jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anshebo Getachew Alemu
Source: International Journal of Current Research in Science Engineering & Technology (article, 2025-06-29)
Field: Chemistry — Electrochemistry

Analysis of Photochemical Kinetics Dependence on Thickness in Dye-Sensitized Nickel Oxide Films with Scanning Electrochemical Microscopy Scanning electrochemical microscopy (SECM) in feedback mode was used to investigate the photochemical kinetics of dye-sensitized solar cells (DSSCs).In this study, two organic dyes, coumarin (C343) and CW1, were used to sensitize nickel oxide (NiO)-based photo electrochemical cells.Six NiO/C343 films with different thicknesses were the subject of a methodical investigation to look at how they affected the charge transfer kinetics.The absorption cross-section (hv), the reduction rate constant (kred) and the effective rate constant (keff) were the three most crucial kinetic parameters that were quantitatively evaluated.The findings unequivocally demonstrate that dye regeneration kinetics demonstrated exceptional sensitivity to incident light intensity, electrode film thickness and sensitizer molecular structure.The fundamentals of the interfacial charge transfer mechanisms that control DSSC performance are explored in this article, which also emphasizes the significance material and operating conditions are to photochemical kinetics.A powerful foundation for spatially resolved analysis of photo electrochemical systems is provided by the SECM-based the approach. Kinetics ; Nickel oxide ; Nickel ; Optical microscope ; Scanning electrochemical microscopy ; Scanning electron microscope ; Microscopy Electrochemical Analysis and Applications ; Thermography and Photoacoustic Techniques ; Corrosion Behavior and Inhibition
Authors: Tatsuya Mori | Shunsuke Mieda | Kotaro Kodama | Tomoyuki Miyao
Source: ChemRxiv (article, 2025-09-15)
Field: Materials Science — Materials Chemistry

Mechanism-Oriented Reaction Descriptors for Dispersity Prediction in Nitroxide-Mediated Radical Polymerization Considering Mediator Stability In recent years, there has been tremendous growth in data-driven approaches in the field of polymer science, mainly using large databases. However, these analyses do not often lead to mechanism-based interpretations, such as validating a hypothesis for a key reaction phenomenon. In this study, quantitative structure-property relationship (QSPR) models for dispersity (Đ) are constructed using reaction representations based on a putative reaction mechanism. These models are built on nitroxide-mediated radical polymerization reaction data sets collected from the literature. The proposed reaction representation consists of 17 descriptors based on the quasi-equilibrium reaction of forming dormant species, including the stability of mediator radicals. The tendency for the decomposition of the mediator radicals is quantified with a single descriptor. Excluding an unstable mediator radical based on this descriptor significantly increases the prediction accuracy for a poly(n-butyl acrylate) data set. Removing reactions proceeding on different reaction paths contributes to more accurate QSPR-based Đ prediction models, and also to clearer model interpretation in light of the mechanism assumption. Additionally, prediction is found to be possible for data sets from different research groups under similar experimental conditions, while no meaningful prediction is achieved for reactions conducted under different experimental conditions and monomer conversion. Dispersity ; Representation (politics) ; Polymerization ; Radical ; Monomer ; Decomposition ; Reaction mechanism ; Stability (learning theory) Machine Learning in Materials Science ; Advanced Polymer Synthesis and Characterization ; Chemical Synthesis and Analysis
Authors: Sonam Sonam | Shama Parveen
Source: International Journal of Multidisciplinary Trends (article, 2025-02-01)
Field: Materials Science — Materials Chemistry

Nanoparticles-enabled smart materials for artificial intelligence applications In this paper, we are exploring the applications of nanoparticles in different domain of artificial intelligence (AI) based systems. The integration of nanoparticles into smart materials has revolutionized the development of AI systems. NMs become the first choice for every field of AI. There are different aspects for design, synthesis, and characterization of nanoparticle-based smart materials that enhance AI performance. By incorporating nanoparticles with unique optical, electrical, and magnetic properties, we create adaptive materials that respond to environmental stimuli, enabling real-time learning and decision-making. Nanoparticle-enabled smart materials empower AI systems with unprecedented adaptability, sensitivity, and resilience. This research paves the way for breakthroughs in AI-driven technologies, transforming industries and revolutionizing human-machine interactions for next generation applications. Nanoparticle ; Nanotechnology ; Materials science ; Computer science ; Artificial intelligence Advanced Nanomaterials in Catalysis
Authors: Imane Chtaini | Mustapha Oukbab | Abdelilah Chtaini
Source: Real-World AI Systems (article, 2025-06-15)
Field: Chemistry — Electrochemistry

Smart Electrodes Enhanced by Machine Learning: Revolutionary Cadmium Extraction from Phosphoric Acid Using Moringa-Enhanced Carbon Sensors This study presents a comprehensive electrochemical investigation of cadmium removal from 54% phosphoric acid solutions using Moringa oleifera-modified carbon paste electrodes (CPE) in sodium chloride medium. The research employed advanced machine learning analytical techniques to optimize electrode performance and characterize the removal mechanisms. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and square wave voltammetry (SWV) were utilized to evaluate the electrochemical behavior of cadmium in the presence of Moringa-modified electrodes. The machine learning-optimized system demonstrated superior performance compared to traditional methods, achieving processing speeds exceeding 10,000 units with enhanced sensitivity and detection capabilities. Principal component analysis revealed three distinct mechanistic clusters: protonation, complex formation, and surface effects. The Moringa-modified electrodes showed excellent correlation (R² &gt; 0.998) between experimental and machine learning-predicted values in Tafel analysis, with cadmium detection accuracy reaching 98.8%. Feature importance analysis identified Moringa particle size, surface roughness, and ionic strength as the most critical parameters influencing removal efficiency. The optimized frequency range of 27.3 Hz provided maximum signal-to-noise ratio and sensitivity. These findings demonstrate the potential of machine learning-enhanced, bio-modified electrodes for efficient heavy metal removal from industrial phosphoric acid solutions. Phosphoric acid ; Electrode ; Cyclic voltammetry ; Dielectric spectroscopy ; Cadmium ; Electrochemistry ; Voltammetry ; Extraction (chemistry) Electrochemical Analysis and Applications ; Extraction and Separation Processes ; Supercapacitor Materials and Fabrication
Authors: Kai Chen | Shenlei Shi | Yan Li | esmaeil heydari | Jianfeng Wang | Karol Bartosiewicz | Gongxun Bai
Source: Information & Functional Materials (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

Luminescent nano‐structured semiconductor materials via doping engineering: Functional applications toward intelligent optoelectronics and photonics Abstract Luminescent ion‐doped materials have gained extensive attention and application in both scientific research and practical fields. The integration of luminescent ions with nano‐structured semiconductors has emerged as a highly promising development trend to meet the growing demands for advanced functional systems. This review focuses on luminescent ion‐doped nano‐structured semiconductors, including 0D, 1D, and 2D systems. It elaborates on the pivotal roles that luminescent ions play within these materials. Subsequently, the article offers a comprehensive overview of the application scenarios and effects of various luminescent ions doped into nano‐structured semiconductors. Additionally, the article systematically discusses the coupling mechanisms between luminescent ions and nano‐structured semiconductors, as well as the synergistic effects of codoping. We also present the specific applications of these materials in the information and functional materials fields. Lastly, this work addresses the current challenges faced in this research area and outlines the frontier development directions, providing valuable insights for future exploration. Luminescence ; Doping ; Photonics ; Semiconductor ; Work (physics) Luminescence Properties of Advanced Materials ; Luminescence and Fluorescent Materials ; Carbon and Quantum Dots Applications
Authors: Dayana Lizeth Sánchez Pinzón | Daniela Lourenço | Tiago Albertini Balbino | Thenner S. Rodrigues
Source: Processes (article, 2025-09-18)
Field: Materials Science — Materials Chemistry

Photoactive Nanomaterials Containing Metals for Biomedical Applications: A Comprehensive Literature Review This review summarizes recent advances in photoactive nanomaterials containing metals and their biomedical applications, particularly in cancer diagnosis and therapy. Conventional approaches such as chemotherapy and radiotherapy suffer from low specificity, systemic toxicity, and resistance, while light-based therapies, including photothermal therapy (PTT) and photodynamic therapy (PDT), offer minimally invasive and localized alternatives. Metal nanomaterials, especially gold and silver, exhibit unique localized surface plasmon resonance (LSPR) effects that enable efficient light-to-heat or light-to-reactive oxygen conversion, supporting precise tumor ablation, drug delivery, and imaging. We discuss strategies for structural design, surface functionalization, and encapsulation to enhance stability, targeting, and therapeutic efficiency. Emerging hybrid systems, such as carbon-based nanostructures and metal–organic frameworks, are also considered for their complementary properties. Computational modeling tools, including finite element and discrete dipole approximations, are highlighted for predicting nanomaterial performance and guiding rational design. Finally, we critically assess challenges such as toxicity, long-term biocompatibility, and clinical translation, and provide perspectives for future development. By integrating materials design, simulation, and preclinical findings, this review aims to inform the advancement of safer and more effective nanotechnology-based platforms for personalized cancer treatment and diagnosis. Photothermal therapy ; Surface plasmon resonance ; Photodynamic therapy ; Cancer therapy ; Nanomaterials ; Drug delivery ; Nanomedicine Quantum Dots Synthesis And Properties
Authors: Kristina Antropova | Ruslan Kuzmin | Н. С. Александрова | Aleksandr Yurgin | Julia Malyutina | Nomina Burkhinova
Source: Chimica Techno Acta (article, 2025-01-09)
Field: Materials Science — Materials Chemistry

Effect of citric acid quantity on LaAlO <sub>3</sub> formation in sol-gel synthesis with combustion Lanthanum aluminate (LaAlO3) was synthesized using the nitrate-citrate sol-gel method followed by the combustion process. The synthesis was conducted using fuel-lean at pH 7, with metal precursor to citric acid mass ratios (Me:C₆H₈O₇) of 1:0.25, 1:0.37, and 1:0.48. The resultant products were analyzed using X-ray diffraction and scanning electron microscopy (SEM). After post-annealing at 900 °C, the formation of crystalline LaAlO3 was confirmed, whereas the as-pyrolized product was found to be X-ray amorphous. It was established through thermal analysis that nitrate-citrate complexes decompose in several stages, and LaAlO3 crystallizes at around 840 °C. An increase in citric acid concentration correlated with a reduction in microstress levels and a decrease in the size of coherent scattering regions, in agreement with the particle size measurement results obtained from SEM images. The synthesized nanoscale particles exhibited an average size in the range of 50–60 nm and a specific surface area greater than 15 m²/g. The synthesized powders were characterized by fragile porous aggregates composed of thin porous walls. Notably, an increase in citric acid concentration promoted the enlargement of pores within the aggregates while simultaneously reducing the pore size within the thin walls. Furthermore, the materials synthesized from the solutions with pH 1 demonstrated a larger average particle size (~75 nm) and smaller pore sizes, with combustion occurring at lower temperatures compared to the samples obtained from the solutions at pH 7. Citric acid ; Combustion ; Sol-gel ; Chemistry ; Chemical engineering ; Materials science ; Inorganic chemistry ; Nanotechnology ; Organic chemistry ; Engineering Catalytic Processes in Materials Science ; Luminescence Properties of Advanced Materials ; Gas Sensing Nanomaterials and Sensors
Authors: REUBEN PAMBANI | Alaaldin Adam | EWENIFA OLUWADOLAPO JOY | YILNI EDWARD BIOLTIF | MUSA YAHAYA ABUBAKAR
Source: International Journal of Chemistry Research (article, 2025-10-01)
Field: Materials Science — Biomaterials

CATALYTIC SYSTEM FOR EFFICIENT BIODEGRADABLE POLYMER SYNTHESIS: A REVIEW Due to the fact that we are capable of getting around nearly all critical obstacles (such as efficiency, sustainability, scalability), advanced catalytic systems for the synthesis of biodegradable polymers have greatly improved the efficiency of these compounds. The use of metal-free organocatalysts, bio-based catalysts, and enzyme catalyses is studied to develop new cutting-edge catalytic ways of producing biodegradable polymers. It has already provided high-performance materials designed for specific applications, and they have shown great capability to modulate polymer molecular weight, stereoregularity, and end group functionality. In order to improve catalyst recovery and reusability and consequently lessen the environmental impact and production cost, advances in heterogeneous catalysis is a suggested area for innovation. Second, the proposed solution for polymerization in a sustainable manner is to work with the synergistic catalytic systems comprising both chemical and biological pathways. In terms of achievements, reaction times, total energy were reduced, and different renewable feedstock were compatible. Without doubt, this study also demonstrates how catalytic technologies can be transformational in the synthesis of biodegradable polymers and identifies the principal research challenges necessary to overcome the challenges inherent in dealing with the feedstock utilization, process integration and scale up of the process. Catalysis ; Raw material ; Biodegradable polymer ; Reusability ; Polymer ; Polymerization ; Renewable energy ; Process (computing) biodegradable polymer synthesis and properties
Authors: G. Zhao | Qi Ou | Zifeng Zhao | Shangqian Chen | Haitao Lin | Xiaohong Ji | Zhen Wang | Hongshuai Wang | Hengxing Cai | Lirong Wu | S.C. Lu | Fan Yang | Yaping Wen | Yingfeng Zhang | Haibo Ma | Zhifeng Gao | Zheng Cheng | E Weinan
Source: npj Computational Materials (article, 2025-10-16)
Field: Materials Science — Materials Chemistry

Virtual characterization via knowledge-enhanced representation learning: from organic conjugated molecules to devices The rational design of organic functional devices relies on understanding structure-property-performance relationships through multi-scale characterization. However, traditional characterizations are costly and require multidisciplinary expertise. Here we present OCNet, a domain-knowledge-enhanced representation learning framework that, for the first time, enables unified virtual characterization from molecules to devices. Pre-trained on over ten million self-generated conjugated molecules and dimers, OCNet learns generalizable microscopic representations comparable to expert-crafted features. As a result, it surpasses state-of-the-art models by over 20% in predicting key computed and experimental molecular optoelectronic properties. OCNet further provides the first transferable model for predicting transfer integrals in thin films, enabling accurate mesoscale carrier mobility estimation via multiscale simulations. By integrating tight-binding-level electronic descriptors, OCNet achieves near real-time, accurate prediction of device power conversion efficiency. Together, OCNet offers a unified and scalable foundation for virtual characterization of organic materials across multiple scales, with broad applicability in photovoltaics, displays, and sensing. Representation (politics) ; Characterization (materials science) ; Key (lock) ; Scalability ; Virtual screening ; Conjugated system ; Power (physics) Machine Learning in Materials Science ; Advanced Memory and Neural Computing ; Computational Drug Discovery Methods
Authors: Senlin Dong
Source: theses.fr (ABES) (article, 2025-11-07)
Field: Chemistry — Inorganic Chemistry

Optimisation of ZSM-5 zeolite properties by low valence metal ions for application in MTO catalytic reaction Cette thèse étudie la modification de la zéolithe ZSM-5 par des cations métalliques à faible valence afin d’ajuster sa structure et son acidité dans la réaction MTO, et ainsi améliorer la sélectivité en oléfines légères et la stabilité catalytique. Les effets de Li+, Na+, K+, Mg2+, Ca2+ et Cu2+ ont été analysés en fonction de la teneur en aluminium. Li+ augmente la stabilité, réduit les transferts d’hydrogène et améliore la sélectivité, tandis que Na+ renforce la cristallinité. Parmi les cations alcalino-terreux, Mg2+ transforme les sites acides forts en sites plus faibles, prolongeant nettement la durée de vie. L'effet de Ca2+ dépend du taux d'aluminium, alors que Cu2+ diminue de manière excessive l’acidité. L’étude montre que le choix du cation permet de moduler finement les propriétés de ZSM-5 et d’optimiser ses performances en MTO. Valence (chemistry) ; Catalysis ; Ion ; Zeolite ; Metal Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Catalytic Processes in Materials Science
Authors: Victor R. de la Rosa | Fabio Cameli | Yves Schuurman | Kevin M. Van Geem | Georgios D. Stefanidis
Source: Catalysis Science & Technology (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

A kinetic model for Pd-based hydrogenation of acetylene-rich streams typical of post-plasma applications The advancement of electrified chemical processes prompts interest in novel technologies such as plasma-based methane (CH<sub>4</sub>) conversion into high-demand chemicals. Specifically, nanosecond-pulsed discharges (NPDs) coupled with downstream Pd-based catalysts have demonstrated the best performance in a two-step, integrated process for converting CH<sub>4</sub> into ethylene (C<sub>2</sub>H<sub>4</sub>). Given the untested composition range involved in this application, the focus of this work is the isolated performance of Pd-based catalysts in typical post-plasma conditions. Extensive campaigns of experiments are run in both traditional and novel stream compositions. The differences with traditional tail-end olefin-rich hydrogenation are highlighted, and a hybrid steady-state kinetic model is proposed, combining the traditional Langmuir-Hinshelwood-Hougen-Watson (LHHW) approach with an improved reversible adsorption methodology. The ability to accurately predict C<sub>2</sub>H<sub>2</sub> hydrogenation kinetics with C<sub>2</sub>H<sub>2</sub>-rich and C<sub>2</sub>H<sub>4</sub>-poor streams is achieved by the new model, contrary to existing conventional models. Preliminary insights into catalyst optimization for scalable plasma-to-olefin routes are presented. Catalysis ; Methane ; Process (computing) ; STREAMS ; Scalability ; Work (physics) ; Adsorption ; Ethylene Catalytic Processes in Materials Science ; Advanced Data Storage Technologies ; Catalysts for Methane Reforming
Authors: Ch. S. Anuradha | Govindarajan Lakshmana Rao | T. Apparao
Source: International Journal of Research Publication and Reviews (article, 2025-09-01)
Field: Chemistry — Organic Chemistry

Functional Metal Nanoparticles for Efficient and Sustainable Organic Transformations Sustainable organic synthesis has become an important research priority due to the growing need for environmentally benign and energy-efficient chemical processes.Metal nanoparticles have emerged as highly effective catalysts in this regard, owing to their exceptional surface activity, tunable electronic properties and high selectivity.This review presents recent advances in the use of metal nanoparticle catalysts for a wide range of organic transformations, including oxidation, reduction, coupling and C-C bond forming reactions.Particular emphasis is placed on how structural parameters such as particle size, morphology and surface functionalization influence catalytic performance and reaction pathways.The integration of metal nanoparticles into heterogeneous catalytic systems is also highlighted as a key strategy to improve catalyst recyclability and minimize waste.Recent developments in green synthesis and immobilization approaches for nanoparticle catalysts are critically discussed to underline their potential in sustainable chemistry.In addition, current limitations and environmental concerns associated with the use of metal nanoparticles are addressed, and future opportunities for developing low-cost, high-performance catalytic systems are identified.By consolidating the latest progress in this rapidly growing field, the review aims to guide researchers toward the rational design of eco-friendly metal nanoparticle catalysts for sustainable organic synthesis. Nanoparticle ; Metal ; Metal-organic framework ; Bimetallic strip ; Catalysis Nanomaterials for catalytic reactions
Authors: Liwen Jin
Source: Applied and Computational Engineering (article, 2025-05-30)
Field: Materials Science — Materials Chemistry

Borohydride Solid-State Electrolytes: Ion Transport Mechanisms and Modifications The ongoing global transition toward higher energy density and enhanced safety in energy systems has positioned all-solid-state lithium batteries as a pivotal solution to current energy storage limitations, owing to their intrinsic safety characteristics and lithium metal anode compatibility. Borohydride-based solid-state electrolytes demonstrate exceptional performance characteristics, including high ionic conductivity exceeding 10-3 S/cm at room temperature, broad electrochemical stability windows, and structurally tunable [BH4] anion frameworks. This paper systematically describes the structural features of borohydride solid-state electrolyte and analyzes the conductive mechanism of this electrolyte from the point of view of defect chemistry; At the same time, this paper not only nearly reviews the progress of modification of borohydride solid-state electrolytes in the direction of solid solution and elemental doping in recent years, but also reveals the technical challenges of borohydride solid-state electrolytes in their own performance and scale-up preparation. Based on this, this paper looks at future research directions for borohydride solid-state electrolytes in terms of material properties, interface engineering and process optimization. Borohydride ; Electrolyte ; Solid-state ; Ion ; Fast ion conductor ; Ion transporter ; Chemistry ; Chemical engineering ; Materials science ; Inorganic chemistry ; Organic chemistry ; Physical chemistry ; Engineering ; Electrode Hydrogen Storage and Materials ; Nuclear Materials and Properties ; Chemical Synthesis and Characterization