jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Salomé Coppens | Dea Gogishvili | Valentina Faustinelli | Emanuele Scollo | Christopher Hopley | Sanne Abeln | Paul A. Dalby | Heidi Goenaga‐Infante | Luise Luckau | Jérôme Vialaret | Sylvain Lehmann | Christophe Hirtz | Eva Illes‐Toth
Source: ACS Chemical Neuroscience (article, 2025-01-02)
Field: Chemistry — Spectroscopy

Neurofilament Light Chain under the Lens of Structural Mass Spectrometry Neurofilament light chain (NfL) is an early nonspecific biomarker in neurodegenerative diseases and traumatic brain injury, indicating axonal damage. This work describes the detailed structural characterization of a selected primary calibrator with the potential to be used in future reference measurement procedure (RMP) development for the accurate quantification of NfL. As a part of the described workflow, the sequence, higher-order structure as well as solvent accessibility, and hydrogen-bonding profile were assessed under three different conditions in KPBS, artificial cerebrospinal fluid, and artificial cerebrospinal fluid in the presence of human serum albumin. The results revealed that NfL is a structurally heterogeneous protein, eliciting a large conformational flexibility. Its structural ensemble changed when it was diluted with an aqueous buffer versus a surrogate matrix, artificial cerebrospinal fluid (aCSF), and/or aCSF with human serum albumin. Various regions of protection and deprotection in the protein head, central helical, and tail domains that experienced altered solvent accessibility and conformational changes caused by different solvent conditions were identified. Moreover, interfacial residues, which may play a role in a potential direct interaction between NfL and human serum albumin, emerged from hydrogen-deuterium exchange mass spectrometry (HDX-MS). These data pinpointed distinct regions of the protein that may participate in such an interaction. Overall, critical quality attributes of a potential primary calibrator for NfL measurements are provided. These findings will ultimately inform ongoing biochemical and clinical assay development procedures and manufacturing practices, giving careful consideration during sample handling and method development. Mass spectrometry ; Lens (geology) ; Chemistry ; Neurofilament ; Chromatography ; Physics ; Medicine ; Optics ; Pathology ; Immunohistochemistry Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics ; Metabolomics and Mass Spectrometry Studies
Authors: Mona E. Arnold | Robert Toews | Lars Schneider | Jonas Schmid | Miftahussurur Hamidi Putra | Michael Busch | Axel Groß | Felix Deschler | Andreas Köhn | Alexander J. C. Kuehne
Source: Advanced Optical Materials (article, 2025-04-21)
Field: Chemistry — Physical and Theoretical Chemistry

The Impact of Donor‐Orientation on the Emission Properties of Chlorinated Trityl Radicals Abstract Chlorinated trityl radicals functionalized with electron‐donating groups are promising red‐emitting materials for optoelectronic and spintronic applications, overcoming the spin‐statistical limit of conventional emitters. Donor functionalization induces charge transfer character, enhancing photoluminescence quantum yield, which depends on the donor strength and its orientation. However, donor‐functionalized tris(trichlorophenyl)methyl radicals often show lower quantum yield than their perchlorinated derivatives, likely due to weaker donor‐acceptor electronic coupling and enhanced non‐radiative decay. A novel trityl derivative is presented with two additional chlorines that restrict the orientation of the donor to a nearly perpendicular arrangement toward the trityl plane, minimizing vibronic coupling and non‐radiative losses. Spectroscopic and computational studies reveal that this steric constraint improves the photoluminescence quantum yield compared to the tris(trichlorophenyl)methyl analogs. These findings highlight the potential of donor‐acceptor decoupling to enable efficient, redshifted emission, offering a design strategy for high‐performance radical emitters. Materials science ; Radical ; Orientation (vector space) ; Photochemistry ; Aggregation-induced emission ; Organic chemistry ; Optics ; Chemistry ; Physics ; Geometry Photochemistry and Electron Transfer Studies ; Organic Light-Emitting Diodes Research ; Luminescence and Fluorescent Materials
Authors: Johannes Gedeon | Izzatjon Allayarov | Antonio Calà Lesina | Emadeldeen Hassan
Source: IEEE Transactions on Antennas and Propagation (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Time-Domain Topology Optimization of Power Dissipation in Dispersive Dielectric and Plasmonic Nanostructures This article presents a density-based topology optimization scheme for locally optimizing the electric power dissipation in nanostructures made of lossy dispersive materials. We use the complex-conjugate pole-residue (CCPR) model, which can accurately model any linear materials’ dispersion without limiting them to specific material classes. Based on the CCPR model, we introduce a time-domain measure of the electric power dissipation in arbitrary dispersive media. The CCPR model is incorporated via auxiliary differential equations (ADE) into Maxwell’s equations in the time domain, and we formulate a gradient-based topology optimization problem to optimize the dissipation over a broad frequency spectrum. To estimate the objective function gradient, we use the adjoint field method, and explain the discretization and integration of the adjoint system into the finite-difference time-domain (FDTD) framework. Our method is demonstrated using the example of topology-optimized spherical nanoparticles made of Gold and Silicon with an enhanced absorption efficiency in the visible-ultraviolet spectral range. In this context, a detailed analysis of the challenges of topology optimization of plasmonic materials associated with a density-based approach is given. Our method offers efficient broadband optimization of power dissipation in dispersive media. Plasmon ; Dielectric ; Dissipation ; Topology (electrical circuits) ; Materials science ; Topology optimization ; Power (physics) ; Nanostructure ; Optoelectronics ; Dissipation factor ; Time domain ; Physics ; Computer science ; Electrical engineering ; Nanotechnology ; Engineering ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Plasmonic and Surface Plasmon Research
Authors: Taoufiq Bouzid | Abdelali Grich | Aicha Naboulsi | Hicham Yazid | Ali Elbasraoui | Mamoune El Himri | Abdelmajid Regti | Mohammadine El Haddad
Source: Journal of Molecular Structure (article, 2025-05-19)
Field: Chemistry — Spectroscopy

Investigating the surface structure effects of dual polymer coatings on eriochrome black T adsorption: A DFT and artificial intelligence approach based on ANN modeling Chemistry ; Eriochrome Black T ; Adsorption ; Dual (grammatical number) ; Artificial neural network ; Polymer ; Chemical engineering ; Physical chemistry ; Artificial intelligence ; Organic chemistry Adsorption, diffusion, and thermodynamic properties of materials ; Water Quality Monitoring and Analysis
Authors: Tri Nguyen | Sherif Abdulkader Tawfik | Truyen Tran | Sunil Gupta | Santu Rana | Svetha Venkatesh
Source: Materials Horizons (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

The search for superionic solid-state electrolytes using a physics-informed generative model The discovery of superionic solid-state electrolytes for cation batteries is currently limited by the range of materials available in online materials databases. Generative artificial intelligence approaches have recently been applied to overcome this limitation and explore unknown stoichiometries and structures, but efficiently generating candidates that satisfy strict stability criteria remains challenging. Here we introduce a physics-informed hierarchical generative framework that leverages symmetry-aware crystallographic principles to systematically explore molecular configurations, lattice parameters, and bonding environments. Our approach integrates empirical physical constraints and reinforcement learning utilizing a hierarchical state representation to generate chemically valid and structurally stable candidates. We propose symmetry-aware hierarchical architecture for flow-based traversal with density (SHAFT-density) that ensures efficient exploration of the material search space, prioritizing low formation energy, molecular packing optimized for stability and conductivity, and enhanced electrochemical properties. We discovered new binary and ternary metastable phases, of which we find highly conductive LiBr, LiCl, Li<sub>2</sub>IBr, and Li<sub>3</sub>CBr<sub>2</sub>. These materials can either function as solid-state electrolyte materials or be part of solid-state electrolyte mixtures. Our results demonstrate the model's capability to identify stable, diverse, and potentially superionic compounds, offering promising candidates for developing next-generation solid-state electrolytes with improved characteristics. Electrolyte ; Generative grammar ; Materials science ; Generative model ; Fast ion conductor ; Solid-state ; State (computer science) ; Chemical physics ; Nanotechnology ; Statistical physics ; Theoretical physics ; Engineering physics ; Physics ; Computer science ; Quantum mechanics ; Artificial intelligence ; Electrode ; Algorithm Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Solid-state spectroscopy and crystallography
Authors: Kota Matsumoto | Eisuke Miyoshi | M. Umezawa | Masato Ito | Yoshiki Mori | Kaoruko Akiba | Nobuhiro Kitahara | Kenichi Yaguchi | Akinori Yamanaka
Source: Computational Materials Science (article, 2025-02-12)
Field: Materials Science — Materials Chemistry

Data-driven phase-field analysis of static recrystallization in an aluminum alloy Alloy ; Recrystallization (geology) ; Materials science ; Aluminium ; Metallurgy ; Phase (matter) ; Field (mathematics) ; Chemistry ; Geology Solidification and crystal growth phenomena ; Metallurgy and Material Forming ; Microstructure and Mechanical Properties of Steels
Authors: Rafael G. Uceda | Alfonso Gijón | Sandra Míguez‐Lago | Carlos M. Cruz | Luı́s Álvarez de Cienfuegos | Antonio J. Mota | D. Miguel | Juan M. Cuerva
Source: ChemPhotoChem (article, 2025-05-01)
Field: Chemistry — Spectroscopy

Chiral Intelligence: The Artificial Intelligence‐Driven Future of Chiroptical Properties Chirality plays a fundamental role in molecular sciences, with chiroptical properties offering valuable insights into the interaction between chiral molecules and polarized light. Designing chiral materials with enhanced properties requires a deep understanding of underlying physical principles, often revealed only through large datasets. In this context, artificial intelligence (AI) emerges as a powerful tool for accelerating discovery and optimization, efficiently exploring vast chemical spaces. This work explores the synergy between AI and chiroptical properties, highlighting recent advances in data‐driven approaches for circular dichroism and circularly polarized luminescence. AI has demonstrated its ability to predict these phenomena accurately while uncovering structure–property relationships that can remain hidden under traditional methods. Various strategies are examined for integrating AI into chiroptical properties and the challenges and future directions of this field are discussed. In conclusion, combining chemical intuition with AI offers great potential for the rational design of next‐generation chiral materials. This integration not only promises to unlock novel compounds with enhanced chiroptical properties but also provides new opportunities to deepen our understanding of chiroptical phenomena. Artificial intelligence ; Cognitive science ; Computer science ; Nanotechnology ; Materials science ; Psychology Molecular spectroscopy and chirality ; Photoreceptor and optogenetics research ; Advanced NMR Techniques and Applications
Authors: Wenda Zhang | Han Zhao | Yong Liu | Zhi‐Guo Gu
Source: Coordination Chemistry Reviews (article, 2025-05-30)
Field: Chemistry — Inorganic Chemistry

Open hollow metal-organic frameworks: Synthesis strategies, applications and challenges Chemistry ; Metal-organic framework ; Nanotechnology ; Combinatorial chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Covalent Organic Framework Applications
Authors: Zhendong Li | Xinxin Wang | Zichao Guo | Kexin Zeng | Subramanian Sundarrajan | Xinwei Li | Seeram Ramakrishna
Source: Virtual and Physical Prototyping (article, 2025-10-12)
Field: Materials Science — Biomaterials

Process engineering and manufacturing technologies for structural control and multifunctionality in electrospun nanofibres Electrospinning has evolved into a mature yet continually expanding technique for assembling fibrous architectures with dimensions spanning the micro – to nanometre range. Over the past two decades, process engineering and manufacturing technologies, ranging from solution formulation and field control to collector design, novel spinning modes, and integration with 4D printing have greatly extended its scope, enabling high precision in regulating fibre diameter, alignment, architecture, and ultimately multifunctionality. This work provides a coherent synthesis of these developments, tracing the interplay between materials chemistry, process physics, and structural outcomes. We examine established and emerging strategies for integrating electrospinning with additive manufacturing and data-driven process optimisation, thereby opening new avenues for multifunctional materials. Applications are considered across a spectrum that includes biomedical scaffolds, energy devices, environmental protection systems, and responsive textiles, with emphasis on how processing decisions shape structural and functional performance. Finally, we identify persistent bottlenecks in scalability, reproducibility, and sustainability, and outline prospective directions in which green chemistry, intelligent control systems, and hybrid manufacturing are expected to converge, positioning electrospun nanofibres – with enhanced structural control and multifunctionality – as a cornerstone of next-generation engineered materials. Spinning ; Electrospinning ; 3D printing ; Process (computing) ; Process control ; Tracing ; Nanometre Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Conducting polymers and applications
Authors: Bin Zheng | Zhuojian Lu | Shangchen Wang | Lichao Liu | Mingjun Ao | You Zhou | Guojing Tang | Ruhai Wang | Yuanhao Liu | Hantian Zhang | Yifan Meng | Jun Qiu | Feng Tian | Ziyi Wang | Ruijie Liu | Yuelong Xiao | Yutong Liu | Ziling Wang | Yifen Huang | Yajun Jiang | Peng Zheng
Source: Nature Chemistry (article, 2025-11-18)
Field: Materials Science — Biomaterials

Computational design of superstable proteins through maximized hydrogen bonding Hydrogen bonds are fundamental chemical interactions that stabilize protein structures, particularly in β sheets, enabling resistance to mechanical stress and environmental extremes. Here, inspired by natural mechanostable proteins with shearing hydrogen bonds, such as titin and silk fibroin, we de novo designed superstable proteins by maximizing hydrogen-bond networks within force-bearing β strands. Using a computational framework combining artificial intelligence-guided structure and sequence design with all-atom molecular dynamics MD simulations, we systematically expanded protein architecture, increasing the number of backbone hydrogen bonds from 4 to 33. The resulting proteins exhibited unfolding forces exceeding 1,000 pN, about 400% stronger than the natural titin immunoglobulin domain, and retained structural integrity after exposure to 150 °C. This molecular-level stability translated directly to macroscopic properties, as demonstrated by the formation of thermally stable hydrogels. Our work introduces a scalable and efficient computational strategy for engineering robust proteins, offering a generalizable approach for the rational design of resilient protein systems for extreme environments. Titin ; Hydrogen bond ; Molecular dynamics ; Protein engineering ; Protein design ; Rational design ; Protein structure ; Protein stability ; Structural stability ; Protein dynamics Silk-based biomaterials and applications ; Bacteriophages and microbial interactions ; Force Microscopy Techniques and Applications
Authors: Mengke You | Hong Liu | Chunpu Li
Source: JACS Au (article, 2025-11-12)
Field: Chemistry — Organic Chemistry

The Current Toolbox for Covalent Inhibitors: From Hit Identification to Drug Discovery Covalent modification of therapeutic targets has emerged as a powerful platform for creating clinical drugs and chemical probes. Covalent drugs have evolved from serendipitous discoveries to rationally designed therapeutics, driven by advances in electrophile-first screening technologies. This perspective takes stock of alternative technologies currently available in laboratories and industry that collectively enable targeted covalent inhibitor development across historically "undruggable" targets. We highlight five such technologies: activity-based protein profiling (ABPP), provides functional proteomic mapping to identify ligandable residues; covalent tethering, exploits dynamic chemistry to capture transient pockets; covalent DNA-encoded libraries, leverages trillion-member libraries for multiresidue targeting; phage/mRNA display, which facilitates evolution of covalent macrocyclic peptides; and sulfur-(VI) fluoride exchange (SuFEx), engages residues beyond cysteine. Integration of these approaches with chemoproteomics and artificial intelligence accelerates the discovery of covalent inhibitors with enhanced selectivity and reduced off-target risks. This technological convergence establishes a new paradigm for precision covalent therapeutics, offering innovative solutions to overcome drug resistance and target challenging protein interfaces. Covalent bond ; Drug discovery ; Toolbox ; Chemical biology ; Identification (biology) ; Drug target Click Chemistry and Applications ; Biochemical and Structural Characterization ; Chemical Synthesis and Analysis
Authors: Yuzhuo Wang | Wan Zhang | Akmaral Karamergenova | Leteng Lin
Source: Materials Today Communications (review, 2025-09-17)
Field: Materials Science — Biomaterials

Fabrication and application of polycaprolactone-based composite scaffolds in tissue engineering: A review Poly(ε-caprolactone) (PCL) is a widely used biodegradable polymer in tissue engineering due to its excellent biocompatibility, processability, and mechanical tunability. However, its clinical translation is limited by inherent drawbacks such as hydrophobicity, low bioactivity, and slow degradation. This review aims to provide a comprehensive and critical evaluation of PCL-based scaffolds, focusing on fabrication strategies, composite modifications, and their performance across diverse tissue engineering applications. Four primary fabrication techniques—electrospinning, 3D printing, freeze-drying, and phase separation—are systematically compared in terms of structural characteristics, mechanical performance, scalability, and biological functionality. Various material modifications involving natural polymers (e.g., gelatin, chitosan, collagen), synthetic polymers (e.g., Polylactic acid, Poly(lactic-co-glycolic acid), Polyethylene glycol) and inorganic or conductive additives (e.g., hydroxyapatite, metal oxides, carbon nanomaterials) are discussed for their roles in enhancing scaffold bioactivity, degradation rate, and tissue-specific functionality. Application-specific insights are provided for PCL-based scaffolds in regenerating bone, skin, nerve, ligament, cartilage, dental and periodontal tissues, as well as emerging roles in cardiac, pulmonary, and hepatic repair. The review also highlights recent advances in intelligent scaffold design using computational modelling and artificial intelligence, and assesses sustainability, sterilisation, and regulatory challenges for clinical translation. Despite current limitations, PCL-based scaffolds show great promise for personalised and functional tissue regeneration. Future research should focus on integrating multiscale fabrication, responsive materials, green manufacturing processes, and standardised evaluation protocols. Interdisciplinary collaboration will be essential to overcome translational barriers and realise the clinical potential of PCL-based biomaterials in regenerative medicine. • Four major scaffold fabrication methods are systematically compared and evaluated. • Composite strategies enhance bioactivity and mechanics of PCL scaffolds. • Application-specific scaffold strategies for various tissues are critically summarised. • Integration of AI and modelling accelerates scaffold design and performance tuning. • Challenges in sterilisation, scalability, and sustainability for clinical use are discussed. Scaffold ; Fabrication ; Tissue engineering ; Composite number ; Polymer ; Regenerative medicine Electrospun Nanofibers in Biomedical Applications ; Bone Tissue Engineering Materials ; Additive Manufacturing and 3D Printing Technologies
Authors: Jinfeng Li | H. Li
Source:  (article, 2025-02-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Liquid Crystal Technology for IoT and Beyond: Advancements and Future Directions This article presents a focused review of past performance, recent advancements and emerging trends in liquid crystal-based reconfigurable millimeter-wave components and systems, with applications extending to the Internet of Things (IoT) and beyond. Two primary developmental trajectories are highlighted: the use of phasereconfigurable delay lines in passively fed phased-array antennas and reconfigurable intelligent surfaces (RIS) to enable adaptive communication, and the implementation of passive tunable filtering for dynamic spectrum allocation. These trends underscore an ongoing shift towards adaptable, intelligent, and energy-efficient hardware solutions, facilitating the next generation of smart, interconnected devices for IoT and AIoT (artificial intelligence of things). Furthermore, the potential of liquid crystal-based multi-modal sensing and communication is proposed and investigated, with a focus on improving power efficiency and enhancing security to support the development of future IoT ecosystems. Internet of Things ; Computer science ; Blockchain ; Data science ; Internet privacy ; Computer security Liquid Crystal Research Advancements ; Advanced Materials and Mechanics ; Optical Wireless Communication Technologies