jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: S Chen | C.Y. Low | Jia Ying Hilda Loh | Wan Yin Tew | Lizhi Ouyang | Peng Shun Ong | Chong Seng Yan | Hui Wei Loh | Ying Chen | Wei Xu | Wen Cai Xu | Tiem Leong Yoon | Mun Fei Yam
Source: Frontiers in Chemistry (article, 2025-10-27)
Field: Chemistry — Analytical Chemistry

A rapid approach for discriminating Ganoderma species using attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy integrated with chemometric analysis and convolutional neural network (CNN) The issue of adulteration and misclassification of <i>Ganoderma</i> species is addressed in this research. In the study, we present a novel and comprehensive framework for <i>Ganoderma</i> authentication by analyzing attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectra using a combined approach of a chemometric analysis and deep learning (DL) with a convolutional neural network (CNN). The three <i>Ganoderma</i> species involved in this study were as follows: <i>Ganoderma lucidum</i>, <i>Ganoderma sinense</i>, and <i>Ganoderma tsugae</i>. Among chemometric models, orthogonal partial least squares discriminant analysis (OPLS-DA) yielded a high accuracy of 98.61%, a sensitivity of 97.92%, and a specificity of 98.96%. Additionally, the root-mean-squared error of estimation (RMSEE), root-mean-squared error of prediction (RMSEP), and root-mean-squared error of cross-validation (RMSECV) values for the OPLS-DA model were <0.3, confirming its reliability. The CNN model also performed well, achieving 89.84% accuracy, 84.75% sensitivity, and 92.38% specificity, with minimal variation during random segregation testing. Additionally, the model exhibited a precision of 0.87 ± 0.02, a recall of 0.85 ± 0.03, and an F1 score of 0.86 ± 0.03 for 10 random segregation tests. As a conclusion, both chemometric and CNN models developed in this study are efficient and robust for classifying <i>Ganoderma</i> species. To further validate this combined approach, we aim to implement chemometric and CNN models in other medicinal herb authentication in the future. Pattern recognition (psychology) ; Convolutional neural network ; Partial least squares regression ; Linear discriminant analysis ; Chemometrics ; Artificial neural network ; Sensitivity (control systems) ; Random forest Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Yasin Yılmaz | Serdar Yılmaz | A. Yilmaz
Source: Research Square (preprint, 2025-04-15)
Field: Materials Science — Materials Chemistry

Eco-friendly organic inhibitors for enhancing the corrosion resistance of Al- 2024 alloy Corrosion ; Alloy ; Environmentally friendly ; Resistance (ecology) ; Materials science ; Metallurgy ; Business ; Biology ; Ecology Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Metal and Thin Film Mechanics
Authors: Delai Zhou | Fude Yang | Jian Xu | Fankui Zeng
Source: Sensors (review, 2025-11-24)
Field: Materials Science — Materials Chemistry

Application of Quantum Dots in Chinese Herbal Medicines: Advances in Detection, Pollutant Degradation, and Pharmacological Enhancement Quantum dots (QDs) are a class of nanomaterials with unique fluorescent properties that have gained significant attention in the research of Chinese herbal medicines (CHMs). Due to their exceptional optical characteristics, stability, biocompatibility, and other advantages, QDs are increasingly utilized in CHM studies. This review explores the diverse applications of QDs, including their use in detecting active ingredients and common exogenous pollutants in CHMs, as well as in assessing the degradation of such pollutants in both CHMs and their growing environments. Furthermore, the paper discusses the potential of QDs synthesized from CHMs as tools for analyzing other substances and modulating their pharmacological effects. The review also highlights the preparation methods, detection principles, and specific research strategies related to QDs. Integrating QDs into CHM research is poised to drive the modernization and internationalization of the CHM industry. Quantum dot ; Nanomaterials ; Pollutant ; Internationalization Carbon and Quantum Dots Applications ; Protein Interaction Studies and Fluorescence Analysis ; Quantum Dots Synthesis And Properties
Authors: Runtong Qian | Shangfeng Yang | Zilin Song | Jing Huang
Source: Scientia Sinica Chimica (article, 2025-04-08)
Field: Materials Science — Materials Chemistry

Accelerating molecular dynamics simulations with artificial intelligence 分子动力学模拟是解析复杂分子体系结构、热力学和动力学性质的重要工具，但其应用受限于计算效率，模拟和真实过程的时间尺度往往存在落差。 随着深度学习技术的飞速发展，利用人工智能加速分子动力学模拟成为可能。本文探讨了人工智能在不同层面上实现加速的潜力：时域加速突破步长限制，序列加速捕捉构象跃迁，空间采样优化构象遍历。我们也讨论了现有方法在物理一致性与跨尺度适应性方面的诸多困难与挑战。未来，多尺度方法与物理约束框架的有机融合，有望协同提升精度、效率与可解释性，推动分子模拟智能化发展，并进一步拓展其在机制解析与筛选设计上的应用潜力。 Psychology Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions ; Nanopore and Nanochannel Transport Studies
Authors: F. M. H. Khaleel | Sabyasachi Chakraborty | Renana Gershoni‐Poranne
Source: ChemRxiv (preprint, 2025-01-15)
Field: Chemistry — Organic Chemistry

Polybenzenoid Hydrocarbons in the S1 State: Simple Structural Motifs Predict Electronic Properties and (Anti)Aromaticity Polybenzenoid hydrocarbons (PBHs) are widely studied for their semiconductive properties and potential applications in organic electronics and photochemistry. Understanding their behavior in excited states is crucial for optimizing their performance in these applications. Here, we computationally investigate a dataset of 43 unbranched cata-condensed PBHs in their first singlet excited state (S₁), revealing clear correlations between molecular structure and electronic properties. By analyzing these molecules through their annulation patterns—specifically the arrangement of linear (L) and angular (A) tricyclic subunits, and tetracyclic zig-zag (Z) and curve (C) motifs—we establish a predictive hierarchy (L > Z > C > A) for the location of unpaired electrons and Baird-antiaromaticity. This structural approach enables semi-quantitative prediction of key properties including excitation energies, magnetic response, and singlet fission capability. Notably, we find that singlet fission propensity is dependent on both the length of the Longest L sequence and the position of the sequence at the edge of the molecule. These insights, derived from analysis of small tri- and tetracyclic components and validated on larger systems, provide a practical framework for understanding and designing PBH-based materials. Aromaticity ; Simple (philosophy) ; State (computer science) ; Computational chemistry ; Chemistry ; Computer science ; Algorithm ; Molecule ; Organic chemistry ; Epistemology Synthesis and Properties of Aromatic Compounds ; Advanced Physical and Chemical Molecular Interactions ; Inorganic and Organometallic Chemistry
Authors: Lexing Che | Bao Ming-dong | Zhihua Sun | Yingwen Cao
Source: Crystals (article, 2025-10-17)
Field: Materials Science — Materials Chemistry

Synthesis, Reaction Process, and Mechanical Properties of Medium-Entropy (TiVNb)2AlC MAX Phase The synthesis, reaction process, and mechanical properties of medium-entropy (TiVNb)2AlC MAX phase materials were investigated. The Ti, V, Nb, Al, and C powders were mixed and sintered by the powder metallurgy method. The experimental results showed that the highest purity M2AlC phase with a mass fraction of 95.8% was obtained when the raw material ratio was M(Ti:V:Nb):Al:C = 2:1.2:0.7 and the sintering temperature was 1450 °C. In order to explore the sintering process reactions and optimize the purity of sintered products, sintering was carried out under different temperatures and various molar ratios of raw materials. During the sintering process, the metal elements firstly reacted with aluminum to generate intermetallic compounds (IMCs), and with the increase in temperature, the IMCs gradually reacted with carbon to generate M2AlC. Mechanical property tests revealed that the Vickers hardness of the medium-entropy (TiVNb)2AlC material was 6.52 GPa, significantly higher than both the theoretical prediction based on the rule of mixtures and the hardness of traditional MAX phases. The severe lattice distortions in the polymeric solid solution structure contributed to this significant increase in hardness. In addition, the medium-entropy (TiVNb)2AlC exhibited temperature-dependent friction behavior within the temperature range of room temperature to 400 °C, with the lowest friction coefficient observed at 200 °C when the sample was in contact with the bearing steel. This study provided an important theoretical and experimental basis for the synthesis and future application of medium-entropy MAX phase materials. Sintering ; Powder metallurgy ; Raw material ; Intermetallic ; Vickers hardness test ; Phase (matter) ; Carbon fibers ; Ceramic MXene and MAX Phase Materials ; Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties
Authors: F. S. Narmanova | Aziz B. Ibragimov | Xayit Turayev | Gulshoda Toirova
Source: YANGI DAVR ILM-FANI INSON UCHUN INNOVATSION G‘OYA VA YECHIMLAR (article, 2025-10-26)
Field: Chemistry — Organic Chemistry

Zn(II) NING 4-AMINOBENZOY KISLOTASI BILAN {[Zn(H2O)2(SO4)2](C7H7NO2)2}n KOMPLEKS BIRIKMASI SINTEZI Ushbu maqolada 4-aminobenzoy kislotasi (p-ABA) va rux(II) sulfat asosida yangi koordinatsion polimer — Poly[catena-[diaqua-bis(μ₂-sulfato-O,O′)-bis(4-aminobenzoic acid)zinc(II)]] {[Zn(H2O)2(SO4)2] (C7H7NO2)2} n — sintez qilinishi va uning kristall tuzilmasining rentgenostruktura tahlili natijalari keltirilgan. Kompleks monoklinik kristall tizimda (P2₁/c fazoviy guruhida) kristallangan bo‘lib, Zn(II) ionlari ikki suv molekulasi va ikki sulfat anioni bilan oktaedrik koordinatsion muhit hosil qilgan. Tuzilma ichida sulfat guruhlari μ₂-ko‘prikli koordinatsiya orqali Zn markazlarini zanjirsimon (catena) tarzda bog‘laydi, p-ABA molekulalari esa vodorod bog‘lari orqali supramolekulyar tarmoqni barqarorlashtiradi. Kristallografik ma’lumotlarga ko‘ra, birikma yuqori tartibli struktura va mustahkam koordinatsion panjaraga ega. Ushbu natijalar Zn(II)–p-ABA asosidagi polimer komplekslarning tuzilish barqarorligi va koordinatsion kimyodagi istiqbolli ahamiyatini tasdiqlaydi Chemical reaction kinetics ; Copper ; Zinc Organometallic Compounds Synthesis and Characterization ; Crystal structures of chemical compounds ; X-ray Diffraction in Crystallography
Authors: Z. C. Zhou | Yu He | Shixian Liu | Lina Yang | Nuo Yang
Source: ArXiv.org (preprint, 2025-10-09)
Field: Materials Science — Materials Chemistry

Effect of non-Fourier heat transport on temperature distribution in High Bandwidth Memory High Bandwidth Memory (HBM), as a key development trend in future memory chip technology, significantly enhances computer performance. At the same time, the thermal challenges arising from its stacked architecture have drawn considerable attention. Most existing studies on HBM thermal management are based on Fourier's law, neglecting the non-Fourier effects introduced by the micro/nanoscale structures within HBM. In this study, the Monte Carlo method (MC) is employed to solve the phonon Boltzmann transport equation (BTE) and investigate the impact of non-Fourier heat transport on the thermal behavior of HBM structures. The results reveal that non-Fourier heat transport leads to a junction temperature that is 59.8 K higher than that predicted by Fourier's law. Furthermore, it is found that the phonon transmittance at the chip interlayers has a severe impact on heat dissipation, with the temperature variation reaching up to 56.6 K. These findings provide more accurate thermal insights, which are critical for the optimized design of HBM systems. Boltzmann equation ; Thermal ; Monte Carlo method ; Thermal management of electronic devices and systems ; Chip ; Phonon ; Bandwidth (computing) ; Thermal conductivity ; Heat equation Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Thermoelastic and Magnetoelastic Phenomena
Authors: Liying Chen
Source: Biomedical Data Science (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Recent Advances in Prodrug Design: Chemical Strategies and Pharmaceutical Applications As a crucial molecular modification strategy, prodrugs enable the release of active pharmaceutical ingredients through enzymatic or chemical reactions within the body, thereby playing a pivotal role in enhancing drug solubility, stability, bioavailability, and safety. With advances in medicinal chemistry, nanotechnology, and biomedicine, prodrug research has expanded beyond mere physicochemical optimization to encompass targeted therapy and personalized medicine. This paper systematically reviews the fundamental principles, classification, primary applications, development challenges, and future directions of prodrugs. It highlights emerging trends such as drug-auxiliary prodrugs, microenvironment-responsive prodrugs, AI-assisted design, and enzyme-mediated prodrug therapies. Prodrug ; Drug ; Drug discovery ; Pharmaceutical technology ; Adept ; Pharmaceutical sciences Click Chemistry and Applications ; Adenosine and Purinergic Signaling ; HIV/AIDS drug development and treatment
Authors: Hamidreza Razavi | Nele Moelans
Source: Research Square (preprint, 2025-10-23)
Field: Materials Science — Materials Chemistry

Physics-Informed GCN-LSTM Framework for Long-Term Forecasting of 2D and 3D Microstructure Evolution Graph ; Encoding (memory) ; Data modeling ; Representation (politics) ; Deep learning ; Computation ; Temporal database Machine Learning in Materials Science ; Metallurgical Processes and Thermodynamics ; Microstructure and Mechanical Properties of Steels
Authors: Abraham Rojas Zuniga | Sam Bakhtiari | Chris Aldrich | Victor M. Calo | Mariano Iannuzzi
Source: npj Materials Degradation (article, 2025-10-08)
Field: Materials Science — Metals and Alloys

Predicting stress corrosion cracking in downhole environments: a Bayesian network approach for duplex stainless steels This study presents a Bayesian network (BN) for the holistic assessment of stress corrosion cracking (SCC) risk. The model is designed to interrogate the optimal operating conditions of duplex stainless steels (DSSs) in downhole environments, addressing the perceived overly conservative limits by current industry standards, particularly those from ISO 15156—Part 3. A knowledge-based dataset on DSS performance was compiled from diverse sources. Machine learning and deep learning techniques facilitated data pre-processing and identification of feature interactions, supporting the BN structure’s development. Extensive cross-validation demonstrated that the BN model accurately predicted the occurrence of both pitting corrosion and SCC with over 90% accuracy. Using the BN model, inference analyses were undertaken to examine SCC risks for DSSs under diverse sour conditions. The results indicate that DSSs could withstand more aggressive conditions than those currently permitted by ISO 15156—Part 3, suggesting potential for broader and more effective use in oilfield applications. Stress corrosion cracking ; Duplex (building) ; Bayesian network ; Corrosion ; Pitting corrosion ; Bayesian inference ; Cracking Hydrogen embrittlement and corrosion behaviors in metals ; Structural Integrity and Reliability Analysis ; Non-Destructive Testing Techniques
Authors: Haoran Liu | Nan Gao | Yurui Fang
Source: ArXiv.org (preprint, 2025-01-21)
Field: Materials Science — Materials Chemistry

Influence of conjugated structure for tunable molecular plasmons in peropyrene and its derivatives Advances in research have sparked an increasing curiosity in understanding the plasmonic excitation properties of molecular-scale systems. Polycyclic aromatic hydrocarbons, as the fundamental building blocks of graphene, have been documented to possess plasmonic properties through experimental observations, making them prime candidates for investigation. By doping different elements, the conjugated structure of the molecule can be altered. In this study, the plasmonic excitation properties influenced by conjugated structures in peropyrene and its derivatives are investigated through first-principles calculations that combine the plasmonicity index, generalized plasmonicity index and transition contribution maps. For molecular plasmonic excitation, the conjugated structure can influence the oscillation modes of valence electrons, which is pivotal in yielding distinct field enhancement characteristics. Furthermore, charge doping can lead to a certain degree of alteration in the conjugated structures, and the doping of elements will result in varying degrees of such alteration, thereby initiating different trends in the evolution of plasmonic resonance. This further enhances the tunability of molecular plasmonic resonance. The results provide novel insights into the development and utilization of molecular plasmonic devices in practical applications. Conjugated system ; Plasmon ; Materials science ; Chemistry ; Photochemistry ; Nanotechnology ; Optoelectronics ; Organic chemistry ; Polymer Porphyrin and Phthalocyanine Chemistry ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Raphael F. Moral | Maher B. Alghalayini | R.N. Nurdillayeva | Do-Kyoung Lee | Tim Kodalle | Paulo E. Marchezi | David P. Fenning | Marcus M. Noack | Craig P. Schwartz | Carolin M. Sutter‐Fella
Source: ChemRxiv (article, 2025-08-25)
Field: Materials Science — Materials Chemistry

Dissymmetry Factor Enhancement: A Data-Driven Approach to Unravel the Synthesis Knobs of Chiral 2D Perovskites Chiral 2D metal halide perovskites (MHPs) hold promise for next-generation spin-optoelectronic applications. While still in early-stage development, significant efforts have focused on optimizing the dissymmetry factor (g), particularly in terms of their circular dichroism (gabs), which quantifies the chiroptical response and is related to spin-polarized optical properties in chiral systems. These materials typically exhibit intrinsically low gabs values (10E-3), with variations spanning two orders of magnitude due to co-dependent structural, morphological, and experimental factors. Here, Pearson correlation analysis identified solvent choice as the primary factor governing gabs variability in chiral 2D MHP thin films based on R-/S-𝛼-methylbenzylammonium. Subsequently, a combination of Pearson correlation, ANOVA, and Gaussian Process Regression revealed that, for acetonitrile-based samples, strain, film thickness, and annealing temperature are the key parameters for optimizing gabs. In contrast, films prepared with higher boiling point solvents exhibit a more complex interdependence of gabs with film texture and excitonic integral intensity. The statistical analysis of the synthesis-chiroptical property relationship provides a foundation for the rational design of chiral 2D MHPs, while also guiding the exploration of alternative chiral cations, compositions, and deposition strategies. Factor (programming language) ; Materials science ; Nanotechnology ; Computer science ; Programming language Machine Learning in Materials Science ; Perovskite Materials and Applications
Authors: Okechukwu Benjamin Okafor | A.P.I. Popoola | Olawale Popoola | Samson Oluropo Adeosun
Source: Journal of Electronic Materials (article, 2025-10-03)
Field: Materials Science — Polymers and Plastics

The Influence of Graphene–Titanium Nitride and Synthesis Parameters on the Electrochemical Properties of Polyaniline Nanocomposite Abstract This study aims to evaluate the effect of reduced graphene (rG) oxide and titanium nitride (TiN) nanoparticle synthesis parameters on the electrochemical performance of polyaniline (PANI) nanocomposite as a supercapacitor electrode material. In the preparation of the PANI nanocomposites, 20 wt.% rG and 10 wt.% TiN were used as reinforcements via solution mixing with the use of ultrasonication and subsequent heat treatment. The ultrasonication time, heat treatment temperature, and holding time were the synthesis parameters modified in this study to obtain the optimum fabrication parameters. The nanocomposite powders were examined using Fourier transform infrared spectroscopy, scanning electron microscopy, and x-ray diffraction. The thermal characteristics were measured using a thermal gravimetric analyzer. Using the Taguchi optimization method, the best processing parameters resulted in specific capacitance of approximately 346 F g −1 at 0.5 A g −1 and coulombic efficiency of 99.8% after 500 charge–discharge cycles. Thus, this study identified the optimal ultrasonication and heat treatment parameters for PANI/rG/TiN nanocomposites, providing a foundation for future research in advanced engineering materials for energy storage applications. Additionally, it establishes a standardized framework for ultrasonication and heat treatment processes, ensuring consistent and comparable results across studies on PANI/rG/TiN nanocomposites. Nanocomposite ; Polyaniline ; Sonication ; Faraday efficiency ; Fourier transform infrared spectroscopy ; Graphene ; Titanium nitride ; Supercapacitor ; Taguchi methods Conducting polymers and applications ; Electrochemical sensors and biosensors ; Supercapacitor Materials and Fabrication
Authors: Nina Danchova | Dimitar Shandurkov | Roumen Tsekov | Luben Mihaylov | Тony Spassov | Stoyan Gutzov
Source: Preprints.org (preprint, 2025-06-03)
Field: Chemistry — Inorganic Chemistry

Porous Silica Gels Doped with Gold Nanoparticles – Preparation, Microstructure, Optical and Textural Properties Porous silica gel powders, doped with gold nanoparticles (AuNPs), were obtained by heating of silica gels containing 1-dodecanethiol and tetrachloroauric acid at temperatures of 450 oC, 700 oC and 900 oC and characterized using X-ray diffraction, TEM/EDS studies, UV/Vis reflectance spectroscopy and DTA/TG investigations. The color and microstructure of the obtained samples with a composition SiO2:AuNPs (about 0.03% Au) depend on the heating temperature. UV/Vis reflection spectra of the samples are explained with Mie&amp;rsquo;s theory. The thermal stability of the obtained samples, as well as the processes occurring in the sol-gel matrix upon heating, were monitored by DTA/TG. The textural properties of the obtained materials were described, based on adsorption-desorption isotherms. The obtained nanocomposites are promising pigments for ceramic glazes, similar to the Purple of Cassius. The textural properties of certain samples, SBET = 200 - 350 m&amp;sup2;/g, mean pore diameter (DAV) of approximately 10 nm, and specific pore volume (Vt) between 0.5 and 0.8 cm&amp;sup3;/g, make them promising candidates for catalytic applications, comparable to aerogel-like materials. Microstructure ; Materials science ; Doping ; Porosity ; Nanoparticle ; Chemical engineering ; Colloidal gold ; Nanotechnology ; Composite material ; Optoelectronics Pigment Synthesis and Properties ; Aerogels and thermal insulation ; Mesoporous Materials and Catalysis