jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mazhar Ali | Habib Ullah | Rajwali Khan | Noor Ul Islam | Ezzat Khan | Maaz Ahmad | Aziz Ullah | Ambreen Begum | Ghafar Ali | Yi Xie
Source: RSC Advances (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Unveiling the chemistry of polynuclear copper complexes: current synthetic strategies, properties and emerging applications Polynuclear copper complexes (PNCCs), featuring an intricate interplay of multiple copper (Cu) ions, represent a highly diverse and complex field of coordination chemistry. In this review, we cover the synthesis, characteristics, factors affecting structural diversity, and applications of PNCCs. The synthesis methods, including direct synthesis, template synthesis, self-assembly, coordination-driven self-assembly, supramolecular approach and solvothermal methods, are described in detail. Various strategies to make stable Cu(i) and Cu(ii) polynuclear networks and to control the nuclearity of PNCCs are documented in detail. The role of density functional theory (DFT) in the optimization of geometry and the prediction of the structure and reactivity of PNCCs is also explained. Physicochemical properties, including electronic, optical, geometrical, structural, and magnetic aspects, are discussed to highlight their fascinating chemistry. For the optimization of PNCC functionality, parameters such as the nature of the ligands and the coordination number of the Cu ions are explored. The potential biomedical applications of PNCCs, particularly due to their binding ability to DNA (opening new windows for cancer treatment) and magnetic properties (opening new avenues for applications in molecular electronics), are also discussed. Additionally, the roles of PNCCs in catalysis, the large-scale separation of C<sub>2</sub> hydrocarbons (C<sub>2</sub>H<sub>2</sub>) at the industrial level, and the development of new materials (such as vapochromic compounds for organic light-emitting diodes) are highlighted. Besides, their roles in electrochemical CO<sub>2</sub> reduction and H<sub>2</sub> production and as photosensitizers for photocatalytic systems of CO<sub>2</sub> reduction and H<sub>2</sub> production are explored. All these fields require further exploration for their optimized and practical applications, as discussed in this review. Supramolecular chemistry ; Copper ; Electrochemistry ; Reduction (mathematics) ; Coordination complex ; Density functional theory ; Cover (algebra) Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Cross-Coupling Reactions ; Asymmetric Hydrogenation and Catalysis
Authors: Mårten S. G. Ahlquist | C. Li
Source: Research Square (preprint, 2026-02-13)
Field: Chemistry — Inorganic Chemistry

MOFBuilder: Automated end-to-end modeling ofMOF dynamics for high-throughput screening Modular design ; Pipeline (software) ; Dynamics (music) ; Space (punctuation) ; Ranging ; System dynamics Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Qiang Wang | Kai Kong | Keying Han | Yuan Li | Yitong Liang | Xingshuai Lv | Thomas Frauenheim | Defeng Guo | Bin Wang
Source: Research Square (preprint, 2026-02-10)
Field: Materials Science — Materials Chemistry

Achieving Non-Degenerate Sliding Ferroelectricity via Band-Edge Pinning: A General Design Principle for Controllable Photocatalysis and Photovoltaics Ferroelectricity ; Photovoltaics ; Heterojunction ; Dipole ; Charge carrier ; Polarization (electrochemistry) ; Photocatalysis ; Exciton 2D Materials and Applications ; Electronic and Structural Properties of Oxides ; Advanced Sensor and Energy Harvesting Materials
Authors: Kedeng Wu | Yucheng Zhu | Yan Chen | Bizhu Zhang | Shuyu Liu | Xiaobin Deng | Yabei Wu | Liangliang Zhu | Hang Xiao
Source: ArXiv.org (article, 2026-03-14)
Field: Materials Science — Materials Chemistry

Generative Inverse Design of Cold Metals for Low-Power Electronics Cold metals are a class of metals with an intrinsic energy gap located close to the Fermi level, which enables cold-carrier injection for steep-slope transistors and is therefore promising for low-power electronic applications. High-throughput screening has revealed 252 three-dimensional (3D) cold metals in the Materials Project database, but database searches are inherently limited to known compounds. Here we present an inverse-design workflow that generates 3D cold metals using MatterGPT, a conditional autoregressive Transformer trained on SLICES, an invertible and symmetry-invariant crystal string representation. We curate a training set of 26,309 metallic structures labeled with energy above hull and a unified band-edge distance descriptor that merges p-type and n-type cold-metal characteristics to address severe label imbalance. Property-conditioned generation targeting thermodynamic stability and 50-500 meV band-edge distances produces 148,506 unique candidates; 92.1% are successfully reconstructed to 3D structures and down-selected by symmetry, uniqueness and novelty filters, followed by high-throughput DFT validation. We identify 257 cold metals verified as novel with respect to the Materials Project database, with gaps around the Fermi level spanning 50-500 meV. First-principles phonon, electronic-structure, and work-function calculations for representative candidates confirm dynamical stability and contact-relevant work functions. Our results demonstrate that SLICES-enabled generative transformers can expand the chemical space of cold metals beyond high-throughput screening, providing a route to low-power electronic materials discovery. Electronics ; Transformer ; Stability (learning theory) ; Generative grammar ; Inverse ; Workflow ; Fermi level ; Uniqueness Machine Learning in Materials Science ; Quantum many-body systems ; Topological Materials and Phenomena
Authors: Muhammed Nur Talha Kilic | Daniel Wines | Kamal Choudhary | Gupta | Youjia Li | Sayak Chakrabarty | Wei‐keng Liao | Choudhary Alok | Ankit Agrawal
Source: Digital Discovery (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Evaluating large language models for inverse semiconductor design Large Language Models (LLMs) can enable inverse materials discovery by generating text-encoded crystal structures from target properties. Inverse ; Language model ; Inverse problem ; Crystal (programming language) ; Natural language Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Block Copolymer Self-Assembly
Authors: Mohammad Amin Akhound | Tara M. Boland | Mikkel Ohm Sauer | Matthias Batzill | Moses Abraham Bokinala | Stela Canulescu | Yury Gogotsi | Hofmann, Philip | András Kis | Jiong Lu | Thomas Michely | Søren Raza | Wencai Ren | Joshua A. Robinson | Zdenek Sofer | Jing Teng | Søren Ulstrup | Meng ZHAO | Xiaoxu Zhao | Jens J. Mortensen | Thomas Olsen | Kristian S. Thygesen
Source: ArXiv.org (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Large-scale Integration of Experimental and Computational Data for 2D Materials The past decade has seen rapid growth in the number of experimentally realized two-dimensional (2D) materials with diverse chemical and physical properties. However, information on their crystal structure, synthesis routes, and measured or predicted properties, remains scattered across thousands of publications. Here we consolidate this fragmented knowledge by establishing X2DB - an open infrastructure that integrates experimental and computational data on 2D materials. Using extensive literature mining and direct community uploads, we identify 370 unique 2D materials that have been realized in monolayer or few-layer form, and link them to their digital counterparts in computational databases, enabling consistent ab initio characterization of their properties across monolayer, bilayer and bulk forms. We describe the structure and content of the database highlighting its support for community uploads, illustrate how it can be used to generate new scientific insight and introduce a hierarchical classification of the known set of 2D materials. Our work provides a foundation for the integration and cross-fertilization of experimental and theoretical knowledge, opening new avenues for data-driven, predictive synthesis of novel 2D materials. Set (abstract data type) ; Characterization (materials science) ; Experimental data ; Ab initio ; Work (physics) ; Foundation (evidence) 2D Materials and Applications ; Machine Learning in Materials Science ; Surface Chemistry and Catalysis
Authors: Qiong Wang | Tongran Lu | Deyue Jiang | Lili Deng | Yushu Wang | Jia Tian | Hui Huo | Haoyuan Cheng | Xiaodong Hu | Xiaodi Yang | Zhi‐Gang Qian | Fei Liu | Xiaojing Wang | Fuliang Chen
Source: Arabian Journal of Chemistry (article, 2026-02-13)
Field: Chemistry — Inorganic Chemistry

Polyethyleneimine-Folic acid modified manganese coordination polymer delivery platform for artemisinin in the treatment of non-small cell lung cancer Non-small cell lung cancer (NSCLC) is responsible for 85% of lung cancer cases and is still the primary cause of cancer-related deaths. Conventional treatments offer limited efficacy, necessitating novel therapeutic strategies to overcome drug resistance. This study isolated and characterized compound 1 from Artemisia annua , confirmed by nuclear magnetic resonance (NMR) and high-resonance electrospray ionization mass spectroscopy (HR-ESI-MS). To enhance its therapeutic potential, we developed PEI-FA@CP1@1, a manganese-based coordination polymer (CP1) encapsulating compound 1 , further modified with folic acid (FA) and polyethyleneimine (PEI). This targeted drug delivery system demonstrated effective NSCLC cell inhibition via apoptosis induction, providing a promising low-toxicity therapeutic approach. Additionally, AI-driven (Molecular Deep Q-Network) MolDQN screening identified potential anticancer compounds related to compound 1 , accelerating drug discovery and offering a new strategy for precision cancer therapy. Artemisinin ; Drug ; Drug delivery ; Lung cancer ; Targeted drug delivery ; Cancer ; Coordination polymer ; Apoptosis Metal-Organic Frameworks: Synthesis and Applications ; Lung Cancer Treatments and Mutations ; Metal complexes synthesis and properties
Authors: Sakshi Goel | Arti Kashyap
Source: arXiv (Cornell University) (article, 2026-03-04)
Field: Materials Science — Materials Chemistry

Machine learning assisted High-Throughput study of M$_4$X$_3$T$_x$ MXenes In this work, we employ a machine-learning-assisted high-throughput density functional theory framework to systematically investigate the stability, electronic structure, and magnetic ground states of 234 M$_4$X$_3$T$_x$ MXenes. The machine learning model predicts lattice parameters with up to 94% accuracy using a relatively small training dataset and significantly reduces structural optimization time in high-throughput calculations. Based on total energy and density-of-states analyses, we classify the magnetic nature of MXenes across different transition- metal compositions and surface terminations. Ti-, Zr-, Hf-, Nb-, and Ta-based MXenes are found to be non-magnetic metals for all functional groups considered, while Sc- and Y-based systems exhibit a range of behaviors including weak ferromagnetism and semiconducting character. V- and Fe-based MXenes are identified as antiferromagnetic metals, whereas Cr- and Mn-based MXenes yield 16 ferromagnetic systems with spin polarization ranging from 50% to 100%. MXenes ; Ferromagnetism ; Antiferromagnetism ; Density functional theory ; Lattice (music) ; Range (aeronautics) ; Spins MXene and MAX Phase Materials ; Heusler alloys: electronic and magnetic properties ; Machine Learning in Materials Science
Authors: Rumin Fu | Cairong Xiao | Zihao Du | Changhong Linghu | Yongdong Shi | Chuyang Xiang | Mingxin Wan | Guoxin Tan | Limin Lu | Chengyun Ning | K Jimmy Hsia
Source: Advanced Functional Materials (article, 2026-01-27)
Field: Materials Science — Surfaces, Coatings and Films

Switchable Supramolecular Adhesive by Tuning Interfacial Bonding and Modulus ABSTRACT High‐strength and reusable adhesives are essential for many applications but are often limited by the trade‐off between strength and detachability, as well as recyclability. Here, we introduce a high‐strength supramolecular adhesive with adhesion strengths exceeding 1 MPa (up to 4.65 MPa) and remarkable detachability, achieving a switchability ratio of up to 1800. These outstanding performances are enabled by synergistically tuning interfacial physical bonds and bulk modulus of a hydrogen‐bond‐and‐dipole‐dipole‐enriched polymer (HyDiP). In its dehydrated state, the adhesive exhibits high modulus (445 MPa) and exposes rich surface bonding groups, yielding robust adhesion on various surfaces. In its rehydrated state, the modulus decreases to 0.11 MPa and the physical bond density on the surface is significantly reduced, allowing easy detachment. Furthermore, the HyDiP adhesive is transparent when dehydrated, recyclable and removable, ideal for sustainable applications like adaptive grippers and superglue for heavy loads. Adhesive ; Modulus ; Adhesion ; Polymer ; Elastic modulus ; Supramolecular chemistry ; Supramolecular polymers ; Nanoindentation Polymer Surface Interaction Studies ; Polymer composites and self-healing ; Advanced Polymer Synthesis and Characterization
Authors: Salman Latif | Jiahao Ni | Ren-Jang Wu | Kaseb D. Alanazi | Basmah H. Alshammari | Amir Al-Ahmed | Abdulaziz M. Alanazi
Source: Arabian Journal of Chemistry (article, 2026-03-16)
Field: Materials Science — Materials Chemistry

Pt decorated Cu₂O nanocomposite to detect ppb level Ozone concentration This study reports the synthesis, characterization, and ozone-sensing performance of platinum (Pt)-decorated cuprous oxide (Cu₂O) nanomaterials at room temperature. Structural and optical analysis confirmed the uniform distribution of Pt nanoparticles (∼4.5 nm) on Cu₂O nanocubes, which effectively reduced the material’s optical bandgap from 2.26 eV to 2.05 eV and facilitated charge transfer. Among various Pt loadings, the 1 wt% Pt/Cu₂O composite exhibited optimal performance, delivering a sensor response of 12.21 to 1 ppm ozone and a low detection limit of 32.8 ppb—over an order of magnitude improvement compared to pristine Cu₂O. The composite also demonstrated excellent long-term stability over 25 days and a reliable, linear response across a range of ozone concentrations. These results indicate that controlled Pt decoration enhances sensitivity by optimizing the trade-off between surface reactivity and electrical conductivity, positioning the 1 wt% Pt/Cu₂O composite as a promising, cost-effective material for ambient ozone monitoring. Ozone ; Nanocomposite ; Detection limit ; Nanomaterials ; Composite number ; Platinum ; Nanoparticle ; Platinum nanoparticles Copper-based nanomaterials and applications ; Gas Sensing Nanomaterials and Sensors ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: T. Hussain | Muhammad Moeen Razzaq | Muhammad Mujtaba | Nida Haneef | Muhammad Usama bin Ubaid | Aasia Perveen
Source: Research Square (preprint, 2026-01-28)
Field: Materials Science — Materials Chemistry

Controlling ZnO Nanoparticle Morphology and Photocatalytic Degradation of Methylene Blue through Solvothermal Parameters Nanorod ; Photocatalysis ; Nanomaterials ; Nanoparticle ; Zinc ; Methylene blue ; Degradation (telecommunications) ; Solvothermal synthesis ; Solvent ZnO doping and properties ; Magnesium Oxide Properties and Applications ; Ga2O3 and related materials
Authors: Shundong Cai | Mengdie Li | S P Wang | Xiaofei Wen | Gang Liu | C.H. Chu
Source: Nano-Micro Letters (article, 2026-04-07)
Field: Materials Science — Materials Chemistry

Metal–Organic Framework Nanozymes: From Rational Design and Synthesis to Biomedical Applications Metal-organic framework (MOF) nanozymes have recently demonstrated considerable potential for biomedical applications. The catalytic activity of MOF nanozymes is primarily determined by the coordination of metal ions and organic ligands. Additionally, optimizing the morphology and pore size enhances the catalytic efficiency. However, a systematic framework bridging structural features to functional performance remains limited. To guide rational design, this review systematically analyzes how the selection of metal ions and organic ligands, as well as morphology, influences the catalytic activity of MOF nanozymes. The advantages and limitations of different synthesis methods are also summarized. Through concrete case studies, this review introduces major biomedical applications of MOF nanozymes, with a focus on their underlying catalytic mechanisms. Finally, key challenges confronting MOF nanozymes are critically analyzed, and future research directions are proposed. Rational design ; Bridging (networking) ; Metal-organic framework ; Selection (genetic algorithm) ; Key (lock) Advanced Nanomaterials in Catalysis ; Metal-Organic Frameworks: Synthesis and Applications ; Nanoplatforms for cancer theranostics
Authors: Marco Anselmi | Greg Slabaugh | Rachel Crespo-Otero | Devis Di Tommaso
Source: Journal of Materials Chemistry A (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Accelerating discovery through integration: a DFT validated machine learning framework for screening MOF photocatalysts An ML-DFT workflow rapidly screens MOF photocatalysts for CO 2 reduction: MGT predictions pre-filter candidates, cutting compute time from weeks to hours while retaining accuracy. Workflow ; Work (physics) ; Bayesian optimization ; Key (lock) Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Advanced Photocatalysis Techniques
Authors: Mir Waqas Alam | K. Radhakrishnan | P. Saravanan | Jothi Vinoth Kumar | Mohamad M. Ahmad | Shima Sadaf | Sajid Ali Ansari | M. Sherlin Nivetha
Source: Journal of Food Process Engineering (article, 2026-01-29)
Field: Materials Science — Materials Chemistry

Carbon Quantum Dots in Food and Environmental Safety: Advances in Sensing Technologies for Contaminant Detections ABSTRACT Recent developments in carbon quantum dot (CQD)‐based detection technologies, with a focus on applications in food and environmental safety. CQDs, an emerging nanomaterial, are widely used to detect pollutants such as heavy metals, pesticides, microbial contaminants, and organic pollutants. The tremendous optical properties, biocompatibility, low toxicity, and tunable surface functionality of CQDs make them suitable for various real‐time monitoring. It also discusses the role of CQD‐based sensors in detecting contaminants in complex matrices, such as food and water, as well as in detecting contaminants using fluorescence, electrochemical, and upconversion emission methods. These sensors can address current field tasks, including expanding the detection field, improving cost‐effectiveness, and increasing accuracy. In addition, the synthesis of novel materials and the development of advanced, targeted sensors by blending CQDs with other nanomaterials are expected to enhance food safety control and risk assessment for environmental protection. Quantum dot ; Photon upconversion ; Carbon quantum dots ; Carbon fibers ; Pollutant ; Nanomaterials ; Contamination Carbon and Quantum Dots Applications ; Melamine detection and toxicity ; Advanced Nanomaterials in Catalysis
Authors: Frederic Gibou | Ron Fedkiw | Russel E Caflisch | Stanley Osher
Source: Modelling and Simulation in Materials Science and Engineering (article, 2026-01-08)
Field: Materials Science — Materials Chemistry

A review of level-set modeling in epitaxial growth and alloys solidification Abstract Level-set methods provide a powerful computational framework for simulating free boundary problems in materials science. This paper presents a unified perspective on their application to two distinct phenomena: multicomponent alloy solidification and epitaxial island growth. Although these problems differ significantly in physical mechanisms and characteristic length scales, they can both be effectively addressed within the level-set framework, highlighting the versatility of the method across diverse applications. We outline the mathematical formulations and highlight computational advances and common features across applications. This overview highlights the role of level-set methods as a foundational tool in predictive materials modeling. Perspective (graphical) ; Epitaxy ; Alloy ; Boundary (topology) ; Boundary value problem Solidification and crystal growth phenomena ; High Temperature Alloys and Creep ; Advanced Numerical Methods in Computational Mathematics
Authors: V.V. Lysko | O.Yu. Mykytiuk
Source: Journal of Thermoelectricity (article, 2026-03-31)
Field: Chemistry — Physical and Theoretical Chemistry

Application of Microcalorimetry in Materials Science This review article discusses the practical use of calorimetric methods in materials science, in particular for studying phase transitions, determining heat capacity and thermal properties, investigating defects and structural changes, studying polymers, biomaterials, surface phenomena, etc. The application of microcalorimetry for monitoring explosives and pyrotechnics is highlighted. Isothermal microcalorimetry ; Pyrotechnics ; Phase (matter) ; Explosive material ; Energetic material ; Thermal thermodynamics and calorimetric analyses ; Chemical Thermodynamics and Molecular Structure ; Thermal and Kinetic Analysis
Authors: Li‐Tang Chi | Chia‐Hui Chuang | Xiang‐Lin Zhuang | Hao Wang | Ki Jin Nam | Heng‐Yu Chi | J. W. LEE | Y. C. Lin | Dun‐Yen Kang
Source: Advanced Materials Technologies (article, 2026-02-06)
Field: Chemistry — Inorganic Chemistry

Mixed‐Linker‐Directed Seed‐Free Growth of CO <sub>2</sub> ‐Selective MOF‐303 Membranes ABSTRACT Realizing metal‐organic framework (MOF) membranes for industrial gas separations hinges on scalable routes to dense, low‐defect layers. We report a mixed‐linker, seed‐layer‐free strategy for the one‐step growth of aluminum MOF‐303 membranes directly on porous α ‐alumina supports. Partial substitution of 3,5‐pyrazoledicarboxylic acid (H 3 PDC) with 2,5‐furandicarboxylic acid (FDCA) accelerates interfacial nucleation and promotes continuous membrane formation, obviating the conventional seeding step required for MOF‐303. Structural and spectroscopic analyses confirm uniform FDCA incorporation without perturbing the intrinsic framework chemistry. The resulting mixed‐linker membranes, exemplified by MOF‐303(P7F3) and MOF‐303(P6F4), deliver outstanding CO 2 separations: for MOF‐303(P6F4), CO 2 /N 2 separation factors reach 170 and 236 at 20% and 50% CO 2 feeds, respectively; CO 2 /CH 4 separation factors reach 431 and 393 under the same conditions, surpassing the 2019 polymeric‐membrane upper bound. Molecular simulations also indicate that FDCA incorporation leaves intrinsic adsorption and diffusivity largely unchanged, attributing the observed performance gains to improved membrane morphology and grain‐boundary suppression arising from the mixed‐linker‐directed growth. This simple, versatile route enables dense, high‐selectivity MOF‐303 membranes without seeding and is readily extendable to MOF systems where conventional in situ synthesis fails to yield defect‐minimized membranes. Membrane ; Seeding ; Nucleation ; Yield (engineering) ; Adsorption ; Porosity Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Membrane Separation and Gas Transport