Hasil untuk "Physical and theoretical chemistry"

P. Frémont, N. Marion, S. Nolan

Pengwei Li, Shao-hua Luo, Yicheng Lin et al.

This review discusses the critical role of fundamentals of battery recycling in addressing the challenges posed by the increasing number of spent lithium-ion batteries (LIBs) due to the widespread use of electric vehicles and portable electronics, by providing the theoretical basis and technical support for recycling spent LIBs, including battery classification, ultrasonic flaw detection, pretreatment (e.g., discharging, mechanical crushing, and physical separation), electrolyte recovery, direct regeneration, and theoretical calculations and simulations. Physical chemistry principles are essential for achieving effective separation of different components through methods like screening, magnetic separation, and flotation. Electrolyte recovery involves separation and purification of electrolytes through advanced physical and chemical techniques. Direct regeneration technology restores the structure of electrode materials at the microscopic scale, requiring precise control of the physical state and crystal structure of the material. Physical processes such as phase changes, solubility, and diffusion are fundamental to techniques like solid-state sintering, eutectic-salt treatment, and hydrothermal methods. Theoretical calculations and simulations help predict the behaviour of materials during recycling, guiding process optimization. This review provides insights into understanding and improving the recycling process, emphasizing the central role of physical chemistry principles in addressing environmental and energy issues. It is valuable for promoting innovation in spent LIB recycling processes and is expected to stimulate interest among researchers and manufacturers.

Ioannis Tanis

The manufacturing of detergent products such as laundry detergents or household cleaners is of increasing interest to the chemical industry. Surfactants and fatty acids are the most important ingredients in detergent formulations, as they are responsible for the cleaning power and the antimicrobial efficiency of the cleaning product. Computational tools can play a key role in the design and performance optimization of detergent products as they allow for quick and efficient screening of candidate surfactants in detergent formulations. In the present study, an automated fragmentation and parametrization protocol is utilized to investigate the adsorption of candidate fatty acid surfactants towards bacterial inner membranes. The effect of the surfactant size, concentration, and tendency for micelle formation on the degree of their adsorption on the inner membrane is examined. Analysis demonstrates that surfactant–inner membrane interaction weakens with surfactant size and aggregation tendency, as confirmed by pertinent experimental and simulation studies. The outcome of this study demonstrates that the adopted multiscale protocol allows for an accurate and cost-effective description of the systems examined at timescales much shorter than those required in laboratory experiments and atomistic simulations.

Vincent Graves, Christoph Sünderhauf, Nick S. Blunt et al.

E. F. Sheka

This review presents the covalent chemistry of carbon within the spin-radical concept of electron interaction. Using the language of valence bond trimodality, the regions of classical spinless covalence and its spin counterpart are defined. Carbon is the only element exhibiting spin covalent chemistry. Classical covalent chemistry of carbon concerns molecular substances whose valence bond structure includes segregate or chained single sp3C-C bonds. Substances with double sp2C-C and triple sp1C-C bonds are the subject of spin covalent chemistry of carbon. The mathematical apparatus of spin covalence forms the basis of algorithms governing the chemical modification of carbon substances, polymerization processes, and catalysis involving them, making it possible to supplement the empirical spin covalent chemistry of carbon with its virtual analog.

Nour Makke, Sanjay Chawla

Machine learning is rapidly making its pathway across all of the natural sciences, including physical sciences. The rate at which ML is impacting non-scientific disciplines is incomparable to that in the physical sciences. This is partly due to the uninterpretable nature of deep neural networks. Symbolic machine learning stands as an equal and complementary partner to numerical machine learning in speeding up scientific discovery in physics. This perspective discusses the main differences between the ML and scientific approaches. It stresses the need to develop and apply symbolic machine learning to physics problems equally, in parallel to numerical machine learning, because of the dual nature of physics research.

Lee‐Ping Wang, A. Titov, R. McGibbon et al.

Chemical understanding is driven by the experimental discovery of new compounds and reactivity, and is supported by theory and computation that provides detailed physical insight. While theoretical and computational studies have generally focused on specific processes or mechanistic hypotheses, recent methodological and computational advances harken the advent of their principal role in discovery. Here we report the development and application of the ab initio nanoreactor – a highly accelerated, first-principles molecular dynamics simulation of chemical reactions that discovers new molecules and mechanisms without preordained reaction coordinates or elementary steps. Using the nanoreactor we show new pathways for glycine synthesis from primitive compounds proposed to exist on the early Earth, providing new insight into the classic Urey-Miller experiment. These results highlight the emergence of theoretical and computational chemistry as a tool for discovery in addition to its traditional role of interpreting experimental findings.

Gabriel R. Schleder, Michele Pizzochero, Efthimios Kaxiras

Twisted bilayer graphene (tBLG) has emerged as a promising platform to explore exotic electronic phases. However, the formation of moiré patterns in tBLG has thus far been confined to the introduction of twist angles between the layers. Here, we propose heterostrained bilayer graphene (hBLG), as an alternative avenue to access twist-angle-free moiré physics via lattice mismatch. Using atomistic and first-principles calculations, we demonstrate that uniaxial heterostrain can promote isolated flat electronic bands around the Fermi level. Furthermore, the heterostrain-induced out-of-plane lattice relaxation may lead to a spatially modulated reactivity of the surface layer, paving the way for the moiré-driven chemistry and magnetism. We anticipate that our findings can be readily generalized to other layered materials.

Nabilah Suhaimi, Muhammad Raziq Rahimi Kooh, Chee Ming Lim et al.

In this study, locally grown bamboo (Gigantochloa spp.) was used as feedstock for pyrolysis production of biochar under various pyrolysis temperatures (400–800°C). The resultant biochars were tested for their performance in adsorptive removal of the methylene blue (MB) dye. The scope of the adsorption experiment includes the effects of adsorbent dosage, solution pH, initial adsorbate concentration, and contact time. The adsorption data confirmed that pyrolysis temperature has a significant effect on adsorptive performance, whereas biochar pyrolysed at 500°C (BC500) has the highest adsorptive performance with the maximum adsorption capacity (derived from the Langmuir model) being 86.6 mg g-1. Basic characterisations (SEM, EDX, XRD, FTIR, and BET) were carried out for BC500 where FTIR and SEM confirmed the adsorption of MB onto the biochar, while the BET data showed the reduction of the BET surface area, total pore volume, and pore diameter after the adsorption process.

Michael Ruggenthaler, Dominik Sidler, Angel Rubio

In this review we present the theoretical foundations and first principles frameworks to describe quantum matter within quantum electrodynamics (QED) in the low-energy regime. Having a rigorous and fully quantized description of interacting photons, electrons and nuclei/ions, from weak to strong light-matter coupling regimes, is pivotal for a detailed understanding of the emerging fields of polaritonic chemistry and cavity materials engineering. The use of rigorous first principles avoids ambiguities and problems stemming from using approximate models based on phenomenological descriptions of light, matter and their interactions. By starting from fundamental physical and mathematical principles, we first review in great detail non-relativistic QED, which allows to study polaritonic systems non-perturbatively by solving a Schrödinger-type equation. The resulting Pauli-Fierz quantum field theory serves as a cornerstone for the development of computational methods, such as quantum-electrodynamical density functional theory, QED coupled cluster or cavity Born-Oppenheimer molecular dynamics. These methods treat light and matter on equal footing and have the same level of accuracy and reliability as established methods of computational chemistry and electronic structure theory. After an overview of the key-ideas behind those novel ab initio QED methods, we explain their benefits for a better understanding of photon-induced changes of chemical properties and reactions. Based on results obtained by ab initio QED methods we identify the open theoretical questions and how a so far missing mechanistic understanding of polaritonic chemistry can be established. We finally give an outlook on future directions within polaritonic chemistry and first principles QED and address the open questions that need to be solved in the next years both from a theoretical as well as experimental viewpoint.

L. Ratke, P. Gurikov

Discover a rigorous treatment of aerogels processing and techniques for characterization with this easy-to-use reference. Presents the basics of aerogel synthesis and gelation to open porous nanostructures, and the processing of wet gels like ambient and supercritical drying leading to aerogels. Describes their essential properties with their measurement techniques and theoretical models used to analyse relations to their nanostructure. Linking the fundamentals and with practical applications, this is a useful toolkit for advanced undergraduates, and graduate students doing research in material and polymer science, physical chemistry, and chemical and environmental engineering.

Meena, Bashdar I., Lakk-Bogáth, Dóra, Keszei, Soma et al.

Hydrogen peroxide and peroxymonocarbonate anion-based bleach reactions are important for many applications such as paper bleach, waste water treatment and laundry. Nonheme iron(III) complexes, $[\mathrm{Fe}^{\mathrm{III}}(\mathrm{L}^{1-4})\mathrm{Cl}_{2}]$ with the 1,3-bis($2^{\prime}$-Ar-imino)isoindolines ligands ($\mathrm{HL}^{n}$, $n=$1–4, Ar $=$ pyridyl, thiazolyl, benzimidazolyl and N-methylbenzimidazolyl, respectively) have been shown to catalyze the oxidative degradation of morin as a soluble model of a bleachable stain by $\mathrm{H}_{2}\mathrm{O}_{2}$ in buffered aqueous solution. In these experiments the bleaching activity of the catalysts was significantly influenced by the Lewis acidity and redox properties of the metal centers, and showed a linear correlation with the $\mathrm{Fe}^{\mathrm{III}}/\mathrm{Fe}^{\mathrm{II}}$ redox potentials (in the range of 197–415 mV) controlled by the modification of the electron donor properties of the ligand introducing various aryl groups on the bis-iminoisoindoline moiety. A similar trend but with low yields was observed for the disproportionation of $\mathrm{H}_{2}\mathrm{O}_{2}$ (catalase-like reaction) which is a major side reaction of catalytic bleach with transition metal complexes. The effect of bicarbonate ions might be explained by the reduction of Fe(III) ions and/or the formation of peroxymonocarbonate monoanion, which is a much stronger oxidant and could increase the formation of the catalytically active high-valent oxoiron species.

Junhan Huang, Shunli Wang, Wenhua Xu et al.

Li-ion battery health assessment has been widely used in electric vehicles, unmanned aerial vehicle and other fields. In this paper, a new linear prediction method is proposed. By weakening the sensitivity of the Rainflow algorithm to the peak data, it can be applied to the field of battery, and can accurately count the number of Li-ion battery cycles, and skip the cumbersome link of parameter identification. Then, a linear criterion is proposed based on the idea of proportion, which makes the life prediction of Li-ion battery linear. Under the verification of multiple sets of data, the prediction error of this method is kept within 2.53%. This method has the advantages of high operation efficiency and simple operation, which provides a new idea for battery life prediction in the field of electric vehicles and aerospace.

Jin Jun, Wang Xiaohong, Zhan Lamin et al.

Xiaoyan Zhao, Yutong Wang, Changjun Ke et al.

Oily wastewater has caused adverse affects on the ecology. In contrast, how to effectively treat the wastewater and recover oil has been a challenge. Herein, we proposed a facile and cost-effective method to solve problem. A copper foam was fabricated by one-step nanosecond laser patterning for the first time and a superwetting surface was obtained. By adjusting ablation parameters, a superhydrophobic and superoleophilic surface was obtained whose water contact angle (WCA) was about 154.5° and oil contact angle (OCA) was 0° in air. In addition, surface morphology and elementary composition were characterized by scanning electron microscopy (SEM) and energy dispersive X-Ray (EDX) spectroscopy respectively. It is obvious hierarchical micro-nano structures were formed on the surface mainly caused by Cu melting and recasting during ablation. The ablated surfaces can be used not only for oil-water separation, but also for oil recovery with the recovery efficiency reaching 100%. Moreover, the surface exhibited outstanding stability which can be used for repeatable oil recovery application.

Stefan Klus, Patrick Gelß, Feliks Nüske et al.

We derive symmetric and antisymmetric kernels by symmetrizing and antisymmetrizing conventional kernels and analyze their properties. In particular, we compute the feature space dimensions of the resulting polynomial kernels, prove that the reproducing kernel Hilbert spaces induced by symmetric and antisymmetric Gaussian kernels are dense in the space of symmetric and antisymmetric functions, and propose a Slater determinant representation of the antisymmetric Gaussian kernel, which allows for an efficient evaluation even if the state space is high-dimensional. Furthermore, we show that by exploiting symmetries or antisymmetries the size of the training data set can be significantly reduced. The results are illustrated with guiding examples and simple quantum physics and chemistry applications.

E. Hausenblas, T. Randrianasolo, M. Thalhammer

Abstract Mathematical models based on systems of reaction–diffusion equations provide fundamental tools for the description and investigation of various processes in biology, biochemistry, and chemistry; in specific situations, an appealing characteristic of the arising nonlinear partial differential equations is the formation of patterns, reminiscent of those found in nature. The deterministic Gray–Scott equations constitute an elementary two-component system that describes autocatalytic reaction processes; depending on the choice of the specific parameters, complex patterns of spirals, waves, stripes, or spots appear. In the derivation of a macroscopic model such as the deterministic Gray–Scott equations from basic physical principles, certain aspects of microscopic dynamics, e.g. fluctuations of molecules, are disregarded; an expedient mathematical approach that accounts for significant microscopic effects relies on the incorporation of stochastic processes and the consideration of stochastic partial differential equations. The present work is concerned with a theoretical and numerical study of the stochastic Gray–Scott equations driven by independent spatially time-homogeneous Wiener processes. Under suitable regularity assumptions on the prescribed initial states, existence, as well as the uniqueness of the solution processes, is proven. Numerical simulations based on the application of a time-adaptive first-order operator splitting method and the fast Fourier transform illustrate the formation of patterns in the deterministic case and their variation under the influence of stochastic noise.

Cong Xiong, Haikou Fu, Lijue Wu et al.

LiNi0.8Co0.1Mn0.1O2 cathode material was successfully modified by using a wet-chemical route to coat WO3. The microstructures, morphologies, crystal structures, elemental distributions and ionic valence of the prepared cathode materials were carefully analyzed by SEM, EDS, TEM, HRTEM, XRD and XPS. The results indicated that the surface of LiNi0.8Co0.1Mn0.1O2 was uniformly covered by WO3 particles, and a small amount of W6+ could enter to the lattice of LiNi0.8Co0.1Mn0.1O2. The WO3 coating could prohibit the corrosion of HF and some side reactions for the cathode material during long cycles, thus greatly improving the electrochemical performance and the structural stability of LiNi0.8Co0.1Mn0.1O2. Among the examined LiNi0.8Co0.1Mn0.1O2cathode materials, 1.0 wt% WO3-coated LiNi0.8Co0.1Mn0.1O2 has the best initial discharge capacity (185.1 mAh g-1) and an excellent capacity retention (93.2%) after 100 cycles at 1 C.

Nicolas Dietrich

In this activity, we describe how the video game Fortnite provides a nice opportunity for students to think about chemistry. The game has a survival system based on the acquisition and use of items, which has interesting chemical and physical properties. In addition, the game also provides an important platform of crafting and base building and open discussion on materials.

Luis Elcoro, Benjamin J. Wieder, Zhida Song et al.

For over 100 years, the group-theoretic characterization of crystalline solids has provided the foundational language for diverse problems in physics and chemistry. However, the group theory of crystals with commensurate magnetic order has remained incomplete for the past 70 years, due to the complicated symmetries of magnetic crystals. In this work, we complete the 100-year-old problem of crystalline group theory by deriving the small corepresentations, momentum stars, compatibility relations, and magnetic elementary band corepresentations of the 1,421 magnetic space groups (MSGs), which we have made freely accessible through tools on the Bilbao Crystallographic Server. We extend Topological Quantum Chemistry to the MSGs to form a complete, real-space theory of band topology in magnetic and nonmagnetic crystalline solids - Magnetic Topological Quantum Chemistry (MTQC). Using MTQC, we derive the complete set of symmetry-based indicators of electronic band topology, for which we identify symmetry-respecting bulk and anomalous surface and hinge states.