jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Roman Adam | M. Mikulics | Daniel E. Bürgler | Kiryl Niherysh | Alexei Kalaboukhov | Sarah Heidtfeld | I. Komissarov | Roman Sobolewski | Claus M. Schneider | Jiřı́ Mayer | H. Hardtdegen
Source: Photonics (article, 2026-03-14)
Field: Materials Science — Materials Chemistry

Laser-Induced Degradation of Bi2Se3 THz Emitters Revealed by Raman Spectroscopy We present an investigation of the thermal damage threshold of passivated Bi2Se3 films upon laser illumination, with a focus on their employment in terahertz (THz) spectroscopic applications. Passivation was achieved by depositing a thin 3 nm Al capping layer which, exposed to the ambient, forms a natural oxide. In THz transient emission experiments, the samples were exposed to a train of 100 fs wide laser pulses with 800 nm wavelength at 78 MHz repetition rate and peak power density up to 295 mW/µm2. For the sake of comparison, the films were also exposed to continuous wave laser light with a wavelength of 532 nm in the average optical power density range from 5 × 10−2 mW/µm2 to 50 mW/µm2. In both cases, changes in film appearance, detected by optical microscopy, or even film removal in a small area close to the center of the illuminated spot could be induced. Raman spectroscopy provided evidence that the crystalline phase of Bi2Se3 films is present in areas that have been exposed but not damaged. Conversely, in the film region illuminated with the highest peak power density no Raman signal was detected in the range under investigation which we ascribe to material removal. At the perimeter of this ablated area, we observed a dominant Raman mode at approximately 255 cm−1 that we can attribute to selenium and indicates partial Bi2Se3 decomposition. In contrast, we observed Raman spectra corresponding to as-deposited Bi2Se3 only a few micrometers away from the laser-damaged area. Hence, the observed THz radiation originates from this illuminated but undamaged region. This detailed knowledge is expected to serve as a guide for designing the emitter’s thermal management and choosing laser parameters for optimal operation. Raman spectroscopy ; Laser ; Passivation ; Terahertz radiation ; Thin film ; Power density ; Wavelength ; Spectroscopy Advanced Thermoelectric Materials and Devices ; Thermography and Photoacoustic Techniques ; Phase-change materials and chalcogenides
Authors: Sana Tat | Ehsan Mohebbi | Ali Reza Akbarzadeh
Source: Research Square (preprint, 2026-02-25)
Field: Materials Science — Biomaterials

Impact of Surface Properties — Including Pore Size — of Porous Structures on Anticancer Drug Delivery Efficiency in Colon Cancer: A Systematic Review Drug delivery ; Anticancer drug ; Porosity ; Targeted drug delivery ; Drug ; Drug carrier ; Colorectal cancer Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Chao Yang | Qianli Liu | Yang Lin | Yongyong Suo | Qingwei Jiang | Jing Feng | Xiaoyu Chong
Source: Research Square (preprint, 2026-02-18)
Field: Materials Science — Materials Chemistry

Integrated Computational Modeling of Electromechanical Coupling Corrosion Behavior in Titanium Alloys Corrosion ; Stress corrosion cracking ; Titanium alloy ; Coupling (piping) ; Titanium ; Stress (linguistics) ; Anode ; Ultimate tensile strength ; Environmental stress fracture Titanium Alloys Microstructure and Properties ; Hydrogen embrittlement and corrosion behaviors in metals ; Structural Integrity and Reliability Analysis
Authors: Zhongzheng Miao
Source: ChemRxiv (article, 2026-03-16)
Field: Materials Science — Materials Chemistry

Freestanding Intrinsic Ferroelectric 2D Ice and Its 3D Stackings: Reshaping the Functional Boundaries of Low-Dimensional Hydrogen-Bonded Networks Can two-dimensional (2D) ice exist independently without a substrate? Can pure water serve as a functional material exhibiting ferroelectricity, semiconducting behavior, and extreme mechanical properties? These two fundamental questions have long remained unresolved. Here, through firstprinciples calculations, we provide the first theoretical confirmation that 2D ice can exist intrinsically and stably without any substrate. We discover a complete family of freestanding intrinsic ferroelectric 2D ice: parallelogram elemental 2D ice (P-Ice, stable at 5 K), biaxial ferroelectric origami-like topological 2D ice (O-Ice, stable at 260 K), and ferroelectric interlocked bilayer 2D ice (I-Ice, stable at 240 K). All three phases rigorously satisfy the golden criteria validation (entirely positive phonon spectra, Born-Huang mechanical stability criteria, and finitetemperature AIMD simulations). Notably, O-Ice and I-Ice maintain their structural integrity near the freezing point of water, providing the first demonstration that 2D hydrogen-bonded networks can survive independently without substrate support. Using these freestanding 2D ices as structural building blocks, we construct the first pure-water-based 3D ferroelectric materials via van der Waals stacking, achieving multilevel synergy between "in-plane hydrogen-bond ferroelectricity" and "interlayer van der Waals ferroelectricity." We uncover and validate a new principle: "2D order dictates 3D strength." These 3D stackings exhibit extraordinary mechanical properties-a Young's modulus along the Z-axis reaching 48.6 GPa (comparable to magnesium metal), a Poisson's ratio in the Y-X direction of 0.973 (approaching the theoretical limit), and a stiffness anisotropy of up to 6.5-fold. The layered frameworks remain structurally intact across a pressure range of 0-3000 GPa (spanning conditions from Earth's core to the interiors of ice giants), with an insulator-to-metal transition occurring at 1190 ± 20 GPa. This work resolves the long-standing debate over whether 2D ice must rely on substrates, elevating water from the most mundane substance to a functional material platform capable of independent existence. It opens new frontiers for green electronics, extreme-environment sensing, and planetary science. Ferroelectricity ; van der Waals force ; Parallelogram ; Anisotropy ; Stiffness ; Modulus ; Bilayer ; Rhombus 2D Materials and Applications ; Graphene research and applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Cody Melton | Jaron T. Krogel
Source: ArXiv.org (article, 2026-01-21)
Field: Materials Science — Materials Chemistry

Assessing Orbital Optimization in Variational and Diffusion Monte Carlo In this work, we investigate the fidelity of orbital optimization in variational Monte Carlo to improve diffusion Monte Carlo results on correlated magnetic systems, using CrSBr as a model system. We compare the performance of different optimization methods, showing that stochastic reconfiguration is a robust and reliable optimizer. We show that short range Jastrow factors are important for improving diffusion Monte Carlo, regardless of the quality of orbitals. Large active spaces are required to converge the variational energy, but ulitmately orbital optimization produces worse diffusion Monte Carlo energies when compared to standard orbitals from density functional theory. We show that this increased bias is due to larger locality errors from the use of pseudopotentials, while the fixed-node error is actually improved by using orbital optimization. Additionally, for observables other than energy, orbital optimization produces a systematically smaller mixed-estimator bias. Ultimately, we believe orbital optimization provides a reliable method to improve variational and pure fixed-node energies as well as lower mixed-estimator bias. Monte Carlo method ; Diffusion Monte Carlo ; Quantum Monte Carlo ; Diffusion ; Variational Monte Carlo ; Dynamic Monte Carlo method ; Atomic orbital ; Monte Carlo molecular modeling Machine Learning in Materials Science ; Magnetic properties of thin films ; Magnetic Properties of Alloys
Authors: Yujing Jing | Ce Yang | Zhaoxia Han | Yue Lu | Dawei Zhang | Ruijin Hong | Chunxian Tao | DeChao Yu
Source: Photonics (article, 2026-03-11)
Field: Materials Science — Materials Chemistry

Synthesis and Applications of Dual-Afterglow Carbon Dot Composites for Advanced Anti-Counterfeiting and Information Encryption Most of the existing carbon dot (CD)-based afterglow materials are limited to a single emission mode of either room-temperature phosphorescence (RTP) or delayed fluorescence (DF), which makes it difficult to meet the application requirements of advanced anti-counterfeiting and multi-level information encryption. Therefore, the development of CD-based composite materials with multi-mode afterglow emission, long lifetime and high stability holds significant research significance and application value. In this study, long-afterglow manganese/nitrogen co-doped CDs@boric acid (BA) composites (Mn, N-CDs @BA) are successfully prepared, and their optical properties and emission mechanism are clarified. The results demonstrate that the Mn, N-CDs @BA composites exhibit wavelength-dependent dual-afterglow emission characteristics of RTP and DF. Under 254 nm ultraviolet (UV) light excitation, they exhibit DF emission with an average lifetime of 903.36 ms. Under 365 nm UV light excitation, RTP emission with an average lifetime of 354.43 ms is observed. Moreover, the afterglow color exhibits time dependence. Based on the triple emission modes (fluorescence, RTP and DF) of the Mn, N-CDs @BA composites, optical patterns were designed and fabricated, and counterfeit-resistant and unclonable anti-counterfeiting and high concealment information encryption were successfully achieved. This work develops a potentially feasible approach for next-generation advanced optical anti-counterfeiting and information encryption systems. Afterglow ; Phosphorescence ; Encryption ; Ultraviolet ; Composite number ; Carbon fibers ; Fluorescence ; Light emission Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Electromagnetic wave absorption materials
Authors: Vsevolod Biryukov | Kamal Choudhary | Timur Bazhirov
Source: arXiv (Cornell University) (article, 2026-02-16)
Field: Materials Science — Materials Chemistry

M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution The rapid advancement of artificial intelligence in materials science requires data standards and data management practices that can capture the complexity of real-world structures, including surfaces, interfaces, defects, and dimensionality reduction. We present M-CODE - Materials Categorization via Ontology, Dimensionality and Evolution - a compact categorization system that links materials-science-specific terminology to a set of reusable concepts as building blocks and provenance-aware transformations. M-CODE classifies structures by dimensionality, structural complexity (from pristine to compound pristine, defective, and processed), and variants that capture common structure creation and evolution approaches. A practical implementation of the categorization is provided in an open-source codebase that includes JSON schemas, examples, and Python and TypeScript types/interfaces, designed to support reproducible dataset generation, validation, and community contributions. Categorization ; Curse of dimensionality ; Python (programming language) ; Codebase ; JSON ; Terminology ; Software portability Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Material Selection and Properties
Authors: Mohammad Khodadad | Ali Shiraee Kasmaee | Mahdi Astaraki | Nicholas Sherck | Hamidreza Mahyar | Soheila Samiee
Source:  (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Benchmark We introduce ChemComp, a benchmark for evaluating compositional multi-hop reasoning in large language models (LLMs) focused on the chemistry domain.To support industrial applications, we develop an automated pipeline that can construct benchmarks from proprietary data sources.The pipeline integrates generative reasoning models, chemical named-entity recognition, and external knowledge bases to build knowledge graphs.Crucially, ChemComp targets domain-specific multi-hop compositional reasoning capabilities rather than factual recall, emphasizing reasoning over memorization in chemical tasks.In this study, we apply this pipeline to recent chemistry literature.Multi-hop questions are generated and refined with domain-expert feedback, resulting in a high-quality dataset and robust evaluation protocols.Using ChemComp, we conduct systematic experiments comparing LLM performance with and without retrieval augmentation, including the idealized scenario of gold-context provision.Our findings reveal that even state-of-the-art models struggle with compositional reasoning: retrieval significantly boosts accuracy, yet reasoning errors persist even under perfect retrieval conditions.These results underscore the limitations of current LLMs and the critical role of retrieval-augmented methods in scientific reasoning.Furthermore, our pipeline is generalizable through domain-specific fine-tuning of the pipeline, enabling the creation of challenging benchmarks across domains and proprietary datasets, advancing the study of multi-hop reasoning in LLMs. Benchmark (surveying) ; Natural language ; Automated reasoning ; Feature (linguistics) ; Semantics (computer science) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Topic Modeling
Authors: Yonghwan Yun | Dongmin Park | Junyoung Choi | Dong Shin Choi | Yousung Jung
Source: Digital Discovery (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Enhancing high-dimensional neural network potential accuracy in OLED systems <i>via</i> element relabeling Accurate atomistic simulations are essential for understanding organic light-emitting diode (OLED) materials in complex condensed-phase environments. Artificial neural network ; Ab initio ; Diode ; OLED ; Field (mathematics) ; Work (physics) Machine Learning in Materials Science ; Organic Light-Emitting Diodes Research ; Organic Electronics and Photovoltaics
Authors: Carina Yi Jing Lim | Zhenan Bao | Lukas Michalek
Source: ChemRxiv (article, 2026-04-02)
Field: Materials Science — Polymers and Plastics

Coupling Nanoscale Viscoelastic Measurements and Infrared Heating of Polymers with AFM-IR In heterogeneous polymer systems, the viscoelastic response of polymers around interfaces or with nanostructured morphology may deviate from bulk values. However, current measurement techniques tend to mask these local variations, which are crucial for understanding and developing these materials. Coupling the high spatial resolution of atomic force microscopy (AFM) with dynamic mechanical analysis (DMA) offers an avenue to circumvent this limitation. We previously demonstrated the advantages of using a focused infrared (IR) laser on an AFM-IR system to locally heat a sample during nanomechanical measurements, with heating modulated by varying the IR repetition rate. [1] Herein, we present a brief demonstration of coupling nDMA with our previously demonstrated chemistry-selective IR heating. We first measured the storage and loss modulus of poly(propylene glycol) (PPG)-4,4′-methylenebis(phenyl urea) (MPU) at varying IR repetition rates, demonstrating a viscoelastic modulus response with typical heating characteristics upon crossing the glass transition temperature. We further demonstrated stress relaxation of an enaminelinked vitrimer possessing significant bond dynamicity at elevated temperatures. Overall, this method is in the preliminary stages of development, and this working paper aims to serve as a basis for feedback and discussion. Viscoelasticity ; Polymer ; Coupling (piping) ; Relaxation (psychology) ; Modulus ; Dynamic mechanical analysis ; Infrared ; Stress relaxation Polymer composites and self-healing ; Force Microscopy Techniques and Applications ; Luminescence and Fluorescent Materials
Authors: Aneta Gądek-Moszczak | Dominik Nowakowski | Norbert Radek
Source: Materials (article, 2026-02-09)
Field: Materials Science — Materials Chemistry

Application of Machine Learning Techniques in the Prediction of Surface Geometry The article presents an attempt by the authors to generate a digital representation of the analyzed surface layer of WC-Co-Al<sub>2</sub>O<sub>3</sub> coating deposited by the ESD method. The WC-Co-Al<sub>2</sub>O<sub>3</sub> surface layer is superhard and abrasion-resistant, significantly increasing the exploitation time of working elements. The authors aim to develop a method for generating series of digital surfaces with similar geometry parameters based on data collected through profilometric analysis. Therefore, the advanced integration of machine learning (ML) techniques with classical statistical approaches for modeling and predicting stochastic processes. While traditional models such as ARMA/ARIMA and hidden Markov models (HMMs) offer mathematical rigor, they often impose assumptions of stationarity and linearity, which limits their application to complex, noisy data. This paper proposes a model for surface geometry generation based on experimental data that combines recurrent neural networks (RNNs) and Monte Carlo simulation. Additionally, the study reviews emerging methods, including generative adversarial networks (GANs) for stochastic simulation and expectation-maximization (EM) algorithms for parameter estimation. An empirical case study on WC-Co-AL<sub>2</sub>O<sub>3</sub> surface geometries demonstrates the effectiveness of ML-stochastic hybrids in capturing both deterministic structures and random fluctuations. The findings underscore not only the benefits but also the limitations of such models, including high computational demands and interpretability challenges, while proposing future research directions toward physics-informed ML and explainable AI. Interpretability ; Surface (topology) ; Representation (politics) ; Generative grammar ; Artificial neural network ; Layer (electronics) ; Monte Carlo method ; Deep learning ; Boltzmann machine Machine Learning in Materials Science ; Tribology and Lubrication Engineering ; Adhesion, Friction, and Surface Interactions
Authors: Takaaki Wajima
Source: Recycling (article, 2026-03-03)
Field: Materials Science — Materials Chemistry

Chemical Conversion of Waste Tire Ash into Layered Double Hydroxide via Acid Leaching for Phosphorus Removal This study investigated a feasible recycling and detoxification process for waste tire ash containing hazardous Zn and Al using acid leaching, followed by layered double hydroxide (LDH) synthesis. The novelty of this work is the direct conversion of a Zn/Al/Fe/Ca-rich real waste system into a phosphorus removal material, in which LDH-related uptake and secondary hydroxyapatite formation cooperatively immobilize phosphorus. Waste tire ash mainly consists of Zn, Al, Fe, Ca, and Si, most of which can be effectively leached with hydrochloric acid (HCl). The optimum leaching conditions for high extraction efficiency involved treatment with 10 M HCl for 10 min at 20 °C (solid–liquid ratio: 50 g/L). Under these conditions, the elution concentrations of Zn and Al from the residue decreased to 0.3 and 0.17 mg/L, respectively, meeting the Japanese leaching standards, whereas the raw ash showed significantly higher values. From the leached solution, LDH-containing products with high phosphorus removal capacity were synthesized at 40 °C for 2 h by adjusting the pH to 11.5. A phosphorus removal performance of 2.0 mmol/g was obtained owing to the formation of hydroxyapatite. The combined process of HCl leaching and LDH synthesis enables the detoxification of waste tire ash and the production of an environmental purification material. Leaching (pedology) ; Hydroxide ; Hazardous waste ; Hydrochloric acid ; Raw material ; Phosphorus ; Toxicity characteristic leaching procedure ; Selective leaching ; Detoxification (alternative medicine) Layered Double Hydroxides Synthesis and Applications ; Phosphorus and nutrient management ; Recycling and utilization of industrial and municipal waste in materials production
Authors: YuHuang Wang | Abhindev Kizhakke Veetil | Alexander Kotsanos | Anna Wang | Fatemeh Hajikarimi | Jacob Fortner | Zhulfaa Zhulficar | Ebenezer Afriyie
Source: Research Square (preprint, 2026-03-05)
Field: Materials Science — Materials Chemistry

Writing DNA Bases into sp3 Quantum Defects Nucleobase ; DNA ; Thymine ; Carbon nanotube ; Guanine ; Covalent bond ; Sequence (biology) ; Molecular biophysics ; Carbon fibers ; Exciton Carbon Nanotubes in Composites ; Molecular Junctions and Nanostructures ; Diamond and Carbon-based Materials Research
Authors: Ruiqi Sun | Ahmed Omran | Muqing Yu | Kyoungjun Lee | Keeyong Lee | Soli Sung | Sangho Oh | Patrick irvin | Jeremy Levy | Chang‐Beom Eom
Source: Advanced Electronic Materials (article, 2026-01-27)
Field: Materials Science — Materials Chemistry

Heterogeneous Integration of Flipped Oxide Heterostructure Membranes for Nanoelectronics ABSTRACT Freestanding complex oxide membranes enable the release and transfer of epitaxial films, offering new design freedoms for next‐generation electronics. While the LaAlO 3 /SrTiO 3 (LAO/STO) heterostructure exhibits remarkable tunable conductivity at its interface, the active interface remains buried beneath the substrate, limiting access to this functionality. Here, we demonstrate how the LAO/STO heterostructure, in membrane form, can be flipped and precisely positioned on silicon and other platforms using polymer‐free micromanipulation. The transferred membranes preserve atomically smooth surfaces, high crystallinity, and key electronic properties. Through the 44‐nm insulating STO layer, ultra‐low‐voltage electron‐beam lithography (ULV‐EBL) writes conductive nanostructures at the now‐accessible STO/LAO interface, offering the potential to function as programmable local gates that modulate charge carriers in the underlying silicon. The platform establishes a general strategy for integrating complex oxide heterostructures with semiconductors, quantum materials, and flexible substrates, enabling new architectures for reprogrammable nanoelectronic devices. Nanoelectronics ; Heterojunction ; Membrane ; Quantum dot ; Oxide ; Graphene ; Lithography ; Semiconductor Electronic and Structural Properties of Oxides ; Semiconductor materials and devices ; Block Copolymer Self-Assembly
Authors: Jingwen Li | Chen Du | Miguel A. Delgado | Garcia-Morales Moises | Ning Lin | Tao Xia | Tobias Amann | Chengqing Yuan | Ke Li
Source: Friction (article, 2026-02-01)
Field: Materials Science — Biomaterials

The application of nanocellulose in eco-friendly lubricants: A review Lubricants are widely employed in mechanical systems to reduce energy loss and the wear induced by friction. With increasing concern for environmental protection, the development of eco-friendly lubricants has become increasingly significant. Nanocellulose, a natural material derived from cellulose, attracts increasing research attention in the field of lubrication due to its renewable, non-toxic, and biodegradable properties. Focusing on this emerging research topic, this state-of-the-art review first analyzes the theoretical basis of applying nanocellulose as a thickening agent in eco-friendly lubricating formulations. The following presents an overview of research advances in cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs), categorized by their applications as additives or thickeners in aqueous, oil, and grease lubricants. This study also highlights the challenges associated with eco-friendly lubricants based on nanocellulose and offers suggestions for future investigations in this field. It is hoped that this review will inform the research direction of eco-friendly lubricants and promote the development of nanocellulose materials for industrial lubrication applications. Nanocellulose ; Lubrication ; Cellulose ; Research development ; Grease Advanced Cellulose Research Studies ; Lubricants and Their Additives ; Power Transformer Diagnostics and Insulation