jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dali Wei | Mengfan Li | Yudi Yang | Chunmeng Deng | Fang Zhu | Ming Li | Yibin Deng | Zhen Zhang
Source: ACS Sensors (article, 2025-07-15)
Field: Materials Science — Materials Chemistry

Ligand Microenvironment-Regulated Nanozymes Enabled Machine Learning-Assisted Sensor Array for Simultaneous Identification of Phenolic Pollutants Phenolic pollutants pose a great threat to human health due to high toxicity, whereas existing methods are difficult to achieve the rapid recognition of multiple phenolic pollutants. In this study, we developed a novel machine learning-assisted sensor array based on ligand microenvironment-regulated Pt nanozymes for the simultaneous differentiation of five phenolic pollutants (phenol, 2,4-DCP, <i>p</i>-chlorophenol, <i>o</i>-chlorophenol, and <i>m</i>-chlorophenol), wherein four cellulose ligands (carboxymethylcellulose, CMC; methylcellulose, MC; hydroxyethyl cellulose, HC; and hydroxypropyl methyl cellulose, HPMC)-regulated Pt nanozymes (Pt@CMC, Pt@MC, Pt@HC, and Pt@HPMC) with considerable laccase-mimicking activity were designed, and the Pt@CMC nanozyme exhibited the highest catalytic activity, which was about 7.5-folds than that of natural laccase. The calculation of density functional theory revealed that Pt@CMC had a stronger ability for capturing 2,4-DCP molecules, showing higher laccase-like activity. More importantly, the different cellulose ligands endowed four Pt nanozymes with laccase-like activity diverse recognition capability to phenolic compounds; thus, a nanozyme sensor array was developed for the differentiation of five phenolic pollutants. Moreover, the integration of a machine learning algorithm and the nanozyme sensor array successfully achieved accurate identification and prediction of the five phenolic pollutants in real water samples. Therefore, this study provided an emerging sensing strategy for the simultaneous identification of phenolic pollutants, carving a promising path for the application of sensor arrays and machine learning algorithms in environmental monitoring. Ligand (biochemistry) ; Pollutant ; Identification (biology) ; Chemistry ; Nanotechnology ; Combinatorial chemistry ; Environmental chemistry ; Materials science ; Biochemistry ; Biology ; Organic chemistry ; Receptor ; Botany Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques
Authors: S. Sathees Kumar | P. Shyamala | Pravat Ranjan Pati | Dipesh Kumar Mishra | Vishal S. Sharma | Gaurang Tank | Mohammad Kanan
Source: Scientific Reports (article, 2025-09-29)
Field: Materials Science — Polymers and Plastics

Investigation and machine learning-based prediction of mechanical properties in hybrid natural fiber composites With the growing emphasis on sustainability and circular economy principles in industrial sectors, the effective utilization of waste-derived and abundantly available natural resources has become imperative. Renewable lignocellulosic fibers such as jute fiber (JF), banana fiber (BaF), coconut coir (CC), and pineapple leaf fiber (PALF) serve as viable reinforcements for developing eco-friendly polymer composites. In this study, hybrid natural fiber (NF) composites were fabricated using the hand lay-up method with varying weight percentages of alkaline-treated JF, CC, BaF, and PALF. Alkaline treatment improved fiber-matrix interfacial bonding by reducing hydroxyl groups and enhancing surface roughness, which significantly contributed to improved mechanical and thermal performance. Mechanical testing revealed that the composite containing 20% JF, 20% CC, and 10% PALF exhibited superior properties, achieving a tensile strength of 85.8 MPa, flexural strength of 134.5 MPa, impact strength of 23.3 J/m<sup>2</sup>, and hardness of 72.6 Shore D. Fourier transform infrared spectroscopy (FTIR) confirmed successful alkaline treatment through reduced hydroxyl group intensity and improved fiber-matrix compatibility. Atomic force microscopy (AFM) further revealed increased surface roughness (Ra = 31.43 nm), indicating enhanced interfacial adhesion. To predict mechanical performance, machine learning (ML) regression models including linear regression, multilinear regression, decision tree, and random forest were developed using experimental data. Among these, the random forest model demonstrated the highest predictive capability, achieving R<sup>2</sup> values of 0.968 for tensile strength, 0.939 for flexural strength, 0.941 for impact strength, and 0.962 for hardness, along with the lowest error metrics (mean absolute error and root mean squared error). These results highlight its suitability for accurate prediction of mechanical properties in fiber-reinforced composites. Furthermore, dynamic mechanical analysis (DMA) revealed enhanced viscoelastic behaviour in treated fiber composites, while thermogravimetric analysis (TGA) confirmed excellent thermal stability up to 690 °C in JF/CC/PALF-reinforced samples. Ultimate tensile strength ; Flexural strength ; Fiber ; Natural fiber ; Coir ; Composite number ; Surface roughness ; Slurry Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research ; Tribology and Wear Analysis
Authors: Xiaojia Chen | Min Nian | Feng Zhao | Yu Ma | Jingzhi Yao | Siyi Wang | Xing Chen | Dan Li | Mingliang Fang
Source: Environmental Science & Technology (article, 2025-04-04)
Field: Materials Science — Polymers and Plastics

Artificial Intelligence for the Discovery of Safe and Effective Flame Retardants Organophosphorus flame retardants (OPFRs) are important chemical additives that are used in commercial products. However, owing to increasing health concerns, the discovery of new OPFRs has become imperative. Herein, we propose an explainable artificial intelligence-assisted product design (AIPD) methodological framework for screening novel, safe, and effective OPFRs. Using a deep neural network, we established a flame retardancy prediction model with an accuracy of 0.90. Employing the SHapley Additive exPlanations approach, we have identified the Morgan 507 (P═N connected to a benzene ring) and 114 (quaternary carbon) substructures as promoting units in flame retardancy. Subsequently, approximately 600 compounds were selected as OPFR candidates from the ZINC database. Further refinement was achieved through a comprehensive scoring system that incorporated absorption, toxicity, and persistence, thereby yielding six prospective candidates. We experimentally validated these candidates and identified compound Z2 as a promising candidate, which was not toxic to zebrafish embryos. Our methodological framework leverages AIPD to effectively guide the discovery of novel flame retardants, significantly reducing both developmental time and costs. Fire retardant ; Environmental science ; Engineering ; Forensic engineering ; Biochemical engineering ; Chemistry ; Organic chemistry Flame retardant materials and properties ; Fire dynamics and safety research ; Toxic Organic Pollutants Impact
Authors: Ramesh Vinayagam | Thivaharan Varadavenkatesan | Raja Selvaraj
Source: Results in Engineering (article, 2025-07-19)
Field: Chemistry — Analytical Chemistry

Tetracycline adsorption research (2015–2025): A bibliometric analysis of trends, challenges, and future directions • Tetracycline adsorption research shows rapid growth in the past decade (2014–2025). • VOSviewer and Bibliometrix visualized the Bibliometric data (567 articles). • China, USA, India are top contributors. • Metal organic frameworks and magnetic biochar are trending adsorbents. • DFT, AI/ML and continuous studies are major research gaps. Tetracycline is a commonly used antibiotic that has emerged as a significant environmental contaminant due to its widespread use and persistence in aquatic ecosystems. Its presence in water bodies poses ecological risks and contributes to the growing concern over antibiotic resistance. Among the various treatment technologies, adsorption has gained prominence as a cost-effective and efficient approach for removing tetracycline from contaminated water. This bibliometric review analyzes 567 articles published between 2015 and 2025 retrieved from the Web of Science Core Collection to uncover the scientific trends, influential contributors, research hotspots, and emerging gaps in the field of tetracycline adsorption. Using VOSviewer and Bibliometrix, the study presents a comprehensive visual mapping of publication growth trends, leading countries, institutions, authors, and journals. China, the USA, and India dominate the research output, with significant institutional contributions from Hunan University and Anhui Agricultural University. “Desalination and Water Treatment” and “Bioresource Technology” are identified as prominent journals, with the latter having 2236 citations. Keyword co-occurrence and thematic evolution analyses highlight trending materials like magnetic biochar and metal-organic frameworks. Additionally, it highlighted underexplored areas, including computational modeling, Artificial Intelligence/Machine Learning integration, and continuous adsorption. The findings offer a holistic understanding of the current research landscape and provide strategic directions for advancing future studies in tetracycline adsorption for environmental sustainability. Tetracycline ; Bibliometrics ; Regional science ; Data science ; Geography ; Computer science ; Library science ; Biology ; Microbiology Analytical chemistry methods development ; Electrochemical sensors and biosensors ; Biosensors and Analytical Detection
Authors: Rani Puthukulangara Ramachandran | Alain Clément | Chyngyz Erkinbaev
Source: Food Research International (review, 2025-05-13)
Field: Chemistry — Analytical Chemistry

Miniaturized spectroscopy and AI-driven probes in food industry automation Automation ; Food industry ; Spectroscopy ; Nanotechnology ; Engineering ; Biochemical engineering ; Business ; Computer science ; Process engineering ; Chemistry ; Materials science ; Food science ; Mechanical engineering ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Niuchang Ouyang | Dongyi Shen | Chen Wang | Ruihuan Cheng | Qi Wang | Yue Chen
Source: Physical review. B./Physical review. B (article, 2025-02-05)
Field: Materials Science — Materials Chemistry

Positive temperature-dependent thermal conductivity induced by wavelike phonons in complex Ag-based argyrodites The phonon transport mechanisms and the anomalous temperature-dependent lattice thermal conductivities (${\ensuremath{\kappa}}_{\mathrm{L}}$) in Ag-based argyrodites have not been fully understood. Herein, we systematically study the phonon thermal transport of five Ag-based crystalline argyrodites ${\mathrm{Ag}}_{7}{\mathrm{PS}}_{6}, {\mathrm{Ag}}_{7}{\mathrm{AsS}}_{6}, {\mathrm{Ag}}_{8}{\mathrm{SnS}}_{6}, {\mathrm{Ag}}_{8}{\mathrm{GeS}}_{6}$, and ${\mathrm{Ag}}_{9}{\mathrm{GaS}}_{6}$ utilizing perturbation theory and the unified theory thermal transport model. Our results show that, as the complexity of the unit cell increases, the proportion of the population terms declines while the coherence contributions become more significant, leading to the relatively weak temperature-dependent ${\ensuremath{\kappa}}_{\mathrm{L}}$ of ${\mathrm{Ag}}_{7}{\mathrm{PS}}_{6}$ and ${\mathrm{Ag}}_{7}{\mathrm{AsS}}_{6}$, while the more complex crystalline argyrodites, ${\mathrm{Ag}}_{8}{\mathrm{SnS}}_{6}, {\mathrm{Ag}}_{8}{\mathrm{GeS}}_{6}$, and ${\mathrm{Ag}}_{9}{\mathrm{GaS}}_{6}$, exhibiting a glass-like behavior in their temperature dependence of ${\ensuremath{\kappa}}_{\mathrm{L}}$. We attribute the positive temperature-dependent and ultralow ${\ensuremath{\kappa}}_{\mathrm{L}}$ of ${\mathrm{Ag}}_{8}{\mathrm{SnS}}_{6}, {\mathrm{Ag}}_{8}{\mathrm{GeS}}_{6}$, and ${\mathrm{Ag}}_{9}{\mathrm{GaS}}_{6}$ to the dominance of wavelike phonons and the strong phonon broadening. Furthermore, using laser flash measurements and the homogeneous nonequilibrium molecular dynamics simulations based on accurate machine learning neuroevolution potentials, we provide further evidence for the glass-like temperature-dependent ${\ensuremath{\kappa}}_{\mathrm{L}}$ of ${\mathrm{Ag}}_{8}{\mathrm{SnS}}_{6}$ and ${\mathrm{Ag}}_{8}{\mathrm{GeS}}_{6}$. Phonon ; Thermal conductivity ; Condensed matter physics ; Materials science ; Conductivity ; Thermal conduction ; Thermal ; Physics ; Thermodynamics ; Composite material ; Quantum mechanics Advanced Thermoelectric Materials and Devices ; Thermal Expansion and Ionic Conductivity ; Solid-state spectroscopy and crystallography
Authors: Subin Antony Jose | Jordan Price | Jéssica López | Erick Perez-Perez | Pradeep L. Menezes
Source: Materials (review, 2025-10-25)
Field: Materials Science — Materials Chemistry

Advances in MXene Materials: Fabrication, Properties, and Applications This review provides a critical overview of MXenes, an innovative class of 2D transition metal carbides, nitrides, and carbonitrides, emphasizing their synthesis, properties, and application potential. We systematically examine synthesis methods, contrasting top-down approaches with emerging green alternatives and bottom-up techniques, evaluating each in terms of scalability, cost, and environmental impact. This paper highlights MXenes' unique characteristics, including high electrical conductivity, tunable surface chemistry, and structural versatility, which enable their use in energy storage, environmental remediation, biomedicine, and electromagnetic shielding. Key challenges such as oxidative instability, interfacial incompatibility, and hazardous etching processes are critically discussed. We identify future research priorities, including defect-engineered stabilization, AI-optimized manufacturing, and advanced integration protocols to bridge the gap between laboratory breakthroughs and industrial deployment. By integrating these insights, this review offers a roadmap for advancing MXenes from laboratory innovation to industrial application. MXenes ; Bridge (graph theory) ; Hazardous waste ; Key (lock) ; Etching (microfabrication) MXene and MAX Phase Materials ; Electromagnetic wave absorption materials ; Energetic Materials and Combustion
Authors: Maciej Szwast | Daniel Polak
Source: Reviews in Chemical Engineering (review, 2025-03-24)
Field: Chemistry — Inorganic Chemistry

Hybrid MOF-COF structures for advanced gas separation membranes: a short review of synthesis, performance analysis and application potential Abstract This review examines the application potential of hybrid MOF-COF structures in fabricating advanced membranes for gas separation. MOF-COF membranes demonstrate exceptional gas separation performance, surpassing the Robeson upper bound for several gas mixtures, including H 2 /CH 4 , CO 2 /CH 4 , CO 2 /N 2 and O 2 /N 2 . Key findings indicate that thin-film MOF-COF membranes exhibit remarkable selectivity and permeability, with some hybrids achieving permeance values exceeding 1,000,000 GPU and ideal separation factors over 30. Additionally, mixed matrix membranes (MMMs) containing MOF-COF hybrids show potential for combining mechanical robustness with high separation efficiency, despite challenges in achieving uniform dispersion. Future research should prioritize scaling up production methods, enhancing the mechanical stability of thin films, and improving polymer-hybrid compatibility in MMMs. Experimental validation of theoretical predictions is essential to address discrepancies and unlock the full potential of these materials. MOF-COF hybrids are poised to revolutionize gas separation technologies and offer promising directions for broader applications, including catalysis and energy storage. Gas separation ; Materials science ; Separation (statistics) ; Industrial chemistry ; Membrane ; Chemical engineering ; Process engineering ; Computer science ; Chemistry ; Engineering ; Biochemical engineering Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Covalent Organic Framework Applications
Authors: T. Kato | Kunihiro Goto | Tadao Niwa | Tsukasa Shimizu | Akinobu Fujii | Bunyo Okumura | Hideaki Oka | Hiroaki Kadoura
Source: Scientific Reports (article, 2025-02-13)
Field: Materials Science — Surfaces, Coatings and Films

A comprehensive and quantitative SEM–EDS analytical process applied to lithium-ion battery electrodes The combination of scanning electron microscopy (SEM) images and energy-dispersive X-ray spectroscopy (EDS) maps (SEM-EDS analysis) enables the analysis of the relationship between the microstructures and elemental compositions of the surfaces of materials. However, conventional SEM-EDS analyses lack comprehensiveness and quantitativeness, resulting in potential inaccuracies in reflecting the properties of the entire sample and variations in the results depending on the analyst. Therefore, herein, we propose an objective SEM-EDS analytical process that addresses the aforementioned issues. Comprehensiveness was addressed by acquiring large volumes of SEM images through automated capturing, whereas quantitativeness was addressed through microstructural analysis of the SEM images based on image features, model-based dimension reduction and clustering methods, and similarity analysis of the elemental distribution in EDS maps based on statistical distances. The proposed method was used to analyze the degradation of lithium-ion battery electrodes, affording objective results that align with subjective insights into the changes in the morphology and composition of solid electrolyte interphase (SEI) films accompanying degradation. Scanning electron microscope ; Battery (electricity) ; Materials science ; Lithium (medication) ; Computer science ; Electrolyte ; Lithium-ion battery ; Cluster analysis ; Energy-dispersive X-ray spectroscopy ; Principal component analysis ; Electrode ; Process (computing) ; Biological system ; Artificial intelligence ; Chemistry ; Physics ; Composite material Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science ; Non-Destructive Testing Techniques
Authors: N. Ahmia | M. Benamira | L. Messaadia | R. Masmoudi | David Horwat | Ivalina Avramova
Source: Journal of Physics and Chemistry of Solids (article, 2025-07-21)
Field: Chemistry — Organic Chemistry

Sol-gel auto-combustion synthesized ZnMn2O4 for efficient photocatalytic Congo red degradation: structural, kinetics, computational, and ecotoxicity analyses Ecotoxicity ; Kinetics ; Combustion ; Congo red ; Degradation (telecommunications) ; Photocatalysis ; Chemical engineering ; Materials science ; Sol-gel ; Chemistry ; Nuclear chemistry ; Physical chemistry ; Nanotechnology ; Catalysis ; Organic chemistry ; Computer science ; Physics Nanomaterials for catalytic reactions ; Advanced Nanomaterials in Catalysis ; Multicomponent Synthesis of Heterocycles
Authors: Vikram Mahamiya | Alok Shukla | Abhishek Kumar Adak | Hoonkyung Lee | Nicola Seriani | Ralph Gebauer
Source: PRX Energy (article, 2025-05-09)
Field: Materials Science — Materials Chemistry

Computational Simulations and Strategies for Optimal Hydrogen Storage Materials Design Hydrogen, as the most abundant element in the universe, holds immense potential as the fuel of the future due to its high energy density per unit weight and its environmentally friendly nature. This article offers a comprehensive overview of recent theoretical advancements in hydrogen storage, outlining a general framework for achieving practical hydrogen uptake. We examine the fundamental interaction mechanisms, emphasizing orbital hybridization, polarization induced by external electric fields, and multipole Coulomb interactions between metal atoms and dihydrogen. Special focus is placed on calcium metal, which exhibits a transition from electrostatic to Kubas-type orbital interactions as multiple hydrogen molecules adsorb. The processes of hydrogen dissociation and spillover on sorbent surfaces, catalyzed by metals, are also discussed. We present the formalism by Lee . [Phys. Rev. Lett. 97, 056104 (2006)] as a method for calculating maximum hydrogen adsorption per site under varying temperatures and pressures, facilitating estimates of reversible hydrogen delivery. General computational strategies are reviewed, highlighting potential sources of error, such as neglecting zero-point vibrational energies, basis set superposition errors, and inaccuracies due to inappropriate density functionals. Additionally, we address practical challenges in designing optimal hydrogen storage materials for real-world applications, including nanostructure breakdown under intense electric fields, metal clustering, and oxygen blockage of metal functional sites. The article concludes by suggesting strategies to bridge the gap between computational simulations and experimental results, guiding the design of next-generation hydrogen storage materials. Hydrogen storage ; Computer science ; Hydrogen ; Chemistry Hydrogen Storage and Materials ; Hybrid Renewable Energy Systems ; Spacecraft and Cryogenic Technologies
Authors: Ruichen Xue | Jiayi Dai | Xuejiao Wang | Ming-Yang Chen
Source: Photonics (article, 2025-08-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Research Progress of Surface-Enhanced Raman Scattering (SERS) Technology in Food, Biomedical, and Environmental Monitoring Surface-enhanced Raman scattering (SERS) technology, leveraging its single-molecule-level detection sensitivity, molecular fingerprint recognition capability, and capacity for rapid, non-destructive analysis, has emerged as a pivotal analytical tool in food science, life sciences, and environmental monitoring. This review systematically summarizes recent advancements in SERS technology, encompassing its enhancement mechanisms (synergistic effects of electromagnetic and chemical enhancement), innovations in high-performance substrates (noble metal nanostructures, non-noble metal substrates based on semiconductors/graphene, and hybrid systems incorporating noble metals with functional materials), and its interdisciplinary applications. In the realm of food safety, SERS has enabled the ultratrace detection of pesticide residues, mycotoxins, and heavy metals, with flexible substrates and intelligent algorithms significantly enhancing on-site detection capabilities. Within biomedicine, the technique has been successfully applied to the rapid identification of pathogenic microorganisms, screening of tumor biomarkers, and viral diagnostics. For environmental monitoring, SERS platforms offer sensitive detection of heavy metals, microplastics, and organic pollutants. Despite challenges such as matrix interference and insufficient substrate reproducibility, future research directions aimed at developing multifunctional composite materials, integrating artificial intelligence algorithms, constructing portable devices, and exploring plasmon-catalysis synergy are poised to advance the practical implementation of SERS technology in precision diagnostics, intelligent regulation, and real-time monitoring. Raman scattering ; Materials science ; Nanotechnology ; Scattering ; Raman spectroscopy ; Optoelectronics ; Optics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Biosensors and Analytical Detection