jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tianyu Zhao | Jie Li | Nian‐Ke Chen | Bai‐Qian Wang | Xiaomin Cheng | Shun‐Yao Qin | Hong Ding | Shengbai Zhang | Hong‐Bo Sun | Xiangshui Miao | Xian‐Bin Li
Source: Advanced Functional Materials (article, 2026-02-04)
Field: Materials Science — Materials Chemistry

Heterogeneous Coherent Interface Enabling Nonstochastic Crystallization for Phase‐Change Memory ABSTRACT Phase‐change memory (PCM) displays great promise for the storage‐class memory (SCM) technology due to its combination of fast speed of dynamic random‐access memory and nonvolatility of Flash. Yet, to meet the high industrial requirement of write/erase speed for the SCM application, robust strategies for further accelerating phase transition, particularly from amorphous to crystalline PCM materials, are urgently needed. In this work, we propose a unique strategy of coherent‐interface induced ultrafast crystallization in PCM materials. Employing rock‐salt YAs/Ge 2 Sb 2 Te 5 as a prototype, systematic first‐principles molecular dynamics demonstrate that rapid nonstochastic crystallization behaviors can be achieved by the rock‐salt‐lattice‐matching and high‐temperature‐resistant heterogeneous interface attached to the popular PCM material Ge 2 Sb 2 Te 5 (GST). Further experiment shows that the YAs‐incorporated GST device has a faster SET process compared with the pure GST device. Finally, to extend the strategy in the family of inorganic materials, high‐throughput screening from over 150 000 structures discovers as many as 71 candidates for coherent interfaces with PCM GST. The present study establishes a promising strategy to overcome the speed bottleneck of PCM through atomic‐scale interface design for future storage‐class memory implementation. Bottleneck ; Crystallization ; Interface (matter) ; Phase-change memory ; Germanium compounds ; Process (computing) ; Ultrashort pulse Phase-change materials and chalcogenides ; Chemical and Physical Properties of Materials ; Advanced Memory and Neural Computing
Authors: Meng Du | Angelica Rodriguez | Matthew Z. Lin | Haoyuan Chen
Source: Journal of Chemical Information and Modeling (article, 2026-01-24)
Field: Chemistry — Inorganic Chemistry

A Transferable Force Field for Simulating Adsorption in Metal–Organic Frameworks with Open Metal Sites Based on the 12–6–4 Lennard-Jones Potential Metal-organic frameworks (MOFs) that contain coordinatively unsaturated open metal sites (OMSs) provide strong host-guest interactions, making them promising sorbents for low-concentration gas adsorption applications such as direct air capture and atmospheric water harvesting. However, accurately modeling host-guest interactions involving OMSs remains challenging for classical force fields (FFs) based on the 12-6 Lennard-Jones (LJ) potential, as the polarization effect of the guest molecule induced by the positively charged OMS is not considered. Here, we introduce an FF based on the 12-6-4 LJ potential, which incorporates charge-induced dipole interactions and is parametrized against a diverse set of host-guest potential energy surfaces (PESs) obtained from density functional theory (DFT). The resulting FF, trained on a generic trimetallic cluster, performs well in both host-guest binding energetics and gas adsorption isotherms across different OMS-containing MOFs, including MOF-74 series and Cu-BTC. These results highlight the excellent transferability of our approach and its potential to enhance the accuracy and robustness of high-throughput MOF discovery workflows, particularly for gas adsorption and separation in large and diverse MOF databases. Transferability ; Adsorption ; Dipole ; Force field (fiction) ; Robustness (evolution) ; Molecule ; Density functional theory ; Polarization (electrochemistry) Metal-Organic Frameworks: Synthesis and Applications ; Advanced Chemical Physics Studies ; Supramolecular Chemistry and Complexes
Authors: Yun‐Cheng Luo | Yi‐Hao Xu | Xingang Zhang
Source: Chinese Journal of Chemistry (article, 2026-01-21)
Field: Chemistry — Organic Chemistry

Kinetic Influence of Electrophile‐Alkene Exchange of Nickel‐Alkene Complexes in Oxidative Addition <sup>†</sup> Comprehensive Summary The oxidative addition of electrophiles to transition metals is a fundamental step in transition‐metal‐mediated cross‐coupling reactions. Although the mechanism of transition‐metal‐enabled C–X bond cleavage has garnered significant attention due to its impact on reaction selectivity and reactivity, the preceding association step between the electrophile and metal has long been underappreciated, particularly with regard to its kinetic effects. Here, we report and validate an associative electrophile‐alkene exchange (E A A) strategy using nickel(0)‐alkene complexes. This approach shifts the rate‐determining step from C–X bond cleavage to electrophile‐alkene exchange. By doing so, it enables selective recognition of C(sp 2 )‐electrophiles based on their coordination kinetics rather than bond dissociation energies, thereby facilitating the selective oxidative addition of C–F bonds over more reactive C–Cl, C–Br, and C–I bonds. Mechanistic studies reveal that the selective coordination of C(sp 2 )‐electrophiles depends on the coordination propensity of the pre‐coordinated alkene and the supporting ligand on the nickel(0) complex. This strategy not only complements the traditional reactivity trends of C–X bonds in oxidative addition but also provides a foundation for the rational design of catalysts and the development of more efficient chemical processes. Electrophile ; Oxidative addition ; Catalysis ; Bond cleavage ; Alkene ; Reactivity (psychology) ; Selectivity ; Ligand (biochemistry) ; Reductive elimination ; Dissociation (chemistry) Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Catalytic Alkyne Reactions
Authors: Zhangke Yang | Zhaoxu Meng
Source: Polymers (article, 2026-02-10)
Field: Materials Science — Polymers and Plastics

A Review of Computational Modeling of Polymer Composites and Nanocomposites Polymer composites and nanocomposites have become indispensable in aerospace, automotive, energy, electronics, soft robotics, and biomedical applications due to their high specific stiffness, strength, and manufacturability with highly tailorable multifunctional performance. Their rational design is complicated by strong, multiscale couplings among microstructural heterogeneity, interfacial physics, anisotropic response, and time- and temperature-dependent behavior, spanning molecular to structural length scales. This review provides a comprehensive survey of the principal computational methodologies used to predict and interpret the mechanical behavior of polymer composites and nanocomposites, highlighting the capabilities, specialties, and complementary roles of different modeling tools. This review first summarizes the essential physical characteristics governing polymer composites and nanocomposites. We then examine computational modeling approaches for polymer composites across four length scales: the constituent scale, microscale, mesoscale, and macroscale. For each scale, the primary modeling objectives, characteristic capabilities, and domains of applicability are discussed in the context of the existing literature. Cross-scale relationships and bridging strategies among these scales are also discussed, emphasizing how lower-scale simulations inform higher-scale models. The review then focuses on computational modeling of polymer nanocomposites, with particular attention to atomistic and coarse-grained molecular dynamics methods. Representative atomistic simulations, which capture interfacial structure, reinforcement-matrix interactions, and nanoscale mechanisms, are discussed. This is followed by discussions on coarse-grained approaches that extend the accessible length and time scales. Finally, we discuss how atomistic and coarse-grained models complement each other within integrated multiscale frameworks, enabling predictive links between nanoscale physics and macroscopic mechanical behaviors. Multiscale modeling ; Polymer nanocomposite ; Bridging (networking) ; Context (archaeology) ; Nanocomposite ; Computational model ; Polymer ; Nanoscopic scale Polymer Nanocomposites and Properties ; Composite Material Mechanics ; Polymer crystallization and properties
Authors: Franziska Flecken | S. Hanf
Source: European Journal of Inorganic Chemistry (article, 2026-01-23)
Field: Chemistry — Organic Chemistry

Recent Developments in the Field of Air‐Stable Nickel(0) Precatalysts for Cross‐Coupling Reactions The development of bench‐stable Ni(0) precatalysts marks a significant turning point in nickel catalysis, offering a practical path beyond the long‐standing dependence on air‐sensitive Ni sources, such as [Ni(COD) 2 ] (COD = cycloocta‐1,5‐diene). These next‐generation complexes provide direct access to the catalytically active Ni(0) oxidation state, while remaining stable to air and moisture. This simplifies their handling and expands their potential for both academic and industrial applications. In this context, two main synthetic strategies dominate: ligand exchange from [Ni(COD) 2 ] and reduction of Ni(II) salts using chemical or electrochemical methods. The success of bench‐stable Ni(0) complexes relies on a targeted ligand design, employing strong π‐acceptors and donors, such as electron‐deficient dienes, carbenes, and fluorophosphines, to balance catalyst stability with a high catalytic activity. At the same time, the ligand environment must allow a facile exchange, without the released ligand inhibiting the metal centre through re‐coordination. Beyond their practical advantages, these systems are compatible with high‐throughput and data‐driven discoveries, accelerating the development of C–C and C–heteroatom cross‐coupling reactions. As nickel catalysis continues, bench‐stable Ni(0) systems are thought to open up a new generation of sustainable and scalable homogeneous catalysts for many organic transformations. Catalysis ; Ligand (biochemistry) ; Nickel ; Homogeneous ; Field (mathematics) ; Metal ; Homogeneous catalysis ; Electrochemistry Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods ; Organometallic Complex Synthesis and Catalysis
Authors: Jacob J. Wardzala | Matthew R. Hennefarth | Valay Agarawal | Bhavnesh Jangid | Aniruddha Seal | Matthew R. Hermes | Daniel S. King | Laura Gagliardi
Source: ChemRxiv (article, 2026-03-10)
Field: Materials Science — Materials Chemistry

Multireference Methods for Chemistry and Materials Science: Automated Active Spaces, Efficient Dynamic Correlation, and Extended Systems While multiconfigurational approaches have long been relegated to expert practitioners working on a case-by-case basis, recent developments have increasingly made these methods more routine and applicable to broader sets of systems. This perspective outlines the state-of-the-art in multiconfigurational approaches, with an emphasis on moving from delicate hand-selected pathways through configuration space towards more robust and efficient approaches to treating a host of challenging chemical systems accurately. First, we overview recent work in automated active-space selection, which has enabled increasingly large-scale applications of multireference methods to modeling vertical excitations and reactivity. Second, we highlight the increasingly efficient methods for recovering correlation energy beyond the active space, as headlined by extensions of pair-density functional theory and its role in accurate and efficient treatment of excited-state dynamics and its utilization to train machine-learned potentials. Finally, we highlight recent efforts to treat extended systems that until recently have lied beyond the traditional limits of active-space methods, giving center stage to product-form wave functions of the localized active space family of methods that allow for the computation of multiconfigurational band structures. These recent advancements point to a broader use of multireference approaches for high-impact chemical and materials science applications. Chemical space ; Space (punctuation) ; Computation ; Perspective (graphical) ; Work (physics) ; Efficient energy use Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Advanced Chemical Physics Studies
Authors: Xing WANG | Edan Bainglass | Miki Bonacci | Andres Ortega-Guerrero | Lorenzo Bastonero | Marnik Bercx | Pietro Bonfà | R. De Renzi | Dou Du | Peter N O Gillespie | Michael A. Hernández-Bertrán | Daniel Hollas | Sebastiaan P. Huber | Elisa Molinari | Ifeanyi John Onuorah | Nataliya Paulish | Deborah Prezzi | Junfeng Qiao | Timo Reents | Christopher J. Sewell | Iurii Timrov | Aliaksandr V. Yakutovich | Jusong Yu | Nicola Marzari | Carlo A. Pignedoli | Giovanni Pizzi
Source: npj Computational Materials (article, 2026-02-03)
Field: Materials Science — Materials Chemistry

Making atomistic materials calculations accessible with the AiiDAlab Quantum ESPRESSO app Despite the wide availability of density functional theory (DFT) codes, their adoption by the broader materials science community remains limited due to challenges such as software installation, input preparation, high-performance computing setup, and output analysis. To overcome these barriers, we introduce the Quantum ESPRESSO app, an intuitive, web-based platform built on AiiDAlab that integrates user-friendly graphical interfaces with automated DFT workflows. The app employs a modular Input-Process-Output model and a plugin-based architecture, providing predefined computational protocols, automated error handling, and interactive results visualization. We demonstrate the app's capabilities through plugins for electronic band structures, projected density of states, phonon, infrared/Raman, X-ray and muon spectroscopies, Hubbard parameters (DFT+<i>U</i>+<i>V</i>), Wannier functions, and post-processing tools. By extending the FAIR principles to simulations, workflows, and analyses, the app enhances the accessibility and reproducibility of advanced DFT calculations and provides a general template to interface with other first-principles calculation codes. Density functional theory ; Plug-in ; Modular design ; Software ; Interface (matter) ; Wannier function ; Plug and play ; Electronic structure Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; Advanced Chemical Physics Studies
Authors: Anvesh Nathani | Arthur RC McCray | Yingtao Liu | Hanping Ding | Pejman Kazempoor | Shuozhi Xu | Colin Ophus | Iman Ghamarian
Source: npj Computational Materials (article, 2026-01-07)
Field: Materials Science — Materials Chemistry

Accelerating electron diffraction analysis using graph neural networks and attention mechanisms Abstract Electron diffraction(ED) often used to solve for unknown structures or refine existing ones. Existing methods for automated ED analysis often struggle with challenges such as computational expense and experimental noise. This study introduces a deep learning framework to accelerate and improve crystal structure determination from diffraction patterns. The methodology treats each diffraction pattern as a relational graph of Bragg spots. Spot features are encoded using a 1D convolutional network, from which a relational attention aggregator constructs an orientation-agnostic graph. This graph is processed by a Graphormer encoder enhanced with Mixture-of-Experts layers, allowing the model to learn complex crystallographic relationships efficiently. Trained and tested on a large dataset of simulated diffraction patterns, the model achieved a crystal system classification accuracy of 89.2% and a space group accuracy of 70.2% from single patterns, significantly outperforming a state-of-the-art random forest baseline (74.2% and 57.8%, respectively). By aggregating predictions across multiple zone axes, these accuracies improved to 96.5% and 79.5%. The model also demonstrated robust performance on experimental data of gold nanoparticles, producing plausible classifications consistent with known orientation degeneracies. By unifying relational graph reasoning with specialized expert networks, this work presents a robust and automated framework for high-throughput materials characterization. Graph ; Encoder ; Diffraction ; Pattern recognition (psychology) ; Convolutional neural network ; Graph theory ; Artificial neural network Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; X-ray Diffraction in Crystallography
Authors: Ermias Abebe Negash | Getinet Asrat Mengesha | Belay Brehane Tesfamariam | Tamirat Addis | Yeabsira Sisay Mekuriya | Sena Tadesse Beyene
Source: Scientific Reports (article, 2026-01-13)
Field: Materials Science — Ceramics and Composites

Synthesis of 3:2 mullite ceramics from silica-enriched filter cake waste via diphasic gels method Mullite ceramics were synthesized from filter cake waste following the diphasic gel method. Filter cake waste, with over 65% silica content, and aluminum nitrate nonahydrate were utilized as the sources of silica and alumina, respectively. The prepared samples were sintered at various temperatures of 1150, 1250, and 1350 °C. The sintered bodies were then evaluated for porosity, density, compressive strength, and dielectric strength. Differential Thermal Analysis (DTA) revealed exothermic peaks at 970 °C and 1147 °C, corresponding to spinel and mullite formation, which was also confirmed by X-ray diffraction (XRD) analysis. The XRD result also showed single-phase mullite crystallization at 1250 °C. Field Emission-Scanning Electron Microscopy (FESEM) and Energy Dispersive Spectroscopy (EDS) demonstrated morphological changes, grain growth, and uniform elemental distribution in sintered mullite ceramics. The mullite ceramics sintered at 1350 °C exhibited a density of 2.615 g/cm<sup>3</sup>, compressive strength of 420 MPa, and dielectric strength of 10.2 kV/mm. These findings highlight the potential of the diphasic gel method to produce high-quality mullite ceramics from industrial waste, contributing to cost-effective, eco-friendly materials with promising applications, including electronic devices, electrical power transmission systems, and other structural and functional advanced ceramics. Mullite ; Ceramic ; Spinel ; Compressive strength ; Differential thermal analysis ; Dielectric ; Exothermic reaction ; Sintering Advanced ceramic materials synthesis ; Recycling and utilization of industrial and municipal waste in materials production ; Nuclear materials and radiation effects
Authors: Ji‐Yong Sung | Jae‐Ho Cheong
Source: Clinical and Translational Medicine (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Quantum medicine: A quantum–mechanical framework for redox biology, disease and precision medicine Quantum biomedicine redefines life as a dynamic equilibrium sustained by quantum coherence, tunnelling and redox resonance. Hybrid quantum-classical algorithms, such as VQE and QPE, enable first-principles modelling of redox and spin-dependent reactions with near-experimental accuracy. NISQ-era hardware supports proof-of-concept simulations of electron tunnelling and radical-pair dynamics, bridging computation with measurable biophysics. Integration of quantum simulations with spectroscopy and cryo-EM establishes a quantum-experimental-clinical (QEC) pipeline linking theory, experiment and medicine. Ethical, educational and governance frameworks are essential for equitable, transparent and sustainable implementation of quantum health technologies. Quantum tunnelling ; Biomedicine ; Quantum ; Bridging (networking) ; Precision medicine ; Redox ; Quantum computer ; Pipeline (software) Metal-Catalyzed Oxygenation Mechanisms ; Free Radicals and Antioxidants ; Electron Spin Resonance Studies
Authors: Xueying Liu | Florent Allais | Sami Fadlallah
Source: Green Chemistry (article, 2026-01-01)
Field: Materials Science — Biomaterials

Itaconic acid as a platform chemical for bio-based polymers: from green polymerization strategies to structure-driven applications As a promising bio-based platform chemical, itaconic acid (IA) combines two carboxyl groups with an activated vinyl group, enabling extensive derivatization and multiple polymerization pathways. Itaconic acid ; Polymerization ; Derivatization ; Chemical modification ; Polymer biodegradable polymer synthesis and properties ; Advanced Polymer Synthesis and Characterization ; Carbon dioxide utilization in catalysis
Authors: Christian Idogho | Godstime Obiajulu Okocha | Tordue Imbur | Agbedor Kingsley Obozokhi
Source: International Journal of Scientific Research and Modern Technology. (article, 2026-02-21)
Field: Materials Science — Materials Chemistry

Material Parameter and Compatibility Factor Dependence of Maximum ZT in Cu and Ni-Based Thermoelectric This work examines thermoelectric transport properties of Cu₂₋ₓSe, Cu₁₂Sb₄S₃, Sn₁₋ₓCuₓSe, Ti(Ni₁₋ₓCuₓ)Sn, NiTiX, and Ni₂CuCrFeAlₓ, representing a broad class of Cu- and Ni-based thermoelectric materials and their alloys. Using experimentally reported transport parameters, the electronic quality factor and the thermoelectric material parameter were evaluated for all compounds. Based on these values, systematic relationships between the maximum thermoelectric figure of merit, (ZT)max, and the material parameter B were constructed. A clear correlation between intrinsic electronic transport quality and achievable thermoelectric efficiency is observed, demonstrating that the material parameter B, evaluated using the Seebeck coefficient S, electronic quality factor BE, and lattice thermal conductivity λL, provides a predictive metric for ZT across diverse material classes. In addition, the temperature-dependent compatibility factor (CF) was calculated for all investigated systems. The CF analysis reveals that Cu-based chalcogenides maintain favorable compatibility over broad temperature ranges, indicating strong potential for segmented thermoelectric generator design, whereas Ni-based intermetallic and high-entropy alloys are intrinsically limited by suppressed compatibility factors. Overall, the results highlight a shift from power-factor-based evaluation toward device-oriented screening using the material parameter and compatibility factor, providing a unified framework for the rational design of high-performance thermoelectric materials. Thermoelectric effect ; Compatibility (geochemistry) ; Thermoelectric materials ; Seebeck coefficient ; Thermal conductivity ; Thermoelectric generator ; Electrical resistivity and conductivity Advanced Thermoelectric Materials and Devices ; Electronic Packaging and Soldering Technologies ; Heusler alloys: electronic and magnetic properties