jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Maryam Sabooni Asre Hazer | Sami Malola | Hannu Häkkinen
Source: Nature Communications (article, 2025-12-18)
Field: Materials Science — Materials Chemistry

Thermal dynamics and coalescence of Au144(SR)60 clusters from a machine-learned potential Ligand-protected metal nanoclusters have gained significant attention due to their diverse applications in catalysis, bioimaging, and nanomedicine. While their ground-state electronic structure and optical properties have been extensively studied via density functional theory (DFT) methods, theoretical insights into their dynamic behavior, particularly for larger clusters, remain scarce due to the prohibitive numerical cost of long-timescale simulations using forces calculated from DFT. Here we investigate, using molecular dynamics (MD) simulations up to 0.12 μs timescale, thermal dynamics of the well-known Au<sub>144</sub>(SR)<sub>60</sub> at 300-550 K using the recently parametrized atomic cluster expansion (ACE) potential, trained from DFT data for thiolate-protected gold clusters. Our findings reveal that thermal effects induce increased mobility in a layer-by-layer fashion, leading to formation of polymeric gold-thiolate units and rings which may fragment from the cluster at high temperatures. The remaining smaller clusters resemble experimentally observed cluster compositions. Close interaction of two Au<sub>144</sub>(SR)<sub>60</sub> clusters leads to coalescence, resulting in a cluster composition and structure of the inner metal core close to ones identified in previous experiments. This work reveals mechanisms for thermal effects in ligand-protected gold clusters and larger nanoparticles that are instrumental for understanding their catalytic activity and inter-particle reactions at the atomistic level. Nanoclusters ; Coalescence (physics) ; Cluster (spacecraft) ; Molecular dynamics ; Thermal ; Density functional theory ; Nanoparticle Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Machine Learning in Materials Science
Authors: Debarghya Mallick | Sujoy Ghosh | An‐Hsi Chen | J. Liao | Jinkyoung Yoo | Qiangsheng Lu | Steven Randolph | Scott T. Retterer | Gyula Eres | Yong P. Chen | Leonid P. Rokhinson | Matthew Brahlek | R. G. Moore
Source: npj Spintronics (article, 2025-10-09)
Field: Materials Science — Materials Chemistry

Next-generation electronics by co-design with chalcogenide materials As Moore’s law approaches its limits, chalcogenides offer a promising route to next-generation computing and sensing, thanks to their topological, magnetoelectric, excitonic, and spintronic properties. Yet the same traits that make them appealing, e.g., exotic properties at monolayer thickness, clean van der Waals interfaces, and strong many-body effects, also heighten sensitivity to fabrication, hindering translation into scalable devices. Progress is further constrained by fragmented knowledge across synthesis, processing, and integration, and by the lack of systematic links between fabrication parameters and performance metrics. This Perspective examines key obstacles in controlling chalcogenide heterostructures and stresses the need for an integrated co-design framework, uniting materials growth, processing, and device architecture to accelerate practical technologies. Chalcogenide ; Electronics ; Spintronics ; Fabrication ; Scalability ; Heterojunction ; Key (lock) 2D Materials and Applications ; Perovskite Materials and Applications ; Chalcogenide Semiconductor Thin Films
Authors: Thomas R. Ward | Zhi Zou | Indrek Kalvet | Boris Lozhkin | E. Matthew Morris | Kailin Zhang | Dongping Chen | M. Ernst | Xiang Zhang | David Baker
Source: Research Square (preprint, 2025-02-13)
Field: Chemistry — Organic Chemistry

De Novo Design and Evolution of an Artificial Metathase for Cytoplasmic Olefin Metathesis Synthetic biology ; Directed evolution ; Olefin metathesis ; Chemistry ; Metathesis ; Computational biology ; Nanotechnology ; Biology ; Materials science ; Biochemistry ; Organic chemistry ; Polymerization ; Gene Cyclopropane Reaction Mechanisms ; Chemical Synthesis and Analysis ; Molecular Junctions and Nanostructures
Authors: Mani Rajasekar | Meenamigai Sivakumar
Source: RSC Advances (review, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent developments and future perspectives for photoresponsive-based gold nanoparticles (Au-NPs) and their biomaterial applications Photoresponsive gold nanoparticles (AuNPs) represent a dynamic class of nanomaterials combining the optical tunability of gold with the reversible photochemistry of organic chromophores. Functionalisation with azobenzene, fluorescein, perylene, and pyrene derivatives enables light-controlled modulation of molecular conformation, fluorescence, and surface interactions. These hybrid systems have shown wide applicability in drug delivery, imaging, biosensing, and photothermal therapy. This review summarises recent advances in their design, synthesis, and biomedical integration, with emphasis on photoisomerisation dynamics, optical coupling, and structure-function relationships. Key challenges including limited light penetration, photostability, and clinical scalability are highlighted alongside emerging prospects such as NIR-responsive and multi-stimuli platforms. Photoresponsive AuNPs thus offer a promising foundation for next-generation light-regulated biomaterials and precision nanomedicine. Photothermal therapy ; Colloidal gold ; Nanomaterials ; Surface modification ; Nanoparticle ; Biomaterial Gold and Silver Nanoparticles Synthesis and Applications ; Nanocluster Synthesis and Applications ; Photochromic and Fluorescence Chemistry
Authors: Totka Dodevska
Source: Acta chimica slovenica (review, 2025-06-11)
Field: Chemistry — Electrochemistry

Electrochemical Sensors for Bisphenol A Analysis in Foods and Beverages – a New Approach in Food Quality Control Modern nanofabrication technologies combined with electrochemical techniques offer benefits in terms of extremely high sensitivity, low limit of detection, minimum power requirement, simplicity, and low cost of the electrochemical sensors making them powerful for food quality evaluation. The limited number of electrochemical non-enzymatic sensing platforms for bisphenol A (BPA) successfully applied for safety assessment of foods and beverages, testifies that the food matrices present significant challenges and there is still a need to improve the analytical performances of these devices. This review systematically explores the contributions of diverse functional nanomaterials, metal-organic frameworks, ionic liquids, and molecular imprinting in improving the sensor performance. A critical discussion on the latest interesting innovations and most promising electrochemical tools for BPA analysis is presented. By addressing the electrochemical aspects and challenges in the design of BPA sensors and exploring innovative solutions, the article offers insights into future prospects and avenues, paving the way for advancements in this field. Nanotechnology ; Computer science ; Biochemical engineering ; Process engineering ; Risk analysis (engineering) ; Materials science ; Engineering ; Business Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies ; Electrochemical sensors and biosensors
Authors: Georgios P. Gakis | Ioannis G. Aviziotis | Costas A. Charitidis
Source: Environmental Science Nano (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Assessing the ecotoxicity of multicomponent nanomaterials using a classification SAR approach A classification SAR approach is developed for the ecotoxicity assessment of multicomponent nanomaterials. Using their structure and composition, the nanomaterials are classified for toxicity towards Bacteria, Eukaryotes, Crustacean, Plants, Fish. Ecotoxicity ; Nanomaterials ; Environmental science ; Environmental chemistry ; Materials science ; Chemistry ; Nanotechnology Nanoparticles: synthesis and applications ; Heavy metals in environment ; Mercury impact and mitigation studies
Authors: Luyang Liu | Jichun Li | Yu Deng | Hou‐Yong Yu | Wenhe Xie | Yonghui Deng | Kaiping Yuan
Source: Nano Research (article, 2025-05-15)
Field: Materials Science — Materials Chemistry

A simultaneous etching and polymerization strategy toward vertically aligned polypyrrole nanosheets on MXene for ammonia sensing Flexible room-temperature gas sensors with good adaptability to various surfaces and low energy consumption hold a great promise for different applications such as environmental monitoring and human exhalation detection. However, the development of flexible sensing devices with stable and superior monitoring capability are still restricted by the insufficiently selectivity or sensitivity at low temperatures. In this study, a simultaneous etching and oxidation polymerization strategy is developed toward the synthesis of porous polypyrrole (PPy)/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene nanocomposites. In the nanocomposites, PPy nanosheets align vertically on the surface of Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub>, forming numerous open and porous channels. As a result, the PPy/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub>-based flexible sensor shows highly exposed active sites and superior ammonia sensing performances at room temperature with good selectivity, high sensitivity, fast response rate and a low detection limit of 375 ppb. The sensor can exhibit stable and reliable sensitivity under different bending angles and even after 100 bending cycles. Moreover, the PPy/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> nanocomposites can be integrated into a portable flexible wireless sensor for remote and real-time ammonia monitoring, exhibiting great potentials in various applications Polypyrrole ; Polymerization ; Ammonia ; Materials science ; Etching (microfabrication) ; Nanotechnology ; Chemical engineering ; Chemistry ; Polymer ; Composite material ; Organic chemistry ; Layer (electronics) MXene and MAX Phase Materials ; Advanced Sensor and Energy Harvesting Materials ; Advanced Memory and Neural Computing
Authors: Batoul Roustaei | Ghodsieh Bagherzade | Hamid Beyzaei
Source: Scientific Reports (article, 2025-11-07)
Field: Chemistry — Inorganic Chemistry

Simultaneous antimicrobial and adsorptive capabilities of a novel surface-modified NH2-MIL-101 (Cu) for sustainable wastewater remediation Metal-organic frameworks (MOFs) are an emerging class of porous materials with remarkable surface area, tunable pore structures, and diverse chemical functionalities. In this study, we reported the green synthesis and comprehensive characterization of a novel modified NH<sub>2</sub>-MIL-101 (Cu) derived from 2-aminoterephthalic acid, followed by post-synthetic modification with terephthalaldehyde to improve its adsorption capabilities. The synthesized Cu-MOF exhibited a very high specific surface area (2037.65 m<sup>2</sup>·g<sup>-1</sup>, BET), a total pore volume of 0.7465 cm<sup>2</sup>·g<sup>-1</sup> and mesoporosity with an average pore diameter of 29.06 nm. SEM and TEM images showed uniform polyhedral particles with an average particle size of ≈ 85 ± 10 nm, while XRD patterns displayed well-defined diffraction peaks with the most intense reflection at ~ 2θ = 28-29°, confirming high crystallinity and preservation of the MIL-101 topology after modification. Under optimized conditions (10 mg adsorbent, 10 mL solution, room temperature and appropriate pH), the material exhibited high adsorption capacities of 230.1, 165.2, and 187.4 mg·g<sup>-1</sup> for crystal violet, methyl orange, and rhodamine B, respectively, attributable to its large porosity and functional surface groups. A plausible mechanism involving electrostatic interaction, π-π stacking, and coordination bonding is proposed for adsorption of dyes onto the modified MOF. The Cu-MOF maintained excellent structural stability and reusability, retaining over 92% of its initial adsorption capacity after five consecutive adsorption-desorption cycles, as confirmed by XRD patterns showing no noticeable framework collapse. This highlights its robustness and potential for sustainable wastewater remediation. In addition to dye removal, the material demonstrated antimicrobial activity, with MIC values of 4, 8, 32 and 128 µg/mL for P. aeruginosa, C. albicans, E. coli, and A. fumigatus, respectively, while no inhibition was observed against Gram-positive strains at concentrations up to 4096 µg/mL. The antimicrobial effect is likely attributed to Cu<sup>2+</sup> ion release and electrostatic interactions leading to membrane disruption and ROS generation. These results highlight the potential of the synthesized Cu-MOF as a multifunctional and eco-friendly candidate for both wastewater treatment and biomedical applications. Adsorption ; Crystallinity ; Specific surface area ; Porosity ; Rhodamine B ; Wastewater ; Particle size ; Porous medium Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Magnesium Oxide Properties and Applications
Authors: Edris Jamshidi | Maryam Haddadi | Faranak Manteghi | Arman Eshaghi | Zari Tehrani
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Experimental and Monte Carlo simulation study on a core–shell NiFe<sub>2</sub>O<sub>4</sub>@HKUST-1/graphene oxide nanocomposite for Congo Red adsorption A copper-based metal-organic framework, nickel ferrite and graphene oxide were prepared as constituents of a new core-shell nanocomposite formed by a layer-by-layer method, then it was applied to absorb Congo Red dye as an organic contaminant. The nanocomposite was studied by XRD, FTIR, EDS, FESEM and VSM methods. Investigating the main factors affecting the adsorption shows that the optimum pH of the dye solution is 7, the best contact time is 60 min with an initial solution concentration of 5 ppm and 0.05 g of adsorbent is the optimum amount. Adaptation of Langmuir, Freundlich, Temkin and Dubinin-Radushkevich adsorption isotherms showed that the dye adsorption process is consistent with two first isotherm models. Regarding the adsorption kinetics and according to the calculations, it was found that the adsorption process follows second-order kinetics. The composite NiFe<sub>2</sub>O<sub>4</sub>@HKUST-1/GO demonstrated a maximum adsorption capacity of 25.64 mg g<sup>-1</sup> for Congo Red dye removal from aqueous solutions. Monte Carlo simulations were used to simulate the adsorption nature between NiFe<sub>2</sub>O<sub>4</sub> (311) molecules and the HKUST-1 surface, GO molecules and NiFe<sub>2</sub>O<sub>4</sub>@HKUST-1, and CR and NiFe<sub>2</sub>O<sub>4</sub>@HKUST-1/GO. Graphene ; Monte Carlo method ; Adsorption ; Nanocomposite ; Oxide ; Materials science ; Congo red ; Core (optical fiber) ; Shell (structure) ; Characterization (materials science) ; Nanotechnology ; Chemical engineering ; Physical chemistry ; Chemistry ; Composite material ; Metallurgy ; Engineering ; Mathematics Graphene research and applications ; Nanomaterials for catalytic reactions ; Graphene and Nanomaterials Applications
Authors: Mostafa Saad Ebied | Sahar Elnobi | Amr Attia Abuelwafa
Source: Scientific Reports (article, 2025-10-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Structural and optical properties of spin coated ZnTTBPc thin films for optoelectronics via DFT and experiments The present research provides a comprehensive theoretical and experimental investigation into the structural and optical properties of zinc 2, 9, 16, 23-tetra-tert-butyl-29 H,31 H-phthalocyanine (ZnTTBPc). Density functional theory (DFT) calculations at the B3LYP/6-31G (d, p) level, were utilized to optimize the molecular structure, analyze Mulliken charges, generate a molecular electrostatic potential map, and compute frontier molecular orbital energies of ZnTTBPc molecule. The nonlinear optical properties, including polarizability and hyperpolarizability, were also determined, confirming the molecule's applicability for nonlinear optical applications. Experimentally, spin-coated ZnTTBPc thin films were fabricated on quartz substrates. Structural characterization using X-ray diffraction and Raman spectroscopy indicated the amorphous nature of the thin films, whereas field emission scanning electron microscopy demonstrated a uniform, nanostructured morphology. Optical properties, including absorption coefficient, refractive index, and extinction coefficient, were analyzed over a wide spectral range (200-2000 nm), demonstrating the presence of direct optical transitions. The energy band gaps corresponding to the Q and B bands were obtained from Tauc plot analysis, with values of 1.42 and 2.25 eV respectively. The dispersion parameters and dielectric properties were evaluated using a single oscillator model. The nonlinear optical parameters such as the third-order nonlinear susceptibility, nonlinear refractive index and nonlinear absorption coefficient were calculated using semi-empirical relations. The results demonstrate that ZnTTBPc thin films possess excellent optical and nonlinear properties, making them highly promising candidates for advanced optoelectronic and photonic devices. This integrated theoretical and experimental approach underscores the importance of molecular design and fabrication techniques in optimizing materials for cutting-edge applications. Thin film ; Polarizability ; Dielectric ; Refractive index ; Density functional theory ; Band gap ; Spin coating ; Amorphous solid Nonlinear Optical Materials Research ; Porphyrin and Phthalocyanine Chemistry ; Nonlinear Optical Materials Studies
Authors: H Fried | Daniel Barragán-Yani | Florian Libisch | Ludger Wirtz
Source: npj Computational Materials (article, 2025-06-11)
Field: Materials Science — Materials Chemistry

A machine learning approach to predict tight-binding parameters for point defects via the projected density of states Abstract Calculating the impact of point defects on the macroscopic properties of technologically relevant semiconductors remains a considerable challenge. Semi-empirical approaches, such as the tight-binding method, are very efficient in calculating the electronic structure of large supercells containing one or several defects. However, the accuracy of these calculations depends on the quality of the parameters. Obtaining reliable parameters by fitting to the large number of entangled bands in defective supercells is a demanding task. We therefore present an alternative way by fitting to the atom and orbital projected densities of states. Starting with a tight-binding fit of the pristine material, we only need a few physically motivated parameters for the fitting of defects. The training is done on data sets generated purely with parameter variations of tight-binding Hamiltonians. We demonstrate the efficiency of our approach for the calculation of the carbon monomer and the carbon dimer substitutions in hexagonal boron nitride. The method opens a path towards understanding complicated defect landscapes using a computationally affordable semi-empirical approach without sacrificing accuracy. Tight binding ; Point (geometry) ; Statistical physics ; Computer science ; Materials science ; Artificial intelligence ; Machine learning ; Physics ; Mathematics ; Condensed matter physics ; Geometry ; Electronic structure Machine Learning in Materials Science ; Semiconductor materials and devices ; Electron and X-Ray Spectroscopy Techniques
Authors: Vishal Irappa Wannur | Archana S. Patil
Source: International Journal on Science and Technology (article, 2025-06-05)
Field: Materials Science — Materials Chemistry

Eutectic Mixtures: Bridging Physicochemical Fundamentals and Technological Applications Eutectic mixtures are unique multi-component systems that melt at a temperature lower than their individual constituents, offering distinct advantages in various scientific and technological domains. This review explores the fundamental principles governing eutectic systems, with emphasis on phase behavior, thermodynamic interactions, and structural characteristics. The article highlights the pharmaceutical potential of eutectic mixtures in enhancing the solubility, dissolution rate, and bioavailability of poorly water-soluble drugs, thereby improving oral and topical drug delivery. Applications in controlled drug release and dermal formulations are thoroughly discussed. Beyond pharmaceuticals, eutectic systems have found valuable applications in materials science, especially in alloy production, phase change materials, and eco-friendly solvents. Recent advances in deep eutectic solvents (DES) and natural deep eutectic solvents (NADES) showcase their promise as sustainable alternatives in green chemistry. The review also discusses characterization methods such as differential scanning calorimetry (DSC), Powder X-ray Diffraction (PXRD), and Fourier-transform infrared spectroscopy (FTIR), essential for analyzing eutectic behavior and interactions. Overall, eutectic mixtures represent a dynamic and versatile class of systems with broad implications for drug delivery, chemical processing, and materials innovation. Bridging (networking) ; Eutectic system ; Materials science ; Nanotechnology ; Chemistry ; Process engineering ; Computer science ; Metallurgy ; Engineering ; Microstructure Crystallization and Solubility Studies ; Analytical Chemistry and Chromatography
Authors: Atsushi Kobayashi | Atsushi Miura | Keisuke Takahashi
Source: RSC Sustainability (article, 2025-01-01)
Field: Materials Science — Biomaterials

Photocatalytic dissolution of cellulose for hydrogen and nanofiber production: unveiling crucial factors <i>via</i> experiments and informatics H 2 evolving photodissolution of cellulose paper was successfully achieved by combining dual-dye-sensitized photocatalysts and a 2,2,6,6-tetramethylpiperidine 1-oxyl oxidation catalyst. Nanofiber ; Cellulose ; Photocatalysis ; Dissolution ; Hydrogen production ; Production (economics) ; Chemical engineering ; Hydrogen ; Chemistry ; Materials science ; Nanotechnology ; Catalysis ; Organic chemistry ; Engineering ; Economics Advanced Cellulose Research Studies ; TiO2 Photocatalysis and Solar Cells ; Catalysis for Biomass Conversion
Authors: Quan Zhang | William W Sprague | Shivani Kozarekar | Stefan C. Pate | Taylor Uekert | Linda J. Broadbelt
Source: Digital Discovery (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Discovery of hybrid chemical synthesis pathways with DORAnet Developing efficient tools for discovering novel synthesis pathways is essential to advance chemical production methods that maximize the use of resources and energy. We introduce DORAnet (Designing Optimal Reaction Avenues Network Enumeration Tool), an open-source computational framework that addresses key limitations in current computer-aided synthesis planning (CASP) tools. DORAnet integrates both chemical/chemocatalytic (<i>i.e.</i>, non-enzymatic) and enzymatic transformations, enabling the discovery of hybrid synthesis pathways. With 390 expert-curated chemical/chemocatalytic reaction rules and 3606 enzymatic rules derived from MetaCyc, it provides extensive flexibility for synthetic chemists and biotechnologists. The framework features customizable network expansion strategies, advanced filtering, and pathway search, ranking, and visualization tools. Validated against known reaction data, DORAnet successfully identified both established and novel synthesis routes for key industrial chemicals. In a case study involving 51 high-volume targets, DORAnet frequently ranked known commercial pathways among the top three results, demonstrating its practical relevance and ranking accuracy, while also uncovering numerous alternative (hybrid) synthesis pathways that were highly ranked. Key (lock) ; Flexibility (engineering) ; Ranking (information retrieval) ; Relevance (law) ; Visualization ; Organic synthesis Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Microbial Metabolic Engineering and Bioproduction