Hasil untuk "Physical and theoretical chemistry"

Mirana Rakotozafy, Rivoarison Randrianasolo, Solomon Tesfaye et al.

In recent years, <i>Biophytum umbraculum</i> Welw. (Oxalidaceae) has undergone several phytochemical and pharmacological investigations. Although its major phytochemical classes have been characterized, few isolated compounds have been reported. The previously detected phytoconstituents, along with the documented antioxidant and anti-inflammatory activities, both align with a potential antiproliferative effect. This study aims to complement the existing chemotaxonomic profile of <i>B. umbraculum</i> through the isolation and identification of phytoconstituents and to evaluate the antiproliferative potential of its extracts. Hexane, ethyl acetate, and methanolic extracts of <i>B. umbraculum</i> were screened against two human adherent cell lines, breast (MCF-7) and cervical (SiSo) adenocarcinomas, by using the crystal violet staining assay. The hexane extract inhibited both MCF-7 and SiSo cell proliferation with IC₅₀ values of 8.93 ± 0.07 and 14.59 ± 0.08 µg/mL, respectively. The ethyl acetate extract showed activity against both cell lines, with IC₅₀ values of 12.60 ± 0.14 and 13.10 ± 0.04 µg/mL, respectively. However, the methanolic extract was inactive on the MCF-7 cell line and only slightly active on the SiSo cell line. Chromatographic fractionations led to the isolation of ursolic acid from the active ethyl acetate extract and rutin from the methanolic extract. A further antiproliferative evaluation is warranted to confirm the contribution of ursolic acid to the effect of the ethyl acetate extract. Additional fractionations may uncover more phytoconstituents of diverse pharmaceutical interests.

Juan B. Pérez-Sánchez, Yunheng Zou, Jorge A. Campos-Gonzalez-Angulo et al.

Quantum chemistry is a foundational enabling tool for the fields of chemistry, materials science, computational biology and others. Despite of its power, the practical application of quantum chemistry simulations remains in the hands of qualified experts due to methodological complexity, software heterogeneity, and the need for informed interpretation of results. To bridge the accessibility gap for these tools and expand their reach to chemists with broader backgrounds, we introduce El Agente Quntur, a hierarchical, multi-agent AI system designed to operate not merely as an automation tool but as a research collaborator for computational quantum chemistry. Quntur was designed following three main strategies: i) elimination of hard-coded procedural policies in favour of reasoning-driven decisions, ii) construction of general and composable actions that facilitate generalization and efficiency, and iii) implementation of guided deep research to integrate abstract quantum-chemical reasoning across subdisciplines and a detailed understanding of the software's internal logic and syntax. Although instantiated in ORCA, these design principles are applicable to research agents more generally and easily expandable to additional quantum chemistry packages and beyond. Quntur supports the full range of calculations available in ORCA 6.0 and reasons over software documentation and scientific literature to plan, execute, adapt, and analyze in silico chemistry experiments following best practices. We discuss the advances and current bottlenecks in agentic systems operating at the research level in computational chemistry, and outline a roadmap toward a fully autonomous end-to-end computational chemistry research agent.

P.V. Komarov, I.K. Patrenkov, M.D. Malyshev et al.

To construct mesoscale models of molecular systems, the structure of all chemical components is simplified through a transformation known as «coarsening». In the case of modeling polymer materials, the conformational properties of roughened polymer chain models may not correspond to the original chemical prototypes. This can be compensated by introducing additional potentials into the model. Conditions for a model of a linear polymer chain with «beads and springs» in the infinitely diluted solution are determined using the dissipative particle dynamic method. It has been shown that the maximum amplitude value of the conservative force, that determines the interaction between the polymer and the solvent corresponding to these conditions, strongly depends on the stiffness constant Kb of the bond deformation potential. When Kb is greater than 30, this value tends to saturate. For Kb = 200, a relationship between the characteristic ratio of model chain lengths and the stiffness constant Ka was calculated. The results obtained are in good agreement with literature data and can be reproduced using theoretical calculations. The functional relationship between C∞ and Ka is universal and can be applied to construct accurate models of various polymers when their conformational characteristics are important.

Robert B. Mann

The introduction of thermodynamics into gravitational physics began 5 decades ago with the discovery that black holes behave like thermodynamic systems once semiclassical quantum effects are taken into account. Notions of temperature, entropy, work, and phase changes that were introduced into gravitational physics and originally applied to black holes, were later extended to cosmological horizons and other settings as well. A major development occurred 15 years ago with the introduction of pressure in the form of a cosmological constant. By extending the thermodynamic phase space to include this term, along with its conjugate volume, black holes were found to exhibit a broad variety of phase transitions that resembled phenomena seen in chemistry labs. Black hole thermodynamics has become Black Hole Chemistry, which has led to a wealth of insights into the nature of black holes, introducing concepts such as Van der Waals fluids, reentrant phase transitions, and triple points into gravitational physics. I discuss the origins of Black Hole Chemistry and its basic features covered in an earlier review [1], and then go on to describe developments in the subject that have taken place since then. Examples include multicritical behaviour, polymeric transitions, superfluid transitions, scalar hair, heat engines, NUT-charge, acceleration thermodynamics, the Joule-Thompson expansion, holography, complexity, central charge criticality, microstructure, thermodynamic tension, phase dynamics, and thermodynamic topology. This wealth of new phenomena suggest that we likely still have a lot to learn from Black Hole Chemistry.

Seokhyun Chin, Junghwan Park, Woojin Cho

Precipitation nowcasting, key for early warning of disasters, currently relies on computationally expensive and restrictive methods that limit access to many countries. To overcome this challenge, we propose precipitation nowcasting using satellite imagery with physics constraints for improved accuracy and physical consistency. We use a novel physics-informed dual neural operator (PIANO) structure to enforce the fundamental equation of advection-diffusion during training to predict satellite imagery using a PINN loss. Then, we use a generative model to convert satellite images to radar images, which are used for precipitation nowcasting. Compared to baseline models, our proposed model shows a notable improvement in moderate (4mm/h) precipitation event prediction alongside short-term heavy (8mm/h) precipitation event prediction. It also demonstrates low seasonal variability in predictions, indicating robustness for generalization. This study suggests the potential of the PIANO and serves as a good baseline for physics-informed precipitation nowcasting.

Jiajia Guo, Yiming Cui, Shi Jin et al.

Large artificial intelligence models (LAMs) are transforming wireless physical layer technologies through their robust generalization, multitask processing, and multimodal capabilities. This article reviews recent advancements in applying LAMs to physical layer communications, addressing obstacles of conventional AI-based approaches. LAM-based solutions are classified into two strategies: leveraging pre-trained LAMs and developing native LAMs designed specifically for physical layer tasks. The motivations and key frameworks of these approaches are comprehensively examined through multiple use cases. Both strategies significantly improve performance and adaptability across diverse wireless scenarios. Future research directions, including efficient architectures, interpretability, standardized datasets, and collaboration between large and small models, are proposed to advance LAM-based physical layer solutions for next-generation communication systems.

Garnet Kin-Lic Chan

We describe the problems of quantum chemistry, the intuition behind classical heuristic methods used to solve them, a conjectured form of the classical complexity of quantum chemistry problems, and the subsequent opportunities for quantum advantage. This article is written for both quantum chemists and quantum information theorists. In particular, we attempt to summarize the domain of quantum chemistry problems as well as the chemical intuition that is applied to solve them within concrete statements (such as a classical heuristic cost conjecture and a classification of different avenues for quantum advantage) in the hope that this may stimulate future analysis.

Masaki MATSUI, Yuki ORIKASA, Tomoki UCHIYAMA et al.

In situ/operando techniques for electrochemical systems are useful for understanding the electrochemical reactions, as we presented in Part 1. Here we present a series of in situ/operando techniques for battery applications. Now the in situ/operando techniques presented in this paper has become powerful tools for the development of advanced battery systems such as Li-ion batteries, solid-state batteries, and other beyond Li-ion batteries. In the present paper we introduce the in situ/operando cell design of each measurement technique and discuss how we apply each technique for in the advanced battery materials development.

Manuel Pastor-Cintas, Luis Felipe-Sesé, Ángel Molina-Viedma et al.

Recently, the combination of Fringe Projection (FP) and 2D Digital Image Correlation (2D-DIC) has become a low-cost alternative for measuring deformations even in dynamic events such as vibration testing. FP and DIC are displacement measurement techniques, so high frequency vibration tests associated with low levels of displacement suppose a challenge. By means of Phase-Based Motion Magnification algorithm (PBMM), the periodic displacement observed in an image sequence can be magnified. This makes it possible to measure clear displacement maps by FP + 2D-DIC even when subtle displacement occurs. This methodology allows a better interpretation of the vibration behavior of mechanical components. In this work, the behavior of a beam excited at its natural frequencies has been studied, showing the potential of PBMM and FP + 2D-DIC

Jun Liu, Haitao Zhao, Dongtang Ma et al.

Recently, deep neural network (DNN)-based physical layer communication techniques have attracted considerable interest. Although their potential to enhance communication systems and superb performance have been validated by simulation experiments, little attention has been paid to the theoretical analysis. Specifically, most studies in the physical layer have tended to focus on the application of DNN models to wireless communication problems but not to theoretically understand how does a DNN work in a communication system. In this paper, we aim to quantitatively analyze why DNNs can achieve comparable performance in the physical layer comparing with traditional techniques, and also drive their cost in terms of computational complexity. To achieve this goal, we first analyze the encoding performance of a DNN-based transmitter and compare it to a traditional one. And then, we theoretically analyze the performance of DNN-based estimator and compare it with traditional estimators. Third, we investigate and validate how information is flown in a DNN-based communication system under the information theoretic concepts. Our analysis develops a concise way to open the "black box" of DNNs in physical layer communication, which can be applied to support the design of DNN-based intelligent communication techniques and help to provide explainable performance assessment.

Michaela Heier, Rolf Merz, Stefan Becker et al.

Wetting is strongly influenced by adsorbate layers, which are omnipresent on surfaces. The influence of the composition and thickness of adsorbate layers on the water contact angle of sessile drops on different substrates was systematically investigated in the present work. Measurements were carried out for gold-sputtered substrates. These new results are compared to results from a previous study, in which corresponding measurements were carried out for technical steel and titanium substrates. In all experiments, different pretreatments of the samples were used to obtain variations of the adsorbate layer. The samples were either exposed to an oil bath or not, and different cleaning agents were used. The analysis of the adsorbate layer was carried out with X-ray photoelectron spectroscopy (XPS). The results for the different substrates reveal that the water contact angle depends mainly on the composition of the adsorbate layer. The substrate has only an indirect influence, as it influences the composition of the adsorbate layer. The thickness of the adsorbate layers was between 1.4 and 14 nm and was large enough to prevent a direct influence of the substrate on the water contact angle. It is shown that using the information on the adsorbate layer composition from XPS and the results for the water contact angle obtained for the gold samples alone, the water contact angles on the steel and titanium samples can be predicted.

A.S. Santhosh, S. Sandeep, H.M. Manukumar et al.

In this research, new green synthesized cow urine silver nanoparticles (CoUSiN particles) were accomplished by using cow urine as a reducing and capping agent. The cow urine silver nanoparticles have been marked by UV–Visible spectroscopy, X-ray diffraction, Fourier Transformer Infrared spectroscopy, Scanning Electron Microscopy, and Transmission Electron Microscopy. The size of the CoUSiN particles had probed by using a dynamic light scattering method and was determined to be 47.8 ​nm. Further, CoUSiN particles evidenced biocidal venture against Escherichia coli and methicillin-resistant Staphylococcus aureus through cell wall destruction and membrane poring. The SEM established the absolute biocidal sheath destabilization of Escherichia coli and whereas the cyclic voltammetry (CV) bolstered the membrane poring mechanism on methicillin-resistant Staphylococcus aureus. Further, the blood congenial nature of CoUSiN particles fortified that it can be a promising candidate to heal epizootic diseases. The inquiry infers that the CoUSiN particles incorporated adopting a simple, inexpensive, eco-friendly modus using cow urine as a reducing agent.

Emily Alicea-Muñoz, Carol Subiño Sullivan, Michael F. Schatz

Graduate Teaching Assistants (GTAs) are key partners in the education of undergraduates. Given the potentially large impact GTAs can have on undergraduate student learning, it is important to provide them with appropriate preparation for teaching. But GTAs are students themselves, and not all of them desire to pursue an academic career. Fully integrating GTA preparation into the professional development of graduate students lowers the barrier to engagement so that all graduate students may benefit from the opportunity to explore teaching and its applications to many potential career paths. In this paper we describe the design and implementation of a GTA Preparation course for first-year Ph.D. students at the Georgia Tech School of Physics. Through a yearly cycle of implementation and revision, guided by the 3P Framework we developed (Pedagogy, Physics, Professional Development), the course has evolved into a robust and comprehensive professional development program that is well-received by physics graduate students.

Konstantin L. Ivanov, Alexander Wagenpfahl, Carsten Deibel et al.

Spin chemistry and spintronics developed independently and with different terminology. Until now, the interaction between the two fields has been very limited. In this review, we compile the two "languages" in an effort to enhance communication. We expect that knowledge of spin chemistry will accelerate progress in spintronics.

Steffen Kaup, André Ludwig, Bogdan Franczyk

The Physical Internet (PI) raises high expectations for efficiency gains in transport and logistics. The PI represents the network of logistics networks for physical objects in analogy to the Data Internet (DI). Road based traffic represents one of these logistics networks. Here, many empty runs and underutilized trips still take place. Hence, there is a lot of potential in the road-based Physical Internet (RBPI), which will have an impact on transport and logistics strategies, but also on vehicle design. On the DI, logistics strategies are implemented in protocols. In order to transfer such concepts to the RBPI, relevant protocols of the DI had been analyzed and transferred to the world of physical objects. However, not all functionalities can be transferred one-to-one, e.g. a data packet in the DI can simply be re-generated by a hub in case of damage or loss. To compensate for the challenges, a framework artifact has been designed with appropriate transformation customizations based on design science principles. From this, resulting requirements for future vehicles were derived. This paper makes a contribution to the implementation of the RBPI in order to fit road based vehicles to the future world of transport and logistics.

A.N. Bolotov, O.O. Novikova

The work is aimed at creating a magnetometric device for accurate determining the saturation magnetization of magnetic nanofluids and similar properties of functional dispersed materials. The device is based on a magnetometric method with the Hall induction transducers, improved taking into account the peculiarities of the physical and mechanical properties of liquids. The measuring magnetic system of the device is designed in such a way that with the help of permanent magnets it is possible to create a uniform magnetizing field up to (2 ÷ 4) · 10^5 A/m in a working gap where the cuvette with the studied magnetic nanofluid is installed. Under the cuvette with a magnetic nanofluid in its middle section is a Hall Converter, which serves to measure the strength of the magnetizing magnetic field. The second Hall Converter, designed to measure the magnetic field induction in a substance, is installed in a rectangular groove and is located in the center of the magnetic nanofluid in the cuvette. The relative error of measuring the magnetization on the device did not exceed 2 % for magnetic nanofluids with a magnetization in the range from 10 kA / m to 50 kA/m. The created device can be used for Express measurements in laboratory and industrial conditions and does not require special professional skills. It is shown that the additive component of the instrumental measurement error depends on the values of the residual voltage (nonequipotential EMF), side galvanomagnetic effects and thermo - EMF of the measuring Converter. The multiplicative component is related to the time and temperature instability of the conversion coefficient and the current or voltage supply. The methodic error of the magnetometer is caused by the fact that not a fully closed magnetic circuit is used for measuring the magnetic field induction. It is shown that the device meets international standards for magnetic measurements of soft magnetic materials in terms of their metrological parameters. The device allowed us to determine the magnetization of colloidal systems in magnetic fields of a start paraprocess, individual magnetization of nanoparticles of the dispersed phase, the aggregative stability of colloids in magnetic and gravity fields to estimate the size of the solvation shell of the nanoparticles.

Thomas Weymuth, Markus Reiher

The impossibility of experiencing the molecular world with our senses hampers teaching and understanding chemistry because very abstract concepts (such as atoms, chemical bonds, molecular structure, reactivity) are required for this process. Virtual reality, especially when based on explicit physical modeling (potentially in real time), offers a solution to this dilemma. Chemistry teaching can make use of advanced technologies such as virtual-reality frameworks and haptic devices. We show how an immersive learning setting could be applied to help students understand the core concepts of typical chemical reactions by offering a much more intuitive approach than traditional learning settings. Our setting relies on an interactive exploration and manipulation of a chemical system; this system is simulated in real-time with quantum chemical methods, and therefore, behaves in a physically meaningful way.

Yutaka Shikano, Hiroshi C. Watanabe, Ken M. Nakanishi et al.

Quantum computational chemistry is a potential application of quantum computers that is expected to effectively solve several quantum-chemistry problems, particularly the electronic structure problem. Quantum computational chemistry can be compared to the conventional computational devices. This review comprehensively investigates the applications and overview of quantum computational chemistry, including a review of the Hartree-Fock method for quantum information scientists. Quantum algorithms, quantum phase estimation, and variational quantum eigensolver, have been applied to the post-Hartree-Fock method.

HaiTao Yan, SenSen Xin, Yong Yang et al.

The microstructure and corrosion behavior of 2205 duplex stainless steel (DSS) welds were investigated by optical microscopy (OM), scanning electronic microscopy (SEM) and electrochemical measurements. The ferrite (δ) phase content increases slightly from the base metal (BM) zone, to the heat affected zone (HAZ) to the weld metal (WM) of the welded joint. HAZ shows a very weak sensitization that was effectively detected by the double-loop electrochemical potentiokinetic reactivation (DL-EPR) test with an H2SO4 + HCl mixed solution. In hot artificial seawater, the pitting corrosion resistance, passivation and repassivation abilities decrease gradually from BM, to WM to HAZ. Weak sensitization plays a dominant role in the pitting corrosion of HAZ even though the degree of sensitization (DOS) is very low. BM and WM do not show intergranular corrosion (IGC) susceptibility and the difference in the pitting resistance between these two zones is small. The pitting corrosion resistance of the three weld zones was discussed in detail.

Robin T. Garrod

The first computational model of solid-phase chemistry in cometary nuclear ices is presented. An astrochemical kinetics model, MAGICKAL, is adapted to trace the chemical evolution in multiple layers of cometary ice, over a representative period of 5 Gyr. Physical conditions are chosen appropriate for "cold storage" of the cometary nucleus in the outer Solar System, prior to any active phase. The chemistry is simulated at a selection of static temperatures in the range 5 - 60 K, while the ice is exposed to the interstellar radiation field, inducing a photochemistry in the outer ice layers that produces significant formation of complex organic molecules. A treatment for the chemistry resulting from cosmic-ray bombardment of the ices is also introduced into the model, along with a new formulation for low-temperature photochemistry. Production of simple and complex molecules to depth on the order of 10~m or more is achieved, with local fractional abundances comparable to observed values in many cases. The production of substantial amounts of O$_2$ (and H$_2$O$_2$) is found, suggesting that long-term processing by high-energy cosmic rays of cometary ices in situ, over a period on the order of 1 Gyr, may be sufficient to explain the large observed abundances of O$_2$, if the overall loss of material from the comet is limited to a depth on the order of 10 m. Entry into the inner solar system could produce a further enhancement in the molecular content of the nuclear ices that may be quantifiable using this modeling approach.