jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jesse Canavan | Omar Abdelrahman | Brandon Foley | Paul J. Dauenhauer
Source: ChemRxiv (preprint, 2025-06-09)
Field: Materials Science — Materials Chemistry

Catalytic Resonance Theory: Experimental and Kinetic Interpretation of Programmable Catalysis The complexity of programmable catalysts that change in physical or electronic state on the time scale of a catalytic turnover results in uncertainty as to the kinetic outcome of standard measurements with dynamic catalyst experiments. To provide interpretation of utility to experimentalists, a general programmable catalytic reaction exhibiting high turnover efficiency was simulated to understand the kinetic behavior of catalysts with varying frequency, binding energy oscillation amplitude, and minimum oscillation binding energy at different temperatures and reactant gas pressures. The time-averaged catalytic rate for varying temperature in the form of an Arrhenius plot exhibited three distinct kinetic regimes, with the intermediate temperatures or applied frequencies exhibiting zero slope indicative of barrier-free kinetic control. Transitions in experimentally-measurable kinetic regimes with both temperature and applied catalyst oscillation frequency were associated with transitions in sensitivity of reaction rate constants and degrees of rate control. These distinct kinetic macroscopic features specific to programmable catalysts were identified for observation in experimental dynamic kinetic measurements. Catalysis ; Interpretation (philosophy) ; Kinetic energy ; Resonance (particle physics) ; Chemistry ; Photochemistry ; Physics ; Computer science ; Organic chemistry ; Particle physics ; Quantum mechanics Machine Learning in Materials Science
Authors: Riyadh Salman | Naser K. Zedain
Source: Kufa Journal of Engineering (article, 2025-11-01)
Field: Materials Science — Biomaterials

CHITOSAN SOURCES AND EXTRACTION: A REVIEW Chitosan is a biopolymer that is obtained by deacetylating the chitin that is recovered from different sources, such as marine and animal. Also, the waste of agriculture and the seawater industry are considered good sources for extraction. This waste may be an environmental pollution source as a result of burning and dumping or a good source for producing important materials such as chitosan which is considered a biocompatible, biodegradable, biopolymer that has many industrial, biomedical, and agricultural applications. Chitosan material, extracted from chitin, has many attractive biomedical properties. This review focuses on the extraction methods of chitosan from different production sources, taking into account industrial considerations, and summarizes them, taking into account their environmental impacts and marketing potential. Also, this article reviews—based on existing publications—the classes of chemical methods and reaction parameters used in chitosan preparation and biological methods Chitosan ; Biopolymer ; Chitin ; Extraction (chemistry) ; Agriculture ; Environmental pollution ; Pollution Nanocomposite Films for Food Packaging ; Advanced Cellulose Research Studies ; Polysaccharides Composition and Applications
Authors: Takaya Sugiura
Source: Electrical materials and applications. (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Materials in Electrical and Electronic Devices: A Review for Multidisciplinary Fields—Part I: Semiconductors ABSTRACT Semiconductor materials on electric and electronic devices are discussed. The fundamental knowledge, material properties and multidisciplinary applications in both matured and state‐of‐the‐art fields are surveyed. From this review, the examples and phenomena of semiconductor devices are available that are useful to design and enhance advanced devices. Note that Part II summarizes the insulators and conductors applications, and checking the article will be helpful for deeper understanding. Multidisciplinary approach ; Semiconductor materials ; Electrical conductor ; Semiconductor ; Electronics ; Semiconductor device ZnO doping and properties ; Nanowire Synthesis and Applications ; Thermal properties of materials
Authors: Sagnik Chakrabarti | Ju Byeong Chae | Kathryn T. Knecht | Nicholas D. Cedron | Liviu M. Mirica
Source: ChemRxiv (preprint, 2025-01-31)
Field: Chemistry — Organic Chemistry

Catalytically Competent Nickel(I)-Isocyanide Compounds Nickel-catalyzed cross-coupling reactions have emerged as a powerful strategy to construct complex molecules. A salient feature of Ni catalysts is their ability to engage in one-electron chemistry involving paramagnetic Ni(I) and Ni(III) intermediates, which has led to development of cross-coupling reactions involving alkyl substrates; however, such reactions generally employ Ni(II) or Ni(0) complexes as pre-catalysts. Although highly desirable, well-defined and catalytically competent Ni(I) sources with exchangeable ancillary ligands are lacking. Here we report the synthesis, characterization, and catalytic activity of a family of thermally stable dinuclear Ni(I) complexes supported by commercially available isocyanides as a general solution to this problem. Two classes of Ni(I) isocyanide complexes showing high thermal and solid-state stability have been developed – coordinatively saturated homoleptic compounds and coordinatively unsaturated Ni(I)-halide compounds. The Ni(I) compounds exhibit rapid ligand substitution and are efficient catalysts in Kumada, Suzuki-Miyaura, and Buchwald-Hartwig cross-coupling reactions, suggesting their potential use as either Ni(I) catalysts or pre-catalysts. In addition, bromide-selective functionalization of polyhalogenated arenes with Grignard reagents was achieved for the first time under nickel catalysis. Finally, spectroscopic and mechanistic studies were performed to establish the general use of simple isocyanide ligands as spectator ligands for cross-coupling reactions, representing an untapped chemical space for new reaction discovery. Homoleptic ; Isocyanide ; Catalysis ; Nickel ; Chemistry ; Combinatorial chemistry ; Halide ; Reagent ; Coupling reaction ; Alkyl ; Ligand (biochemistry) ; Bromide ; Organic chemistry ; Metal Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods ; Polyoxometalates: Synthesis and Applications
Authors: Eugene S. Stevens | Felipe Curtolo | Brian Derby | Duane C. Wallace | Yan Zhao | Sijia S. Dong
Source: ChemRxiv (preprint, 2025-06-13)
Field: Chemistry — Analytical Chemistry

Modeling Molecularly Imprinted Nanoparticles with LNKD: A Resource Efficient Algorithm for Polymer Crosslinking Chemical crosslinking has been widely used to modify the physical and chemical properties of materials. Molecularly imprinted polymers (MIPs) are a sub-class of crosslinked polymers. Their designable binding sites make them highly useful in a broad range of chemical and biological applications. Computational efforts to model, characterize, and design crosslinked polymers are limited in part due to challenges in obtaining their matrix-like and probabilistic structures experimentally. Computational prediction of polymer crosslinking is resource-intensive and underexplored. Here, we propose LNKD (Linking Nodes in KD-trees), a resource-efficient algorithm for predicting pairs of reactive atoms in pre-crosslinked 3D structures of monomers that applies not only to the modeling of MIPs, but also chemical crosslinking in other materials. LNKD performs a spatial query around all reactive atoms in a structure and uses a crosslinking probability function to predict pairs of atoms most likely to form crosslinks. Additionally, we introduce a protocol for modeling molecularly imprinted nanoparticles (MINPs), a type of MIP, combining molecular dynamics simulations with LNKD. We validate the method by its accurate modeling of MINPs in their binding properties in comparison to experimental results. For the MINPs tested, LNKD found crosslinking pairs for 88-95% of the 780 total reactive atoms in approximately three seconds on a laptop and docking results reproduce experimental trends in ligand binding. Molecularly imprinted polymer ; Nanoparticle ; Materials science ; Computer science ; Resource (disambiguation) ; Algorithm ; Nanotechnology ; Chemistry ; Organic chemistry ; Catalysis ; Selectivity ; Computer network Analytical chemistry methods development
Authors: Alena Doroshenko | Mariya Berezhnaya | E.V. Tomina
Source: Forestry Engineering Journal (article, 2025-12-26)
Field: Materials Science — Materials Chemistry

Composite material with high adsorption-catalytic activity based on biochar from sawdust of birch (Betula Pendula) Currently, a pressing issue is the search for new methods of wastewater treatment based on cheap environmentally friendly materials. Composite materials based on a biocoal matrix with nanosized modifiers make it possible to solve problems of increasing the efficiency of pollutant adsorption and photocatalytic purification of aquatic environments. Nanosized cobalt ferrite with a CoFe2O4 spinel structure and a biocoal-based composite with cobalt ferrite nanoparticles CoFe2O4@C were synthesized by the citrate combustion method. Carbon for the composite was obtained by carbonization of birch sawdust at a temperature of 600 ⁰C. The formation of nanosized CoFe2O4 spinel crystallites in all samples was confirmed by X-ray diffractometry. The average size of nanoparticles decreases from 31 ± 4 nm for pure cobalt ferrite to 17 ± 2 nm for a biocoal-based composite. The formation of the cobalt spinel phase and the presence of a large number of surface functional groups (–OH, –C=O, –C=C, –CH3) in the composite were confirmed by IR spectroscopy. The adsorption and catalytic activity of CoFe2O4 and CoFe2O4@C in relation to the purification of aqueous solutions from 2,4-dinitrophenol (DNP) was analyzed. High efficiency of DNP purification by nanosized cobalt ferrite (99.95%) and biochar-based composite (96.84%) was established due to sorption on porous materials and photocatalytic degradation of the toxicant under UV irradiation. The results of the study confirm that biochar-based composites from wood processing waste are promising sorbents/catalysts for the purification of wastewater from paper, pharmaceutical and textile industries from organic pollutants. Due to the magnetic sensitivity of the composite due to CoFe2O4 nanoparticles, the extraction of the sorbent/catalyst by an external magnetic field is significantly simplified for subsequent regeneration and reuse. Cobalt ; Carbonization ; Sawdust ; Spinel ; Composite number ; Adsorption ; Biochar ; Sorption ; Calcination Magnetic Properties and Synthesis of Ferrites ; Adsorption and biosorption for pollutant removal ; Magnesium Oxide Properties and Applications
Authors: Pengwei Li
Source: Inorganics (article, 2025-11-21)
Field: Materials Science — Materials Chemistry

Recent Research on the Applications of Amorphous Materials Inorganic amorphous materials continue to play a foundational role in modern materials science, enabling advances in photonics, catalysis, electronics, energy storage, and biomedical technologies [...] Amorphous solid ; Energy (signal processing) ; Amorphous metal ; Amorphous carbon ; Context (archaeology) Chemical and Physical Properties of Materials ; Pigment Synthesis and Properties ; TiO2 Photocatalysis and Solar Cells
Authors: Wafa Benaatou | Mudasir Ahmad Wani | Kashish Ara Shakil
Source: Digital Discovery (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Deep Generative Inverse Design of Biofunctional Polymer Coatings Using Conditional GANs Designing biofunctional surface coatings for biomedical implants requires balancing multiple biological objectives, including cell viability, antibacterial activity, and controlled drug release. Conventional experimental optimization of such multi-objective systems is time-intensive... Polymer ; Inverse ; Generative grammar ; Inverse problem Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms ; 3D Printing in Biomedical Research
Authors: François Rousseau | Thierry Belmonte | Frédéric Sur | Alexandre Nominé
Source: Research Square (preprint, 2025-12-25)
Field: Materials Science — Materials Chemistry

Inverse Design of High-Entropy Superalloys Using Machine Learning and Generative Artificial Intelligence Autoencoder ; Interpretability ; Workflow ; Superalloy ; Orthonormal basis ; Property (philosophy) ; Matching (statistics) ; Pattern recognition (psychology) Machine Learning in Materials Science ; Additive Manufacturing Materials and Processes ; High Entropy Alloys Studies
Authors: Michał K. Leszczyński | María K. Kochaniec | Michał Terlecki | Iwona Justyniak | S. Şahin | Busra Aydogdu | Recep Yüksel | Maciej Siekierski | Marcin Hołdyński | W. Wieczorek | Janusz Lewiński
Source: Communications Materials (article, 2025-12-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Functional porous carbons derived from alkali metal-based coordination polymers for energy storage Abstract The application of alkali metal-based coordination polymers as precursors to porous materials for energy storage appears as a very promising, but yet essentially unexplored approach. Here, we provide comprehensive investigations of the alkali metal (Li, Na, K)-based coordination polymers with 1,3,5-benzenetricarboxylate as an organic linker, which revealed a variety of 2D and 3D coordination networks accessible in mild conditions and aqueous environment. The resulting coordination polymers were applied as self-templating precursors to porous carbon materials with hierarchical porosity, which exhibited Brunauer-Emmett-Teller (BET) surface areas up to 1871 m 2 /g. Furthermore, the developed porous carbons were applied as supercapacitors and aqueous Zn-ion capacitors (AZICs), which showed promising specific capacitance, as well as high cyclic stability and rate capability. In particular, the top-performing device, prepared using the carbon material developed from the K-based coordination polymer, achieved one of the highest performances reported for AZICs, exhibiting a remarkable specific capacitance of 754.7 F g -1 at 0.1 A g -1 . Supercapacitor ; Polymer ; Alkali metal ; Porosity ; Aqueous solution ; Coordination polymer ; Energy storage Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Agnieszka Gonciarz | Robert Pich | Krzysztof Artur Bogdanowicz | Witalis Pellowski | Jacek Miedziak | Sebastian Lalik | Marcin Szczepaniak | Monika Marzec | Agnieszka Iwan
Source: Nanomaterials (review, 2025-09-10)
Field: Materials Science — Polymers and Plastics

Review of Current Achievements in Dendrimers and Nanomaterials for Potential Detection and Remediation of Chemical, Biological, Radiological and Nuclear Contamination—Integration with Artificial Intelligence and Remote Sensing Technologies Current scientific and technological developments indicate that the need for dendrimers and nanomaterials should be taken into account in aspects such as the detection and remediation of chemical, biological, radiological and nuclear (CBRN) contamination. To evaluate the benefits of dendrimers in CBRN contamination, different characterization methods, toxicological evaluation, and recyclability must be used. The aim of this article is to systematize knowledge about selected nanomaterials and dendrimers as well as chemical, biological, radiological and nuclear (CBRN) hazards in accordance with the principles of green chemistry, engineering, technology and environmental safety. So far, many review articles on dendrimers and nanomaterials have focused on biomedical applications or environmental remediation. In this article, we discuss this topic in more detail, especially in relation to the integration of dendrimers with artificial intelligence and remote sensing technologies. We highlight interdisciplinary synergies-artificial intelligence for smarter design and remote sensing for deployment-that could bridge the gap between nanoscale innovation and real CBRN countermeasures. Dendrimer ; Environmental remediation ; Radiological weapon ; Bridge (graph theory) ; Nanomaterials ; Relation (database) Dendrimers and Hyperbranched Polymers ; Microplastics and Plastic Pollution ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Ramin Khajavi
Source: Applied Nanomaterials and Smart Polymers (article, 2025-06-10)
Field: Materials Science — Polymers and Plastics

Smart Polymers: A Comprehensive Literature Review of Recent Developments and Advancements Smart polymers, also known as stimuli-responsive materials, represent a frontier in materials science, distinguished by their ability to undergo significant, often reversible, changes in their physicochemical properties in response to small external triggers.Drawing inspiration from adaptive biological systems, these polymers are at the heart of innovations across numerous scientific and technological domains.This comprehensive review synthesizes recent advancements in the field, systematically classifying smart polymers based on their primary stimuli, including temperature, pH, light, and mechanical forces.For each class, we delve into the fundamental response mechanisms, from the molecular-level hydrophobic-hydrophilic balance and ionization dynamics to macroscopic phenomena like phase transitions and swelling/deswelling.Key synthesis methodologies, advanced characterization techniques, and the structure-property relationships that govern their behavior are discussed in detail.Furthermore, the review highlights the expanding applications of these intelligent materials in high-impact areas such as targeted drug delivery, regenerative medicine, tissue engineering, biosensing, and soft robotics.Finally, we address the current challenges, including the need for enhanced biocompatibility, precise control over response kinetics, and multifunctionality, while outlining future research directions poised to unlock the full potential of smart polymers in creating the next generation of advanced materials. Engineering ethics ; Engineering ; Nanotechnology ; Management science ; Systems engineering ; Computer science ; Materials science Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Polydiacetylene-based materials and applications
Authors: Manushri Deva | Sri Phani Krishna Karri
Source: International Journal of Research Publication and Reviews (article, 2025-11-01)
Field: Materials Science — Materials Chemistry

MATLAB Assisted Surface Morphologies of Pure and Doped ZnO Using Image Processing Nanoparticles possess distinctive physical, chemical, and catalytic attributes attributable to their high surface area relative to volume when compared with bulk materials.This research synthesized both pure and metal-doped zinc oxide (ZnO) nanoparticles using a co-precipitation approach, with surface morphology assessed through Scanning Electron Microscopy (SEM).Advanced image processing in MATLAB was applied for quantitative analysis of particle surfaces and size distributions, employing morphological techniques such as dilation, erosion, opening, closing, boundary extraction, and region filling to refine and interpret SEM imagery.These procedures helped to more accurately delineate particle boundaries and identify surface features, resulting in reliable measurements of area, shape, and spatial distribution.The findings show that using MATLAB for morphological processing of SEM images is a robust, computational method for quantitatively characterizing nanomaterials, especially for capturing doping-induced morphological variations. Doping ; Image processing ; MATLAB ; Surface (topology) ; Surface roughness ; Zinc ZnO doping and properties ; Surface Roughness and Optical Measurements ; Optical Coatings and Gratings
Authors: Ruiqi Lyu | Xiangya Xu | Yi Man | Qiang Cai | Wei Li | Dongbing Liu
Source: RSC Advances (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Prognosis of simplified metal and organic sites resembling a quasi-MOF structure for hydrogen storage: investigation and insight Hydrogen energy plays an important strategic role as a sustainable and clean energy source for the future, and the use and efficient design of hydrogen storage and transportation materials are essential. Exploration into the usage and efficient design of hydrogen energy storage and transportation materials is necessary. However, a state of confusion and uncertainty exists regarding the similar operational mechanisms and details of hydrogen storage materials. This article focuses on the study of Zr-, Co-, In-, and Cu-based gas adsorption materials represented by metal organic framework (MOF)-derived structures. In this work, the basic unit planning and configuration design of metal coordination were analyzed and compared separately; the summarized working mode and rules of organic linking agents, represented by benzene-1,4-dicarboxylic acid (BDC) and its longitudinal chain derivatives, were concluded; based on experimental references, the adsorption relationship of samples under non adiabatic conditions was processed and evaluated, and the dynamic evolution process of sample gas adsorption was elucidated. Through the deployment of specific functions and non-adiabatic environment orchestration, we found that both the structural design and samples met the expected actual values, and some structural samples exceeded the theoretical level of the normal UIO-66 and MOF-74 series. This work analyzes and advocates for a potential benign hydrogen adsorption scheme using a MOF morphology, provides potential adsorption materials that can improve environmental tolerance, and reveals their adsorption response laws. Ultimately and fortunately, these materials could become strong competitors in the field of hydrogen storage functional materials. Hydrogen storage ; Adsorption ; Hydrogen ; Adiabatic process ; Energy carrier ; Confusion ; Work (physics) ; Metal Metal-Organic Frameworks: Synthesis and Applications ; Inorganic Fluorides and Related Compounds ; Catalytic Processes in Materials Science
Authors: Wenjiang Zhou | Bing Tang | Zheyong Fan | Federico Grasselli | Stefano Baroni | Bai Song
Source: arXiv (Cornell University) (preprint, 2025-12-04)
Field: Materials Science — Materials Chemistry

Heat transport in superionic materials via machine-learned molecular dynamics Precise modeling and understanding of heat transport in the superionic phase are of great interest. Although simulations combining Green-Kubo (GK) molecular dynamics with machine-learned potentials (MLPs) stand as a promising approach, substantial challenges remain due to the crucial impact of atomic diffusion. Here, we first show that the thermal conductivity ($κ$) of superionic materials calculated via conventional GK integral of the energy flux varies notably with the MLP model. Subsequently, we highlight that reliable, model-independent $κ$ values can be obtained by applying Onsager's reciprocal relations to correctly capture the coupled heat and mass transport. Remarkably, an anomalously invariant $κ$ can be observed over a wide temperature range, distinct from the characteristic trends in traditional crystals and glasses. In addition, we illustrate that conventional $κ$ decompositions into kinetic, potential, and cross terms suffer from ambiguities in the physical interpretation, despite their mathematical rigor. Finally, we propose a criterion for the necessity of the Onsager correction and reveal the underlying mechanism as a competition between thermally and chemically driven ion fluxes. Molecular dynamics ; Thermal conductivity ; Heat flux ; Heat current ; Thermal conduction ; Invariant (physics) ; Mass transport ; Thermal ; Reciprocal Machine Learning in Materials Science ; Thermal properties of materials ; Material Dynamics and Properties