Quantum Chemical Simulations Research Articles

A Review of Machine Learning in Organic Solar Cells

Organic solar cells (OSCs) are a promising renewable energy technology due to their flexibility, lightweight nature, and cost-effectiveness. However, challenges such as inconsistent efficiency and low stability limit their widespread application. Addressing these issues requires extensive experimentation to optimize device performance, a process hindered by the complexity of OSC molecular structures and device architectures. Machine learning (ML) offers a solution by accelerating material discovery and optimizing performance through the analysis of large datasets and prediction of outcomes. This review explores the application of ML in advancing OSC technologies, focusing on predicting critical parameters such as power conversion efficiency (PCE), energy levels, and absorption spectra. It emphasizes the importance of supervised, unsupervised, and reinforcement learning techniques in analyzing molecular descriptors, processing data, and streamlining experimental workflows. Concludingly, integrating ML with quantum chemical simulations, alongside high-quality datasets and effective feature engineering, enables accurate predictions that expedite the discovery of efficient and stable OSC materials. By synthesizing advancements in ML-driven OSC research, the gap between theoretical potential and practical implementation can be bridged. ML can viably accelerate the transition of OSCs from laboratory research to commercial adoption, contributing to the global shift toward sustainable energy solutions.

A study on free radical behaviors and reactions in supercritical water using quantum chemical simulation

A study on free radical behaviors and reactions in supercritical water using quantum chemical simulation

Raman and DFT study of non-covalent interactions in liquid benzophenone and its solutions

Analysis of intermolecular interactions in liquid benzophenone and its solutions in acetone and acetic acid by Raman spectroscopy and quantum-chemical simulation is presented. The results of the experiment show that in binary solutions of benzophenone, a red shift was observed for the C ˭ O stretching band, and a blue shift was observed for the C–H stretching and breathing bands. Such shifts were predicted to occur due to weak (non-classical) hydrogen bonds of C–H⋅⋅⋅O ˭ C type between benzophenone and solvent molecules. The nature and strength of solute-solvent interactions are discussed. The electron density distribution in benzophenone and its complexes with acetone and acetic acid molecules was visualized using the molecular electrostatic potential surface. The electronic properties of the molecular complexes were characterized using the frontier molecular orbitals and localization functions.

Transition metal complexes of N-furfuryl-N′-benzoylthiourea: A study of synthesis, antibacterial activities, quantum chemical calculations and molecular modeling simulations

Transition metal complexes of N-furfuryl-N′-benzoylthiourea: A study of synthesis, antibacterial activities, quantum chemical calculations and molecular modeling simulations

Study of anti-corrosion properties of ellagic acid and curcumin derived from plants in saline medium: Experimental, quantum chemical, Monte Carlo and Molecular Dynamic simulation

Study of anti-corrosion properties of ellagic acid and curcumin derived from plants in saline medium: Experimental, quantum chemical, Monte Carlo and Molecular Dynamic simulation

Computational Modeling of the Enzymatic Achmatowicz Rearrangement by Heme-Dependent Chloroperoxidase: Reaction Mechanism, Enantiopreference, Regioselectivity, and Substrate Specificity.

The chloroperoxidase from Caldariomyces fumago (CfCPO) catalyzes the oxidative ring expansion of α-heterofunctionalized furans via the Achmatowicz rearrangement, providing an elegant tool to convert furan rings into complex-prefunctionalized scaffolds. However, the mechanism of this transformation remains unclear. Herein, the CfCPO-catalyzed reaction of rac-1-(2-furyl)ethanol (1a) is studied by quantum chemical calculations and molecular dynamics simulations. The calculations reveal that the conversion follows the general mechanism of the Achmatowicz reaction. Notably, the binding of 1a to the enzyme's active site influences the Compound I (Cpd I) formation, and the (R)-1a enantiomer binding results in a lower barrier compared to (S)-1a, explaining the observed (R)-enantiopreference toward a racemic substrate. Additionally, due to the weaker steric hindrance between the porphyrin ring and substrate, the nucleophilic attack of Cpd I on the furan core of 1a is preferred at the less-substituted C4=C5 bond, providing a rationale for the experimentally observed regioselectivity. Finally, the bottleneck residues in the substrate delivery channel and also the active site surroundings are proposed to be responsible for the substrate specificity of CfCPO. This study lays a theoretical foundation for the rational design of new CPOs that catalyze the Achmatowicz rearrangement with a broader substrate spectrum or specific stereopreference.

Tale of Three Dithienylethenes: Following the Photocycloreversion with Ultrafast Spectroscopy and Quantum Dynamics Simulations.

Photocycloreversion reactions of three diarylethene derivatives whose structures differ only in the placement of two sulfur atoms in the cyclopentene rings are investigated. Despite the minuscule differences between the molecules, both the yields and times of the photoreactions vary considerably. Using UV-vis and infrared femtosecond spectroscopy and quantum chemical dynamics simulations, we elucidate the relationships among the quantum yield, electronic and vibrational relaxation time, and structural properties of the dithienylethene photoswitches. We show that the local aromaticity of the molecule's central ring could be one of the predictors of the quantum yield and the rate of cycloreversion. While from the perspective of electronic dynamics, the cycloreversion is completed within a few picoseconds at most, all three derivatives exhibit much longer (10-25 ps) nuclear rearrangement times that determine the actual times of stable photoproduct formation.

Computer‐aided ionic liquids design and molecular insight for chloromethane dehydration

AbstractIn the process of butyl rubber production, excessive water content in chloromethane has a significant impact on the conversion and molecular weight distribution of the products. In this work, a computer‐aided ionic liquids design method was used for solvent design in the chloromethane dehydration process. The generate‐and‐test method was utilized to solve the mixed‐integer nonlinear programming problem formed in the design process. A multilayer perceptron was trained to predict the surface tension of ionic liquids. Quantum chemical calculations and molecular dynamics simulations were employed to test the dehydration performance of several designed ionic liquids. A candidate was selected for experimental synthesis and characterization. The impact of different ionic liquids on the vapor–liquid equilibrium of water was measured to confirm the feasibility, which indicates that the designed ILs exhibit a better dehydration potential compared to the basement solvent, 1‐Ethyl‐3‐methylimidazolium tetrafluoroborate. Anions play a leading role in the dehydration process.

Selective Novel Metal‐Coordinated Biomedical Agents Encompassing Tetradentate Salen Ligand: Structural Elucidation, DFT Calculation, Cytotoxic, and Antioxidant Activities Supported by Molecular Docking Approach

ABSTRACTSeveral physicochemical and analytical methods were employed to elucidate the structural analysis of some novel complexes derived from the {3,4‐bis‐[(3‐ethoxy‐2‐hydroxy‐benzylidene)‐amino]‐phenyl}‐phenyl‐methanone (ESAB ligand). Decomposition point determination, elemental analysis (CHN), spectroscopy (IR, NMR, and mass spectrometry), conductivity, magnetic susceptibility, UV–Vis spectrum study, and theoretical investigations were among these methods. With conductance values ranging from 7.5 to 15.12 Ω−1 cm2 mol−1, molar conductance values showed that the Zn (II), Cu (II), and Ru (III) complexes are nonelectrolytes in fresh DMSO solutions, with the exception of the ESABRu complex, which is a monoelectrolyte. According to IR spectra, the ligand uses the (N & O) donor sites from the (C=N & C‐O) groups in the ligand moiety to coordinate through the metal ions in a tetradentate form. A 1:1 (metal:ligand) molar ratio was proposed by Job's approach based on analytical data from solution complexation. According to the stability constant (Kf) values, the complexes' stability order was found to be ESABRu > ESABCu > ESABZn. The pH profile showed that the complexes under study are stable throughout a broad pH range, usually between pH = 4 and pH = 10. The complexes' geometric structures and ligand coordination capabilities were inferred with the use of magnetic and electronic spectrum studies. The DFT method uses quantum chemical simulations to evaluate the electronic structures of the ligand under investigation and its complexes. The unbound ligand's B3LYP level, B3LYP/6/311G* degree, and the complexes' B3LYP/6/311G**/LANL2DZ functional categories were employed in the computations of the density function concept (DFT). The findings revealed the consistency between the experimental and DFT computations. Natural bond orbital (NBO) analysis was used to investigate bond strength between molecules' charge exchange, hyperconjugative connections, and molecular equilibrium. By computing the hyperpolarizability (β) and molecular polarizability (α) parameters, the ensuing nonlinear optical properties were investigated, leading to a number of surprising optical properties for the produced compounds. The antipathogenic activity of the generated materials was experimentally verified against a subset of gram (+) and gram (−) bacteria as well as some fungi using the agar well diffusion method. Additionally, hepatic cellular carcinomas, cells from colon and breast cancer, were utilized to test the cytotoxic activity of the ESAB ligand and its metal chelates. Furthermore, the examined compounds' ability to suppress the DPPH radical was examined. Additionally, simulations of molecular docking were performed to ascertain how the produced compounds attached to the specific protein binding sites.

Synthesis and properties of a new environmentally friendly bicyclic imidazoline quaternary ammonium salt as a corrosion inhibitor of carbon steel

Abstract A new corrosion inhibitor, environment-friendly bicyclic imidazoline quaternary ammonium salt (DL-IM), was synthesized using DL-aspartic acid, hydroxyethyl ethylenediamine, and benzyl chloride as the main raw materials. The amidation, cyclization, and quaternization reactions were carried out at 140 °C for 4 h, 220 °C for 3 h, and 70 °C for 3 h, respectively. The structure of DL-IM was characterized by infrared spectroscopy and nuclear magnetic hydrogen spectroscopy. The corrosion experiments of carbon steel sheets (American Petroleum Institute, API 5CT N80, primarily used in well drilling operations to protect the wellbore), protected with or without DL-IM, demonstrated that DL-IM had a good anti-corrosion performance (with the inhibition efficiency and corrosion rate of 97.13% and 0.6528 mm/a, respectively) in the 1 M HCl solution at 60 °C. DL-IM was a kind of cathodic protection-type corrosion inhibitor confirmed by Tafel curves. The analysis of adsorption kinetics by quantum chemical simulations demonstrated that the imidazoline ring in the DL-IM molecule can form covalent bonds with the empty d-orbitals of Fe through charge sharing. Moreover, the dipole moment of DL-IM is 1.3931 D (1 D = 3.34×10-30 C·m), suggesting a good hydrophobicity of DL-IM. Therefore, the adsorption film formed by DL-IM on the surface of N80 can effectively isolate the corrosive medium from N80. Thus, successful synthesis of DL-IM provides a new insight into the design and synthesis of the environment-friendly corrosion inhibitor with stronger corrosion inhibition effect.

Revealing a new mechanism of stable intersolubility of methanol-n-heptane blended fuel assisted by co-solvents at the microscopic molecular level: Insights and validation from quantum chemical simulation

Methanol, a promising green alternative to traditional fossil fuels, requires blending with high-energy fuels or additives due to its low energy density and cetane number. However, methanol’s high polarity often causes phase separation with other fuels, hindering its widespread use. Adding suitable co-solvents is a known method to address phase separation in fuel blends. For the first time, this study aims to reveal the microscopic molecular mechanism by which butanol, as a co-solvent, can improve the miscibility stability of methanol-gasoline blends. To simplify the analysis in this study, n-heptane, which is a single-component fuel was used as a representative of the multi-component gasoline. Firstly, experimental tests were conducted to investigate the miscibility of different blend ratios of methanol-n-heptane under the influence of different butanol isomers. Secondly, molecular simulation research through the Gaussian and Multiwfn software. Next, through Fourier transform infrared spectroscopy, the mutual solubility of ternary blends was studied. The results showed that the addition of butanol, particularly n-butanol (in comparison to isobutanol), could effectively stabilize the miscibility of anhydrous methanol and n-heptane. Molecular conformation simulations and infrared spectroscopy experiments revealed that the presence of butanol restructures the electrostatic interactions (hydrogen bonding) on the surface of methanol molecules, shielding their polarity. This allows the butanol and methanol molecules to associate more like non-polar species, enhancing their interaction with n-heptane through van der Waals forces, thereby improving the overall miscibility stability of the methanol and n-heptane. These findings offer new insights into the micro-molecular miscibility mechanism of methanol-gasoline blends, which is essential for the successful application of methanol as an alternative fuel.

Experimental and computational studies of cationic Gemini surfactants as corrosion inhibitors for carbon steel in 15% HCl.

In the process of oil and gas exploration, the corrosion of carbon steel pipes results in substantial economic losses, numerous casualties, environmental contamination, and resource waste. The advancement of highly efficient and stable corrosion inhibitors holds significant importance for protecting carbon steel from corrosion during oil and gas exploitation. In this study, two new cationic Gemini surfactants (2CncoesT, where n = 12, 14) were synthesized through a straightforward two-step reaction. Weight-loss tests demonstrated that the inhibition efficiency (ηw%) increases with the increase in temperature. Specifically, the maximum ηw% values for 2C12coesT and 2C14coesT were 98.0% and 98.3% respectively at 85 °C. The adsorption of these surfactants conformed to the Langmuir adsorption isotherm. Electrochemical measurements suggested that the two surfactants functioned as mixed-type inhibitors. The findings obtained from scanning electron microscopy (SEM) were consistent with the experimental outcomes that 2C12coesT and 2C14coesT are efficient corrosion inhibitors for the metal in an acidic environment. The quantum chemical investigation and molecular dynamics simulation (MD) further substantiated the experimental results and offered insights for a deeper comprehension of the inhibition mechanism of Gemini surfactants.

Deciphering the role of flutamide, fluorouracil, and furomollugin based ionic liquids in potent anticancer agents: Quantum chemical, medicinal, molecular docking and MD simulation studies

Deciphering the role of flutamide, fluorouracil, and furomollugin based ionic liquids in potent anticancer agents: Quantum chemical, medicinal, molecular docking and MD simulation studies

Chatbot-assisted quantum chemistry for explicitly solvated molecules.

Advanced computational chemistry software packages have transformed chemical research by leveraging quantum chemistry and molecular simulations. Despite their capabilities, the complicated design and the requirement for specialized computing hardware hinder their applications in the broad chemistry community. Here, we introduce AutoSolvateWeb, a chatbot-assisted computational platform that addresses both challenges simultaneously. This platform employs a user-friendly chatbot interface to guide non-experts through a multistep procedure involving various computational packages, enabling them to configure and execute complex quantum mechanical/molecular mechanical (QM/MM) simulations of explicitly solvated molecules. Moreover, this platform operates on cloud infrastructure, allowing researchers to run simulations without hardware configuration challenges. As a proof of concept, AutoSolvateWeb demonstrates that combining virtual agents with cloud computing can democratize access to sophisticated computational research tools.

Exploring the Synergistic Potential of Artificial Intelligence and Machine Learning in Chemistry

Machine learning (ML) and artificial intelligence (AI) have become specialists in different areas of chemistry. These technologies help to change the standard approaches to data analysis and molecular design along with the properties forecast. This review describes the interesting applications and increasing potential of AI and ML, specifically in drug discovery, chemical synthesis, material science, and computational chemistry. Computationally, the focus was on the application of AI algorithms to quantum chemistry simulations to predict properties of elements within a molecule, or possible reactions of molecules at a rate that would not have been possible manually. Moreover, AI-driven robotic synthesis platforms and experimental techniques have become less labor-intensive. The methods used for the identification of new chemical structures have improved in terms of speed. The benefits and the limitations of integrating AI, as well as the opportunities, are discussed in detail. In this review, it is also reiterated that there are risks that come with the integration of ML in chemistry and how interdisciplinary collaboration and data sharing are crucial to advancing in this field. In a single summary, this review demonstrates how the use of AI and ML can and will expand the horizons of chemical science and discovery.Keywords: Artificial Intelligence, Machine Learning, Drug Discovery, Chemical Synthesis, Materials Science, Computational Chemistry.

Mechanistic Insights Into NIR‐II AIEgens Boosted Multimodal Phototheranostics

AbstractExploiting single molecular species synchronously affording powerful second near‐infrared (NIR‐II) fluorescence, superior photoacoustic output, prominent reactive oxygen species generation, and satisfactory photothermal conversion is supremely appealing for phototheranostics, yet remains formidably challenging. In this work, electron donor/π‐bridge engineering is implemented on the basis of 6,7‐di(thiophen‐2‐yl)‐[1,2,5]thiadiazolo[3,4‐g]quinoxaline moiety. The optimal molecule, namely TPATO‐TTQ, is demonstrates to exhibit those notable features requested by exceptional phototheranostics, which are systematically elucidated through the depictions of excited‐state energy dissipation pathways and the influence of intramolecular motion on the photophysical properties, with assistances of quantum chemical calculation and molecular dynamic simulation. By utilizing TPATO‐TTQ nanoparticles, unprecedented performance on NIR‐II fluorescence‐photoacoustic‐photothermal trimodal imaging‐navigated type I photodynamic‐photothermal synergistic therapy to orthotopic breast cancer is authenticates by the precise tumor diagnosis and complete tumor ablation.

Piperine as a molecular bridge mediates a ternary coamorphous system of polyphenols with enhanced pharmaceutical properties.

The coamorphous formulations have attracted increasing interest due to enhanced solubility and bioavailability, together with synergistic pharmacological effects. In this study, a ternary coamorphous system of polyphenols was successfully prepared, wherein baicalein (Bai) and resveratrol (Res) were constructed into a single-phase coamorphous system mediated by piperine (Pip). FTIR and ss 13C NMR spectra together with quantum chemical calculation and molecular dynamics simulation suggested Pip as a molecular bridge connected Bai and Res molecules through π-π stacking and hydrogen bonding interactions. The configuration of coamorphous Bai-Pip-Res could minimize the system energy to facilitate its formation and enhance the stability. The ternary system showed 3.2, 4.3 and 5.3-fold increase in apparent solubilities of Bai, Res and Pip, and maintained the peak concentrations for at least 24 h. Compared to binary coamorphous systems, the ternary system exhibited superior physical stability under temperature and humidity conditions. Furthermore, coamorphous Bai-Pip-Res exhibited enhanced antibacterial activity, significant antioxidant ability and synergistic anti-inflammatory effect. This work offers a promising strategy to construct a ternary coamorphous delivery system with enhanced pharmaceutical properties by incorporating a molecular bridge, especially for components with the lack of intermolecular interactions.

Biomolecular Interaction of Carnosine and Anti-TB Drug: Preparation of Functional Biopeptide-Based Nanocomposites and Characterization through In Vitro and In Silico Investigations.

Host-directed therapies (HDTs) resolve excessive inflammation during tuberculosis (TB) disease, which leads to irreversible lung tissue damage. The peptide-based nanostructures possess intrinsic anti-inflammatory and antioxidant properties among HDTs. Native carnosine, a natural dipeptide with superior self-organization and functionalities, was chosen for nanoformulation. In the present work, multiscale self-assembly approaches of carnosine were developed using a solvent-mediated process (hexafluoro-2-propanol) and further linked with first-line anti-TB drugs. The organofluorine compound in a solvent is attributed to the self-assembling process with heteroatom acceptors in carnosine. In the carnosine-anti-TB drug nanocomposite, the functional moieties represent the involvement of hydrogen bonding and the electrostatic force of attraction. The minimum inhibitory concentration of carnosine-anti-TB drug composites represents an antimycobacterial effect on par with standard drugs. The silicon findings complemented the in vitro results through quantum chemical simulations, elucidating the respective binding pockets between putative Mtb drug targets and carnosine-anti-TB composites. These findings confirmed that the carnosine and anti-TB drug nanocomposites prepared through a solvent-mediated process act as a rational design for functional nanodelivery systems for sustainable TB therapeutics.

Computational insights into potent USP5 inhibitors based on multistep virtual screening and molecular dynamics simulation

USP5 is widely distributed in various malignant tumors and can regulate the stability and promoting tumor progression of many tumor-related proteins. However, there is still a lack of highly active USP5 inhibitors. Therefore, effective inhibitors were screened in the TCMIO database in this study. Three hit compounds, CHEMBL3645368, CHEMBL3689818, and CHEMBL2070208, were finally obtained by molecular docking, molecular fingerprint, quantum chemistry, and molecular dynamics simulation. Molecular docking results showed hit compounds had similar binding mode comparing with positive compound. Quantum chemistry and molecular dynamics results showed hit compounds had better binding energy and higher affinity than the positive compound. ADMET predicted hit compounds had low toxicity. These results all suggest CHEMBL3645368, CHEMBL3689818, and CHEMBL2070208 may inhibit USP5 and could be candidates for further exploration.

Molecular Design and Mechanism Study of Non-Activated Collectors for Sphalerite (ZnS) Based on Coordination Chemistry Theory and Quantum Chemical Simulation.

Sphalerite flotation is generally achieved by copper activation followed by xanthate collection. This study aims to propose a design idea to find novel collectors from the perspective of molecular design and prove the theoretical feasibility that the collector can effectively recover sphalerite without copper activation. To address this, 30 compounds containing different structures of sulfur atoms and different neighboring atoms were designed based on coordination chemistry. Twelve potential collectors were screened, and their properties and interactions with a hydrated sphalerite (110) surface were evaluated. Compound 27 (C2H4S22-) showed the greatest reactivity, suggesting that the double-coordination structure of two sulfhydryl groups is an effective molecular structure for direct sphalerite flotation. The DFTB+ and MD results demonstrate that 1,2-butanedithiol (C4H10S2), having a similar coordination structure to compound 27, has the potential to replace the traditional reagent scheme of sphalerite flotation. The strong reagent-surface interaction is attributed to the overlap of Zn 3d with S 3p orbitals, the most negative electrostatic potential, the relatively high EHOMO and low average local ionization energy, and the eliminated steric hindrance effect. It is expected that this study can provide a design idea for the targeted design and development of novel reagents for complex sulfide ore flotation.