jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Andrea Mistrini | Amin Hodaei | Martina Meisnar | Davoud Jafari | Riccardo Casati
Source: Progress in Additive Manufacturing (article, 2026-02-12)
Field: Materials Science — Materials Chemistry

Wafer-scale PBF-LB/M additive manufacturing of SnAg3 as thermal interface materials for advanced high-power electronics cooling To support the miniaturization of electronics with increasing power, advanced cooling strategies are needed. Unlike conventional cooling pathways for wafer-scale electronics that involve the use of thermal pastes, we introduce an additive manufacturing route using laser powder bed fusion (PBF-LB/M) to fabricate 50–200 μm thick SnAg3 deposits that function as thermal interfaces between the Si substrate and the heat exchanger. The results reveal that by fine tuning the PBF-LB/M process parameters, it is possible to engineer the microstructure of the printed thermal interface materials onto Si wafer and to limit the Si damage. These findings demonstrate a promising solution for wafer-scale additive manufacturing of advanced cooling architectures, enabling the fabrication of high-power electronics. Electronics ; Miniaturization ; Fabrication ; Wafer ; Thermal ; Substrate (aquarium) ; Microstructure ; Interface (matter) Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies
Authors: Kenan Li | Yijian Zhang | Jin Wang | Haipeng Gan | Zeying Sun | Xiaoguang Lei | Hao Dong
Source: arXiv (Cornell University) (preprint, 2026-01-06)
Field: Materials Science — Materials Chemistry

ChemBART: A Pre-trained BART Model Assisting Organic Chemistry Analysis Recent advances in large language models (LLMs) have demonstrated transformative potential across diverse fields. While LLMs have been applied to molecular simplified molecular input line entry system (SMILES) in computer-aided synthesis planning (CASP), existing methodologies typically address single tasks, such as precursor prediction. We introduce ChemBART, a SMILES-based LLM pre-trained on chemical reactions, which enables a unified model for multiple downstream chemical tasks--achieving the paradigm of "one model, one pre-training, multiple tasks." By leveraging outputs from a mask-filling pre-training task on reaction expressions, ChemBART effectively solves a variety of chemical problems, including precursor/reagent generation, temperature-yield regression, molecular property classification, and optimizing the policy and value functions within a reinforcement learning framework, integrated with Monte Carlo tree search for multi-step synthesis route design. Unlike single-molecule pre-trained LLMs constrained to specific applications, ChemBART addresses broader chemical challenges and integrates them for comprehensive synthesis planning. Crucially, ChemBART-designed multi-step synthesis routes and reaction conditions directly inspired wet-lab validation, which confirmed shorter pathways with ~30% yield improvement over literature benchmarks. Our work validates the power of reaction-focused pre-training and showcases the broad utility of ChemBART in advancing the complete synthesis planning cycle. Variety (cybernetics) ; Tree (set theory) ; Task (project management) ; Yield (engineering) ; Reinforcement learning ; Transformative learning Machine Learning in Materials Science ; Asymmetric Hydrogenation and Catalysis ; Computational Drug Discovery Methods
Authors: Pengjin Liu | S.-L. Zhang | Y. Wang
Source: Journal of Magnetism and Magnetic Materials (article, 2026-02-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Preparation of Sm2Fe17 and high-performance Sm2Fe17Nx via direct diffusion method Nitriding ; Coercivity ; Alloy ; Diffusion ; Analytical Chemistry (journal) ; Phase (matter) ; Magnetization ; Raw material Magnetic Properties of Alloys ; Magnetic and transport properties of perovskites and related materials ; Inorganic Chemistry and Materials
Authors: Abhijeet Puri | Popat Mohite | Aakansha Ramole | Sagar Pardeshi | Krutika Bhoir | Sonali Verma | Sudarshan Singh
Source: Polysaccharides (article, 2026-03-20)
Field: Materials Science — Biomaterials

Dual Modification of Red Lentil Starch: Enhancing Functionality for Environmental and Pharmaceutical Applications This study explored the dual chemical modification of starch isolated from red lentils (Lens culinaris) to develop a biodegradable polymer with enhanced functionality for multifaceted applications. Native starch was isolated via combined salt–alkali treatment and sequentially modified through epichlorohydrin-mediated crosslinking, followed by cationization using glycidyl trimethylammonium chloride (GTAC). Utilizing a Quality by Design (QbD) strategy through Response Surface Methodology (RSM), the cationization endured fine-tuning to reach an optimal degree of substitution (DS = 0.572) under foremost conditions (GTAC: 2.1 mol, NaOH: 0.09 mol, reaction time: 18 h). Structural and functional characterization using FTIR, XRD, TGA, SEM, and zeta potential analysis confirmed the successful modification, indicating enhanced thermal stability, a transition to a more amorphous structure, and a moderately positive surface charge (+7.24 mV). The dual modified cationic lentil starch (CLS) demonstrated effective flocculation of kaolin suspensions, achieving a transmittance of up to 94%. Additionally, CLS showed significantly improved emulsion stability, maintaining over 70% stability after 24 h, compared to native starch, which dropped below 30%. These results emphasize the promising potential of CLS as an eco-friendly and high-performance alternative to synthetic polymers for water treatment and stabilization of emulsion-based formulations. Cationic polymerization ; Zeta potential ; Starch ; Flocculation ; Polymer ; Thermal stability ; Emulsion ; Chemical modification Nanocomposite Films for Food Packaging ; Food composition and properties ; Coagulation and Flocculation Studies
Authors: Gunjan | Marilyn Daisy Milton
Source: Journal of Molecular Structure (article, 2026-01-24)
Field: Materials Science — Materials Chemistry

Synthesis of phenothiazine–5–oxide–based dual–state emitters and their applications in trace water detection, visualization of latent fingerprints, anti–counterfeiting ink and dual–state acid triggered molecular switching Trifluoroacetic acid ; Fluorescence ; Intramolecular force ; Substituent ; Stokes shift ; Analytical Chemistry (journal) ; Detection limit ; Molecular wire Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Carbon and Quantum Dots Applications
Authors: Ummed Singh | G. Janaki Ram | Sahi Ram | Himanshu
Source: Applied Physics A (article, 2026-02-17)
Field: Materials Science — Materials Chemistry

Investigating the influence of erbium doping on structural, morphological, compositional and magnetic properties of Zn0.6Mg0.4ErxFe(2-x)O4 ferrites Diffractometer ; Crystallite ; Tetragonal crystal system ; Magnetometer ; Scanning electron microscope ; Analytical Chemistry (journal) ; Spectroscopy ; Fourier transform infrared spectroscopy Magnetic Properties and Synthesis of Ferrites ; Iron Metabolism and Disorders ; Electromagnetic wave absorption materials
Authors: Lukas Bührmann | Amrit Chandi | Nadeschda Geibel | Lena Albers | Marc Schmidtmann | Thomas Müller
Source: Inorganic Chemistry (article, 2026-03-24)
Field: Chemistry — Organic Chemistry

Boragerma[5]pyramidanes via a Germole-to-Borole Rearrangement The scope and limitations of a germole-to-borole rearrangement are reported. Double salt metathesis reactions of dipotassium germolediides with amino-, aryl-, and ferrocenyl-substituted boron dihalides allow for the preparation of borole complexes of Ge(II) in synthetically useful yields and quantities. The analogous silole-to-borole transformation is viable but is less selective and of limited synthetic use. The analysis of the molecular and electronic structure of the obtained Ge(II) borole complexes classifies them as boragerma[5]pyramidanes, molecular <i>nido</i>-type clusters. The molecular structure can be fine-tuned as strongly electron-donating substituents at the boron atom induce an opening of the cluster. The boragerma[5]pyramidanes bind via the germanium atom to transition metal complexes and behave as σ-donors with only insignificant π-acceptor abilities. Their reduction with elemental lithium and their reaction with strong nucleophiles such as N-heterocylic carbenes (NHCs) lead to the elimination of germanium and isolation of borole derivatives. Salt metathesis reaction ; Germanium ; Boron ; Nucleophile ; Metathesis ; Salt (chemistry) ; Lithium (medication) Organoboron and organosilicon chemistry ; Synthesis and characterization of novel inorganic/organometallic compounds ; Organometallic Complex Synthesis and Catalysis
Authors: Chi Zhang | Zongpeng Zou | Jiajian Gao | Y. C. Zhu | Shengwei Tang | Wenxiang Tang
Source: SSRN Electronic Journal (preprint, 2026-01-01)
Field: Materials Science — Materials Chemistry

Selectively Anchoring Pt nanoclusters on TiO2@SiO2 Core-shell nanostructure with Spatially and Electronically Co-Confined Effect for Durable Hydrocarbon Oxidation Nanoclusters ; Catalysis ; Nanostructure ; Sintering ; Propane ; Thermal stability ; Platinum ; Thermal ; Metal Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Oxidation Reactions
Authors: Zhibo Liu | Zheng Zhang | Hikaru Sotome | Takashi Hirose
Source: ChemRxiv (article, 2026-02-17)
Field: Chemistry — Organic Chemistry

Topology-Directed π-Extension of Helical PAHs: Tunable Energy Gap and Excited-State Dynamics The topology of π-extension critically dictates the physicochemical properties of helical systems. Herein, we report the synthesis and characterization of two novel helically π-extended polycyclic aromatic hydrocarbons (HPAHs), 1 and 2, derived from per-peri-perbenzo[7]helicene (PB[7]H) via central and terminal ring fusion, respectively. Structural analysis reveals that terminal extension in 2 yields a unique dispersion-dominated "π-clamped" geometry. While optical energy gaps decrease monotonically with extension size, oscillator strengths exhibit a non-monotonic trend, a "decoupling" phenomenon rationalized by transition-moment density (TMD) analysis which visualizes spatial cancellations of transition densities. Furthermore, transient absorption spectroscopy demonstrates that the rigidified inner rim of 1 retards non-radiative decay compared to PB[7]H, highlighting the role of polyene-like electronic character in excited-state dynamics. Importantly, these topology-directed fusions bridge the discrete energy gaps of the homologous PB[n]H series (n = 5, 7, 9). This work establishes a design strategy for the continuous fine-tuning of chiroptical properties and dynamics in HPAHs beyond the limitations of discrete homologous series. Homologous series ; Work (physics) ; Spectroscopy ; Dynamics (music) ; Characterization (materials science) ; Series (stratigraphy) ; Terminal (telecommunication) ; Absorption (acoustics) ; Topology (electrical circuits) Synthesis and Properties of Aromatic Compounds ; Photochromic and Fluorescence Chemistry ; Fullerene Chemistry and Applications
Authors: Muhammad bin Javaid | Hasham Hussain | Ashima Khanna | Berke Kisin | Jonathan Pirnay | Alexander Mitsos | Dominik G. Grimm | Martin Grohe
Source: Open MIND (preprint, 2026-02-12)
Field: Materials Science — Materials Chemistry

Amortized Molecular Optimization via Group Relative Policy Optimization Molecular design encompasses tasks ranging from de-novo design to structural alteration of given molecules or fragments. For the latter, state-of-the-art methods predominantly function as "Instance Optimizers'', expending significant compute restarting the search for every input structure. While model-based approaches theoretically offer amortized efficiency by learning a policy transferable to unseen structures, existing methods struggle to generalize. We identify a key failure mode: the high variance arising from the heterogeneous difficulty of distinct starting structures. To address this, we introduce GRXForm, adapting a pre-trained Graph Transformer model that optimizes molecules via sequential atom-and-bond additions. We employ Group Relative Policy Optimization (GRPO) for goal-directed fine-tuning to mitigate variance by normalizing rewards relative to the starting structure. Empirically, GRXForm generalizes to out-of-distribution molecular scaffolds without inference-time oracle calls or refinement, achieving scores in multi-objective optimization competitive with leading instance optimizers. Directed acyclic graph ; Oracle ; Graph ; Group (periodic table) ; Variance (accounting) ; Key (lock) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: G.M. Dhanush | C.K. Praveen Kumar | K. Pramoda | H.K. Vivek | Y.R. Girish
Source: Materials Today Nano (article, 2026-01-20)
Field: Materials Science — Materials Chemistry

2-Dimensional black phosphorus nanostructures for biomedical applications Black phosphorus ; Biocompatibility ; Drug delivery ; Nanomaterials ; Low energy ; Biocompatible material 2D Materials and Applications ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: Qian Xu | Yong Nie | Jacob‐Jan Haaksma | Ronghua Zhang | Natalie Holmberg-Douglas | Farid W. van der Mei | Paul M. Scola | Chloe Williams | Jeremiah A. Johnson | Alison E. Wendlandt
Source: Nature (article, 2026-03-10)
Field: Chemistry — Organic Chemistry

Alcohol group migration by proximity-enhanced H atom abstraction Functional group ; Alcohol ; Stereocenter ; Catalysis ; Reagent ; Group (periodic table) ; Molecule ; Molecular dynamics Radical Photochemical Reactions ; Oxidative Organic Chemistry Reactions ; Asymmetric Hydrogenation and Catalysis
Authors: Jeff Armstrong | Adam Jackson | Alin M. Elena
Source: Science and Technology Facilities Council (preprint, 2026-03-05)
Field: Materials Science — Materials Chemistry

High-Pressure Inelastic Neutron Spectroscopy: A true test of Machine-Learned Interatomic Potential energy landscapes Machine-learned interatomic potentials (MLIPs) promise to provide near density-functional theory accuracy at a fraction of the computational cost, offering a transformative route toward genuinely predictive chemistry. Yet their predictive validity beyond the training regime remains largely untested experimentally. Here we use pressure-dependent broadband inelastic neutron spectroscopy (INS) as a direct experimental probe of MLIP transferability. Employing a newly developed high-pressure superalloy clamp cell, we measure INS spectra of crystalline 2,5-diiodothiophene at 10~K under ambient conditions and at 1.5~GPa. A MACE-based MLIP, fine-tuned on targeted DFT data, reproduces the experimental spectra across 0--1200~cm$^{-1}$ at both pressures and remains thermodynamically stable under rigorous molecular dynamics validation at 300~K. The model captures systematic pressure-induced blue shifts arising from steric stiffening and reproduces an anomalous red shift at 453~cm$^{-1}$ driven by pressure-modified intermolecular interactions, providing direct validation of its many-body character. This constitutes the first experimental demonstration of MLIP transferability across distinct thermodynamic states using neutron spectroscopy, and establishes high-pressure INS as a stringent benchmark for predictive machine-learned potentials. Spectral line ; Neutron ; Transferability ; Interatomic potential ; Neutron spectroscopy ; Spectroscopy ; Inelastic neutron scattering ; Neutron scattering Machine Learning in Materials Science ; High-pressure geophysics and materials ; Inorganic Chemistry and Materials
Authors: Mahdi Astaraki | Mohammad Arshi Saloot | Ali Shiraee Kasmaee | Hamidreza Mahyar | Soheila Samiee
Source: Open MIND (preprint, 2026-01-27)
Field: Materials Science — Materials Chemistry

When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering Retrieval-Augmented Generation (RAG) extends large language models (LLMs) beyond parametric knowledge, yet it is unclear when iterative retrieval-reasoning loops meaningfully outperform static RAG, particularly in scientific domains with multi-hop reasoning, sparse domain knowledge, and heterogeneous evidence. We provide the first controlled, mechanism-level diagnostic study of whether synchronized iterative retrieval and reasoning can surpass an idealized static upper bound (Gold Context) RAG. We benchmark eleven state-of-the-art LLMs under three regimes: (i) No Context, measuring reliance on parametric memory; (ii) Gold Context, where all oracle evidence is supplied at once; and (iii) Iterative RAG, a training-free controller that alternates retrieval, hypothesis refinement, and evidence-aware stopping. Using the chemistry-focused ChemKGMultiHopQA dataset, we isolate questions requiring genuine retrieval and analyze behavior with diagnostics spanning retrieval coverage gaps, anchor-carry drop, query quality, composition fidelity, and control calibration. Across models, Iterative RAG consistently outperforms Gold Context, with gains up to 25.6 percentage points, especially for non-reasoning fine-tuned models. Staged retrieval reduces late-hop failures, mitigates context overload, and enables dynamic correction of early hypothesis drift, but remaining failure modes include incomplete hop coverage, distractor latch trajectories, early stopping miscalibration, and high composition failure rates even with perfect retrieval. Overall, staged retrieval is often more influential than the mere presence of ideal evidence; we provide practical guidance for deploying and diagnosing RAG systems in specialized scientific settings and a foundation for more reliable, controllable iterative retrieval-reasoning frameworks. Ideal (ethics) ; Context (archaeology) ; Oracle ; Iterative method ; Benchmark (surveying) ; Parametric statistics ; Iterative refinement ; Question answering Machine Learning in Materials Science ; Topic Modeling ; Advanced Graph Neural Networks
Authors: Yanqiu Zhao | Wei Chen | Jinshan Xu | Hua Zhao | Xiangyu Xiao | Guomin Xia
Source: Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (article, 2026-01-06)
Field: Materials Science — Materials Chemistry

Rigid π-conjugation engineering in twisted molecules for efficient dual-state emission and lipid droplet bioimaging Cyan ; Triphenylamine ; Rational design ; Fluorescence ; Anthracene ; Molecule ; Molecular engineering Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Hao Yu | Meng Li | Xiong Chen | Ningxu Han | Zinuo Gao | Ziteng Guo | Xinrui Zhang | Yude Wei | Zihan Xu | Ming Wang
Source: Chemical Synthesis (article, 2026-01-21)
Field: Materials Science — Materials Chemistry

Nitrogen atom modulation enables high-sensitive mechanofluorochromism of tetraphenylethylene-based luminescent materials Mechanofluorochromic (MFC) materials, capable of undergoing color changes in response to external forces, hold vast potential for a wide range of applications. Here, we designed and synthesized four compounds based on the tetraphenylethylene (TPE) unit, denoted as TPE-1 , TPE-2 , TPE-3 , and TPE-4 . The TPE moiety serves as the common core among these compounds, while nitrogen atom fine-tuning is employed on the modifying groups of the four compounds to explore its influence on their photophysical properties and MFC performance. These compounds display significant variations in their solid-state photophysical properties and MFC characteristics. Especially, TPE-3 and TPE-4 exhibit excellent MFC properties and different sensitivity to external mechanical stimuli. These research findings not only offer a fresh perspective on the MFC mechanism of TPE-based compounds but also provide valuable insights for the design and development of novel MFC molecules. Moiety ; Tetraphenylethylene ; Luminescence ; Atom (system on chip) ; Nitrogen atom ; Nitrogen ; Range (aeronautics) Luminescence and Fluorescent Materials ; Crystallography and molecular interactions ; Molecular Sensors and Ion Detection
Authors: Liping Luo | Ping Chen | Jingquan Wang | Han Wu | Hongguang Guo
Source: Analytical Chemistry (article, 2026-02-13)
Field: Chemistry — Spectroscopy

A Phenoxyl Radicals-Triggered Colorimetric Analytical Platform for Rapid and In-situ Visual Detection of Amino Pollutants in Water Environments Amino pollutants ubiquitously discharged from medical, animal husbandry, and aquaculture industries represent a hazardous subgroup of emerging contaminants, yet their rapid and reliable on-site monitoring remains challenging. Herein, we developed a selective analytical system for amino pollutants based on a liquid oxidation recognition probe (<b>LORP</b>) synthesized via a Mn-based advanced oxidation process. The probe selectively captures amino groups through group-selective radical coupling reactions, while crystal violet (CV) enables quantitative and visual readout by converting pollutant concentrations into absorbance signals and color changes. Impressively, this detection system exhibits high selectivity and anti-interference capacity toward complex water matrices and good practicability in tap water, Lake water, fountain water, and aquaculture wastewater with SMX recovery rates of 83.9 to 119.1%. A general synthetic strategy employing structurally diverse phenols was validated, expanding probe accessibility and allowing precise modulation of the LODs and ranges by fine-tuning the phenolic structures. This offers flexible adaptability to different water qualities and detection needs. Overall, this study presents a rapid and practical onsite visual sensing strategy for amino pollutants, featuring phenoxyl radical probes with facile synthesis and operational simplicity. Pollutant ; Tap water ; Wastewater ; Diazo ; Phenols ; Absorbance ; Selectivity ; Optical sensing Molecular Sensors and Ion Detection ; Advanced Nanomaterials in Catalysis ; Analytical Chemistry and Sensors
Authors: Wanli Ma | Xiaoyu Song | Xiao Li | Ruiheng Jia | Hongshuang Guo | Yang Li | X Liu
Source: Langmuir (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

Ni(II)-Based Porphyrin-Conjugated Microporous Polymers as Promising Anode for Lithium Storage Conjugated microporous polymers (CMPs) have emerged as promising electrode materials for secondary lithium-ion batteries (LIBs), owing to their intrinsic insolubility, structural tunability, permanent porosity, and robust reversibility toward lithium intercalation and deintercalation. However, achieving the simultaneous optimization of capacity, rate performance, and cycling stability remains a long-standing challenge. Herein, we designed a rationally engineered porphyrin-based CMP (NiP-CMP) that integrates multiple electrochemically active sites, including metal-N<sub>4</sub> conjugated macrocycles and conjugated alkyne linkages, within a robust π-conjugated framework. By fine-tuning the polycondensation conditions, NiP-CMP with a high specific surface area (1110 m<sup>2</sup> g<sup>-1</sup>) was obtained, ensuring efficient ion diffusion and charge transport. Benefiting from its well-defined conjugated architecture and abundant electrochemically active centers, NiP-CMP delivers a high specific capacity of ∼702 mA h g<sup>-1</sup> at 0.1 A g<sup>-1</sup>, together with a rate capability (355 mA h g<sup>-1</sup> at 1 A g<sup>-1</sup>) and long-term cycling stability. This work demonstrates a strategic design that effectively resolves the electrode material "trilemma", achieving high capacity, fast kinetics, and durability simultaneously, and thus offers a viable design paradigm for high-performance organic electrode materials in energy storage applications. Conjugated microporous polymer ; Anode ; Electrode ; Conjugated system ; Lithium (medication) ; Polymer ; Microporous material ; Energy storage Covalent Organic Framework Applications ; Advancements in Battery Materials ; Supercapacitor Materials and Fabrication