Hasil untuk "Physical and theoretical chemistry"

Haruka HOMMA, Aika MOCHIZUKI, Kaori MIYAKOSHI et al.

The one-pot electrooxidative allylation of carbamates was successfully demonstrated in the presence of HBF4 and H2O. Anodic oxidation of carbamates generated the corresponding α-hydroxylated intermediates in the presence of H2O. Without separating the intermediates after electrolysis, reacting them with allyltrimethylsilane in the presence of HBF4 yielded the corresponding α-allylated products in high yields. This method was found to be applicable to several carbamates, except those with an acid-labile Boc protecting group.

Ashfaq Ahmad Khan, Muhammad Kashif Shahid

Food irradiation is gaining popularity worldwide due to its potential to extend shelf life, improve hygienic quality, and meet trade requirements. The electron paramagnetic resonance (EPR) method is a reliable and sensitive technique for detecting untreated and irradiated foods. This study investigated the effectiveness of EPR in identifying irradiated meat and seafood containing bones. Beef, lamb, chicken, and various fish were irradiated with electron beams at different doses and analysed using an EPR spectrometer. During irradiation, the food samples were surrounded by small ice bags to prevent autodegradation of cells and nuclei. After the irradiation process, the samples were stored at −20 °C. For EPR signal recording, the flesh, connective tissues, and bone marrow were removed from the bone samples, which were then oven-dried at 50 °C. The EPR spectra were recorded using an X-band EPR analyzer. Unirradiated and irradiated samples were identified based on the nature of the EPR signals as well as the g-values of symmetric and asymmetric signals. The study found that the EPR method is effective in distinguishing between unirradiated and irradiated bone-containing foods across nearly all applied radiation doses. The peak-to-peak amplitude of the EPR signals increased with increasing radiation doses. It was observed that unirradiated bone samples showed low-intensity symmetrical signals, while irradiated samples showed typical asymmetric signals. Overall, the study demonstrated that the EPR method is a reliable and sensitive technique for identifying irradiated foods containing bones and can be used for the control, regulation, and proper surveillance of food irradiation.

Tetiana Krupska, Myroslav Lenov, Qiliang Wei et al.

Sergey V. Uchaikin, Boris I. Ivanov, Arjan F. van Loo et al.

We present the development of two complementary amplifier architectures for axion haloscope experiments, based on two types of Josephson Parametric Amplifiers (JPAs). The first employs a multi-chip module of flux-driven JPAs in a parallel–series configuration, enabling near quantum-limited amplification over an extended tunable range of between 1.2 and 1.5 GHz. The second design features a lumped-element JPA, offering continuous tunability across a wide frequency range from 2.4 to 4 GHz. Both approaches demonstrate near-quantum-limited noise performance and are compatible with operation in cryogenic environments. These amplifiers significantly enhance the sensitivity and frequency coverage of axion search experiments, and also provide new opportunities for broadband quantum sensing applications.

O.A. Golovanova

Lanthanide-doped hydroxyapatite nanoparticles can be used as luminescent labels and become an alternative to organic fluorophores, as they are more stable and have a longer service life. Such materials allow tissue studies in surgery, the bone engineering and tissue regeneration. Lanthanides are known to have a high affinity for hydroxyapatite. This is due to the fact that lanthanides have ionic radii close to that of the calcium ion which is associated with their biological activity. Rare earth elements inhibit the formation of osteoclast-like cells and the process of the bone resorption. At the same time, lanthanides have a biological effect on the body, as a result bacterial growth is suppressed and, at the same time, the structure of the outer cell membrane, responsible for cell permeability, changes. Substituted hydroxyapatites were synthesized with varying content of the lanthanum (III) and cerium (III) ions. The formation of substituted hydroxyapatite was proven by X-ray diffraction and infrared spectroscopy. The parameters of the crystal lattices of the synthesized phases were shown to change, indicating the replacement of calcium ions by rare earth element ions in the hydroxyapatite structure. The presence of rare earth element ions in solid phases was proven by inductively coupled plasma atomic emission spectroscopy. The study of the resorption of thesynthesized samples revealed that cation-substituted hydroxyapatites are less soluble than unmodified hydroxyapatite. Thus, lanthanum (III) and cerium (III) ions can inhibit and suppress the action of osteoclasts and thereby prevent the destruction of the bone tissue maintaining its integrity. Accordingly, the material based on hydroxyapatite dosed with rare earth element ions can have a positive effect when used in bone engineering.

Andrew D. McNaughton, Gautham Ramalaxmi, Agustin Kruel et al.

Large language models (LLMs) have shown remarkable potential in various domains, but they often lack the ability to access and reason over domain-specific knowledge and tools. In this paper, we introduced CACTUS (Chemistry Agent Connecting Tool-Usage to Science), an LLM-based agent that integrates cheminformatics tools to enable advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama2-7b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b and Mistral-7b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with domain-specific tools, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment. Furthermore, CACTUS represents a significant milestone in the field of cheminformatics, offering an adaptable tool for researchers engaged in chemistry and molecular discovery. By integrating the strengths of open-source LLMs with domain-specific tools, CACTUS has the potential to accelerate scientific advancement and unlock new frontiers in the exploration of novel, effective, and safe therapeutic candidates, catalysts, and materials. Moreover, CACTUS's ability to integrate with automated experimentation platforms and make data-driven decisions in real time opens up new possibilities for autonomous discovery.

Andrew J. Wildridge, Jack P. Rodgers, Ethan M. Colbert et al.

Bumblebee is a foundation model for particle physics discovery, inspired by BERT. By removing positional encodings and embedding particle 4-vectors, Bumblebee captures both generator- and reconstruction-level information while ensuring sequence-order invariance. Pre-trained on a masked task, it improves dileptonic top quark reconstruction resolution by 10-20% and excels in downstream tasks, including toponium discrimination (AUROC 0.877) and initial state classification (AUROC 0.625). The flexibility of Bumblebee makes it suitable for a wide range of particle physics applications, especially the discovery of new particles.

O.E. Korolkov, V.V. Stolyarov

The article studies the effect of stress relaxation caused by strain stops and pulsed current on the tensile deformation behavior of Grade 4 ultrafine-grained titanium. The samples were deformed in the following modes: without current; continuously with current; with periodic current supply, periodic current supply during stops of strain. The microhardness of the working zone of the tested specimens was studied. Fracture studies of the failure zone were carried out. It is shown that, as a result of the continuous introduction of current during tension, the flow stresses decrease, and the elongation to failure increases. Periodic introduction of current, accompanied by strain stops, leads to a maximum increase in the relative elongation to failure due to stress relaxation. The relaxation effect of the pulsed current is manifested in a decrease in microhardness and the transition of the fracture type from a dimple-cup fracture to a predominantly dimple fracture.

Emilie Panek, Jean-Philippe Beaulieu, Pierre Drossart et al.

Studying chemistry and chemical composition is fundamental to go back to formation history of planetary systems. We propose here to have another look at five targets to better determine their composition and the chemical mechanisms that take place in their atmospheres. We present a re-analysis of five Hot Jupiters, combining multiple instruments and using Bayesian retrieval methods. We compare different combinations of molecules present in the simulated atmosphere, different chemistry types as well as different clouds parametrization. As a consequence of recent studies questioning the detection of Na and K in the atmosphere of HD 209458b as being potentially contaminated by stellar lines when present, we study the impact on other retrieval parameters of misinterpreting the presence of these alkali species. We use spatially scanned observations from the grisms G102 and G141 of the WFC3 on HST, with a wavelength coverage of $\sim$0.8 to $\sim$1.7 microns. We analyse these data with the publicly available Iraclis pipeline. We added to our datasets STIS observations to increase our wavelength coverage from $\sim$0.4 to $\sim$1.7 microns. We then performed a Bayesian retrieval analysis with the open-source TauREx using a nested sampling algorithm. We explore the influence of including Na and K on the retrieval of the molecules from the atmosphere. Our data re-analysis and Bayesian retrieval are consistent with previous studies but we find small differences in the retrieved parameters. After all, Na and K has no significant impact on the properties of the planet atmospheres. Therefore, we present here our new best-fit models, taking into account molecular abundances varying freely and equilibrium chemistry. This work is a preparation for a future addition of more sophisticated representation of chemistry taking into account disequilibrium effects such as vertical mixing and photochemistry.

Yilan Qin, Jiayu Ma, Mingle Jiang et al.

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this paper, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. In addition, we introduce a variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.

O. Sipilä, P. Caselli, E. Redaelli et al.

We aim to quantify the effect of chemistry on the infall velocity in the prestellar core L1544. Previous observational studies have found evidence for double-peaked line profiles for the rotational transitions of several molecules, which cannot be accounted for with the models presently available for the physical structure of the source, without ad hoc up-scaling of the infall velocity. We ran one-dimensional hydrodynamical simulations of the collapse of a core with L1544-like properties (in terms of mass and outer radius), using a state-of-the-art chemical model with a very large chemical network combined with an extensive description of molecular line cooling, determined via radiative transfer simulations, with the aim of determining whether these expansions of the simulation setup (as compared to previous models) can lead to a higher infall velocity. After running a series of simulations where the simulation was sequentially simplified, we found that the infall velocity is almost independent of the size of the chemical network or the approach to line cooling. We conclude that chemical evolution does not have a large impact on the infall velocity, and that the higher infall velocities that are implied by observations may be the result of the core being more dynamically evolved than what is now thought, or alternatively the average density in the simulated core is too low. However, chemistry does have a large influence on the lifetime of the core, which varies by about a factor of two across the simulations and grows longer when the chemical network is simplified. Therefore, although the model is subject to several sources of uncertainties, the present results clearly indicate that the use of a small chemical network leads to an incorrect estimate of the core lifetime, which is naturally a critical parameter for the development of chemical complexity in the precollapse phase.

Joonho Lee, Hung Q. Pham, David R. Reichman

In this work, we present an overview of the phaseless auxiliary-field quantum Monte Carlo (ph- AFQMC) approach from a computational quantum chemistry perspective, and present a numerical assessment of its performance on main group chemistry and bond-breaking problems with a total of 1004 relative energies. While our benchmark study is somewhat limited, we make recommendations for the use of ph-AFQMC for general main-group chemistry applications. For systems where single determinant wave functions are qualitatively accurate, we expect the accuracy of ph-AFQMC in conjunction with a single determinant trial wave function to be between that of coupled-cluster with singles and doubles (CCSD) and CCSD with perturbative triples (CCSD(T)). For these applications, ph-AFQMC should be a method of choice when canonical CCSD(T) is too expensive to run. For systems where multi-reference (MR) wave functions are needed for qualitative accuracy, ph-AFQMC is far more accurate than MR perturbation theory methods and competitive with MR configuration interaction (MRCI) methods. Due to the computational efficiency of ph-AFQMC compared to MRCI, we recommended ph-AFQMC as a method of choice for handling dynamic correlation in MR problems. We conclude with a discussion of important directions for future development of the ph-AFQMC approach.

Jan Hermann, James Spencer, Kenny Choo et al.

Machine learning and specifically deep-learning methods have outperformed human capabilities in many pattern recognition and data processing problems, in game playing, and now also play an increasingly important role in scientific discovery. A key application of machine learning in the molecular sciences is to learn potential energy surfaces or force fields from ab-initio solutions of the electronic Schrödinger equation using datasets obtained with density functional theory, coupled cluster, or other quantum chemistry methods. Here we review a recent and complementary approach: using machine learning to aid the direct solution of quantum chemistry problems from first principles. Specifically, we focus on quantum Monte Carlo (QMC) methods that use neural network ansatz functions in order to solve the electronic Schrödinger equation, both in first and second quantization, computing ground and excited states, and generalizing over multiple nuclear configurations. Compared to existing quantum chemistry methods, these new deep QMC methods have the potential to generate highly accurate solutions of the Schrödinger equation at relatively modest computational cost.

Xingze Li

Flavonoid as a newly discovered nutrient, has essential physiological health effects on the human body. In this work, a very fast technique was proposed for the electrochemical analysis of rutin in food samples. Nitrogen-doped carbon nanospheres were synthesized for the surface modification of glassy carbon electrodes. The modified electrodes exhibited a sensitive response to rutin. After optimizations, this method can detect rutin in the range of 50 nM-10 μM, with the detection limit calculated to be 15.3 nM. In addition, the proposed electrochemical has been successfully adopted for detecting rutin in juice, pickled cucumbers and tomatoes.

Shunyu Huang, Jingji Li, Jipeng Wang

Soil leucine aminopeptidase (LAP) is a hydrolytic enzyme involved in the acquisition of nitrogen by microorganisms. In contaminated soils, LAP activity is affected not only by the type and concentration of heavy metals but also by the form of enzyme. Here, we investigated the degree and mechanism of cadmium (Cd) inhibition of soil LAP and purified LAP. We also examined the effect of montmorillonite and kaolinite on LAP and LAP contaminated with Cd. The results showed that Cd inhibition of LAP activity increased with increasing Cd concentration and that Cd exerted noncompetitive inhibition of LAP. The addition of clay minerals decreases LAP activity and the maximum reaction rate (Vmax), regardless of the presence of Cd. Montmorillonite decreases the affinity of LAP to the substrate (Km), while kaolinite increases the affinity of LAP to the substrate. The clay mineral-immobilized LAP showed an increase in resistance to Cd contamination compared with the free LAP. The results obtained in this study may aid in understanding the toxic effects of heavy metals on soil enzymes.

Qi Hu, Qiang Yu, Zhen Chen et al.

Three-dimensional porous PbO2 (3D-PbO2) electrode was prepared by anodic oxidation deposition method，using an oxygen bubble template. To prepare 3D-PbO2 electrode controllably, the influence of current density, Pb2+ ion concentration, and pH value on the structure and performance of PbO2 electrode was studied. The results show that the current density determined the appearance of oxygen bubbles. The nucleation and growth of the oxygen bubbles were controlled by Pb2+ concentration and the pH value, respectively. The effect of the process conditions on the performance of electrode materials was obtained by comparing the electrocatalytic activities of the electrodes. The morphology and phase composition of the different anode materials were analyzed, and electrocatalytic activities were investigated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The CV curve shows that the total voltammetric charge (qT⁎) of the 3D-PbO2 electrode was 70 times larger than that of the flat-PbO2 electrode. In addition, during the evolution of oxygen, the 3D-PbO2 electrode had a higher exchange current density (j0), lower apparent activation energy (Ea) and lower charge transfer resistance (Rct) than the flat-PbO2 electrode.

Yu.A. Malkanduev, A.A. Kokoevа, А.T. Dzhalilov

The results of spontaneous polymerization of α-chloroacrylic and α-bromoacrylic acids with tertiary amines at a low temperature are presented. As a result of spontaneous polymerization during the interaction of α-halodacrylic acids with tertiary amines, polymers containing quaternary ammonium groups are formed. In order to confirm this assumption, nuclear magnetic resonance and infrared spectroscopic studies of the products of the spontaneous polymerization were carried out. Spontaneous polymerization proceeds, consisting of two stages: the quaternization reaction and the polymerization reaction. The kinetic regularities of the polymerization reaction were studied and it was shown that the quaternization reaction, which is the limiting stage of the spontaneous polymerization process, proceeds according to the SN2 - mechanism. It has described the first attempts to obtain new nanocomposite materials based on synthesized copolymers and modified montmorillonite. Analysis of the literature data shows that the features of the preparation of nanocomposites based on Na+ - montmorillonite and water-soluble copolymers have not been previously studied.

Sahrish Jaleel Shaikh, Benoit Montreuil, Moussa Hodjat-Shamami et al.

The Physical Internet (PI) puts high emphasis on enabling logistics to reliably perform at the speed mandated by and promised to customers, and to do so efficiently and sustainably. To do so, goods to be moved are encapsulated in modular containers and these are flowed from hub to hub in relay mode. At each hub, PI enables fast and efficient dynamic consolidation of sets of containers to be shipped together to next hubs. Each consolidated set is assigned to an appropriate vehicle so to enact the targeted transport. In this paper, we address the case where transportation service providers are available to provide vehicles and trailers of distinct dimensions on demand according to openly agreed and/or contracted terms. We describe the essence of such terms, notably relative to expected frequency distribution of transport requests, and expectations about time between request and arrival at hub. In such a context, we introduce rigorous generic protocols that can be applied at each hub so as to dynamically generate consolidation sets of modular containers and requests for on-demand transportation services, in an efficient, resilient, and sustainable way ensuring reliable pickup and delivery within the promised time windows. We demonstrate the performance of such protocols using a simulation-based experiment for a national intercity express parcel logistic network. We finally provide conclusive remarks and promising avenues for field implementation and further research.

Xingrui Zheng, Song Lv, Zhentao Yuan et al.

A glucose biosensor based on hollow sphere TiO2 was prepared via a simple synthesized method that used carbonaceous spheres as template. The studies indicated that the glucose biosensor based on hollow sphere TiO2 is characterized to high surface area, narrow pore size distribution as well as the high sensitivity of 5.64 mA M-1cm-1, which facilitates the direct electron transfer between glucose oxidase (GOx) and surface of electrodes. Most importantly, this material display long-time stability and reproducibility and achieved 94% stable current only with 3s. Meanwhile, it still maintains the 70% of current response after two months later, indicating that the hollow sphere TiO2 prepared via a carbon-sphere template method is a promising material for the construction of glucose biosensor and other biologic applications.

Jinghua Li, Xianyong Hong, Yumei Luo et al.

Porous carbon materials are one of the most widely studied electrode materials in supercapacitor electrode materials. Many studies have shown that increasing the specific surface area of porous carbon materials, increasing the pore structure, and hetero-atom doping can improve the electrochemical performance of porous carbon materials. Here, three-dimensional-graded porous carbon materials were successfully prepared by carbonization and activation using pine nut shells as carbon sources. After activation by potassium hydroxide, the specific surface area is as high as 2192 m2/g and the pore volume is 1.4 nm. As a supercapacitor electrode material, the specific capacitance at a current density of 0.5 A/g is as high as 408 F/g. The material also has good cycle stability (the specific capacity retention rate after 5,000 cycles of testing at a current density of 10 A/g was 95%). The large specific surface area, outstanding specific capacitance, and good cycle stability make the pine nut-shell porous carbon material a potential supercapacitor electrode material