jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alexander Selverian | Svilen Bobev
Source: Inorganics (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Synthesis and Structural Characterization of Potentially Topologically Non-Trivial Zintl Phases ACaBi (A = K, Rb, Cs) For the first time, the ternary Zintl phases RbCaBi and CsCaBi have been synthesized and structurally characterized via single-crystal X-ray diffraction methods. These two compounds, alongside KCaBi, are confirmed to crystallize in a tetragonal crystal system with the space group P4/nmm (no. 129) with two formula units per cell. The lattice constants increase monotonically from a = 5.3812(10) Å and c = 8.410(3) Å for KCaBi, to a = 5.4139(7) Å and c = 8.6180(17) Å for RbCaBi, and to a = 5.4709(11) Å and c = 8.914(3) Å for CsCaBi. The crystal structure can be visualized as an array of square prisms formed of Bi atoms, which are centered by alkali metal atoms, while the Ca atoms fill tetrahedra formed of Bi atoms. There are no direct Bi–Bi interactions in the crystal structure; therefore, with full cation ordering present, the chemical bonding in the ACaBi compounds can be rationalized within the fully ionic approximation as A+Ca2+Bi3− (A = K, Rb, Cs). This suggests the opening of an (narrow) energy gap between the valence and conduction bands, i.e., semiconducting behavior. Tetragonal crystal system ; Ternary operation ; Crystal structure ; Valence (chemistry) ; Tetrahedron ; Ionic bonding ; Lattice constant ; Alkali metal ; Diffraction Advanced Thermoelectric Materials and Devices ; Rare-earth and actinide compounds ; Boron and Carbon Nanomaterials Research
Authors: Yuxin Zhao
Source: FlexMat. (article, 2026-02-10)
Field: Materials Science — Materials Chemistry

Ideal building blocks for flexible electronics: Strong, ductile, and conductive metallic nanowires via coherent twinning Abstract While pioneering studies on coherently twinned metallic nanowires revealed extraordinary mechanical‐electrical properties over a decade ago, the field has seen diminishing momentum despite its transformative potential. A renewed focus is warranted, as these nanostructures uniquely circumvent the classic trade‐off between strength, ductility, and conductivity through their coherent internal interfaces. Key deformation mechanisms and uncharted frontiers in electro‐mechanical coupling are outlined, intended to inspire the application of these concepts in next‐generation flexible electronics and nanodevices. Crystal twinning ; Ideal (ethics) ; Nanowire ; Electrical conductor ; Coupling (piping) ; Field (mathematics) ; Electronics Carbon Nanotubes in Composites ; Nanowire Synthesis and Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Dilani Chathumalee | Stephen J. Butler | Amanda K. Pearce
Source: Macromolecular Chemistry and Physics (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Fluorescent Polymeric Materials for Bacterial Interaction and Detection ABSTRACT Bacteria play a crucial role in maintaining human health, particularly within the microbiome of the gastrointestinal tract and skin. However, pathogenic species such as Escherichia coli , Staphylococcus aureus , and Salmonella can disrupt this balance, leading to severe infections and contributing to the global rise of antimicrobial resistance (AMR). Rapid and species‐selective bacterial detection is therefore critical for effective diagnosis and control of healthcare infections. Fluorescence‐based sensing has emerged as a promising strategy for rapid, sensitive, and cost‐effective detection of bacterial species. Polymer‐based materials are particularly interesting due to their tunable chemistry, structural versatility, and enhanced stability. By integrating fluorophores with functional polymer backbones, these systems can interact selectively with bacterial surfaces through electrostatic, hydrophobic, and directed hydrogen‐bonding interactions, enabling non‐disruptive interactions and detection. This review highlights advances in fluorescent polymeric materials for bacterial sensing, classifying systems by polymer type and outlining design strategies that control selectivity, sensitivity, and photophysical behavior. Emphasis is placed on fully synthetic polymers that achieve bacterial recognition without biological components, offering new pathways toward non‐toxic, responsive bacterial sensors. Polymer ; Fluorescence ; Bacteria ; Microbiome ; Human health ; Antimicrobial Luminescence and Fluorescent Materials ; Antimicrobial agents and applications ; Molecular Sensors and Ion Detection
Authors: Yajuan Li | Yuhong Zhou | Yixi Wang | Wei Jiang | Fubao Yang | Peng Jin | Jiping Huang
Source: Advanced Materials (article, 2026-02-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Invisible Hydrodynamic Sensing via Metamaterial Shells Optimized by Machine Learning Accurate flow-field sensing is crucial for microfluidics, biomedicine, and environmental monitoring. However, conventional sensing devices inherently distort the flow due to permeability mismatch, leading to erroneous data. To overcome this fundamental limitation, we propose and validate a hydrodynamic sensing mechanism based on a rationally designed metamaterial shell that creates a protected sensing core while leaving the external flow almost undisturbed. Specifically, the shell restores the pressure field in the core region to the background pressure field that would exist in the absence of any obstacle, so that an actual sensor placed there would read the true undisturbed pressure, and at the same time suppresses the disturbance of the combined core-shell structure to the surrounding flow. This shell, with anisotropic permeability derived from scattering-cancellation theory, thus renders the sensing core invisible to the background flow. Navigating the vast design space is achieved via a deep neural network, which inversely designs microstructures with exceptional accuracy (prediction error <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo><</mml:mo> <mml:mn>1</mml:mn></mml:mrow> <mml:annotation>$< 1$</mml:annotation></mml:semantics> </mml:math> %). Our metashell-enabled sensing scheme reduces pressure measurement errors by four to five orders of magnitude, achieving near-perfect fidelity even under severe permeability contrasts. This theoretical-machine learning framework establishes a blueprint for distortion-free hydrodynamic sensing, readily extendable to thermotics, acoustics, and electromagnetics. Metamaterial ; Anisotropy ; Permeability (electromagnetism) ; Pressure sensor ; Artificial neural network ; Parameter space ; Blueprint ; Relative permeability Metamaterials and Metasurfaces Applications ; Acoustic Wave Phenomena Research ; Advanced Sensor and Energy Harvesting Materials
Authors: Bienfait Kabuyaya Isamura | Olivia Aten | Mohamadhosein Nosratjoo | Paul Lode Albert Popelier
Source: Communications Chemistry (article, 2026-03-31)
Field: Materials Science — Materials Chemistry

Unprecedented robustness of physics-informed atomic energy models at and beyond room temperature Machine-learned potentials (MLPs) have become widely adopted alternatives to traditional electronic structure and molecular mechanics methods. However, despite excelling on fixed test sets, most MLPs remain prone to instability when deployed in molecular dynamics simulations, particularly at elevated temperatures. Here, we present the first physics-informed Gaussian process (GP)-based atomic energy models that achieve practically unlimited stability in NVT simulations at temperatures as high as 1000 K. Our findings highlight the importance of the GP prior mean function and demonstrate the models' ability to predict restoring forces that preserve the system's physical integrity. The quantum chemical topology information embedded in these models acts as an inductive bias to mitigate arbitrary fluctuations in the predicted atomic energies. Finally, the models' robustness is evidenced by 50 successful simulations of four flexible organic molecules (peptide-capped glycine and serine, malondialdehyde, and aspirin), yielding a cumulative simulation time of 0.5 microseconds completed within two CPU days. Robustness (evolution) ; Molecular dynamics ; Gaussian ; Quantum ; Potential energy ; Stability (learning theory) ; Instability ; Topology (electrical circuits) Machine Learning in Materials Science ; Protein Structure and Dynamics ; Mechanical and Optical Resonators
Authors: Manisha Rajput | Ashutosh Kumar Shukla | Avinash Mahapatra | Swapneswar Bisoi | G. V. Pavan Kumar | Atikur Rahman
Source: Communications Materials (article, 2026-03-17)
Field: Materials Science — Materials Chemistry

Morphotaxial Cu doping in monolayer MoS2 for high-performance optoelectronics Doping is crucial for semiconductor technology, enabling the design of integrated circuits, microprocessors, and other advanced optoelectronic devices with desired properties. The emergence of two-dimensional (2D) materials has opened pathways for atomic-scale integration. However, their 2D nature limits conventional ion implantation methods for doping, which poses a significant barrier to further device development and optimization. Here, we report a solvent-based cation-exchange morphotaxy that enables substitutional incorporation of Cu atoms into CVD-grown MoS2 monolayers. This approach induces stable p-type doping, suppressing dark current by four orders of magnitude and enhancing the light-to-dark current ratio by over 1000-fold compared to pristine MoS2. The substitutional Cu incorporation modifies the trap-state landscape, leading to faster photoresponse and reduced noise. As a result, Cu-doped MoS2 photodetectors achieve specific detectivity values up to 1014 Jones and response times improved by more than an order of magnitude, outperforming many previously reported doped transition metal dichalcogenide devices. This scalable and CMOS-compatible doping strategy provides a pathway for defect and electronic structure engineering in 2D semiconductors, opening new opportunities for high-performance optoelectronics, including neuromorphic and spintronic applications. Doping challenges in 2D materials hinder the advancement of semiconductor devices. Here, the authors introduce a solvent-based cation-exchange method to incorporate Cu into MoS2 monolayers, achieving stable p-type doping leading to faster photoresponse and reduced noise, paving the way for advanced optoelectronic applications in neuromorphic and spintronic technologies. Neuromorphic engineering ; Doping ; Spintronics ; Photodetector ; Monolayer ; Semiconductor ; Scalability 2D Materials and Applications ; Graphene research and applications ; Nanowire Synthesis and Applications
Authors: Štěpán Sklenák | Jiri Dedecek
Source: Chemical Society Reviews (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Alpha oxygen – a unique oxidation active site from a quantum chemical viewpoint The alpha oxygen (also α-O, Fe(IV)O, and Fe(III)-O<sup>-</sup>˙) stabilized in zeolite matrices exhibits a unique reactivity. It is, for example, able to oxidize methane to methanol at room temperature. Such a high oxidation activity makes the alpha oxygen an extremely attractive species from the point of view of oxidation catalysis. The alpha oxygen can be prepared by splitting either N<sub>2</sub>O or O<sub>2</sub> also at low temperatures over different transition metal cations stabilized in extra-framework cationic sites of zeolites in the form of either isolated cations or two cooperating cations forming distant binuclear cationic sites. The alpha oxygen was primarily defined by its reactivity, and up to now, experimental data concerning its structure are rather scarce. Quantum chemical calculations are used to interpret experimental data and thus yield significantly deeper insights into the preparation, structure, and reactivity of this otherwise omitted active species with enormous potential for applications. This review represents the first collection and systematic interpretation of experimental data and quantum chemical calculations to provide a complex description of the alpha oxygen and its structure, reactivity, and properties. Quantum chemical ; Cationic polymerization ; Oxygen ; Quantum yield ; Yield (engineering) ; Reactivity (psychology) ; Methanol ; Zeolite ; Metal Catalytic Processes in Materials Science ; Metal-Catalyzed Oxygenation Mechanisms ; Electrocatalysts for Energy Conversion
Authors: Minsun Oh | Yubin Kim | Minjeong Ha
Source: npj Spintronics (article, 2026-01-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Strain-decoupled magnetism in flexible spintronic sensors Abstract Flexible spintronic sensors provide contactless, vector-resolved readout for wearables, implantable bioelectronics, and microrobotics, yet strain-induced inverse magnetostriction disrupts anisotropy and compromises stability. Magnetoelasticity originates from spin–orbit coupling, orbital hybridization, and exchange interaction in ferromagnets, further intensified by nanoscale thin-films. Strain-decoupled strategies—low-magnetostriction alloys and stress-relaxation architectures—stabilize domain states and preserve sensitivity. Looking forward, multiscale predictive frameworks bridging electronic structure, micromagnetics, and finite-element mechanics offer robust design of strain-resilient, conformable devices. Spintronics ; Conformable matrix ; Bridging (networking) ; Magnetism ; Magnetostriction ; Nanoelectronics ; Ferromagnetism ; Anisotropy Multiferroics and related materials ; Magnetic properties of thin films ; Advanced Sensor and Energy Harvesting Materials
Authors: Iwo Słodczyk | A. M. Frisch | Xufei Fang | Inna M. Gitman | Fengxian Liu
Source: Journal of the American Ceramic Society (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

A Data‐Driven Quest for Room‐Temperature Bulk Plastically Deformable Ceramics ABSTRACT The growing number of ceramics exhibiting bulk plasticity at room temperature has renewed interest in revisiting plastic deformation and dislocation‐mediated mechanical and functional properties in these materials. In this work, a data‐driven approach is employed to identify the key parameters governing room‐temperature bulk plasticity in ceramics. The model integrates an existing dataset of 55 ceramic materials, including 38 plastically deformable and 17 brittle, and achieves accurate classification of bulk plasticity. The analysis reveals several key parameters essential for predicting bulk plasticity: (i) Poisson's ratio and Pugh's ratio as macroscopic indicators reflecting the balance between shear and volumetric deformation resistance, and (ii) Burgers vector, crystal structure and melting temperature as crystallographic descriptors associated with lattice geometry, slip resistance and thermal stability, and iii) Bader charge as a microscopic measure of bonding character. Together, these parameters define a multiscale descriptor space linking intrinsic materials properties to bulk room‐temperature plasticity in ceramics, bridging the gap between empirical ductility criteria and atomistic mechanisms of dislocation‐mediated plasticity. While preliminary, this study provides the first systematic, data‐driven mapping of the governing factors of ceramic plasticity. The resulting framework establishes a foundation for unifying experimental and computational studies through shared datasets and descriptors, fostering collective progress toward understanding and designing intrinsically ductile ceramics. Ceramic ; Plasticity ; Bridging (networking) ; Slip (aerodynamics) ; Crystal plasticity ; Ductility (Earth science) ; Lattice (music) ; Deformation (meteorology) ; Deformation mechanism Machine Learning in Materials Science ; Advanced ceramic materials synthesis ; Advanced materials and composites
Authors: Sam Daniel Fenny A | Prasanth Samykkannu | Yokesvaran Kalidasan | Ajithkumar S | S. Balaguru
Source: Springer Link (Chiba Institute of Technology) (article, 2026-03-03)
Field: Materials Science — Polymers and Plastics

A Lightweight Advanced Composite System: Polypropylene Fabric Reinforced Expandable Polystyrene Polymer matrix composite (PMCs) have the primary strengths of high specific strength, low density, and corrosion and abrasion resistance. Their performance is largely determined by the effectiveness of the transfer of loads between fiber reinforcement and polymer matrix. To produce a lightweight composite material, a polypropylene (PP) fabric was reinforced into an expandable polystyrene (EPS) matrix with gaseous softening and processing ingredient of gasoline. A composite was developed using the reinforcement in order to determine the effect of polypropylene reinforcement on the mechanical and physical behavior of an EPS-based matrix. The mechanical characterization tests such as tensile , flammability and hardness tests were performed in this research. It is found that besides increasing the surface hardness, the presence of polypropylene textiles also enhances the structural integrity, tensile responsiveness, as well as flame- resistance characteristics in the EPS matrix. The suggested work recognizes the potential of the PP-fabric-reinforced EPS composites as an example of a low-density material that can be used in the lightweight structural and insulating areas. Polypropylene ; Composite number ; Ultimate tensile strength ; Reinforcement ; Polystyrene ; Softening ; Polymer ; Tensile testing Flame retardant materials and properties ; Fiber-reinforced polymer composites ; Natural Fiber Reinforced Composites
Authors: Ved Sharma
Source: ChemRxiv (article, 2026-03-02)
Field: Materials Science — Polymers and Plastics

Sustainable Elastomer Development Using Computational Intelligence and Bio-Based Modification Techniques The transition toward environmentally responsible materials has intensified research on sustainable elastomers that combine high performance with reduced ecological impact.This study presents an integrated framework for elastomer development that merges computational intelligence with bio-based modification strategies.Machine learning algorithms were employed to model structure-property relationships and predict optimal formulations based on mechanical strength, elasticity, thermal stability, and biodegradability targets.Experimental validation was conducted using partially bio-derived polymers, natural fillers, and green crosslinking agents to replace conventional petroleum-based additives.Bio-based modifiers, including plant-derived plasticizers and lignocellulosic reinforcements, were incorporated to enhance flexibility and tensile performance while minimizing carbon footprint.Computational optimization significantly reduced trial-and-error experimentation by identifying synergistic interactions among polymer matrices, curing systems, and bio-additives.The resulting elastomer composites demonstrated improved sustainability metrics without compromising durability or processability.Life-cycle considerations indicated measurable reductions in energy consumption and greenhouse gas emissions compared with traditional synthetic elastomers.The findings highlight the potential of combining data-driven design with renewable material engineering to accelerate the development of next-generation elastomers suitable for automotive, medical, and industrial applications.This approach establishes a scalable pathway toward circular material innovation and responsible manufacturing practices. Computational intelligence ; Development (topology) ; Elastomer ; Expert system ; Applications of artificial intelligence Polymer composites and self-healing ; Material Selection and Properties ; Calcium Carbonate Crystallization and Inhibition
Authors: Kai Zhang | Yan Yan Shery Huang | Jiangxue Han | Zhangpeng Li | Jinqing Wang | Shengrong Yang
Source: Materials (article, 2026-03-10)
Field: Chemistry — Spectroscopy

Design and Sensing Applications of Eutectogels: A Review Deep eutectic solvent (DES), when used as the continuous phase of eutectogels, can significantly improve their electrical and mechanical properties due to its excellent conductivity, freeze resistance and chemical stability. The development of eutectogels effectively solves the key limitations of traditional hydrogels and organogels, such as low-temperature freezing, high-temperature volatilization, and organic solvent leakage. It also realizes the collaborative optimization of environmental friendliness and comprehensive performance, which makes it show broad application prospects in the field of flexible sensing. This review summarizes the design principles, material selection, sensing mechanisms, and flexible sensing applications of eutectogels. By examining the design of eutectogels, the selection of DES, and the synthesis of the gel network, it provides a theoretical basis for the development of eutectogel-based sensor devices. A detailed description of the sensing mechanism is provided to elucidate the signal generation and transition in eutectogels toward the purpose of the practical applications. Finally, the application prospects of eutectogels for high-performance sensors and detection devices are discussed. Additionally, we provide a theoretical support for their structural design, performance optimization, and practical application. Self-healing hydrogels ; Field (mathematics) ; Process (computing) ; Key (lock) ; Mechanism (biology) ; SIGNAL (programming language) ; Design methods ; Material Design Aerogels and thermal insulation ; Hydrogels: synthesis, properties, applications ; Polydiacetylene-based materials and applications
Authors: Igor D. Borges | Antônio S. N. Aguiar | Ademir J. Camargo | Hamilton B. Napolitano
Source: Frontiers in Chemical Engineering (article, 2026-01-09)
Field: Chemistry — Organic Chemistry

Biodiesel stabilization by dibrominated dimethoxybenzaldehydes: a comprehensive computational perspective The oxidative instability of biodiesel remains a critical barrier to its widespread adoption despite its advantages as renewable, biodegradable, and low-emission fuel. Antioxidant additives are an established strategy to suppress free radical chain reactions, yet their efficiency is strongly modulated by molecular structure and solvent environment. This is the first comparative density functional theory study of dibrominated dimethoxybenzaldehydes and standard phenolic antioxidants under biodiesel-relevant solvent conditions using the conductor-like polarizable continuum model. Frontier molecular orbitals, Fukui index, ionization potentials, spin density distributions, and natural bond orbital hyperconjugations were systematically analyzed across polar and nonpolar environments. The computational results suggest that bromination is associated with increased electronic softness and electron transfer potential, while also leading to changes in the stability of radical intermediates, especially in ortho-substituted derivatives. Among the dibrominated compounds, IB1 exhibits the most balanced combination of computed properties, whereas IB3, although highly reactive in silico , is predicted to form comparatively less stable radical species. Compared with commercial benchmarks, these halogenated systems constitute a distinct mechanistic class governed by polarization rather than hydroxyl-centered resonance. These computational findings provide guidance for the rational design of next-generation biodiesel stabilizers, pending future experimental validation. Density functional theory ; Biodiesel ; Solvent ; Solvent effects ; Polarizable continuum model ; Molecular dynamics ; Regioselectivity ; Antioxidant Free Radicals and Antioxidants ; Advanced Combustion Engine Technologies ; Biodiesel Production and Applications