Hasil untuk "Physical and theoretical chemistry"

Collen TAKAZA, Yasuhiro FUKUNAKA, Takayuki HOMMA

This study investigates the growth process and thermoelectric properties of electrodeposited Cu2Se films. The growth mechanism revealed that morphology, stoichiometry, Seebeck coefficient (S), and electrical conductivity (σ) all vary with film thickness. Voltammetric results showed a consistent appearance and variation of the anodic peak, highlighting its role in defining the electrochemical window for the controlled co-deposition of Cu and Se, which is crucial for developing semiconductors. SEM analysis revealed that the film morphology strongly depends on deposition time. Microstructural analysis demonstrated a distinct evolution in the film growth mechanism, starting with an early-stage transition from layer-plus-island-like growth. EDX and XRD analyses indicated changes in atomic composition during growth, beginning with a Se-rich mixture of Cu-Se phases. The electrical conductivity (σ) of the films increased as the layer thickness decreased. The Seebeck coefficient (S) increases with film thickness, reaching an optimal value of +16 µV/K at 10.5 µm.

Mingwei Ding, Chen Huang, Yibo Hu et al.

Automating multistep computational chemistry tasks remains challenging because reasoning, workflow specification, software execution, and high-performance computing (HPC) execution are often tightly coupled. We demonstrate a decoupled agent-skill design for computational chemistry automation leveraging OpenClaw. Specifically, OpenClaw provides centralized control and supervision; schema-defined planning skills translate scientific goals into executable task specifications; domain skills encapsulate specific computational chemistry procedures; and DPDispatcher manages job execution across heterogeneous HPC environments. In a molecular dynamics (MD) case study of methane oxidation, the system completed cross-tool execution, bounded recovery from runtime failures, and reaction network extraction, illustrating a scalable and maintainable approach to multistep computational chemistry automation.

Minghan Chu, Weicheng Qian

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation Method (EPM) is a widely used physics-based approach to quantify model-form uncertainty, but being purely physics-based it can overpredict uncertainty bounds. We propose a convolutional neural network (CNN)-based modulation of EPM perturbation magnitudes to improve calibration while preserving physical consistency. Across canonical cases, the hybrid ML-EPM framework yields substantially tighter, better-calibrated uncertainty estimates than baseline EPM alone.

M.N. Lapushkin

For the first time, the adsorption of barium atoms on the surface of the (0001) face of GaN was calculated using the density functional method. The 2D GaN layer was modeled using a GaN(0001) 2×2 supercell containing 10 GaN bilayers. The electron density of state and the adsorption energy of the Ba atom were calculated for five adsorption sites of the Ba atom: in the hollow position, in the bridge position between the surface Ga (N) atoms, and above the surface Ga (N) atom. There was one Ba atom per 4 surface Ga atoms in the first GaN bilayer. The adsorption of the barium atom above the surface N atom was most preferable. The adsorption energy was 2,96 eV. The adsorption of Ba atoms resulted in an insignificant reconstruction of the GaN surface: the maximum shift of the Ga (N) atoms did not exceed 0,11 Å. The adsorption of Ba resulted in the formation of a surface band below the Fermi level.

Chang Liao, Yemin Yu, Yu Mei et al.

In recent years, Large Language Models (LLMs) have achieved significant success in natural language processing (NLP) and various interdisciplinary areas. However, applying LLMs to chemistry is a complex task that requires specialized domain knowledge. This paper provides a thorough exploration of the nuanced methodologies employed in integrating LLMs into the field of chemistry, delving into the complexities and innovations at this interdisciplinary juncture. Specifically, our analysis begins with examining how molecular information is fed into LLMs through various representation and tokenization methods. We then categorize chemical LLMs into three distinct groups based on the domain and modality of their input data, and discuss approaches for integrating these inputs for LLMs. Furthermore, this paper delves into the pretraining objectives with adaptations to chemical LLMs. After that, we explore the diverse applications of LLMs in chemistry, including novel paradigms for their application in chemistry tasks. Finally, we identify promising research directions, including further integration with chemical knowledge, advancements in continual learning, and improvements in model interpretability, paving the way for groundbreaking developments in the field.

Emil Dimitrov, Goar Sanchez-Sanz, James Nelson et al.

Accurate and scalable methods for computational quantum chemistry can accelerate research and development in many fields, ranging from drug discovery to advanced material design. Solving the electronic Schrodinger equation is the core problem of computational chemistry. However, the combinatorial complexity of this problem makes it intractable to find exact solutions, except for very small systems. The idea of quantum computing originated from this computational challenge in simulating quantum-mechanics. We propose an end-to-end quantum chemistry pipeline based on the variational quantum eigensolver (VQE) algorithm and integrated with both HPC-based simulators and a trapped-ion quantum computer. Our platform orchestrates hundreds of simulation jobs on compute resources to efficiently complete a set of ab initio chemistry experiments with a wide range of parameterization. Per- and poly-fluoroalkyl substances (PFAS) are a large family of human-made chemicals that pose a major environmental and health issue globally. Our simulations includes breaking a Carbon-Fluorine bond in trifluoroacetic acid (TFA), a common PFAS chemical. This is a common pathway towards destruction and removal of PFAS. Molecules are modeled on both a quantum simulator and a trapped-ion quantum computer, specifically IonQ Aria. Using basic error mitigation techniques, the 11-qubit TFA model (56 entangling gates) on IonQ Aria yields near-quantitative results with milli-Hartree accuracy. Our novel results show the current state and future projections for quantum computing in solving the electronic structure problem, push the boundaries for the VQE algorithm and quantum computers, and facilitates development of quantum chemistry workflows.

David T. Limmer, Andreas W. Götz, Timothy H. Bertram et al.

Atmospheric aerosols facilitate reactions between ambient gases and dissolved species. Here, we review our efforts to interrogate the uptake of these gases and the mechanisms of their reactions both theoretically and experimentally. We highlight the fascinating behavior of $\mathrm{N}_2\mathrm{O}_5$ in solutions ranging from pure water to complex mixtures, chosen because its aerosol-mediated reactions significantly impact global ozone, hydroxyl, and methane concentrations. As a hydrophobic, weakly soluble, and highly reactive species, $\mathrm{N}_2\mathrm{O}_5$ is a sensitive probe of the chemical and physical properties of aerosol interfaces. We employ contemporary theory to disentangle the fate of $\mathrm{N}_2\mathrm{O}_5$ as it approaches pure and salty water, starting with adsorption and ending with hydrolysis to HNO$_3$, chlorination to $\mathrm{ClNO}_2$, or evaporation. Flow reactor and gas-liquid scattering experiments probe even greater complexity as added ions, organic molecules, and surfactants alter interfacial composition and reaction rates. Together, we reveal a new perspective on multiphase chemistry in the atmosphere.

Roger F Loring

Multidimensional optical spectra are measured from the response of a material system to a sequence of laser pulses and have the capacity to elucidate specific molecular interactions and dynamics whose influences are absent or obscured in a conventional linear absorption spectrum. Interpretation of complex spectra is supported by theoretical modeling of the spectroscopic observable, requiring implementation of quantum dynamics for coupled electrons and nuclei. Performing numerically correct quantum dynamics in this context may pose computational challenges, particularly in the condensed phase. Semiclassical methods based on calculating classical trajectories offer a practical alternative. Here I review the recent application of some semiclassical, trajectory-based methods to nonlinear molecular vibrational and electronic spectra. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

E. Sibert

High-resolution vibrational spectra of C-H, O-H, and N-H stretches depend on both molecular conformation and environment as well as provide a window into the frequencies of many other vibrational degrees of freedom as a result of mode mixing. We review current theoretical strategies that are being deployed to both aid and guide the analysis of the data that are encoded in these spectra. The goal is to enhance the power of vibrational spectroscopy as a tool for probing conformational preferences, hydrogen bonding effects away from equilibrium, and energy flow pathways. Recent years have seen an explosion of new methods and strategies for solving the nuclear Schrödinger equation. Rather than attempt a comprehensive review, this work highlights specific molecular systems that we have chosen as representing bonding motifs that are important to chemistry and biology. We focus on the choices theoretical chemists make regarding the level of electronic structure theory, the representation of the potential energy surface, the selection of coordinates, preferences in basis sets, and methods of solution. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Hadizadeh Nastaran, Zeidi Saba, Khodabakhsh Helia et al.

With the glorious discovery of graphene back in 2004, the field of nanotechnology was faced with a breakthrough that soon attracted the attention of many scientists from all over the world. Owing to its unique bidimensional structure and exquisite physicochemical properties, graphene has successfully managed to cave its way up to the list of the most investigated topics, while being extensively used in various fields of science and technology. However, serious concerns have been raised about the safety of graphene, for which numerous studies have been conducted to evaluate the toxicity of graphene derivatives in both in vitro and in vivo conditions. The reproductive toxicity of graphene is one of the most important aspects of this subject as it not only affects the individual but can also potentially put the health of one’s offsprings at risk and display long-term toxic effects. Given the crucial importance of graphene’s reproductive toxicity, more attention has been recently shifted toward this subject; however, the existing literature remains insufficient. Therefore, we have conducted this review with the aim of providing researchers with assorted information regarding the toxicity of graphene derivatives and their underlying mechanisms, while mentioning some of the major challenges and gaps in the current knowledge to further elucidate the path to exploring graphene’s true nature. We hope that our work will effectively give insight to researchers who are interested in this topic and also aid them in completing the yet unfinished puzzle of graphene toxicity.

David Hovancik, Dalibor Repcek, Fedir Borodavka et al.

We use the synergy of infrared, terahertz, and Raman spectroscopies with DFT calculations to shed light on the magnetic and lattice properties of VI3. The structural transition at TS1 = 79 K is accompanied by a large splitting of polar phonon modes. Below TS1, strong ferromagnetic fluctuations are observed. The variations of phonon frequencies at 55 K induced by magnetoelastic coupling enhanced by spin-orbit interaction indicate the proximity of long-range ferromagnetic order. Below TC = 50 K, two Raman modes simultaneously appear and show dramatic softening in the narrow interval around the temperature TS2 of the second structural transition associated with the order-order magnetic phase transition. Below TS2, a magnon in the THz range appears in Raman spectra. The THz magnon observed in VI3 indicates the application potential of 2D van der Waals ferromagnets in ultrafast THz spintronics, which has previously been considered an exclusive domain of antiferromagnets.

Patrick Reiser, Marlen Neubert, André Eberhard et al.

Machine learning plays an increasingly important role in many areas of chemistry and materials science, e.g. to predict materials properties, to accelerate simulations, to design new materials, and to predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growing classes of machine learning models. They are of particular relevance for chemistry and materials science, as they directly work on a graph or structural representation of molecules and materials and therefore have full access to all relevant information required to characterize materials. In this review article, we provide an overview of the basic principles of GNNs, widely used datasets, and state-of-the-art architectures, followed by a discussion of a wide range of recent applications of GNNs in chemistry and materials science, and concluding with a road-map for the further development and application of GNNs.

W. Fan, Yi Han, Xuhui Wang et al.

The synthesis of kekulene and its higher homologues is a challenging task in organic chemistry. The first successful synthesis and characterization of the parent kekulene were reported by Diederich and Staab in 1978. Herein, we report the facile preparation of a series of edge-extended kekulenes by bismuth(III) triflate-catalyzed cyclization of vinyl ethers from the properly designed macrocyclic precursors. Their molecular structures were confirmed by X-ray crystallographic analysis and NMR spectroscopy. Their size- and symmetry-dependent electronic structures (frontier molecular orbitals, aromaticity) and physical properties (optical and electrochemical) were investigated by various spectroscopic measurements, assisted by theoretical calculations. Particularly, the acene-like units along each zigzag edge demonstrate a dominant local aromatic character. Our studies provide an easy synthetic strategy toward various fully fused carbon nanostructures and give some insights into the electronic properties of cycloarenes.

Bernhard Stanje, H. Martin R. Wilkening

V. Pershina

Abstract Theoretical chemical studies demonstrated crucial importance of relativistic effects in the physics and chemistry of superheavy elements (SHEs). Performed, with many of them, in a close link to the experimental research, those investigations have shown that relativistic effects determine periodicities in physical and chemical properties of the elements in the chemical groups and rows of the Periodic Table beyond the 6th one. They could, however, also lead to some deviations from the established trends, so that the predictive power of the Periodic Table in this area may be lost. Results of those studies are overviewed here, with comparison to the recent experimental investigations.

M. Mondal, Li Zhang, Zhongtao Feng et al.

The search for main-group element-based radicals is one of the main research topics in contemporary chemistry because of their fascinating chemical and physical properties. The Group 15 element-centered radicals mainly feature a V-shaped two coordinate structure, with a couple of radical cations featuring trigonal tricoordinated geometry. In this work, we successfully synthesized nontrigonal compounds R3E (E = P, As and Sb) by introducing a new rigid tris-amide ligand. The selective one-electron reduction of R3E afforded the first stable tricoordinate pnictogen-centered radical anion salts, in which the pnictogen atoms retain planar T-shaped structures. Electron paramagnetic spectroscopy and theoretical calculations reveal that the spin density mainly resides at the p orbitals of the pnictogen atoms, which are perpendicular to the N3E planes.

Fontani, Marco, Orna, Mary Virginia, Costa, Mariagrazia

It is appropriate to recall that 2019 was the year dedicated to the Periodic Table. But when we speak about false elements – in the aftermath of the celebrations marking this year, – we are greeted most warmly, but with some puzzlement, as to how it came to mind to celebrate “Mendeleev’s creature” in such a peculiar way, that is, by commemorating elements that never existed. In the course of many years, we have discovered and collected a great number of discoveries of simple bodies that sooner or later turned out to be detours or false tracks.

David E. Woon, Dominique M. Maffucci, Eric Herbst

Accurate and thorough characterization of the chemistry of compounds containing the third-row elements sulfur and chlorine is critical for modeling the composition of the atmosphere of Venus. We have used a combination of ab initio quantum chemistry and kinetic theory to characterize a group of nine exothermic reactions that involve the exotic sulfur-chlorine species SCl, SCl2, and HSCl, which are thought to be present in trace quantities in the atmosphere of Venus and are included to various degrees in the published atmospheric models. Reaction pathways were characterized with coupled cluster theory at the RCCSD(T) level with triple zeta quality correlation consistent basis sets. For reactions with barriers that lie above the reactant asymptote, the barrier height was extrapolated to the RCCSD(T) complete basis set level via single-point calculations with quadruple and quintuple zeta quality sets. Rate coefficients were predicted with capture theory and transition state theory as appropriate. We have found that in some cases addition-elimination reactions can compete with abstraction reactions due to the tendency of sulfur to form hypervalent compounds and intermediates via recoupled pair bonding.

A. Lebedev, Franklin Anariba, J. Tan et al.

Abstract The paper reviews metal oxides’ physiochemical and photocatalytic mechanisms of toxicity against E. coli. Photocatalysis is a process that aims to efficiently convert solar-to-chemical energy. This technology is extensively used in the environmental and energy fields, water purification systems and hydrogen evolution. This paper surveys metal oxides’ antibacterial properties with special attention to reactive oxygen species (ROS), lipid peroxidation as a main process governing photocatalytic activity against E. coli, and theoretical models aiming at predicting disinfection rates. Furthermore, the paper highlights ways to improve photocatalytic efficiency, such as increased amount of ROS, specific light spectrum and intensity, and particles’ morphology. This work would be incomplete without attention to physiochemical toxicity mechanisms towards E. coli. These processes are primarily based on metal oxides’ solubility, and depending upon solubility properties, the mechanism is driven either by physical (mechanical) or chemical (metal ions) interaction. Finally, potential challenges to overcome during ROS-bacteria interaction (like, gas and nanobubbles formation) are enumerated. The review aims to fill the gap between photocatalysis as a chemical reaction and photocatalysis as a disinfection process. It would be helpful for materials scientists to get acquainted with another application of semiconductors, and challenges/opportunities laying on the boundary between materials and biological sciences.

Benjamin D. Geller, Julia Gouvea, Benjamin W. Dreyfus et al.

Students in one discipline often receive their scientific training from faculty in other disciplines. As a result of tacit disciplinary differences, especially as implemented in courses at the introductory college level, such students can have difficulty in understanding the nature of the knowledge they are learning in a discipline that they do not identify as their own. We developed a course in introductory physics for life science (IPLS) students that attempts to help them cross disciplinary boundaries. By analyzing student reasoning during recitation sections and interviews, we identified three broad ways in which students in our course meaningfully crossed boundaries: (i) by unpacking biochemical heuristics in terms of underlying physical interactions, (ii) by locating both biochemical and physical concepts within a mathematical bridging expression, and (iii) by coordinating functional and mechanistic explanations for the same biological phenomenon. Drawing on episodes from case-study interviews and in-class problem-solving sessions, we illustrate how each of these types of boundary crossing involves the coordination of students’ conceptual and epistemological resources from physics, chemistry, and biology in distinct but complementary ways. Together, these boundary crossing categories form a theoretical framework for classifying student coherence seeking. We explore how the IPLS course helps our life science students fill in the gaps that exist between traditional introductory courses, by finding and exploring questions that might otherwise fall through disciplinary cracks. By identifying these types of explanatory coherence, we hope to suggest ways of inviting life science students to participate in physics and see physics as a tool for making sense of the living world.