jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Elisa Roldan | Kirstie Andrews | Stephen M. Richardson | Reyhaneh Fatahian | Glen Cooper | Rasool Erfani | Tasneem Sabir | Neil D. Reeves
Source: Frontiers in Bioengineering and Biotechnology (article, 2026-02-18)
Field: Materials Science — Biomaterials

FibreCastML: an open web platform for predicting electrospun nanofibre diameter distributions for biomedical applications By shifting from mean-centric to distribution-aware modelling, this work establishes a new paradigm for electrospinning design. FibreCastML enables reproducible, sustainable, and data-driven optimisation of scaffold architecture, bridging experimental and computational domains. Openly available, it empowers laboratories worldwide to perform faster, greener, and more reproducible electrospinning research, advancing sustainable nanomanufacturing and biomedical innovation. Interpretability ; Scalability ; Feature (linguistics) ; Process (computing) ; Polyvinyl alcohol ; Dimensionality reduction ; Support vector machine ; Variable (mathematics) ; Nanoscopic scale Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Machine Learning in Materials Science
Authors: Elif Özlem TORUN | Mehmet Emin KOÇAK | Buse KAYRA | Fahriye Ercan | Serap Yalçin
Source: Tekirdağ Ziraat Fakültesi Dergisi (article, 2026-01-07)
Field: Materials Science — Materials Chemistry

Green Synthesis of Silver Nanoparticles with Black chokeberry [Aronia melanocarpa (Michx.) Elliot] Leaf Extract and Evaluation of Insecticidal Activity on the Greater Wax Moth [Galleria mellonella (Lepidoptera:Pyralidae)] The greater wax moth, Galleria mellonella (Lepidoptera:Pyralidae), is a harmful species that settles on honeycombs in beehives and causes a decrease in productivity. In the control of harmful insects, the discovery of alternative methods to chemical control, which are environmentally friendly and not effective on non-target organisms has been studied for many years. - Plant-derived substances are widely used among these alternative methods. Black chokeberry [Aronia melanocarpa (Michx.) Elliot] is a shrub-like plant belonging to Family Rosaceae and is cultivated for fruit production. While there are many studies on the medical importance of this plant, known as the "super/miracle plant", studies on its effects on insects are limited. Nanotechnology is one of the topics that has attracted a lot of attention in recent years. The use of nanotechnology is increasing in the agricultural sector as in other disciplines. An agrochemical system with superior properties such as targeted pesticide, controlled release of active substances, and biodegradable materials can be created from modified nanomaterials. With these features, nanotechnology gives hope to solve the environmental problems caused by traditional chemical pesticides. In this study, the leaf extract of A. melanocarpa was green synthesized with silver nanoparticles. The green synthesized nanoparticles were tested on late stage larvae of G. mellonella and their insecticidal effect was demonstrated. In addition, the binding ability of the main components in the leaf extract (n-hexadecanoic acid, oleic acid and octadecanoic acid) to the antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)) of the insect has been demonstrated in silico. Thus, it was aimed to reveal a plant-derived extract, an effective bioinsecticide alternative to chemical control, by in vivo and in silico methods. LC50 and LC99 values of G. mellanolla larvae applied with silver nanoparticle leaf extract were determined as 5.51 and 11.58µl, respectively. Moreover, the effect of main components of A. melanocarpa on SOD and CAT enzymes, which are the main elements of the enzymatic defense system of G. mellonella, was demonstrated in silico. Galleria mellonella ; Wax ; Silver nanoparticle ; Oleic acid ; Agrochemical ; Antifungal ; Chemical control Nanoparticles: synthesis and applications ; Phytochemical compounds biological activities ; Plant Growth Enhancement Techniques
Authors: Lan Yi | Christian Dreyer
Source: Polymers (article, 2026-04-10)
Field: Materials Science — Biomaterials

Macromolecular Design Principles Governing Electrospinning of Polymer Nanofibers Electrospinning is a versatile technique for producing polymer nanofibers with high ratios of surface area to volume and tunable porosity. Conventional approach to the optimization of processing parameters such as voltage and flow rate frequently encounters limitations in reproducibility and scalability. This review proposes a comprehensive framework that integrates macromolecular design principles with established electrohydrodynamic theories. We analyze how intrinsic molecular traits, specifically chain entanglement density, molecular weight distribution (MWD), topological architecture, and polymer–solvent thermodynamic interactions, define the boundaries of jet stability and solidification. Key findings highlight that while molecular weight establishes a baseline for spinnability, the MWD dictates the dynamic response under extreme deformation. Notably, high-molecular-weight fractions act as elastic load-bearers that suppress capillary breakup. Furthermore, we discuss here how molecular architecture and solvent-mediated segmental mobility determine whether molecular orientation is kinetically trapped or relaxed during the nanosecond timescales of jet flight. By establishing a hierarchical design logic prioritizing molecular and formulation variables over processing parameters, this framework provides a robust strategy to overcome challenges in scalability and reproducibility, positioning electrospinning as a sensitive probe for macromolecular dynamics under extreme elongation. Nanofiber ; Polymer ; Macromolecule ; Electrospinning ; Molecular dynamics ; Nanosecond ; Scalability Electrospun Nanofibers in Biomedical Applications ; Electrohydrodynamics and Fluid Dynamics ; Surface Modification and Superhydrophobicity
Authors: Orhun Ayar | Bhargav Sriram Siddani | Ishan Srivastava | Abhinendra Singh
Source: arXiv (Cornell University) (article, 2026-03-12)
Field: Materials Science — Materials Chemistry

Recent Computational Advances in Dense Suspension Mechanics Dense suspensions of particles dispersed in liquids are central to industrial and geophysical processes and serve as model systems for out-of-equilibrium soft matter. At high particle concentrations, they exhibit stress-dependent rheology, including discontinuous shear thickening and shear jamming, arising from frictional contacts. Nonlinear physics arises from the interplay among direct contacts, interfacial chemistry, and fluid-mediated hydrodynamics. The relative importance of these mechanisms depends on particle properties and flow conditions, making predictive modeling inherently multi-scale and, therefore, computationally challenging. Recent advances in computational methods have transformed our ability to simulate the physics of dense suspensions across scales. In this Perspective, we discuss state-of-the-art simulation frameworks that integrate the mechanics of dry granular materials, mediated by contact friction, with suspension hydrodynamics to provide predictive models of dense suspension rheology. We highlight recent computational developments for simulating dense suspensions at varying levels of fidelity, ranging from particle-resolved to continuum models, as well as models that investigate their mesoscale organization during flow. Together, these approaches reveal a hierarchical structure in which microscale constraints give rise to mesoscale frictional networks that ultimately govern macroscopic flow. By synthesizing developments across computational mechanics and soft matter physics, this Perspective highlights emerging directions toward a predictive, multi-scale modeling framework of dense suspensions in realistic geometries and complex flow environments. Microscale chemistry ; Mesoscale meteorology ; Computational mechanics ; Continuum mechanics ; Computational model ; Suspension (topology) ; Multiscale modeling ; Particle (ecology) ; Flow (mathematics) Material Dynamics and Properties ; Granular flow and fluidized beds ; Lattice Boltzmann Simulation Studies
Authors: Zhongwei Liu | Xiaoyu Yang | Xi He | Yuanhui Sun
Source: Materials (article, 2026-03-31)
Field: Materials Science — Materials Chemistry

Computational Screening of Bonding-Controlled Electronic Structures in One-Dimensional Cu/Ag-Based Hybrid Semiconductors One-dimensional hybrid organic-inorganic semiconductors enable band-edge engineering through reduced dimensionality and interfacial orbital hybridization. Nevertheless, the electronic physics of Cu/Ag-based systems has received limited attention. Here, we perform high-throughput first-principles calculations on 90 Cu/Ag halide HOISs derived from experimentally reported parent structures to elucidate bonding-dependent electronic behavior. We uncover a clear transition from electronically isolated inorganic chains in ionic hybrids to strongly hybridized band edges in covalent and mixed-bonding hybrid frameworks, where ligand <i>p</i> orbitals cooperatively couple with Cu-derived states and halogen <i>p</i> orbitals. This hybridization produces <i>p</i>-orbital-dominated band edges, enhanced dispersion, and light-hole effective masses along the 1D chains. Guided by this bonding-driven mechanism, we further identify four Cu-based compounds, which are helpful for tuning light-harvesting properties in low-dimensional hybrid semiconductors. Semiconductor ; Ionic bonding ; Atomic orbital ; Orbital hybridisation ; Covalent bond ; Electronic structure ; Halogen ; Halide 2D Materials and Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Copper-based nanomaterials and applications
Authors: Neha Jain | Michio Iwaoka
Source: Frontiers in Chemistry (article, 2026-03-10)
Field: Chemistry — Organic Chemistry

Sulfur-and selenium-targeting warheads: reaction-based design of electrophilic warheads for selective inhibition of enzyme Covalent inhibitors for nucleophilic residues, particularly cysteine (Cys) and selenocysteine (Sec), have resurfaced as precision therapies for modifying disease-associated enzymes. The main advantage of covalent inhibition is its ability to form a stable covalent bond with a particular residue near the binding site. Permanent alteration of Cys and Sec residues by covalent inhibitors is possible since the sulfur and selenium atoms have high chemical reactivities and intrinsic variations in the redox behaviors, which enable the rational design of covalent inhibitors targeting the Cys/Sec residues. Moreover, recent breakthroughs covering a wide range of warheads (reactive moieties of covalent inhibitors), from traditional thiol-selective motifs (e.g., acrylamides) to emerging selenol-selective analogs (e.g., Ebselen D, diacyl furoxan derivatives, etc.), exhibit the potent inhibition against kinases and redox-regulating enzymes having a thiol/selenol group in the active sites. Although we have comprehensively encountered numerous promising therapeutic potentials and preclinical data of Cys/Sec-targeted covalent inhibitors, there is still a room of challenges in attaining the precise Cys-/Sec-selectivity, reducing the warhead toxicity, and improving the in vivo stability. This mini-review combines recent insights and developments of thiol- and selenol-selective warheads within the midst of the intersection of chemical biology and medicinal chemistry. We also discuss future directions of the relevant research with the goal of improved safety and effectiveness. Schematic representation of covalent inhibition: A small-molecule warhead with a guiding system form a covalent bond to the thiol (SH) or selenol (SeH) reactive site of a kinase or redox-regulating enzyme. Covalent bond ; Warhead ; Selenocysteine ; Cysteine ; Nucleophile ; Electrophile ; Enzyme ; Chemical biology ; Residue (chemistry) ; Ebselen Click Chemistry and Applications ; Organoselenium and organotellurium chemistry ; Sulfur-Based Synthesis Techniques
Authors: Eid Mohamed
Source: Journal of Umm Al-Qura University for Engineering and Architecture (article, 2026-01-27)
Field: Materials Science — Materials Chemistry

Performance analysis of the solar-powered thermoelectric air conditioning system for a light vehicle cabin Photovoltaic system ; Air conditioning ; Battery (electricity) ; Thermoelectric cooling ; Solar energy ; Water cooling ; Mode (computer interface) ; Power (physics) ; Thermoelectric effect Advanced Thermoelectric Materials and Devices ; Refrigeration and Air Conditioning Technologies ; Adsorption and Cooling Systems
Authors: Bo Durbeej | Simone Pintér | Andreas Hirsch | Michał Andrzej Kochman
Source: ChemRxiv (article, 2026-03-16)
Field: Materials Science — Materials Chemistry

Photochemistry of the Energy-Storing Isomer of a Norbornadiene-Based Molecular Switch: Ring Opening, Rehybridized Intramolecular Charge Transfer, and Isomerization into a Carbene Photoproduct Photoswitches based on the norbornadiene-quadricyclane (NBD-QC) isomer pair capture solar energy by undergoing the NBD→QC photoisomerization reaction. The energy-storing QC isomer contains two highly strained three-membered rings, which implies that it may be susceptible to photodegradation through exposure to the ultraviolet (UV) component of sunlight. In the present study, we use nonadiabatic molecular dynamics simulations to investigate the UV-induced photochemistry of the QC isomer of a representative NBD-QC photoswitch with a push-pull substitution motif. A pattern recognition algorithm is employed to analyze and systematize the simulation results. We find that the predominant outcome of UV absorption, observed in 75 out of the 100 simulated trajectories, is the opening of the four-membered ring which belongs to the QC moiety, although in about half of the trajectories which follow this relaxation pathway, the ring promptly closes again. However, in a small fraction of trajectories, the QC moiety instead breaks up, leading to the formation of a carbene photoproduct. We hypothesize that that the breakup of the QC moiety is the first step in a reaction pathway which leads to the decomposition of the photoswitch. Photoisomerization ; Isomerization ; Moiety ; Carbene ; Intramolecular force ; Ring (chemistry) ; Photoswitch ; Photodissociation Photochromic and Fluorescence Chemistry ; Photochemistry and Electron Transfer Studies ; Light effects on plants
Authors: Alexander Urban | Leo Luber | Daphne Benedikt | Andreas Singldinger
Source: Research Square (preprint, 2026-01-23)
Field: Materials Science — Materials Chemistry

Universal statistics of nanocrystal photoluminescence Photoluminescence ; Exciton ; Gaussian ; Nanocrystal ; Spontaneous emission ; Coupling (piping) ; Radiative transfer ; Exponential function ; Statistical ensemble Quantum Dots Synthesis And Properties ; Semiconductor Quantum Structures and Devices ; Silicon Nanostructures and Photoluminescence
Authors: Ernesto Estrada
Source:  (article, 2026-02-16)
Field: Chemistry — Organic Chemistry

MAGNETIC HÜCKEL THEORY: FRAMEWORK FOR THE HERMITIAN ADJACENCY MATRIX OF GRAPHS We introduce a magnetic extension of the Hückel molecular orbital (HMO) method in which the effect of an external magnetic field is incorporated through the Peierls substitution. In this formulation, the π-electron Hamiltonian of a conjugated molecule becomes a complex-weighted hopping operator defined on the hydrogen-depleted molecular graph. Under the standard Hückel assumptions, this operator coincides with the Hermitian adjacency matrix of the graph, providing a physical realization of Hermitian adjacency operators within molecular electronic structure theory. The magnetic-HMO framework enables the calculation of flux-dependent electronic observables such as bond currents, ring currents, orbital magnetization, and orbital susceptibility directly from the spectrum of the magnetic adjacency matrix. Applications to polycyclic aromatic hydrocarbons show that the magnetic response of π-electron systems is strongly controlled by molecular topology. In particular, linearly fused systems exhibit regular flux-dependent oscillations in the orbital magnetization, whereas nonlinear and extended molecules display more complex spectral rearrangements associated with multiple conjugation pathways. MSC (2020): 05C50; 92E10; 81Q10; 05C90. Hermitian matrix ; Extension (predicate logic) ; Magnetic field ; Adjacency matrix ; Hamiltonian (control theory) ; Graph theory ; Adjacency list Synthesis and Properties of Aromatic Compounds ; Graph theory and applications ; Magnetism in coordination complexes
Authors: Sarah-Jane Richards | Matthew I. Gibson
Source: Chemical Communications (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Polymer-tethered glycosylated gold nanoparticles as versatile tools for bio-sensing Glycans direct many biological recognition and signalling processes, spanning basic cell biology to diagnostics and therapy. Multivalent presentation of glycans is well established to increase avidity (but not always selectivity) and hence glycosylated (nano)materials have emerged as versatile scaffolds to probe glycobiological processes and for application in biomedicine. In this Feature article we review our laboratory's contributions to the development of polymer-tethered glycosylated gold nanoparticles. This approach exploits the steric stability of the polymer coating, ease of glycan capture and the plasmonic signal-generation of the gold core. The article covers the synthetic rationale for the polymeric tether, glycan capture modalities and application to screen (un)natural glycans binding patterns and translation into point-of-care lateral flow glyco-diagnostics and solution-phase colourimetric biosensors. We also suggest areas for future development and comparison to related systems. Glycan ; Avidity ; Colloidal gold ; Nanoparticle ; Galectin ; Protein stability Advanced Nanomaterials in Catalysis ; Polydiacetylene-based materials and applications ; Advanced Polymer Synthesis and Characterization
Authors: Zhijian Yang | Edwin Setiadi Sugeng | Mhedine Alicherif | Tat Loon Chng
Source: Plasma Sources Science and Technology (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

An interpretable operator-learning model for electric field profile reconstruction in discharges based on the EFISH method Abstract Machine learning (ML) models have recently been utilized for reconstructing the electric field distribution from a corresponding electric-field-induced second-harmonic (EFISH) signal profile—a task described in earlier works as the ‘inverse EFISH problem’. This approach is one of several that addresses the inaccuracy of a (line-of-sight) EFISH measurement caused by the Gouy phase shift present in focused laser beams. A key advantage of this approach is that the accuracy of the reconstructed, or ‘inverted’, profile (assuming that this solution is unique) can be readily evaluated through a ‘forward transform’ of the underlying EFISH equation. Motivated by this latest success, the present study introduces a novel ML model with significantly enhanced performance. This model is built on a more complex, but powerful operator-learning architecture, and moves beyond the simpler class of artificial and convolutional neural networks (i.e. ANNs and CNNs) employed in previous work. Termed here as Decoder-Deep Operator Network (or DDON), its main asset is the ability to learn function-to-function mappings, a feature essential for recovering electric field profiles of an unknown shape. The superior performance of DDON is exemplified via a comparison with our published CNN model and the feasibility of a classical mathematical method, as well as its application to both discharge simulations and experimental EFISH data from a nanosecond pulsed discharge. In almost all cases, the DDON model exhibits better generalizability, higher prediction accuracy, and wider applicability. Furthermore, the intrinsic nature of this operator-learning architecture renders it less sensitive to the exact location(s) of the acquired data, enabling electric field reconstruction even with seemingly ‘incomplete’ input profiles—an issue often accompanying poor signal sensitivity. Another important aspect of this work is the use of ‘integrated gradients’, which helps identify input (signal) regions that most critically influence the accuracy of a reconstructed profile. This quantitative metric can in turn provide guidance on the optimal sampling region (or window) for acquiring EFISH data. Overall, we believe that the DDON model is a robust and comprehensive model which can be readily applied to reconstruct ‘bell-shaped’ electric field profiles with an existing axis of symmetry, especially in non-equilibrium plasmas. Electric field ; Field (mathematics) ; Convolutional neural network ; Artificial neural network ; Feature (linguistics) ; Operator (biology) ; Pattern recognition (psychology) ; Convolution (computer science) High voltage insulation and dielectric phenomena ; Plasma Applications and Diagnostics ; Plasma and Flow Control in Aerodynamics
Authors: Andrzej P. Kądzielawa
Source: ArXiv.org (article, 2026-02-11)
Field: Materials Science — Materials Chemistry

On generating Special Quasirandom Structures: Optimization for the DFT computational efficiency We present our novel evolutionary algorithm for generating Special Quasirandom Structures (SQS) designed to optimize the computational efficiency of Density Functional Theory (DFT) computations. Operating on the premise that symmetry proxies non-randomness, we rigorously filter out 1.P1 candidate structures prior to evaluating correlation functions. Our extinction-based workflow includes the seeding, filtration, evaluation, extinction, and repopulation phases to produce efficient supercells with maximal local environmental distinctness. We compare our results against those generated by established software packages, on the example of the W\textsubscript{70}Cr\textsubscript{30} alloy. Although standard tools achieve (marginally) lower correlation errors, our best-performing structures require approximately five times fewer unique displacements for phonon calculations. This approach sacrifices negligible quantitative disorder accuracy to significantly reduce the computational cost of modeling thermal properties. Workflow ; Filter (signal processing) ; Computational complexity theory ; Software ; Symmetry (geometry) ; Degrees of freedom (physics and chemistry) ; Density functional theory ; Evolutionary algorithm Thermal Expansion and Ionic Conductivity ; Machine Learning in Materials Science ; Boron and Carbon Nanomaterials Research