jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bachir Benarba | Khadidja Belhouala | Cansu Korkmaz | Meltem Taş Küçükaydın | Selçuk Küçükaydın | Mehmet Emin Duru
Source: Journal of Phytology (article, 2024-12-13)
Field: Materials Science — Biomaterials

Phenolic profile, antioxidant, anti-inflammatory and anticancer activities of Telephium imperati L. Telephium imperati L. is one of the most valuable spices used by Algerians for food and different medicinal purposes. Here, we report the main phenolic compounds of T. imperati that grows in arid regions and its antioxidant, anti-inflammatory, and anticancer activities. The phenolic profiles of methanolic and aqueous extracts of T. imperati roots was obtained using HPLC-DAD, whereas antioxidant activity was evaluated using 2.2-diphenyl-1-picrylhydrazyl (DPPH), potassium ferricyanide, and Hydrogen peroxide (H2O2) assays. Moreover, the anti-inflammatory activity was investigated by measuring the level of protection of the human red blood cell (HRBC) membrane against hypotonicity-induced lysis. The anticancer activity was evaluated using the MTT assay against three human cancer cell lines (HT-29, PC-3, A-549) and one non-tumorigenic (CCD18-Co) cells. Our results showed that the methanolic extract was rich in phenols (493.17±0.0 mg GAE/g), flavonoids (271.56±0.1 mg QE/g), and tannins (106.50±2.3 mg CE/g). The HPLC-DAD analysis revealed that caffeic acid (78.61 mg/g), ferulic acid (49.12 mg/g), rosmarinic acid (42.80 mg/g), coumarin (39.87 mg/g), rutin (37.68 mg/g), myricetin (25.62 mg/g), syringic acid (18.90 mg/g), and quercetin (18.65 mg/g) were mainly present in T. imperati extracts. Although the DPPH assay showed slight antioxidant activity for both extracts, the methanolic extract exhibited significant potent anti-inflammatory action in all in vitro tests, protecting HRBC damage and BSA denaturation at rates of 80.18 and 97.62%, respectively. Likewise, the methanolic extract exhibited an important anticancer activity against the HT-29 and A-549 cell lines, with IC50 values ranging from 1.85 to 2.00 log10 μg/mL. Interestingly, no toxic effects on CCD18-Co were observed. Therefore, the present study revealed that T. imperati root extracts are rich in phenolic compounds and could be a promising source of anti-inflammatory and anticancer molecules. Chemistry ; DPPH ; Rutin ; Antioxidant ; Syringic acid ; Caffeic acid ; Quercetin ; Myricetin ; Phenols ; MTT assay ; Rosmarinic acid ; Traditional medicine ; Biochemistry ; Chromatography ; In vitro ; Gallic acid ; Kaempferol Phytochemistry and Bioactive Compounds ; Phytochemistry and Biological Activities ; Cynara cardunculus studies
Authors: D. Zhong | Huamin Yuan | Qiuyan Tian | Gongping Deng | Yanhong Ouyang | Yi Chen | Yang Wang | Zhiqin Yuan
Source: Journal of Food and Drug Analysis (article, 2024-06-10)
Field: Materials Science — Materials Chemistry

Fluorescent carbon nanodot-based rapid cell nucleus staining and application for diagnosis Cell nucleus status decides the activities of corresponding cells, making its rapid and effective staining important for revealing the actual condition of biological environment in life science and related fields. In this study, fast staining of cell nucleus is realized by fluorescent carbon nanodots (CDs). The staining mechanism is due to the positively charged CD surface-induced cell membrane penetration, which facilitates the CD-nucleus binding via electrostatic attraction. The size of cell nucleus is easily measured with fluorescence imaging technique. In addition, the CD-based cell nucleus stain is applied for discriminating the normal and cancer cells by determining the cell-to-nucleus ratio with fluorescence images. Fluorescence ; Nanodot ; Nucleus ; Carbon fibers ; Fluorescent staining ; Staining ; Biophysics ; Cell ; Chemistry ; Nanotechnology ; Materials science ; Cell biology ; Biology ; Pathology ; Biochemistry ; Medicine ; Optics ; Physics Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Nanocluster Synthesis and Applications
Authors: Priyanka Kumari | Madureira Sanches Ribeiro Guilherme | Pratyush Choudhary | Thomas Van Laethem | Marianne Fillet | Phillipe Hubert | Pierre Yves Sacre | Cédric Hubert
Source: Journal of Chemical Information and Modeling (article, 2024-09-16)
Field: Chemistry — Analytical Chemistry

Transfer Learning Approach to Multitarget QSRR Modeling in RPLC QSRR is a valuable technique for the retention time predictions of small molecules. This aims to bridge the gap between molecular structure and chromatographic behavior, offering invaluable insights for analytical chemistry. Given the challenge of simultaneous target prediction with variable experimental conditions and the scarcity of comprehensive data sets for such predictive modelings in chromatography, this study introduces a transfer learning-based multitarget QSRR approach to enhance retention time prediction. Through a comparative study of four models, both with and without the transfer learning approach, the performance of both single and multitarget QSRR was evaluated based on Mean Squared Error (MSE) and <i>R</i><sup>2</sup> metrics. Individual models were also tested for their performance against benchmark studies in this field. The findings suggest that transfer learning based multitarget models exhibit potential for enhanced accuracy in predicting retention times of small molecules, presenting a promising avenue for QSRR modeling. These models will be highly beneficial for optimizing experimental conditions in method development by better retention time predictions in Reversed-Phase Liquid Chromatography (RPLC). The reliable and effective predictive capabilities of these models make them valuable tools for pharmaceutical research and development endeavors. Computer science ; Artificial intelligence ; Chromatography ; Chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Analytical Chemistry and Chromatography
Authors: Guang F. Yang | Hong X. Song | Dan Wang | Hao Wang | Hua-Yun Geng
Source: Physical review. B./Physical review. B (preprint, 2024-03-20)
Field: Materials Science — Materials Chemistry

Topological and superconducting properties of two-dimensional <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi mathvariant="normal">C</mml:mi><mml:mrow><mml:mn>6</mml:mn><mml:mo>−</mml:mo><mml:mn>2</mml:mn><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>BN</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math> biphenylene network: First-principles investigation First-principles calculations have been used to investigate the electronic and topological properties of the two-dimensional ${\mathrm{C}}_{6\ensuremath{-}2x}{(\mathrm{BN})}_{x}$ biphenylene network, a graphenelike structure composed of not only hexagonal ring but also octagonal and square rings. Nontrivial topological properties have been found in two of them, with a stoichiometry of ${\mathrm{C}}_{4}\mathrm{BN}$ and ${\mathrm{C}}_{2}{(\mathrm{BN})}_{2}$. The former ${\mathrm{C}}_{4}\mathrm{BN}$ is predicted to be a type-II Dirac semimetal with a superconducting critical temperature ${T}_{\mathrm{c}}=0.38$ K, which is similar to the pure carbon biphenylene network (C-BPN). The latter shows an isolated edge state exists between the conduction and valence bands. By regulation of strains and virtual-crystal approximation calculations, we found the annihilation of two pairs of Dirac points (DPs) in the nonhigh-symmetric region causes the two corresponding edge states to stick together to generate this isolated edge state. In addition, we found that one pair of DPs arises from the shift of DPs in the C-BPN, while another pair of DPs emerges around the time-reversal invariant momenta point $X$ due to the doping of boron and nitrogen. We constructed a tight-binding model to reveal the mechanism of forming the isolated edge state from the C-BPN to ${\mathrm{C}}_{2}{(\mathrm{BN})}_{2}$. This study not only demonstrates the existence and mechanism of forming the isolated edge state in semimetals, but also provides an example in which the DPs can move away from the high-symmetry region. Biphenylene ; Superconductivity ; Topology (electrical circuits) ; Materials science ; Physics ; Condensed matter physics ; Mathematics ; Combinatorics ; Composite material Graphene research and applications ; Carbon Nanotubes in Composites ; Fullerene Chemistry and Applications
Authors: Yaoguang Zhai | Rashmi Richa | Etienne Palos | Francesco Paesani
Source: ChemRxiv (preprint, 2024-03-21)
Field: Materials Science — Materials Chemistry

Many-body interactions and deep neural network potentials for water We present a detailed assessment of deep neural network potentials developed within the DeePMD framework and trained on the MB-pol data-driven many-body potential energy function. Specific focus is directed at the ability of DeePMD-based potentials to correctly reproduce the accuracy of MB-pol across various water systems. Analyses of bulk and interfacial properties as well as many-body interactions characteristic of water elucidate inherent limitations in the transferability and predictive accuracy of DeePMD-based potentials. These limitations can be traced back to an incomplete implementation of the “nearsightedness of electronic matter” principle, which may be common throughout machine learning potentials that do not include a proper representation of self-consistently determined long-range electric fields. These findings provide further support for the "short-blanket dilemma" faced by DeePMD-based potentials, highlighting the challenges in achieving a balance between computational efficiency and a rigorous, physics-based representation of the properties of water. Finally, we believe that our study contributes to the ongoing discourse on the de- velopment and application of machine learning models in simulating water systems, offering insights that could guide future improvements in the field. Computer science ; Artificial neural network ; Representation (politics) ; Artificial intelligence ; Machine learning ; Dilemma ; Field (mathematics) ; Transferability ; Range (aeronautics) ; Focus (optics) ; Function (biology) ; Data science ; Physics ; Aerospace engineering ; Engineering ; Mathematics Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Protein Structure and Dynamics
Authors: Iman Taghavi | Omid Esmaeeli | Sheri Jahan Chowdhury | Awan, Kashif | Hammood, Mustafa | Matthew Mitchell | Donald Witt | Cory Pecinovsky | Jason W. Sickler | Young, Jeff | Nicolas S. B. Jaeger | Sudip Shekhar | Lukas Chrostowski
Source: arXiv (Cornell University) (preprint, 2024-05-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

GHz-rate optical phase shift in light matter interaction-engineered, silicon-ferroelectric nematic liquid crystals Organic electro-optic materials have demonstrated promising performance in developing electro-optic phase shifters. Their integration with other silicon photonic processes, nanofabrication complexities, and durability remains to be developed. While the required poling step in electro-optic polymers limits their potential and utilization on a large scale, devices made of paraelectric nematic liquid crystals suffer from slow bandwidth. In ferroelectric nematic liquid crystals, we report an additional GHz-fast phase shift that ultimately allows for significant second-order nonlinear optical coefficients related to the Pockels effect. It avoids poling issues and can pave the way for hybrid silicon-organic systems with CMOS-foundry compatibility. We report DC and AC modulation efficiencies of $\approx$~0.25 V$\cdot$mm (from liquid crystal orientation) and $\approx$~25.7 V$\cdot$mm (from Pockels effect), respectively, an on-chip insertion loss of $\approx$~2.6 dB, and an electro-optic bandwidth of $f_\text{-6dB}$&gt;4.18 GHz, employing improved light-matter interaction in a waveguide architecture that calls for only one lithography step. Liquid crystal ; Ferroelectricity ; Materials science ; Silicon ; Phase (matter) ; Optoelectronics ; Optics ; Condensed matter physics ; Physics Liquid Crystal Research Advancements ; Optical Polarization and Ellipsometry ; Photonic and Optical Devices
Authors: 葛宏义 Ge Hongyi | 补雨薇 Bu Yuwei | 蒋玉英 Jiang Yuying | 季晓迪 Ji Xiaodi | 贾柯柯 Jia Keke | 吴旭阳 Wu Xuyang | 张元 Zhang Yuan | 张玉洁 Zhang Yujie | 孙庆成 Sun Qingcheng | 王顺 Wang Shun
Source: Laser & Optoelectronics Progress (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

人工智能在太赫兹超材料设计与优化领域的研究进展 近年来，基于人工智能技术的超材料器件设计方法成为当前研究的焦点。人工智能技术的加入显著减少了超材料器件传统设计方法对设计人员电磁学理论及仿真经验的依赖，并有效缩减研究者的设计周期。然而，尽管该领域取得了一定进展，但太赫兹波段的器件设计仍然是一个相对欠发展的领域。首先从器件功能的角度出发，对太赫兹超材料器件传统设计方法进行了细致梳理，同时关注可调谐多功能超材料器件的研究现状。此外，详细阐述了人工智能技术（机器学习、进化算法、深度学习等）如何为超材料器件基于结构参数的正向优化与基于电磁响应的逆向设计过程提供支持。最后对该领域的未来发展和挑战进行了探讨，旨在为从事相关研究的科研人员提供有益参考。 Computer science Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Junju Xu | Yuzhou Zhang | Yajing Zhang | Lin Chen | Ziyang Gao | Haihui Ruan
Source: Journal of the American Ceramic Society (article, 2024-10-24)
Field: Materials Science — Ceramics and Composites

Modeling of ternary ion exchange and stress evolution in lithium‐containing glass Abstract A computational model of ternary ion exchange (IOX) for strengthening glass is proposed to predict the cation concentration and residual stress distributions in glass after ternary IOX. The comparison between theoretical predictions and experimental results indicated the validates the model. Additionally, it provides a method to determine ion diffusivity and volume expansion through ternary IOX experiments. Simulations of K–Na–Li ternary IOX were conducted using the parameters calibrated based on experimental results from a thick silicate glass. Then the process parameters were changed to clarify their influences. Key findings reveal that for thick glass (where lateral expansion is negligible), the optimum ratio of K + and Na + concentrations in a molten salt is 2:1. We further consolidate the effects of process parameters by training a neural network (NN) and demonstrate that the NN can be a surrogate model to replace the time‐consuming simulations, which could be more adaptable by the glass industry. Ternary operation ; Materials science ; Lithium (medication) ; Volume expansion ; Thermal diffusivity ; Thermodynamics ; Ion ; Ion exchange ; Mineralogy ; Composite material ; Analytical Chemistry (journal) ; Chemistry ; Chromatography ; Organic chemistry ; Computer science Glass properties and applications ; Nuclear materials and radiation effects ; Ferroelectric and Piezoelectric Materials
Authors: Jiaxin Hong | Minghui Liu | Youxing Liu | Shengcong Shang | Xinyu Wang | Changsheng Du | Wenqiang Gao | Chunyu Hua | Helin Xu | Zewen You | Yunqi Liu | Jianyi Chen
Source: Angewandte Chemie (article, 2024-01-09)
Field: Materials Science — Materials Chemistry

Solid‐Liquid Interfacial Engineered Large‐Area Two‐Dimensional Covalent Organic Framework Films Abstract Constructing uniform covalent organic framework (COF) film on substrates for electronic devices is highly desirable. Here, a simple and mild strategy is developed to prepare them by polymerization on a solid‐liquid interface. The universality of the method is confirmed by the successful preparation of five COF films with different microstructures. These films have large lateral size, controllable thickness, and high crystalline quality. And COF patterns can also be directly achieved on substrates via hydrophilic and hydrophobic interface engineering, which is in favor of preparing device array. For application studies, the PyTTA‐TPA (PyTTA: 4,4′,4′′,4′′′‐(1,3,6,8‐Tetrakis(4‐aminophenyl)pyrene and TPA: terephthalaldehyde) COF film has a high photoresponsivity of 59.79 μA W −1 at 420 nm for photoelectrochemical (PEC) detection. When employed as an active material for optoelectronic synaptic devices for the first attempt, it shows excellent light‐stimulated synaptic plasticity properties such as short‐term plasticity (STP), long‐term plasticity (LTP), and the conversion of STP to LTP, which can be used to simulate biological synaptic functions. Covalent bond ; Materials science ; Liquid crystalline ; Nanotechnology ; Covalent organic framework ; Chemical engineering ; Chemistry ; Organic chemistry ; Liquid crystal ; Optoelectronics ; Engineering Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Pickering emulsions and particle stabilization
Authors: Fengyu Miao | Jie Li | Feng Zhang | Xin Bi | Xin Huang | Zhihong Yang | Yunhui Wang | Yakui Weng
Source: International Journal of Energy Research (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Sodium‐Decorated SiB Monolayer for Reversible Hydrogen Storage: High‐Capacity Achieved by Carbon Doping Based on the first‐principles calculation and grand canonical Monte Carlo (GCMC) simulation, the reversible hydrogen storage of Na‐decorated silicon boron (SiB) and C‐doped SiB monolayers have been investigated. For double side 4Na‐decorated SiB monolayer, each Na atom can adsorb five H 2 molecules with the average adsorption energy of −0.18 eV/H 2 , yielding an H 2 gravimetric density of 9.09 wt% and desorption temperature T D of 227 K. To further improve the H 2 gravimetric density and desorption temperature, doping effect was employed to enhance the internal electric field between Na atom and SiB substrate. When two Si atoms in the SiB monolayer were replaced by C atoms, the adsorption energy for H 2 was significantly improved. The H 2 gravimetric density reaches to 10.63 wt% with the average adsorption energy of −0.22 eV/H 2 . Meanwhile, the desorption temperature T D was raised from 227 to 282 K, reaching the ideal condition near room temperature. In addition, the GCMC simulations further confirm that the H 2 gravimetric density can fully meet the latest hydrogen storage target (5.5 wt%) for both Na‐decorated SiB monolayer and Na‐decorated C‐doped SiB monolayer. Our results indicate that both Na‐modified SiB and C‐doped SiB monolayers can be used as promising materials for reversible hydrogen storage. Monolayer ; Hydrogen storage ; Doping ; Carbon fibers ; Hydrogen ; Materials science ; Chemical engineering ; Sodium ; Chemistry ; Nanotechnology ; Optoelectronics ; Engineering ; Organic chemistry ; Composite material ; Metallurgy MXene and MAX Phase Materials ; Hydrogen Storage and Materials ; Graphene research and applications
Authors: Zhi Wang | Wen Yan
Source: arXiv (Cornell University) (preprint, 2024-12-24)
Field: Materials Science — Materials Chemistry

OpenMM-Python-Force: Deploying Accelerated Python Modules in Molecular Dynamics Simulation We present OpenMM-Python-Force, a plugin designed to extend OpenMM's functionality by enabling integration of energy and force calculations from external Python programs via a callback mechanism. During molecular dynamics simulations, data exchange can be implemented through torch.Tensor or numpy.ndarray, depending on the specific use case. This enhancement significantly expands OpenMM's capabilities, facilitating seamless integration of accelerated Python modules within molecular dynamics simulations. This approach represents a general solution that can be adapted to other molecular dynamics engines beyond OpenMM. The source code is openly available at https://github.com/bytedance/OpenMM-Python-Force. Python (programming language) ; Computer science ; Molecular dynamics ; Programming language ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions
Authors: Chamanthi Denisha Jayaweera | David Fernandes del Pozo | Ivaylo Plamenov Hitsov | Maxime Van Haeverbeke | Thomas Diekow | Arne Verliefde | Ingmar Nopens
Source: npj Materials Degradation (article, 2024-12-19)
Field: Materials Science — Materials Chemistry

Assessing the feasibility of using a data-driven corrosion rate model for optimizing dosages of corrosion inhibitors Abstract Optimizing dosages of corrosion inhibitors requires experimental data gathered from time-consuming methods. The current study examines the feasibility of optimizing inhibitor dosages using a model trained for predicting corrosion rates more easily measured using linear polarization resistance in a full-scale cooling water system. A comprehensive study on variable selection showed that linearly correlated variables are necessary to predict corrosion trends. The Sobol sensitivity of inhibitors is trivialized by variables linearly correlated to the corrosion rate. The study highlights the importance of achieving high model prediction accuracy and high Sobol sensitivity of inhibitors to the corrosion rate, for using the model for inhibitor dosage optimization. Corrosion ; Dose ; Materials science ; Metallurgy ; Medicine ; Pharmacology Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Ireneusz Plebankiewicz | Krzysztof Artur Bogdanowicz | Paweł Kwaśnicki | Wojciech Przybył | Magdalena Skunik‐Nuckowska | Paweł J. Kulesza | Agnieszka Iwan
Source: Scientific Reports (article, 2024-03-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inorganic–organic modular silicon and dye-sensitized solar cells and predicted role of artificial intelligence towards efficient and stable solar chargers based on supercapacitors Appropriate and rational management of the energy produced by renewable energy sources is one of the most urgent challenges for the global energy sector. This paper is devoted to the systematic experimental and theoretical studies of a modular solar charger based on silicon and dye-sensitized solar cells as an energy source, and supercapacitor as an energy bank. Using the MathCAD program, I-V characteristics were plotted for both a single cell and a photovoltaic module based on various series-to-parallel connections. To assess the surface quality of the modules, additional tests using a thermal imaging camera were carried out as well. The charging characteristics of the supercapacitor (two series-connected cells with a capacity of 300 F), were determined depending on the parameters of the photovoltaic module as well as considering the influence of the voltage balancing system and control system. The charge, discharge, and recharge characteristics were carefully analyzed to optimize the operating conditions, i.e. the number of photovoltaic cells. To evaluate the stability of parameters with operation time, and their temperature dependence (17-65 °C), solar modules were tested for ten days under Central European weather conditions. Importantly, a comparative analysis of solar chargers based on different configurations of photovoltaic cells showed an increase in electrical parameters for the proposed modular inorganic-organic concept compared to dye-sensitized solar cells produced alone on a rigid substrate. Finally, preliminary assumptions (requirements) were developed regarding the electrical and optical parameters for new dye-sensitized solar cells that could be used in the innovative solar charger instead of silicon cells along with a predicted role of artificial intelligence (AI) in these devices. Photovoltaic system ; Modular design ; Supercapacitor ; Renewable energy ; Solar energy ; Materials science ; Dye-sensitized solar cell ; Computer science ; Solar cell ; Process engineering ; Electrical engineering ; Automotive engineering ; Optoelectronics ; Engineering ; Chemistry ; Electrode ; Capacitance Supercapacitor Materials and Fabrication ; Advancements in Battery Materials ; Advanced battery technologies research