Hasil untuk "Physical and theoretical chemistry"

B. Eliasson, M. Hirth, U. Kogelschatz

A. Rich, A. Nordheim, A. Wang

B. Albert, H. Hillebrecht

Jingxu Wu, Yuwei Yin

This paper explores the ontological and epistemological foundations of Lev Landau's theoretical physics through the lens of his unpublished philosophical notes and scientific practice. We identify a unique form of geometric reductionism where physical laws emerge as inevitable consequences of symmetry breaking in progressively constrained phase spaces. Landau's dismissal of quantum interpretation debates and his famous "axiomatic minimalism" in the Course of Theoretical Physics are shown to stem from a deep epistemological commitment to dimensional aesthetics - the belief that fundamental truths must manifest through dimensional economy in mathematical representations.

He Liu, Xin‐Bing Cheng, Zhehui Jin et al.

Abstract Lithium metal has been considered as a “Holy Grail” anode for rechargeable batteries due to its ultrahigh theoretical specific capacity and the most negative electrochemical potential. Sodium and potassium, the alkali metals that are more abundant in the earth's crust are also regarded as candidates for next-generation anode materials, considering the low crust abundance and high cost of lithium carbonate. However, all of these alkali metal anodes are susceptible to dendrite growth, causing safety concerns, low energy density, and short lifespan, which severely hampers their practical applications. A number of models have been proposed to describe the dendrite growth mechanism/behavior and offer strategies to render a uniform and dendrite-free deposition behavior. In this review, we summarize the progress in the energy chemistry of alkali metal anodes. Firstly, the similarities and differences among three alkali metals in chemical/physical/electrochemical features are addressed. Then, special attention is paid to the understanding of mechanisms and models for Li dendrite nucleation and growth, including the thermodynamic model, space-charge model, stress and inelastic deformation model, film growth model, and phase field kinetics model. The feasibility of these models to Na and K anode systems is also discussed. Finally, general conclusions and perspectives on the current limitations and future research directions toward the understanding of mechanisms on dendrite growth are presented. This review should provide important insights into alkali metal deposition behaviors and alkali metal anode protection.

M. Freedman, Qishen Huang, Kiran R Pitta

C. Schäfer, M. Ruggenthaler, V. Rokaj et al.

Experiments at the interface of quantum optics and chemistry have revealed that strong coupling between light and matter can substantially modify the chemical and physical properties of molecules and solids. While the theoretical description of such situations is usually based on nonrelativistic quantum electrodynamics, which contains quadratic light–matter coupling terms, it is commonplace to disregard these terms and restrict the treatment to purely bilinear couplings. In this work, we clarify the physical origin and the substantial impact of the most common quadratic terms, the diamagnetic and self-polarization terms, and highlight why neglecting them can lead to rather unphysical results. Specifically, we demonstrate their relevance by showing that neglecting these terms leads to the loss of gauge invariance, basis set dependence, disintegration (loss of bound states) of any system in the basis set limit, unphysical radiation of the ground state, and an artificial dependence on the static dipole. Besides providing important guidance for modeling of strongly coupled light–matter systems, the presented results also indicate conditions under which those effects might become accessible.

E. Haque, Jeonghun Kim, Victor Malgras et al.

Here, an interesting, new 0D material is presented: graphene quantum dots. The new properties arising from quantum confinement and edge effects after converting 2D graphene into graphene quantum dots have attracted great interest in various disciplines, such as physics, biology, materials, and chemistry. Here, the recent technological advances in the field of graphene quantum dots reported in the literature on both a theoretical and an experimental basis are highlighted. Various synthesis methodologies and physical properties are discussed, along with their implementation in energy (supercapacitors, fuel cells, photovoltaic devices, light-emitting diodes), biomedical (biosensors, drug delivery, bioimaging), and environmental applications.

Lasbleiz, Arthur, Pelissier, Franck, Renault, Jean-Hugues et al.

A new generation of ecocatalysts$^{\text{®}}$ derived from Invasive Alien Species (IAS) (Fallopia japonica and Arundo donax) was used as starting material for the preparation of novel biosourced catalysts. The preparation of these ecocatalysts$^{\text{®}}$ is a new way to support the management of IAS. These catalysts were characterized by microwave plasma atomic emission spectrometry (MP-AES) and X-ray powder diffraction (XRPD), which revealed basic properties. After calculating Pearson’s correlations to evaluate the relative importance of reaction parameters, a design of experiments (DoE) was implemented to synthesize glyceryl caprylate and oleate with a high selectivity. These molecules constitute emollients and non-ionic emulsifiers of high industrial interest. The ecocatalysts$^{\text{®}}$ were efficient and recyclable for the transesterification of methyl and ethyl fatty esters, leading to high yields (66–83%). These ecocatalysts$^{\text{®}}$ are an alternative to usual base catalysts previously reported for the transesterification of methyl caprylate, methyl oleate and ethyl caprylate with glycerol, which are often non-recyclable, not systematically selective and require questionable preparation conditions.

Abigail Parra Parra, Marina Vlasova, Pedro Antonio Márquez Aguilar et al.

In the present study, XRD, SEM/EDS, Raman, EMR/EPR spectroscopy, and vibrating sample magnetometry (VSM) were used to analyze the reduction of hematite by the carbonization products of waste activated sludge (WAS) at 500–1000 °C. The reduction process includes the following steps: α-Fe₂O₃ → Fe₂O₃ + Fe₃O₄ (T_tr~500 °C) → Fe₃O₄ (T_tr~600–700 °C) → FeO → Fe_amorph. (T_tr~1000 °C). The prevalence of certain phase compositions at different hematite reduction temperatures makes it possible to predict the areas viable for the application of reduced oxides: adsorbents (after T_tr~500 °C) → soft ferromagnetic materials (after T_tr~600–700 °C) → electrically engineered amorphous iron (after T_tr~1000 °C).

Wojciech G Stark, Julia Westermayr, O. A. Douglas-Gallardo et al.

The reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, plays a crucial role in energy storage and fuel cells. Theoretical studies can help to decipher underlying mechanisms and reaction design, but studying dynamics at surfaces is computationally challenging due to the complex electronic structure at interfaces and the high sensitivity of dynamics to reaction barriers. In addition, ab initio molecular dynamics, based on density functional theory, is too computationally demanding to accurately predict reactive sticking or desorption probabilities, as it requires averaging over tens of thousands of initial conditions. High-dimensional machine learning-based interatomic potentials are starting to be more commonly used in gas-surface dynamics, yet robust approaches to generate reliable training data and assess how model uncertainty affects the prediction of dynamic observables are not well established. Here, we employ ensemble learning to adaptively generate training data while assessing model performance with full uncertainty quantification (UQ) for reaction probabilities of hydrogen scattering on different copper facets. We use this approach to investigate the performance of two message-passing neural networks, SchNet and PaiNN. Ensemble-based UQ and iterative refinement allow us to expose the shortcomings of the invariant pairwise-distance-based feature representation in the SchNet model for gas-surface dynamics.

M. D. J. Velasquez-Hernandez, R. Riccò, F. Carraro et al.

Laura J. Fox, R. Richardson, W. Briscoe

PAMAM dendrimers have been conjectured for a wide range of biomedical applications due to their tuneable physicochemical properties. However, their application has been hindered by uncertainties in their cytotoxicity, which is influenced by dendrimer generation (i.e. size and surface group density), surface chemistry, and dosage, as well as cell specificity. In this review, biomedical applications of polyamidoamine (PAMAM) dendrimers and some related cytotoxicity studies are first outlined. Alongside these in vitro experiments, lipid membranes such as supported lipid bilayers (SLBs), liposomes, and Langmuir monolayers have been used as cell membrane models to study PAMAM dendrimer-membrane interactions. Related experimental and theoretical studies are summarized, and the physical insights from these studies are discussed to shed light on the fundamental understanding of PAMAM dendrimer-cell membrane interactions. We conclude with a summary of some questions that call for further investigations.

S. Lyman, I. Cheng, L. Gratz et al.

The atmosphere is a key component of the biogeochemical cycle of mercury, acting as a reservoir, transport mechanism, and facilitator of chemical reactions. The chemical and physical behavior of atmospheric mercury determines how, when, and where emitted mercury pollution impacts ecosystems. In this review, we provide current information about what is known and what remains uncertain regarding mercury in the atmosphere. We discuss new ambient, laboratory, and theoretical information about the chemistry of mercury in various atmospheric media. We review what is known about mercury in and on solid- and liquid-phase aerosols. We present recent findings related to wet and dry deposition and spatial and temporal trends in atmospheric mercury concentrations. We also review atmospheric measurement methods that are in wide use and those that are currently under development.

S. Al-Qaisi, D. P. Rai, B. Haq et al.

Abstract We present a comprehensive first-principles study on the physical properties of the lead-free double perovskites halides, Cs2LiYX6 (X = Br, I). Our calculated results of lattice constants (a0) of both compounds are in nice agreement with the reported experimental and theoretical investigations. The predicted band structures of both compounds show that both compounds are wide and direct bandgap materials at T-point. Similarly, our computed results of elastic analysis predict that the investigated materials are elastically anisotropic, mechanically stable, and of ductile nature. The results of optical parameters such as absorption coefficients, refractive index, optical conductivity, optical reflectivity, electron energy loss, and extinction coefficients for an energy range of 0–14 eV are calculated and analyzed as well. The analysis of obtained results of wide and direct band gaps as well as optical parameters particularly absorption coefficients reflect the suitability of both compounds for ultraviolet high-frequency device applications.

Giuseppe Carleo, Y. Nomura, M. Imada

Obtaining accurate properties of many-body interacting quantum matter is a long-standing challenge in theoretical physics and chemistry, rooting into the complexity of the many-body wave-function. Classical representations of many-body states constitute a key tool for both analytical and numerical approaches to interacting quantum problems. Here, we introduce a technique to construct classical representations of many-body quantum systems based on artificial neural networks. Our constructions are based on the deep Boltzmann machine architecture, in which two layers of hidden neurons mediate quantum correlations. The approach reproduces the exact imaginary-time evolution for many-body lattice Hamiltonians, is completely deterministic, and yields networks with a polynomially-scaling number of neurons. We provide examples where physical properties of spin Hamiltonians can be efficiently obtained. Also, we show how systematic improvements upon existing restricted Boltzmann machines ansatze can be obtained. Our method is an alternative to the standard path integral and opens new routes in representing quantum many-body states. Significant improvements in numerical methods for quantum systems often come from finding new ways of representing quantum states that can be optimized and simulated more efficiently. Here the authors demonstrate a method to calculate exact neural network representations of many-body ground states.

Dufour Gwenaëlle, Steven B. Charnley

We have investigated the chemistry of dense interstellar clouds and found new bistable solutions in the nitrogen and carbon chemistries. We identify the autocatalytic processes that are present in the pure, reduced, chemical networks and, as previously found for oxygen chemistry, that He$^+$ plays an important role. The applicability of these results to astronomical environments is briefly discussed. The bistable solutions found for carbon chemistry occur for low densities and high ionization fractions that are not compatible with that found cold, dense clouds. Bistability in the pure nitrogen chemistry occurs for conditions that are relevant for prestellar cores in which significant CO depletion has taken place. We conclude that several autocatalyses are embedded in gas-phase interstellar chemistry and that many more are potentially present.

Yujie Qian, Zhening Li, Zhengkai Tu et al.

This paper focuses on using natural language descriptions to enhance predictive models in the chemistry field. Conventionally, chemoinformatics models are trained with extensive structured data manually extracted from the literature. In this paper, we introduce TextReact, a novel method that directly augments predictive chemistry with texts retrieved from the literature. TextReact retrieves text descriptions relevant for a given chemical reaction, and then aligns them with the molecular representation of the reaction. This alignment is enhanced via an auxiliary masked LM objective incorporated in the predictor training. We empirically validate the framework on two chemistry tasks: reaction condition recommendation and one-step retrosynthesis. By leveraging text retrieval, TextReact significantly outperforms state-of-the-art chemoinformatics models trained solely on molecular data.

O.V. Malyshkina, G.S. Shishkov, A.I. Ivanova

The paper presents the results of a study of the influence of a constant magnetic field on the dispersion of the complex permittivity of a layered composite (connectivity 2-2) based on barium titanate – barium ferrite. It is shown that in the manufacture of a magnetoelectric composite of barium titanate – barium ferrite with a connectivity of 2-2, a strong diffusion of iron appears into the barium titanate ceramic layer at the interface between the two materials. It was found that iron penetrates evenly, with random deviations, and no exponential decline as iron enters into barium titanate is observed. It has been established that a constant magnetic field does not affect the dielectric characteristics in an alternating electric field at frequencies above 1600 Hz. At lower frequencies, annealing in the paraelectric phase increases the resistance of the sample, and subsequent exposure to a constant magnetic field leads to its decrease. It was revealed that changing the type of connectivity of the magnetoelectric composite from 0-3 to 2-2 adds additional, smaller, resonance and antiresonance peaks in the study of piezoelectric properties by the resonance-antiresonance method. At the same time, the samples have sufficient values of the piezoelectric modulus for practical application (d31 > 40·10-12 C/N; d33 > 120·10-12 C/N).

Lixin Wei, Yu Zhang, Guifen Liu et al.

The pulse current electrodeposition (PCE) technique was employed to successfully deposit Ni/W–TiN coatings on X52 steel. The effect of frequency and duty cycle on coating parameters like surface morphological characteristics, grain orientation, micro-hardness, crystal size, the number of deposited TiN CNPs, and corrosion resistance was investigated in detail. The findings show that TiN particles agglomerate, resulting in particle clouds with mean diameters of approximately 116.1 nm that are enclosed as second phases in the Ni/Co coating matrix. The Ni/W-TiN coating generated at a duty cycle of 10% and a pulse frequency of 10 Hz was able to process a maximum TiN content of 11.6 v/v%. It also showed that the coating grain became smaller when the duty cycle decreased or pulse frequency increased. The maximum micro-hardness value of the Ni/W-TiN coating synthesized at a duty cycle of 10% and a 10 Hz pulse frequency was 671.8 kg/mm, whereas the Ni/W-TiN coating deposited at 20 Hz and 30% had a maximum micro-hardness value of 642.4 kg/mm. Furthermore, the size of the semicircle was affected by charge-transfer resistance at the electrode/solution, therefore the size was observed to grow with the decrease in duty cycle and pulse frequency.