Chemical Calculations Research Articles

H-atom-assisted formation of key radical intermediates in interstellar sugar synthesis

Context. Despite the identification of the smallest sugar molecule, glycolaldehyde (GA), in the interstellar medium (ISM), its mechanism of formation in the ISM is still not fully understood. A more profound understanding of the interstellar chemistry of GA and related molecules could provide insights into whether larger sugar molecules can also form and survive under such conditions. Aims. The primary objectives of this research are to delve into the sugar formation mechanism in the ISM, especially in dark molecular clouds; unravel intricate details of H-atom-mediated reactions involving glyoxal (GO), GA, and ethylene glycol (EG); and identify intermediates playing potential roles in the formation of larger sugars or serving as intermediates in the destruction reaction paths of sugar molecules. Methods. The study utilizes the para-H2 matrix isolation method with infrared (IR) spectroscopic detection and quantum chemical computations to investigate H-atom reactions of GO, GA, and EG at a low temperature. Results. Several radical products were spectroscopically identified that might be key active species in the interstellar formation of larger sugar molecules.

A novel imprinted porous liquid for lithium extraction

AbstractPorous liquids (PLs) are a novel material that combines the advantages of porous solids and liquid fluidity. In this study, we propose an imprinted porous liquid (IPL) with imprinted polymers as the porous framework and a mixture of TOP + FeCl3 as sterically hindered solvents. Quantum chemical computations and characterization results demonstrate the presence of unoccupied pore structure in IPLs. The prepared IPLs exhibit excellent selective adsorption and extraction performance for lithium extraction, achieving a Li/Mg separation factor of 1540 and a single‐stage Li+ extraction efficiency of 86%. The Li+ extraction efficiency remains above 84% even after eight cycles. Analytical characterization along with quantum chemical computations elucidates the mechanism underlying the coupling between extraction and adsorption in IPLs, enabling efficient lithium extraction. By combining imprinting technology with PLs, IPLs expand upon existing frameworks for PLs materials while providing new insights for designing functional solvents.

Insight into the corrosion resistance of mild steel in an acidic environment in the presence of an organic extract: Experimental and computational approach

Green corrosion inhibitors are crucial in lowering the rate at which metals corrode as well as the negative environmental effects of hazardous substances. Considering this, Curcuma longa (CL) root extract was used as an effective and safe corrosion inhibitor in this study. The inhibitory efficacy was thoroughly investigated using the weight loss (WL), open circuit potential (OCP), electrochemical impedance spectroscopy (EIS), and potentiodynamic polarization (PDP) techniques, respectively. The inhibitor was found to be effective at impeding the rate of deterioration of mild steel in 1 M HCl and 0.5 M H2SO4 environments. In a mixed-type mode, the CL reduced the anodic and cathodic reactions. However, in a 0.5 M H2SO4 environment, CL proved to be slightly more effective compared to a 1 M HCl environment. Inhibition efficiency values of 91.8 % (0.5 M H2SO4) and 89.6 % (1 M HCl) were obtained. The Langmuir adsorption isotherm (LAI) was used to validate the results. Some surface probe analysis such as scanning electron microscopy (SEM), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FR-IR), and X-ray photoelectron spectroscopy (XPS), were used to complement the electrochemical results. Quantum chemical computations confirmed some active sites on the molecular structures of a few selected active constituents of the CL extract.

Comparative study of Sombor index and its various versions using regression models for top priority polycyclic aromatic hydrocarbons

The aromatic compounds having structural configurations with two or more fused benzene rings are the polycyclic aromatic hydrocarbons (PAHs). Topological indices are valuable tools for studying the structure property relationships of PAHs and also helps in predicting various properties and activities. They find applications widely in computational chemistry, drug design and QSPR studies. This article focuses on analysing the potential predictive index for Sombor index (SO), elliptic Sombor index (ESO), Euler Sombor index (EU), reverse Sombor index (RSO), reverse elliptic Sombor index (RESO) and reverse Euler Sombor index (REU) using regression models for top priority 38 PAHs. From the study it is evident that, SO and RSO have proved to be potential predictive indices among the considered degree-based and reverse degree-based indices. The variation of best predictive index with minimal RMSE are plotted for linear, quadratic and cubic regression models for better understanding.

Making 2D Materials Sparkle in Energy Storage via Assembly.

ConspectusTwo-dimensional (2D) materials such as graphene and MXenes offer appealing opportunities in electrochemical energy storage due to their large surface area, tunable surface chemistry, and unique electronic properties. One of the primary challenges in utilizing these materials for practical electrodes, especially those with industrial-level thickness, is developing a highly interconnected and porous conductive network. This network is crucial for supporting continuous electron transport, rapid ion diffusion, and effective participation of all active materials in electrochemical reactions. Moreover, the demand for efficient energy storage in advanced electronic devices and electric vehicles has led to the need for not only thicker but also denser electrodes to achieve compact energy storage. Traditional densification methods often compromise between volumetric capacitance and ion-accessible surface area, which can diminish rate performance. As versatile building blocks, 2D materials can overcome these limitations through the assembly into complex superstructures such as 1D fibers, 2D thin films, and 3D porous networks, a capability less attainable by other nanomaterials.This Account explores the pathways from exfoliated 2D nanosheets to densely packed, yet porous assemblies tailored for compact energy storage. Focusing on graphene and MXenes, we delve into the intricate relationships between surface structure, assembly behaviors, and electrochemical performance. We emphasize the crucial role of surface chemistry and interfacial interactions in forming stable colloidal dispersions and subsequent macroscopic structures. Furthermore, we highlight how solvents, acting as spacers, are instrumental in microstructure formation and how capillary force-driven densification is essential for creating compact assemblies. With precise control over shrinkage, the customized dense assemblies can strike a balance between high packing density and sufficient porosity, ensuring efficient ion transport, mechanical stability, and high volumetric performance across various electrochemical energy storage technologies.Furthermore, we highlight the importance of understanding and manipulating the surface chemistry of 2D materials at the atomic level to optimize their assembly and enhance electrochemical behaviors. Advanced in situ characterizations with high temporal and spatial resolution are necessary to gain deeper insights into the complex assembly process. Moreover, the integration of machine learning and computational chemistry emerges as a promising method to predict and design new materials and assembly strategies, potentially accelerating the development of next-generation energy storage systems. Our insights into the assembly and densification of 2D materials provide a comprehensive foundation for future research and practical applications in compact, high-performance energy storage devices. This exploration sets the stage for a transformative approach to overcoming the challenges of current energy storage technologies, promising significant advancements in 2D materials in the field.

Spectroscopic elucidation, quantum chemical computations (FMO, HOMO–LUMO, MEP, NLO), and biological activity on some novel heterocyclic compounds using 3-substituted-6,8-dimethylchromones

The chemical transformations of substituted chromones 1a–c were examined toward some nucleophiles namely dimedone (R1), 4-hydroxycoumarin (R2) and 4-hydroxy-1-methylquinolin-2(1H)-one (R3). DFT computation at the B3LYP/6-311 G(d,p) level of theory was used to perform the theoretical computations for the produced compounds. HOMO and LUMO analyses were performed to determine the electronic charge distribution and reactivity of the molecules. Molecular electrostatic potential (MEP) surface analysis was utilized to predict the molecule’s reactive sites. Moreover, the studied compounds showed NLO characteristics, where they have first order hyperpolarizability greater than urea. In addition, the GIAO method was used to estimate the 1H-NMR and 13C-NMR chemical shifts; and the findings were compared with experimental values. Testing the generated compounds for antibacterial and anticancer activities revealed varied degrees of inhibitory effect. According to the Lipinski, Veber, and Egen rules, these compounds exhibit physicochemical properties.

On the Formation and Detectability of H2CNCN and Its Progenitors

New highly exothermic formation pathways incorporating both thermodynamic and kinetic control for the newly astronomically detected H2CNCN molecule are paired with extremely accurate quantum chemical rovibrational spectroscopic computations. The reactions between astronomically known CH2CN/CH2CCH + HNCN follow effectively identical pathways and proceed through stable intermediates and over deeply submerged transition states to form H2CNCN and HCN/HCCH coproducts. Similarly, the reaction between CH2CN and NCN− can also form H2CNCN, although this pathway first requires the initial formation of NCN−, which is currently undetected in space, via HNCN + CN−. This two-step mechanism uses the highly abundant CN− as the catalyst. Incredibly accurate quantum chemical spectroscopic data are reported for all reactants and products of these reactions, with errors between experimental values and the computations herein on the order of 0.1% or less. Anharmonic vibrational frequencies and intensities are also reported in order to guide experimental and observational searches for these molecules that have mostly been detected in the radio but may now be detectable via JWST.

Jupyter widgets and extensions for education and research in computational physics and chemistry

Interactive notebooks are a precious tool for creating graphical user interfaces and teaching materials. Python and Jupyter are becoming increasingly popular in this context, with Jupyter widgets at the core of the interactive functionalities. However, while packages and libraries which offer a broad range of general-purpose widgets exist, there is limited development of specialized widgets for computational physics, chemistry and materials science. This deficiency implies significant time investments for the development of effective Jupyter notebooks for research and education in these domains. Here, we present custom Jupyter widgets that we have developed to target the needs of these communities. These widgets constitute high-quality interactive graphical components and can be employed, for example, to visualize and manipulate data, or to explore different visual representations of concepts, clarifying the relationships existing between them. In addition, we discuss with one example how similar functionality can be exposed in the form of JupyterLab extensions, modifying the JupyterLab interface for an enhanced user experience when working with applications within the targeted scientific domains.

A novel angiotensin I-converting enzyme inhibitory peptide APPLRP from Grifola frondosa ameliorated the Ang II-induced vascular modeling in zebrafish model by mediating smooth muscle cells

Grifola frondosa has garnered significant popularity as an edible mushroom attributable to its exceptional taste and nutritional benefits. This study isolated APPLRP, a potent ACE-inhibitory peptide, from the alcohol-soluble fraction of Grifola frondosa. The underlying mechanisms of APPLRP in antihypertension were explored through computational chemistry, cell experiments, and zebrafish model. Results demonstrated that APPLRP was an active competitive ACE inhibitor (IC50 = 29.93 μM) that could bind to the active pocket S2 and S1′ of ACE. APPLRP exhibited resistance to pepsin and pancreatin digestion. In vitro experiments revealed that APPLRP significantly attenuated Ang II-induced VSMCs proliferation and migration by down-regulating AT1R expression and inhibiting ERK1/2 and STAT3 phosphorylation. APPLRP intervention significantly ameliorated myocardial fibrosis, as evidenced by reductions in cardiac output, blood flow velocity, and cardiac collagen deposition levels in Ang II-induced hypertensive zebrafish model. Furthermore, APPLRP improved vascular remodeling in hypertensive zebrafish, indicated by increased vessel diameter and decreased vessel wall thickness. Notably, APPLRP treatment resulted in down-regulation of ACE and up-regulation of ACE2 expression in the vessels of hypertensive zebrafish. These findings indicated that APPLRP was a representative component of Grifola frondosa peptides, and its antihypertensive effects were associated with ACE inhibition and the improvement of VSMCs-mediated vascular remodeling.

Observations of phosphorus-bearing molecules in the interstellar medium

The chemistry of phosphorus (31P) in space is particularly significant due to the key role it plays in biochemistry on Earth. Utilising radio and infrared spectroscopic observations, several key phosphorus-containing molecules have been detected in interstellar clouds, circumstellar shells, and even extragalactic sources. Among these, phosphorus nitride (PN) was the first P-bearing molecule detected in space, and still is the species detected in the largest number of sources. Phosphorus oxide (PO) and phosphine (PH3) were also crucial species due to their role both in chemical networks and in forming biogenic compounds. The still limited high-angular resolution observations performed so far are shading light on the geometrical distribution of these molecules, which represent crucial insights on their formation processes. Observations have also highlighted the challenges and complexities associated with detecting and understanding phosphorus chemistry in space, owing to the low elemental abundance of P relative to other elements. This review article provides a state-of-art picture of the observational results obtained so far on phosphorus compounds in the interstellar medium. Special attention is given to star-forming regions, and to their implications for our understanding of prebiotic chemistry and the potential for life beyond Earth. Our knowledge of the dominant formation and destruction pathways of the most abundant species has improved, but critical questions remain open, among which: what is (are) the main phosphorus carrier(s) in space? Upcoming new facilities are expected to contribute significantly to this field, offering opportunities to both detect new phosphorus-bearing molecules and enlarge the number of sources in which the chemistry of P can be studied. The synergy between observations, theoretical models, laboratory experiments, and computational chemistry is mandatory to significantly progress in our comprehension of the chemistry of this important but poorly studied chemical element.

Distinct vibrational motions promote disparate excited-state decay pathways in cofacial perylenediimide dimers.

A complex interplay of structural, electronic, and vibrational degrees of freedom underpins the fate of molecular excited states. Organic assemblies exhibit a myriad of excited-state decay processes, such as symmetry-breaking charge separation (SB-CS), excimer (EX) formation, singlet fission, and energy transfer. Recent studies of cofacial and slip-stacked perylene-3,4:9,10-bis(dicarboximide) (PDI) multimers demonstrate that slight variations in core substituents and H- or J-type aggregation can determine whether the system follows an SB-CS pathway or an EX one. However, questions regarding the relative importance of structural properties and molecular vibrations in driving the excited-state dynamics remain. Here, we use a combination of two-dimensional electronic spectroscopy, femtosecond stimulated Raman spectroscopy, and quantum chemistry computations to compare the photophysics of two PDI dimers. The dimer with 1,7-bis(pyrrolidin-1'-yl) substituents (5PDI2) undergoes ultrafast SB-CS from a photoexcited mixed state, while the dimer with bis-1,7-(3',5'-di-t-butylphenoxy) substituents (PPDI2) rapidly forms an EX state. Examination of their quantum beating features reveals that SB-CS in 5PDI2 is driven by the collective vibronic coupling of two or more excited-state vibrations. In contrast, we observe signatures of low-frequency vibrational coherence transfer during EX formation by PPDI2, which aligns with several previous studies. We conclude that key electronic and structural differences between 5PDI2 and PPDI2 determine their markedly different photophysics.

Advancements and Challenges in Chemoinformatics: From Drug Discovery to Natural Products Research

Chemoinformatics, an interdisciplinary field combining chemistry, computer science, and information technology, is revolutionising scientific research by using computational methods to analyse, interpret, and predict chemical and biological data. This review explores its pivotal role across drug discovery and natural product research, highlighting key methodologies and challenges. It is critical in drug discovery because it expedites the identification and optimization of drug candidates through techniques such as virtual screening, molecular docking, and quantitative structure-activity relationship (QSAR) studies. It also facilitates the integration of computational chemistry with experimental validation, improving predictions iteratively. Chemoinformatics helps with managing databases, virtually screening bioactive compounds, and figuring out structures through molecular dynamics simulations and metabolomics in the field of natural products research. These tools enable researchers to explore the therapeutic potential of indigenous medicinal plants and other natural sources, facilitating the discovery of novel bioactive molecules with potential pharmaceutical applications. However, challenges such as data quality, computational resources, and ethical considerations persist, particularly in regions with limited infrastructure and expertise. The integration of machine learning and big data analytics promises to further enhance predictive modelling and accelerate discoveries in chemoinformatics. Keywords: Chemoinformatics, Drug Discovery, Natural Products, Research

Pyridazine Derivatives: Molecular Docking, ADMET Prediction, and Synthesis for Antihypertensive Activity.

The drug discovery and development domain has witnessed remarkable advancements due to the integration of computational methods, particularly Computer-Aided Drug Design (CADD). Discovering and creating new drugs involves structural modifications to enhance their effectiveness and physical attributes. This frequently includes employing semisynthetic techniques to investigate structure-activity relationships thoroughly. Noticeable progress in molecular biology, computational chemistry, combinatorial chemistry, and highthroughput screening is steering transformative changes in the pharmaceutical industry. High blood pressure or hypertension, a significant health issue, elevates the chances of heart, kidney, and brain complications, among other health concerns. It's a leading cause of untimely mortality globally. Therefore, it is important to search for new antihypertensive compounds that have fewer side effects and higher therapeutic activity. Following molecular docking of the pyridazine derivatives, compounds were subjected to In-silico ADMET analysis. Subsequently, a low molecular weight compound was synthesized. Among the synthesized compounds characterization procedures include TLC, FT-IR, 1HNMR, and LC-MS techniques. Compound 8 exhibited the most favorable molecular docking results with alpha A1 and beta 1 adrenergic receptors. Compounds 3, 5, and 6 fulfilled the essential ADMET criteria. Subsequently, Compounds 3, 4, and 5 underwent additional synthesis and characterization procedures, including TLC, FT-IR, 1H-NMR, and LC-MS techniques. Similar behavior was observed in compounds 6, 8, 10, and 11, all violating Pfizer's 3/75 rules in terms of TPAS. Hydrazinolysis of these b-benzoyl propionic acids produced pyridazine, which was utilized in synthesizing pyridazine derivatives. TLC, FT-IR, 1HNMR, and LCMS have characterized the compounds.

Computational Design of a Novel Inhibitor Against COVID

Background: In recent years, in silico computational approaches have tremendously guided computational medicinal chemists and research scientists to analyze protein structures, kinetics, functions, and molecular interactions of the administered drugs. Objective: This study aimed to identify a novel inhibitor against SARS-CoV-2 using human CD26 and modeled spike protein through suitable in silico approaches. Methods: In this work, molecular docking and molecular dynamics simulation experiments were conducted to gain insights into the binding affinity and stability, respectively. The docked complex of CD26 with modeled spike protein showed higher binding affinity than the complex of CD26 with resolved spike protein due to the existence of strong interactions with the crucial amino acid residues of the target proteins. Results: The results of the molecular dynamics simulation demonstrated that CD26 with the modeled spike protein docked complex showed good stability when compared with the resolved protein. Conclusion: From this computational finding, it was also suggested that the structure was stable and would rapidly guide the discovery of potential inhibitors against COVID-19.

Structural Fine‐Tuning to Achieve Highly Fluorescent Organic and Water‐Soluble Thiazolo[5,4‐d]thiazole Chromophores

AbstractFluorescent molecular systems are important for various applications such as sensing of analytes, probes for biologically relevant processes and as optoelectronic materials. Achieving high fluorescence quantum yield across the spectrum of solvent polarity and in solid‐state is challenging in molecular materials. Herein, we present a strategy to achieve strongly fluorescent molecular materials based on weak intramolecular charge‐transfer (ICT) in a family of unsymmetrical donor‐thiazolo[5,4‐d]thiazole‐acceptor systems (both neutral and cationic). Detailed photophysical studies reveal that the delicate balance between the donor and acceptor result in high solution‐state fluorescence quantum yield (>80 %) in both polar protic and apolar solvents. Quantum chemical computations uncover a hitherto unappreciated insight that the extent of ICT is aptly represented by the change in Mulliken charges between the ground and excited state for different fragments rather than the classical approach of monitoring the change in dipole moment for the entire molecule. This insight rationalizes the observed photophysical properties and can have implications in the design of tuneable donor‐π‐acceptor systems.

Perspective on Theoretical and Experimental Advances in Atmospheric Photochemistry.

Research that explores the chemistry of Earth's atmosphere is central to the current understanding of global challenges such as climate change, stratospheric ozone depletion, and poor air quality in urban areas. This research is a synergistic combination of three established domains: earth observation, for example, using satellites, and in situ field measurements; computer modeling of the atmosphere and its chemistry; and laboratory measurements of the properties and reactivity of gas-phase molecules and aerosol particles. The complexity of the interconnected chemical and photochemical reactions which determine the composition of the atmosphere challenges the capacity of laboratory studies to provide the spectroscopic, photochemical, and kinetic data required for computer models. Here, we consider whether predictions from computational chemistry using modern electronic structure theory and nonadiabatic dynamics simulations are becoming sufficiently accurate to supplement quantitative laboratory data for wavelength-dependent absorption cross-sections, photochemical quantum yields, and reaction rate coefficients. Drawing on presentations and discussions from the CECAM workshop on Theoretical and Experimental Advances in Atmospheric Photochemistry held in March 2024, we describe key concepts in the theory of photochemistry, survey the state-of-the-art in computational photochemistry methods, and compare their capabilities with modern experimental laboratory techniques. From such considerations, we offer a perspective on the scope of computational (photo)chemistry methods based on rigorous electronic structure theory to become a fourth core domain of research in atmospheric chemistry.

A chemical reservoir computer

A chemical reservoir computer

Structure and intermolecular interactions in ionic liquid 1-ethyl-3-methylimidazolium bromide and its aqueous solutions investigated by vibrational spectroscopy and quantum chemical computations.

The recently developed efficient protocol to explicit quantum mechanical modeling of structure and IR spectra of liquids and solutions (S. A. Katsyuba, S. Spicher, T. P. Gerasimova, S. Grimme, J. Phys. Chem. B 2020, 124, 6664) is applied to ionic liquid (IL) 1-ethyl-3-methylimidazolium bromide (EmimBr), its C2-deuterated analog [Emim-d]Br and its aqueous solutions. It is shown that the solvation strongly modifies frequencies and IR intensities of the CH/CD stretching vibrations (νCH/νCD) of the imidazolium ring. The main vibrational spectroscopic features of the neat IL are reproduced by the simulations for a cluster (EmimBr)9, in which all three imidazolium CH moieties of the solvated cation form short contacts with three Br- anions, and another two Br- anions are located on top and bottom of imidazolium ring. Cluster models of aqueous solutions reproduce the experimental vibrational frequencies of actual solutions, provided that the Br- anion of solvated contact ion pair (CIP) is situated on top of imidazolium ring, and CH/CD moieties of the latter participate in short contacts with surrounding water molecules. Both structural and spectroscopic analysis allow to interpret the short contacts CH/CD⋯Br- and CH/CD⋯OH2 as hydrogen bonds of approximately equal strength. Enthalpies of bonding of these liquid-state H-bonds, estimated with the use of empirical correlations, amount to ca. 1.4 kcal⋅mol-1, while the analogous estimates obtained for the gas-phase charged species [Emim]2Br+ increase to 5.6 kcal⋅mol-1. It is shown that formation of solvent-shared ion pair (SIP) in aqueous solution, where the counterions of IL are separated by two water molecules H-bonded to a Br- anion, produces frequency shifts ΔνCH/CD, strongly different from the case of CIP formation. This difference can be used for IR/Raman spectroscopic differentiation of the type of solvated ion pairs of EmimBr or other related ILs.

Application of Mechanistic Multiparameter Optimization and Large-Scale In Vitro to In Vivo Pharmacokinetics Correlations to Small-Molecule Therapeutic Projects.

Computational chemistry and machine learning are used in drug discovery to predict the target-specific and pharmacokinetic properties of molecules. Multiparameter optimization (MPO) functions are used to summarize multiple properties into a single score, aiding compound prioritization. However, over-reliance on subjective MPO functions risks reinforcing human bias. Mechanistic modeling approaches based on physiological relevance can be adapted to meet different potential key objectives of the project (e.g., minimizing dose, maximizing safety margins, and/or minimizing drug-drug interaction risk) while retaining the same underlying model structure. The current work incorporates recent approaches to predict in vivo pharmacokinetic (PK) properties and validates in vitro to in vivo correlation analysis to support mechanistic PK MPO. Examples of use and impact in small-molecule drug discovery projects are provided. Overall, the mechanistic MPO identifies 83% of the compounds considered as short-listed for clinical experiments in the top second percentile, and 100% in the top 10th percentile, resulting in an area under the receiver operating characteristic curve (AUCROC) > 0.95. In addition, the MPO score successfully recapitulates the chronological progression of the optimization process across different scaffolds. Finally, the MPO scores for compounds characterized in pharmacokinetics experiments are markedly higher compared with the rest of the compounds being synthesized, highlighting the potential of this tool to reduce the reliance on in vivo testing for compound screening.

Perspectives on aqueous organic redox flow batteries

Aqueous organic redox flow batteries (AORFBs) have pioneered new routes for large-scale energy storage. The tunable nature of redox-active organic molecules provides a robust foundation for creating innovative AORFBs with exceptional performance. Molecular engineering endows various organic molecules with considerable advantages in solubility, stability, and redox potential. Advanced characterizations have enabled a comprehensive understanding of the redox reaction and degradation mechanisms of these organic molecules. Computational chemistry and machine learning have guided the development of new organic molecules. The practical application of AORFBs will depend on the complementary efforts of multiple parties. This paper consolidates the current design principles of molecular engineering, degradation mechanisms, characterization techniques, and the utilization of computational chemistry. It also offers perspectives and forecasts the necessary attributes and strategic efforts for the next-generation AORFBs, aiming to provide the research community with a deeper understanding.