jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Matylda Wacławska | Wojciech Dzwolak
Source: Photochem (review, 2025-01-23)
Field: Materials Science — Materials Chemistry

Shedding Light on the Proteinaceous Envelope Protecting Luminescent Gold Nanoclusters: A Review Atomically precise noble metal nanoclusters protected by ligands are broadly discussed in the literature as a promising new class of materials with many interesting properties. Of those, the most prominent is the characteristic luminescence in the visible and near-infrared light. Within the plethora of conjugates of metal nanoclusters to various protective ligands, protein-enveloped systems present several unique features arising from an interplay of the nanocluster photophysics and the protein chemistry along its macromolecular dynamics. The specific properties of protein–metal nanocluster conjugates underlie various applications of these systems, especially in bioimaging. This review, in contrast to many already published, focuses on protein-protected gold nanoclusters (AuNCs) from the standpoint of the proteinaceous shell which plays a crucial role in the biocompatibility, solubility, and excellent in-solution stability of such nanohybrid complexes. Factors such as the protein’s size, structural rigidity, amino acid composition, electric charge, and the electron donor properties of composite amino acids are discussed. Nanoclusters ; Luminescence ; Luminescent Measurements ; Nanotechnology ; Envelope (radar) ; Chemistry ; Photochemistry ; Materials science ; Biophysics ; Optoelectronics ; Biology ; Computer science ; Telecommunications Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Kan Luo | Xianghua Kong | Shiyu Du | Hong Guo
Source: Journal of Materials Chemistry C (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Prediction of room-temperature antiferromagnetism in V<sub>2</sub>CT<sub>2</sub> (T = Cl, Br, I) MXenes Systematic DFT calculations reveals V 2 CT 2 (T = Cl, Br, I) MXenes as high- T c 2D AFM materials with room-temperature magnetism via superexchange interactions. Monte Carlo simulations using spins2 code elucidate the strain-dependent variations in T c . MXenes ; Antiferromagnetism ; Materials science ; Crystallography ; Condensed matter physics ; Nanotechnology ; Physics ; Chemistry MXene and MAX Phase Materials ; 2D Materials and Applications ; Ferroelectric and Negative Capacitance Devices
Authors: Hassan Khartabil | Amuda Rajamani | Corentin Lefebvre | Julien Pilmé | Éric Hénon
Source: Journal of Computational Chemistry (review, 2025-06-08)
Field: Chemistry — Organic Chemistry

A 30‐Year Journey Towards an Accelerated Scheme for Visualizing ELF Basins in Molecules The Electron Localization Function (ELF) has been successfully used to understand the concept of electron-pair localization in molecules and solids. The topological analysis of ELF enables partitioning of the molecular space into basins (core, valence, monosynaptic, and polysynaptic). The gradient field of ELF, examined using quantum chemical topology algorithms, is a key component of this analysis, which can be time-consuming. Combining ELF and the Independent Gradient Model (IGM), we propose a novel approach that is approximately two orders of magnitude faster than traditional methods, providing a rapid visual methodology to identify the synaptic order of ELF basins, which defines their connectivity and corresponding bonding schemes. We validate this combined <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msup><mml:mrow><mml:mtext>ELF</mml:mtext></mml:mrow> <mml:mrow><mml:mo>&</mml:mo></mml:mrow> </mml:msup> <mml:mtext>IGM</mml:mtext></mml:mrow> <mml:annotation>$$ {\mathrm{ELF}}^{\&}\mathrm{IGM} $$</mml:annotation></mml:semantics> </mml:math> approach across a wide range of representative chemical systems, demonstrating its efficiency in generating visual ELF analyses and in enhancing traditional approaches where topological analysis may struggle. The <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msup><mml:mrow><mml:mtext>ELF</mml:mtext></mml:mrow> <mml:mrow><mml:mo>&</mml:mo></mml:mrow> </mml:msup> <mml:mtext>IGM</mml:mtext></mml:mrow> <mml:annotation>$$ {\mathrm{ELF}}^{\&}\mathrm{IGM} $$</mml:annotation></mml:semantics> </mml:math> analysis serves as a stepping stone for full ELF topological analyses through programs like TopChem2. Scheme (mathematics) ; Computer science ; Mathematics Free Radicals and Antioxidants ; Photochemistry and Electron Transfer Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Eduardo da Silva Barbosa Ferreira | Elieber Barros Bezerra | Carlos Bruno Barreto Luna | Edson Antônio dos Santos Filho | Renate Maria Ramos Wellen | Edcleide Maria Araújo
Source: Polymers (article, 2025-11-06)
Field: Materials Science — Polymers and Plastics

Tailoring PBT Performance Through PBT/POE-g-GMA Nanocomposites with MWCNT The production of polymer nanocomposites from supertough blends reinforced with carbon-based nanofillers has garnered attention in recent years due to improvements in their mechanical, thermal, and electrical properties. Currently, the main challenge is to develop materials with balanced performance for diverse industrial demands. In this context, this work aimed to produce nanocomposites of poly(butylene terephthalate) (PBT) and poly(ethylene-octene) grafted with glycidyl methacrylate (POE-g-GMA), reinforced with carbon nanotubes (MWCNTs). The PBT, the PBT/POE-g-GMA blend, and the respective MWCNT nanocomposites were initially premixed in an internal mixer and then processed in a co-rotational twin-screw extruder. After processing, they were injection-molded to obtain tensile, impact, and HDT test specimens. Mechanical (tensile, impact, and Shore D hardness), thermal (differential scanning calorimetry-DSC), thermomechanical (heat deflection temperature-HDT), electrical resistivity/conductivity, morphology, and Fourier transform infrared spectroscopy (FTIR) properties were evaluated. The results demonstrated a good balance among the investigated properties, with improvements in mechanical, thermal, and thermomechanical properties when compared to PBT. The impact strength of the nanocomposites reached 186 J/m, approximately 158% higher than that of neat PBT. The HDT reached approximately 55 °C in the PBT/POE-g-GMA/MWCNT5 nanocomposites, while the crystallization temperature increased by 11 °C, as evidenced by DSC, an aspect of great relevance for industrial applications. Furthermore, the PBT/POE-g-GMA/MWCNT5 nanocomposites exhibited an electrical conductivity of 1.06 × 10<sup>-7</sup> S/cm, indicating potential for electrical applications. Nanocomposite ; Heat deflection temperature ; Carbon nanotube ; Fourier transform infrared spectroscopy ; Crystallization ; Glycidyl methacrylate ; Polymer Polymer crystallization and properties ; Fiber-reinforced polymer composites ; Graphene research and applications
Authors: Péter Gurin | Szabolcs Varga
Source: Physical Review Research (article, 2025-06-26)
Field: Materials Science — Materials Chemistry

Ordering and association of patchy particles in quasi-one-dimensional channels We show that the formalism of Wertheim's first-order thermodynamic perturbation theory can be generalized for the fluid of rotating sticky particles with anisotropic hard core confined to a quasi-one-dimensional channel. Using the transfer-matrix method, we prove that the theory is exact if the hard-body interaction is additive, only the first neighbors interact, and the particles can stick together only along the channel. We show that the most convenient treatment of association in narrow channels is to work in the ensemble, where all structural and thermodynamic quantities can be expressed as a function of pressure and fraction of sites unbonded. Association (psychology) ; Geology ; Geometry ; Psychology ; Mathematics Pickering emulsions and particle stabilization ; Heat and Mass Transfer in Porous Media ; Material Dynamics and Properties
Authors: Ivan A. Pelevin | Maria Lyange | L. Fedorenko | Stanislav V. Chernyshikhin | И. С. Терешина
Source: Condensed Matter (article, 2025-04-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The Laser Powder Bed Fusion of Nd2Fe14B Permanent Magnets: The State of the Art In recent years, significant effort was made to make the 3D printing of fully dense rare-earth permanent magnets a reality. Since suitable Nd2Fe14B-based initial powder material became available, additive manufacturing implementation spread widely, which led to many studies being focused on using this material in 3D printing. This study shows the principal possibilities of the synthesis of Nd-Fe-B magnets by means of the laser powder bed fusion technique; moreover, this study shows significant progress in increasing their magnetic properties. This progress was made possible by different approaches, such as 3D-printing process optimization, the addition of a second phase (a low-melting eutectic) into the initial powder, the tuning of the main phase’s composition, and exploring different scanning strategies. However, the current level of material magnetic properties obtained via laser powder bed fusion is still far from that of magnets produced by using conventional powder metallurgy methods. The present review aims to capture the current state-of-the-art trials and highlight the main challenges. Magnet ; Fusion ; Materials science ; Laser ; Metallurgy ; Optics ; Mechanical engineering ; Physics ; Engineering Magnetic Properties of Alloys ; Additive Manufacturing Materials and Processes ; High Entropy Alloys Studies
Authors: Leon Gerard | Michael Scherbela | Halvard Sutterud | W. M. C. Foulkes | Philipp Grohs
Source: Nature Computational Science (article, 2025-10-22)
Field: Materials Science — Materials Chemistry

Transferable neural wavefunctions for solids Deep-learning-based variational Monte Carlo has emerged as a highly accurate method for solving the many-electron Schrödinger equation. Despite favorable scaling with the number of electrons, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>O</mml:mi> <mml:mrow><mml:mo>(</mml:mo> <mml:mrow> <mml:msup> <mml:mrow> <mml:msub><mml:mrow><mml:mi>n</mml:mi></mml:mrow> <mml:mrow><mml:mi>el</mml:mi></mml:mrow> </mml:msub> </mml:mrow> <mml:mrow><mml:mn>4</mml:mn></mml:mrow> </mml:msup> </mml:mrow> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , the practical value of deep-learning-based variational Monte Carlo is limited by the high cost of optimizing the neural network weights for every system studied. Recent research has proposed optimizing a single neural network across multiple systems, reducing the cost per system. Here we extend this approach to solids, which require numerous calculations across different geometries, boundary conditions and supercell sizes. We demonstrate that optimization of a single ansatz across these variations significantly reduces optimization steps. Furthermore, we successfully transfer a network trained on 2 × 2 × 2 supercells of LiH, to 3 × 3 × 3 supercells, reducing the number of optimization steps required to simulate the large system by a factor of 50 compared with previous work. Ansatz ; Monte Carlo method ; Artificial neural network ; Scaling ; Boundary value problem ; Boundary (topology) ; Hybrid Monte Carlo ; Wave function ; Monte Carlo molecular modeling Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Quantum, superfluid, helium dynamics
Authors: Jiuyi Wang | Xiaogang Lin | Jinyu Wu | Xiao Lv | B. T. Dai | Ke Wang | Jayne Wu
Source: Preprints.org (preprint, 2025-09-22)
Field: Chemistry — Analytical Chemistry

Research Progress on Molecularly Imprinted Polymer-Aptasensors for Food Safety Detection The biological accumulation of microcontaminants and associated antibiotic resistance in food poses significant threats to both human and environmental health. Therefore, it is particularly important to design and develop methods of efficient identification and detection. Recently, molecularly imprinted polymers (MIPs) and aptamers (Apts), as an emerging hybrid recognition element, have received widespread attention from researchers. Because the dual recognition-based sensors have exhibited improved properties and desirable features, such as high sensitivity, low limit of detection, high stability under harsh environmental conditions, high binding affinity, which are expected to be applied in food safety fields. This paper compares the characteristics of MIP and Apt, highlighting the significant advantages of aptamer-integrated MIP (MIP@Apt) dual recognition. It then systematically discusses three synthetic strategies for MIP-Aptamer hybrid recognition systems and their applications for food safety detection, focusing on analyzing their detection strategies, sensing mechanisms, construction methodologies, performance evaluations, and potential application value. It also offers substantive perspectives on both the prevailing limitations and promising developmental pathways for MIP-aptamer hybrid recognition-based sensing platforms. Molecularly imprinted polymer ; Food safety ; Aptamer ; Identification (biology) ; Dual (grammatical number) ; Consumer safety Analytical chemistry methods development ; Advanced biosensing and bioanalysis techniques ; bioluminescence and chemiluminescence research
Authors: Andrew Fulkerson | Ipek Bayram | Eric A. Decker | Carlos Parra-Escudero | Jiakai Lu | Carlos M. Corvalán
Source: Foods (article, 2025-06-18)
Field: Chemistry — Analytical Chemistry

Machine Learning Identifies a Parsimonious Differential Equation for Myricetin Degradation from Scarce Data Accurately modeling the degradation of food antioxidants in oils is essential for understanding oxidative stability and improving food shelf life. This study presents an innovative machine learning approach integrating neural differential equations and sparse symbolic regression to derive a parsimonious differential equation for myricetin degradation in stripped soybean oil. Despite being trained on a small experimental dataset, the model successfully predicts degradation trends across a wide range of initial concentrations and extrapolates beyond the learning data. This capability demonstrates the robustness of machine learning for uncovering governing equations in complex food systems, particularly when experimental data is scarce. Our findings provide a framework for improving antioxidant efficiency in food formulations. Robustness (evolution) ; Machine learning ; Artificial intelligence ; Degradation (telecommunications) ; Computer science ; Biological system ; Myricetin ; Stability (learning theory) ; Artificial neural network ; Experimental data ; Biochemical engineering ; Mathematics ; Chemistry ; Statistics ; Antioxidant ; Engineering ; Biology Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Antioxidant Activity and Oxidative Stress
Authors: Sam Layding | Robert A. Riggleman
Source: Soft Matter (article, 2025-12-23)
Field: Materials Science — Materials Chemistry

Small particle dynamics in glassy polymers: diffusion, relaxation, and machine-learned softness In this work, we explore the simulated transport dynamics of small particles through a polymer melt at temperatures spanning from liquid-like behavior down to near and below the simulated glass transition temperature. Using softness, a machine-learned scalar quantity, we connect the structural neighborhood surrounding a particle with its dynamic behavior to relate the probability of a glassy rearrangement to its local environment. An energetic and entropic scale for the rearrangement process of these small particles emerges and is compared across systems of different particle sizes and interaction strengths. Diffusion coefficients and relaxation times both show strong dependence on our tuning parameters, and the barriers to rearrangement show increasing nonlinearity as the particles become smaller. The trends we observe provide some insight into how local structure plays a role in small molecule transport when the surrounding medium is undergoing a glass transition, leading to large changes in system mobility. Scalar (mathematics) ; Glass transition ; Particle (ecology) ; Relaxation (psychology) ; Molecular dynamics ; Polymer ; Diffusion ; Nonlinear system ; Dynamics (music) Material Dynamics and Properties ; Advanced Physical and Chemical Molecular Interactions ; Block Copolymer Self-Assembly
Authors: Oscar Castillo | Hasan Dinçer | Serhat Yüksel | Serkan Eti
Source: Scientific Reports (article, 2025-08-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Assessing carbon–neutral supercapacitors in renewable energy systems with self-improving agent-based molecular fuzzy intelligent algorithms Carbon-neutral supercapacitors play an important role in renewable energy investments as environmentally friendly devices that both function as energy storage and aim to reduce carbon footprint. This situation can cause waste of resources and wrong prioritization decisions. In this context, the main problem is that the most important factors affecting the technical investment performance of carbon-neutral supercapacitors have not been determined. To fill this gap, this study proposes an original decision-making model to determine the importance levels of variables affecting the performance of these devices and to present appropriate investment strategies. The proposed model includes the integrated use of Entropy-game-based expert weighting method, Q-learning algorithm, molecular fuzzy intelligence algorithms, Bayesian network-based weighting (BANEW) and ant colony optimization (ACO) techniques. This study contributes to making more accurate and effective technical decisions for sustainable energy investments by filling an important gap in the literature with its original decision model. It is determined that recyclability rate is the most significant factor because it has the highest weight (0.316). On the other side, the best investment choice for carbon-neutral supercapacitors in renewable energy systems is gravity-based energy storage with the greatest fitness value of 4.044. Supercapacitor ; Computer science ; Renewable energy ; Fuzzy logic ; Carbon fibers ; Algorithm ; Artificial intelligence ; Chemistry ; Electrical engineering ; Engineering ; Electrode ; Capacitance ; Composite number Supercapacitor Materials and Fabrication ; Fuel Cells and Related Materials ; Process Optimization and Integration
Authors: Karlo Raić | Vaso Manojlović
Source: Metallurgical and Materials Data (article, 2025-06-30)
Field: Materials Science — Materials Chemistry

Corrosion Behavior of Dental Metallic Alloys Dental metallic alloys undergo electrochemical degradation in the oral environment, which compromises structural integrity and surface functionality. Ionic dissolution can activate hypersensitivity and potential cytotoxic or genotoxic effects; therefore, released ion levels must remain within defined safety limits. Corrosion also accelerates fatigue, fretting fatigue, and tribocorrosion, increasing the risk of deformation and fracture. This review consolidates methodologies for immersion and galvanic corrosion testing, presents the electrochemical background required for study design and data interpretation, and identifies the physiological variables that govern intraoral degradation, including saliva composition and pH cycling, proteins and biofilms, mechanical loading, temperature fluctuations, and fluoride exposure. Evidence on the corrosion behavior of dental alloys is summarized across in vitro, in situ, and in vivo contexts. In addition, surface engineering approaches are examined, including passivation strategies, surface modification, and protective coatings, with the aim of reducing ion release, improving corrosion resistance, and extending clinical service life. Corrosion ; Galvanic corrosion ; Passivation ; Galvanic cell ; Dissolution ; Tribocorrosion ; Electrochemistry ; Fretting Corrosion Behavior and Inhibition ; Metallurgy and Material Science ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Yuxi Deng | Boyun Liu | Jinhua Yan
Source: Photonics (article, 2025-05-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High-Efficiency Polarization-Independent LCoS Utilizing a Silicon-Based Metasurface In this paper, we propose and demonstrate a liquid crystal on silicon (LCoS) device that achieves high-efficiency, broadband, polarization-independent phase modulation by integrating a metasurface between the liquid crystal layer and the backplane of a commercial LCoS device. The metasurface is composed of rectangular silicon pillars encapsulated in silicon dioxide. By precisely adjusting the orientation and dimensions of these silicon pillars, the metasurface effectively controls the polarization state of the incident light, enabling polarization-independent phase modulation across the C+L band. Experimental results show that the polarization conversion ratio remains approximately 95% throughout the entire C+L band under varying driving voltages. Due to the low absorption characteristics of silicon and silicon dioxide, the metasurface integration introduces minimal loss. Additionally, the experimental results indicate that the reflectance of the metasurface-integrated LCoS exceeds 96% of the original LCoS reflectance. Notably, the metasurface does not affect the phase modulation characteristics of the device or exacerbate the fringing field effect, which could otherwise degrade modulation efficiency. The fabrication process for incorporating the silicon metasurface into the LCoS is fully compatible with standard semiconductor manufacturing techniques, thus facilitating the potential for large-scale production. Theoretical analysis further confirms that the design is tolerant to fabrication errors. Liquid crystal on silicon ; Polarization (electrochemistry) ; Silicon ; Optics ; Materials science ; Optoelectronics ; Diffraction efficiency ; Computer science ; Physics ; Liquid crystal ; Grating Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Photonic Crystals and Applications