeng Wang","doi":"10.1016/j.chphi.2025.100987","DOIUrl":"10.1016/j.chphi.2025.100987","url":null,"abstract":"<div><div>Photocatalytic is a promising technology for pollutants treatment, however, the practical application is still hindered by the lack of efficient photocatalysts. Herein, a novel Z-scheme g-C<sub>3</sub>N<sub>4</sub>/MoO<sub>3</sub> (CN/MO) heterojunction photocatalyst was designed via in-situ calcination method for efficient degrading methylene blue (MB). The introduction of CN can greatly improve the light absorption capacity and accelerate the migration and separation efficiency of photoinduced e<sup>-</sup>-h<sup>+</sup> pairs, showing a significant enhancement in photocatalytic activity. Upon visible light irradiation, the optimal CN/MO composites exhibited superior MB removal efficiency (95 % within 25 min), which is 2.0 times and 3.3 times greater than those of pure CN and MO. In addition, the CN/MO composites showed excellent recycling stability. The radical experiments unveiled that the •OH, O<sub>2</sub>˙<sup>−</sup> and h<sup>+</sup> play major roles in MB removal, then a Z-scheme degradation mechanism was proposed. This work provided new insights into the design of more efficient photocatalysts for environmental degradation applications.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100987"},"PeriodicalIF":4.3,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-03DOI: 10.1016/j.chphi.2025.100986
Santosh Kumar , Akula Umamaheswara Rao , Amit Kumar Chawla , Shikha Awasthi , Ratnesh K Pandey
Metal oxide semiconductor-based gas sensors have attracted widespread attention for the detection of toxic gases such as ammonia, hydrogen sulfide and nitrogen dioxide due to their simplicity, cost-effectiveness and sensitivity. This review presents a comprehensive analysis of recent advancements in SnO2, WO3 and ZnO based nanocomposites, emphasizing their structural modifications, heterojunction engineering, synthesis strategies and gas sensing mechanisms. Particular focus is given to heterojunction formation (like n-n, p–n, and p-p) which improves charge separation and modulates resistance, thereby enhancing sensor response. The integration of hierarchical nanostructures such as nanoflowers, nanotubes and hollow microspheres significantly improve surface-to-volume ratio, gas diffusion and active site availability. Doping with noble metals (such as Ag, Pt) and mixed-valence oxides (e.g., CeO2, FeCo2O4) further enhances sensitivity and environmental stability. Finally, this review identifies the most effective material combinations for the selective detection of the studied gases. This review also discusses the critical role of fabrication techniques such as sol-gel, hydrothermal, and electrospinning in tailoring morphology and performance. Challenges related to selectivity, humidity interference, long-term stability and scalability are addressed. This work aims to guide the design and optimization of next-generation gas sensors with improved sensitivity, selectivity and reliability for environmental and industrial applications.
{"title":"Exploring the Role of Metal Oxide Heterostructures for Next-Generation Gas Sensors: A Focus on NH3, H2S and NO2 gases","authors":"Santosh Kumar , Akula Umamaheswara Rao , Amit Kumar Chawla , Shikha Awasthi , Ratnesh K Pandey","doi":"10.1016/j.chphi.2025.100986","DOIUrl":"10.1016/j.chphi.2025.100986","url":null,"abstract":"<div><div>Metal oxide semiconductor-based gas sensors have attracted widespread attention for the detection of toxic gases such as ammonia, hydrogen sulfide and nitrogen dioxide due to their simplicity, cost-effectiveness and sensitivity. This review presents a comprehensive analysis of recent advancements in SnO<sub>2</sub>, WO<sub>3</sub> and ZnO based nanocomposites, emphasizing their structural modifications, heterojunction engineering, synthesis strategies and gas sensing mechanisms. Particular focus is given to heterojunction formation (like n-n, p–n, and p-p) which improves charge separation and modulates resistance, thereby enhancing sensor response. The integration of hierarchical nanostructures such as nanoflowers, nanotubes and hollow microspheres significantly improve surface-to-volume ratio, gas diffusion and active site availability. Doping with noble metals (such as Ag, Pt) and mixed-valence oxides (e.g., CeO<sub>2</sub>, FeCo<sub>2</sub>O<sub>4</sub>) further enhances sensitivity and environmental stability. Finally, this review identifies the most effective material combinations for the selective detection of the studied gases. This review also discusses the critical role of fabrication techniques such as sol-gel, hydrothermal, and electrospinning in tailoring morphology and performance. Challenges related to selectivity, humidity interference, long-term stability and scalability are addressed. This work aims to guide the design and optimization of next-generation gas sensors with improved sensitivity, selectivity and reliability for environmental and industrial applications.</div></div>","PeriodicalId":9758,"journal":{"name":"Chemical Physics Impact","volume":"12 ","pages":"Article 100986"},"PeriodicalIF":4.3,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145735333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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