Molecular Cluster Model Research Articles

Atomically precise Cu32 nanoclusters with selenide doping: Synthesis, bonding, and catalysis

AbstractCopper nanoclusters with stable compositions and precise structures have long been sought after, as they possess properties that are absent in gold and silver counterparts. However, the creation of copper nanoclusters with novel compositions, structures, and functionalities remains largely unexplored in the literature. In this study, we demonstrate that selenide doping is an effective method for fabricating stable copper nanostructures through controlled synthesis and structure determination of a copper–selenide nanocluster. The nanocluster of [Cu32Se7(BnSe)18(PPh3)6]+ (denoted as Cu32Se7, Bn is benzyl) has been prepared by reducing copper salts in the presence of organic diselenides. The atomic structure of the Cu32Se7 cluster, accurately determined through single‐crystal X‐ray diffraction, reveals a core–shell arrangement of Cu20Se7@Cu12(BnSe)18(PPh3)6, where Se2− anions are well dispersed in the Cu20 framework. Notably, this cluster represents a rare example of copper–selenide semiconductor nanoclusters. Experimental and theoretical analysis shows strong interactions between Se ligands and metal atoms, resulting in high stability of the Cu32Se7 cluster. Furthermore, the cluster exhibits excellent catalytic performance in the hydroboration reaction of alkynes, producing a range of vinylboron compounds with adjustable structures and functions. Importantly, the cluster undergoes no structural or nuclearity changes during the reaction, as confirmed by extended X‐ray absorption fine structure and X‐ray photoelectron spectroscopy studies. This study not only presents a molecular cluster model highlighting the effectiveness of selenide dopants in fabricating new copper nanostructures but also paves the way for utilizing stable copper nanoclusters in diverse and exciting areas beyond catalysis.

Electrocatalytic Performance of 2D Monolayer WSeTe Janus Transition Metal Dichalcogenide for Highly Efficient H2 Evolution Reaction.

Nowadays, the development of clean and green energy sources is the priority interest of research due to increasing global energy demand and extensive usage of fossil fuels, which create pollutants. Hydrogen has the highest energy density by weight among all chemical fuels. For the commercial-scale production of hydrogen, water electrolysis is the best method, which requires an efficient, cost-effective, and earth-abundant electrocatalyst. Recent studies have shown that the 2D Janus transition metal dichalcogenides (JTMDs) are promising materials for use as electrocatalysts and are highly effective for electrocatalytic H2 evolution reaction (HER). Here, we report a 2D monolayer WSeTe JTMD, which is highly effective toward HER. We have studied the electronic properties of 2D monolayer WSeTe JTMD using the periodic hybrid DFT-D method, and a direct electronic band gap of 2.39 eV was obtained. We have explored the HER pathways, mechanisms, and intermediates, including various transition state (TS) structures (Volmer TS, i.e., H*-migration TS, Heyrovsky TS, and Tafel TS) using a molecular cluster model of the subject JTMD noted as W10Se9Te12. The present calculations reveal that the 2D monolayer WSeTe JTMD is a potential electrocatalyst for HER. It has the lowest energy barriers for all the TSs among other TMDs. It has been shown that the Heyrovsky energy barrier (= 8.72 kcal mol-1) in the case of the Volmer-Heyrovsky mechanism is larger than the Tafel energy barrier (= 3.27 kcal mol-1) in the Volmer-Tafel mechanism. Hence, our present study suggests that the formation of H2 is energetically more favorable via the Volmer-Tafel mechanism. This study helps to shed light on the rational design of 2D single-layer JTMD, which is highly effective toward HER, and we expect that the present work can be further extended to other JTMDs to find out the improved electrocatalytic performance.

Tailoring Se-rich glassy arsenoselenides employing the nanomilling platform

By XRPD analysis related to diffuse peak-halos in Se-rich glassy AsxSe100-x, the high-energy nanomilling driven reamorphization in these substances is recognized as molecular-to-network transformations of Se chains bridging cation polyhedrons (like AsSe3/2 pyramids) from preferential cis- to trans-configurated topology. At the medium-range structure, the process of reamorphization is revealed as enhancement in the intermediate-range ordering of these glasses due to high-angular shifted and broadened first sharp diffraction peak (FSDP) accompanied by suppression in extended-range ordering due to high-angular shifted but narrowed principal diffraction peak (PDP), so that peak-halos become more distinguishable after nanomilling. Principal trend in the XRPD patterns of glassy arsenoselenides with growing Se content is revealed as suppression in intermediate-range ordering accompanied by enhancement in extended-range ordering, resulting in more overlapped peak-halos. Irregular sequence of randomly distributed cis- and trans-configurated linkages in Se-rich g-AsxSe100-x is visualized by ab initio quantum-chemical modeling of molecular and chain-like network clusters.

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning.

Computational modeling of atmospheric molecular clusters requires a comprehensive understanding of their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, a collection of automated scripts that facilitate and streamline molecular cluster modeling workflows. Jammy Key handles file manipulations between varieties of integrated third-party programs. The framework is divided into three main functionalities: (1) Jammy Key for configurational sampling (JKCS) to perform systematic configurational sampling of molecular clusters, (2) Jammy Key for quantum chemistry (JKQC) to analyze commonly used quantum chemistry output files and facilitate database construction, handling, and analysis, and (3) Jammy Key for machine learning (JKML) to manage machine learning methods in optimizing molecular cluster modeling. This automation and machine learning utilization significantly reduces manual labor, greatly speeds up the search for molecular cluster configurations, and thus increases the number of systems that can be studied. Following the example of the Atmospheric Cluster Database (ACDB) of Elm (ACS Omega, 4, 10965-10984, 2019), the molecular clusters modeled in our group using the Jammy Key framework have been stored in an improved online GitHub repository named ACDB 2.0. In this work, we present the Jammy Key package alongside its assorted applications, which underline its versatility. Using several illustrative examples, we discuss how to choose appropriate combinations of methodologies for treating particular cluster types, including reactive, multicomponent, charged, or radical clusters, as well as clusters containing flexible or multiconformer monomers or heavy atoms. Finally, we present a detailed example of using the tools for atmospheric acid-base clusters.

Модифицированные бороуглеродные нанотрубки как эффективные сенсорные датчики контроля загрязнения окружающей среды

Recently, more and more people have become aware of the need to protect the environment and find new ways to protect our planet from various types of pollution. In this regard, science and technology play an important role in finding new solutions to protect the environment. One innovative development is boron-carbon nanotubes, which contain equal amounts of boron and carbon atoms. Modification of such nanotubes with an amine group would allow to use them for creation of highly sensitive sensor devices, which would help to control the levels of lithium, sodium, potassium in the environment and prevent their negative impact on nature and human health. In this article, a theoretical study of the sensing properties of a functionalized amino-group boron-carbon nanotube of the zig-zag type (6.0) containing equal amounts of carbon and boron is discussed. Such a nanotube could act as an element of a sensor device for environmental protection. The simulation was performed within a molecular cluster model using the DFT computational method, the B3LYP functional, and the 6-31G basis set. It is concluded that the system can be used to detect the presence of alkali metal atoms.

Quantum chemical modeling of atmospheric molecular clusters involving inorganic acids and methanesulfonic acid

Atmospheric molecular cluster formation is the first stage toward aerosol particle formation. Despite intensive progress in recent years, the relative role of different vapors and the mechanisms for forming clusters is still not well-understood. Quantum chemical (QC) methods can give insight into the cluster formation mechanisms and thereby yield information about the potentially relevant compounds. Here, we summarize the QC literature on clustering involving species such as sulfuric acid, methanesulfonic acid, and nitric acid. The importance of iodine species such as iodous acid (HIO2) and iodic acid (HIO3) in atmospheric cluster formation is an emerging topic, and we critically review the recent literature and give our view on how to progress in the future. We outline how machine learning (ML) methods can be used to enhance cluster configurational sampling, leading to a massive increase in the cluster compositions that can be modeled. In the future, ML-boosted cluster formation could allow us to comprehensively understand complex cluster formation with multiple pathways, leading us one step closer to implementing accurate cluster formation mechanisms in atmospheric models.

Development of molecular cluster models to probe pyrite surface reactivity.

The recent discovery that anaerobic methanogens can reductively dissolve pyrite and utilize dissolution products as a source of iron and sulfur to meet their biosynthetic demands for these elements prompted the development of atomic-scale nanoparticle models, as maquettes of reactive surface sites, for describing the fundamental redox steps that take place at the mineral surface during reduction. The given report describes our computational approach for modeling n(FeS2 ) nanoparticles originated from mineral bulk structure. These maquettes contain a comprehensive set of coordinatively unsaturated Fe(II) sites that are connected via a range of persulfide (S2 2- ) ligation. In addition to the specific maquettes with n = 8, 18, and 32 FeS2 units, we established guidelines for obtaining low-energy structures by considering the pattern of ionic, covalent, and magnetic interactions among the metal and ligand sites. The developed models serve as computational nano-reactors that can be used to describe the reductive dissolution mechanism of pyrite to better understand the reactive sites on the mineral, where microbial extracellular electron-transfer reactions can occur.

On the Short-Range Nature of Cooperativity in Hydrogen-Bonded Large Molecular Clusters.

The variation in the hydrogen bond (HB) strength has considerable consequences on the physicochemical properties of molecular clusters. Such a variation mainly arises due to the cooperative/anti-cooperative networking effect of neighboring molecules connected by HBs. In the present work, we systematically study the effect of neighboring molecules on the strength of an individual HB and the respective cooperativity contribution toward each of them in a variety of molecular clusters. For this purpose, we propose a use of a small model of a large molecular cluster called the spherical shell-1 (SS1) model. This SS1 model is constructed by placingg the spheres of an appropriate radius centered on X and Y atoms of the X-H···Y HB under consideration. The molecules falling within these spheres constitute the SS1 model. Utilizing this SS1 model, the individual HB energies are calculated within the molecular tailoring approach-based framework and the results are compared with their actual counterparts. It is found that the SS1 is a reasonably good model of large molecular clusters, providing 81-99% of the total HB energy estimated using the actual molecular clusters. This in turn suggests that the maximum cooperativity contribution toward a particular HB is due to the fewer number of molecules (in the SS1 model) directly interacting with two molecules involved in its formation. We further demonstrate that the remaining part of the energy or cooperativity (∼1 to 19%) is captured by the molecules falling in the second spherical shell (SS2) centered on the hetero-atom of the molecules in the SS1 model. The effect of increasing size of a cluster on the strength of a particular HB, calculated by the SS1 model, is also investigated. The calculated value of the HB energy remains unchanged with the increase in the size of a cluster, emphasizing the short-ranged nature of the HB cooperativity in neutral molecular clusters.

Revealing the Superior Electrocatalytic Performance of 2D Monolayer WSe2 Transition Metal Dichalcogenide for Efficient H2 Evolution Reaction

AbstractH2 evolution reaction (HER) requires an electrocatalyst to reduce the reaction barriers for the efficient production of H2. 2D transition metal dichalcogenides (2D TMDs) have emerged as a pinnacle group of materials for many potential applications, including HER. In this work, a pristine 2D monolayer WSe2 TMD is computationally designed using the first principle‐based hybrid density functional theory (DFT) to investigate its structural, electronic properties and the electrocatalytic performance for HER. The possible Volmer‐Heyrovsky and Volmer‐Tafel reaction mechanisms for HER at the W‐edge of the active site of WSe2 are studied by using a nonperiodic finite molecular cluster model W10Se21. The study shows that the pristine 2D monolayer WSe2 follows either the Volmer‐Heyrovsky or the Volmer‐Tafel reaction mechanisms with a single‐digit low reaction barrier about 6.11, 8.41 and 6.61 kcal mol−1 during the solvent phase calculations of H•‐migration, Heyrovsky and Tafel transition (TS) states, respectively. The lower reaction barriers, high turnover frequency (TOF) ≈ 4.24 × 106 s−1 and 8.86 × 107 s−1 during the Heyrovsky and Tafel reaction steps and the low Tafel slope 29.58 mV dec−1 confirm that the pristine 2D monolayer WSe2 might be a promising alternative to platinum group metals (PGM) based electrocatalyst.

Two-Step ONIOM Method for the Accurate Estimation of Individual Hydrogen Bond Energy in Large Molecular Clusters.

The study of molecular clusters to understand the properties of condensed systems has been the subject of immense interest. To get insight into these properties, the knowledge of various noncovalent interactions present in these molecular clusters is indispensable. Our recently developed molecular tailoring approach-based (MTA-based) method for the estimation of the individual hydrogen bond (HB) energy in molecular clusters is useful for this purpose. However, the direct application of this MTA-based method becomes progressively difficult with the increase in the size of the cluster. This is because of the difficulty in the evaluation of single-point energy at the correlated level of theory. To overcome this caveat, herein, we propose a two-step method within the our own N-layer integrated molecular orbital molecular mechanics (ONIOM) framework. In this method, the HB energy evaluated by the MTA-based method employing the actual molecular cluster at a low Hartree-Fock (HF) level of theory is added to the difference in the HB energies evaluated by the MTA-based method, employing an appropriate small model system, called the shell-1 model, calculated at high (MP2) and low (HF) levels of theory. The shell-1 model of a large molecular cluster is made up of only a few molecules that are in direct contact (by a single HB) with the two molecules involved in the formation of an HB under consideration. We tested this proposed two-step ONIOM method to estimate the individual HB energies in various molecular clusters, viz., water (Wn, n = 10-16, 18 and 20), (H2O2)12, (H2O3)8, (NH3)n and strongly interacting (HF)15 and (HF)m(W)n clusters. Furthermore, these estimated individual HB energies by the ONIOM method are compared with those calculated by the MTA-based method using actual molecular clusters. The estimated individual HB energies by the ONIOM method, in all these clusters, are in excellent linear one-to-one agreement (R2 = 0.9996) with those calculated by the MTA-based method using actual molecular clusters. Furthermore, the small values of root-mean-square deviation (0.06), mean absolute error (0.04), |ΔEmax| (0.21) and Sε (0.06) suggest that this two-step ONIOM method is a pragmatic approach to provide accurate estimates of individual HB energies in large molecular clusters.

Computational Studies on the Interaction of Organophosphorus Pesticides with Acetylcholinesterase and Butyrylcholinesterase: Quantum Chemical Cluster Model and HSAB Approaches

In the present study, the interaction between organophosphorus pesticides and cholinesterase enzymes was investigated by quantum chemical cluster model and hard-soft acid-base (HSAB) approaches. The computational results of the equilibrium structure and reaction enthalpy were used to decipher the mechanism of organophosphorus pesticides coumaphos, dicrotophos, phorate, and terbufos, which interacted with the molecular cluster models of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. In addition, the HOMO-LUMO energy gap and the HSAB descriptors prove that AChE has outstanding electron acceptability, which is suitable as a biosensing material. In terms of the calculated electronic spectrum, because the energy level of the ground state and the excited state are changed after adding pesticides with enzymes, a significant red shift phenomenon will occur.

Modified boron-carbon nanotubes as effective sensor devices for environmental pollution control

In this article, a theoretical study of the sensing properties of a functionalized amino-group boron-carbon nanotube of the zig-zag type (6.0) containing equal amounts of carbon and boron is discussed. Such a nanotube could act as an element of a sensor device for environmental protection. The simulation was performed within a molecular cluster model using the DFT computational method, the B3LYP functional and the 6-31G basis set. The main characteristics of nanotube functionalization, its sorption and sensory activity with respect to the alkali metal atoms Li, Na, and K are obtained. It is concluded that the system can be used to detect the presence of alkali metal atoms.

A quantum chemical study on the anti-SARS-CoV-2 activity of TMPRSS2 inhibitors.

Nafamostat and camostat are known to inhibit the spike protein-mediated fusion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by forming a covalent bond with the human transmembrane serine protease 2 (TMPRSS2) enzyme. Previous experiments revealed that the TMPRSS2 inhibitory activity of nafamostat surpasses that of camostat, despite their structural similarities; however, the molecular mechanism of TMPRSS2 inhibition remains elusive. Herein, we report the energy profiles of the acylation reactions of nafamostat, camostat, and a nafamostat derivative by quantum chemical calculations using a combined molecular cluster and polarizable continuum model (PCM) approach. We further discuss the physicochemical relevance of their inhibitory activity in terms of thermodynamics and kinetics. Our analysis attributes the strong inhibitory activity of nafamostat to the formation of a stable acyl intermediate and its low activation energy during acylation with TMPRSS2. The proposed approach is also promising for elucidating the molecular mechanisms of other covalent drugs.

The Magnetic Behaviour of CoTPP Supported on Coinage Metal Surfaces in the Presence of Small Molecules: A Molecular Cluster Study of the Surface trans-Effect.

Density functional theory, combined with the molecular cluster model, has been used to investigate the surface trans-effect induced by the coordination of small molecules L (L = CO, NH3, NO, NO2 and O2) on the cobalt electronic structure of cobalt tetraphenylporphyrinato (CoTPP) surface-supported on coinage metal surfaces (Cu, Ag, and Au). Regardless of whether L has a closed- or an open-shell electronic structure, its coordination to Co takes out the direct interaction between Co and the substrate eventually present. The CO and NH3 bonding to CoTPP does not influence the Co local electronic structure, while the NO (NO2 and O2) coordination induces a Co reduction (oxidation), generating a 3d8 CoI (3d6 CoIII) magnetically silent closed-shell species. Theoretical outcomes herein reported demonstrate that simple and computationally inexpensive models can be used not only to rationalize but also to predict the effects of the Co–L bonding on the magnetic behaviour of CoTPP chemisorbed on coinage metals. The same model may be straightforwardly extended to other transition metals or coordinated molecules.

Поверхностно-модифицированные нитрогруппой бороуглеродные BC5 нанотрубки как элемент сенсорного устройства: теоретические исследования

The problem of modification of boron-carbon nanotubes (BCNT) by functional groups is relevant in connection with the intensive development of the nano industry, in particular, nano- and microelectronics. For example, a modified nanotube can be used as an element of a sensor device for detecting microenvironments of various substances, in particular metals included in salts and alkalis. The paper discusses the possibility of creating a high-performance sensor using single-layer boron-carbon nanotubes as a sensitive element, the surface of which is modified with a functional nitro group -NO2. Quantum-chemical studies of the process of attaching a nitro group to the outer surface of a single-layer boron-carbon nanotube (BCNT) of type (6, 6) were carried out, which proved the possibility of modifying the BCNT and the formation of a bond between the group -NO2 and the carbon atom of the surface of the nanotube. The results of computer simulation of interaction of surface-modified boron-carbon nanotube with alkali metal atoms (lithium, sodium, potassium) are presented. The sensory interaction of the modified boron-carbon nanosystem with the selected metal atoms was investigated, which proved the possibility of identifying these atoms using a nanotubular system that can act as an element of the sensor device. When reacting with alkali metal atoms in the “BСNT+NO 2” complex, the number of basic carriers increases, due to the transfer of electron density from metal atoms to modified BСNT. The results presented in this paper were obtained using the molecular cluster model and the calculated DFT method with exchange-correlation functionality B3LYP (valence-split basis set 6-31G).

Исследование взаимодействия кислорода с поверхностью боросодержащих нанотрубок

Studies of semiconductor carbon nanotubes show that they are extremely sensitive to the chemical environment, and the effects of oxygen drastically change their properties. It has been found that narrow-zone semiconductor carbon tubes can be converted into an apparent metal by such action. Since other types of nanotubes, such as boron-carbon nanotubes of the BC3 type and boron-nitride BN nanotubes, are of great interest, it seems important to investigate whether they are capable of absorbing atomic and molecular oxygen. The study was conducted using the MNDO calculation method within molecular and ion-nested covalent-cyclic cluster models. The results of the study of the interaction of atomic and molecular oxygen with the external surfaces of boron-carbon (BC3), boron-nitride (BN) and boron nanotubes are considered: chair (n, n) and zigzag (n, 0) type. The study was performed by the MNDO method as part of a covalent-cyclic cluster model with embedded ions. Optimal geometry of adsorption complexes is determined and their main electronic and energy properties are described. Boron-carbon nanotubes have been shown to be better oxygen adsorbents than other types of nanotubes considered.

Surface Carboxylation of a Boron-Carbon BC<sub>5</sub> Nanotube in the Development of Sensor Devices

This article discusses the possibility of the fabrication of a highly sensitive sensor based on single-walled boron-carbon BC5 nanotubes surface modified with functional carboxyl groups (-COOH). The sensor potential for detection of alkali (lithium, potassium, and sodium) metals were investigated. The results of computer simulation of the interaction process between the sensor and an arbitrary surface of the modified tube containing atoms of the studied metals are presented. The carboxylated BC5 nanotube and a similarly modified BC3 nanotube was compared. The effect of boron atoms on sensory properties of the obtained system is concluded. The calculations were carried out within the framework of the density functional theory (DFT) method using the molecular cluster model. It has been proved that surface-modified boron-carbon nanotubes by carboxyl group show high sensitivity for the metal atoms under study and can be used as the sensor device.

Surface-modified boroncarbon BC5 nanotube with amine group as a sensor device element: theoretical research

The modification of boron-carbon nanotubes by functional groups is relevant in connection with the intensive development of the nano-industry, in particular, nano- and microelectronics. The thus modified nanotube can be used as an element of a sensor device for detecting micro amounts of various substances, for example metals included in salts and alkalis. The possibility of creating a highly effective sensor based on a single-layer boron-carbon ВС5 nanotube with a surface modified functional amine group (—NH2) is being discussed in this paper. Results of quantum-chemical studies showed that the functional amine group connecting to the boron-carbon nanotube (BCNT) type (6, 0) at a distance of 0.16 nm (when modified to both a surface carbon atom and a boron atom), and to BCNT type (6, 6) — at a distance of 0.16 nm when the group connecting to the carbon atom and 0.17 nm when connecting to the boron atom, which indicates the emergence of a chemical bond between the investigated BCNT and the amine group. The results of computer simulation of interaction between surface-modified ВС5 nanotube and alkali metal atoms (lithium, sodium, potassium) to be initialized are presented. The sensory interaction of the modified boron-carbon nanosystem with metal atoms is investigated, at which the selected atoms are identified at a certain distance. When reacting with alkali metal atoms in the BC5 + NH2 complex, it increases the number of carriers due to the transfer of electron density from metal atoms to modified BCNT. The results presented in this paper were obtained within the molecular cluster model by quantum-chemical calculations using the calculating DFT method with exchange-correlation functionality B3LYP (valence-split basis set 6-31G). It has been shown that the amine group modified boron-carbon ВС5 nanotube shows a sensory response to the above alkali metal atoms and can be used as an element of the sensor device.

ТЕПЛОФИЗИЧЕСКИЕ И ТЕРМОДИНАМИЧЕСКИЕ СВОЙСТВА ВЕЩЕСТВ В ГАЗОВОЙ ФАЗЕ – ОСНОВЕ КЛАСТЕРНОЙ МОДЕЛИ ГАЗА

The research is devoted to calculated-theoretical and applied analysis of thermo physical and thermodynamic properties of substances in gaseous phase used in heat-power engineering basing on cluster model. It is impossible to make measurements under all conditions that can be in heat-power engineering practice, so the theory is required that is based on reliable model. Such a model is considered to be a molecular-cluster model and computation schemes have been developed within its frameworks. These are schemes for computation of thermodynamic properties of substances in gaseous phase. The research of gases cluster model properties is due to necessity to develop and apply it with the use of experimental data in certain heat and power processes. Cluster model application is developed for thermodynamic potentials and for calculation of gas heat capacity. The areas of new research aims based on cluster model of a substance are connected with analysing structural compounds – equilibrium and “quasi-reactive”. The provided results have been achieved by analytic method of equation system calculation for clusters of any structure. Besides, it is required to test calculation methods where parameters of cluster model of a substance in gaseous state are considered. In this connection, modern computational program is used that is based on calculation of small, medium, and large clusters under certain state parameters.

Mathematical modeling of the process of interaction of sulfur dioxide with pyrolyzed polyacrylonitrile

The paper presents a study of the interaction of sulfur dioxide with a polymer-pyrolyzed polyacrylonitrile (PPAN). The possibility of using PPAN as an element of an electronic sensor device for recording the presence and identification of sulfur dioxide in the atmosphere is shown. The results of the established geometric and electron-energy characteristics of the polymer interacting with gas are described. Theoretical calculations were performed using the molecular cluster model and the quantum-chemical MNDO method.