jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hyunjun Han | Kyuhyun Hwang | Eunhwan Jo | Daeyeon Koh | Bowoong Heo | Jongbaeg Kim
Source: Nature Communications (article, 2026-01-21)
Field: Materials Science — Materials Chemistry

Ice sublimation transfer of vertically aligned carbon nanotubes for residue-free and structure-preserving integration Vertically aligned carbon nanotubes exhibit exceptional properties but typically require high temperature (> 700 °C) for growth, thereby complicating low-temperature device integration. Herein, an ice sublimation-based transfer process is proposed for integrating vertically aligned carbon nanotubes into diverse substrates without structural damage. Ambient vapor is condensed under controlled atmospheric conditions to form a thin and uniform ice layer on the acceptor substrate, serving as a temporary adhesive. After transfer, the ice sublimes, enabling the clean release of vertically aligned carbon nanotubes with no residual contaminants while preserving their pristine vertical architecture. Vertically aligned carbon nanotube micropatterns with feature sizes ranging from 10 µm to 1 cm are successfully transferred, achieving yields exceeding 95%. To broaden its practical applications in electronics, micropatterned vertically aligned carbon nanotubes have been successfully transferred onto various substrates like silicon wafers, polymers, and metals, while retaining their electrical, optical, and thermal properties. Furthermore, the transferred vertically aligned carbon nanotubes function as thermal interface materials that reduced smartphone hotspot temperature by 4 °C compared to commercial thermal interface materials, and as infrared absorbers that enhanced sensor sensitivity by up to 3.43-fold. This sublimation-based transfer method expands the potential for direct vertically aligned carbon nanotube integration in next-generation electronic systems. Carbon nanotube ; Sublimation (psychology) ; Thermal ; Silicon ; Carbon fibers ; Chemical vapor deposition ; Potential applications of carbon nanotubes ; Nanotube ; Nanoscopic scale Carbon Nanotubes in Composites ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials
Authors: ELLA R. JENNINGS | HANNAH S. TODD | EMILIE PERELMAN | COURTNEY B. LIMEHOUSE | HUNTER J. SAVAGE | Marcello Forconi
Source: ChemRxiv (article, 2026-04-06)
Field: Chemistry — Organic Chemistry

A TALE OF TWO HETEROCYCLES: HOW OXYGEN AND SULFUR SHAPE DIVERGENT KEMP REACTIVITY The Kemp elimination is a well-studied reaction that proceeds through the deprotonation of the carbon-3 of benzisoxazoles, followed by irreversible ring opening by cleavage of the labile O-N bond.The base-catalyzed reaction is concerted, with no detectable intermediate.Due to the similarity in composition and structure, benzisothiazoles are also candidates for Kemp elimination reactions; however, little information was previously available on such compounds.We found that benzisothiazoles also undergo Kemp elimination, and we have fully characterized the Kemp product.As previously observed with benzisoxazoles, reactions of benzisothiazoles are significantly accelerated by polar, aprotic solvents and by the presence of electron-withdrawing groups (EWG) on the six-membered ring.In mixed water/DMSO systems, we found a strong inverse linear relationship between the logarithm of the second-order rate constant and the molar fraction of water for both benzisoxazoles and benzisothiazoles.Extrapolations from the observed data to neat solvent suggest that the hydroxide ion is 14 orders of magnitude more efficient as a catalyst in DMSO than in pure water for benzisoxazoles and 7 orders of magnitude more efficient for benzisothiazoles.Electrostatic potential (ESP) analyses of the products, used as proxies for late-transition states, support a picture in which oxygen-based systems develop more localized negative charge that benefits disproportionately from strong solvent dipoles and electron-withdrawing substituents, whereas sulfur allows broader charge delocalization and thus a muted response.These findings rationalize the different solvent and substituent sensitivities of the two scaffolds and provide guidance for selecting Kemp substrates when benchmarking general-base catalysis and de novo enzyme designs Reactivity (psychology) ; Deprotonation ; Hydroxide ; Substituent ; Solvent ; Catalysis ; Reaction rate constant ; Sulfur Synthesis of Tetrazole Derivatives ; Chemical Reaction Mechanisms ; Chemical Reactions and Mechanisms
Authors: Ian Geiger | Penghui Cao | Timothy J. Rupert
Source: Materials Advances (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Local chemical order suppresses grain boundary migration under irradiation in CrCoNi Complex concentrated alloys with intrinsic chemical heterogeneity are promising candidates for nuclear applications, where local chemical order can strongly influence defect evolution under irradiation. Grain boundaries also contribute to radiation... Grain boundary ; Irradiation ; Chemical stability ; Population ; Radiation damage ; Molecular dynamics ; Crystallographic defect ; Radiation ; Alloy Fusion materials and technologies ; Nuclear Materials and Properties ; Nuclear materials and radiation effects
Authors: Min Li | Xiaoyu Wu | Hongyun Wang | Jiao Bai | Xi-Qiao Feng
Source: Journal of Applied Physics (article, 2026-01-23)
Field: Materials Science — Materials Chemistry

Dimensional analysis-guided neural network for nanoindentation tests of composites Machine learning holds a great promise for applications in the experimental characterization of the mechanical properties of composites. However, conventional neural networks often suffer from low training efficiency, limited predictive accuracy, and strong dependence on the amount and quality of experimental data. In this paper, we propose a generalizable framework, referred to as a dimensional analysis-guided neural network (DANN), by integrating dimensional analysis with the neural network architecture. Through the introduction of a dimensionless transformation layer, DANN converts both the inputs and outputs into dimensionless groups, thereby embedding the principle of physical similarity into the learning process. The framework is validated via an inverse indentation problem involving fiber-reinforced composites. In comparison with conventional neural networks, DANN demonstrates higher accuracy, improved data efficiency, and greater robustness. Thus, DANN provides a physics-informed, data-efficient, and scalable approach for addressing complex problems in solid mechanics. Artificial neural network ; Nanoindentation ; Dimensionless quantity ; Characterization (materials science) ; Inverse problem ; Indentation ; Inverse ; Similarity (geometry) Machine Learning in Materials Science ; Model Reduction and Neural Networks ; Force Microscopy Techniques and Applications
Authors: Mehdi Feizpour | Ignaas S M Jimidar | Mitch T J de Waard | Gert Desmet | Heidi Ottevaere
Source: Small Methods (article, 2026-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

SERS Substrate Fabrication via Rapid Triboelectrification‐Driven Self‐Assembly of Close‐Packed Colloidal Monolayers Surface-enhanced Raman spectroscopy (SERS) amplifies Raman signals on nanostructured metallic surfaces, enabling the detection of trace analytes. There has been a spur on the precise fabrication of conventional planar SERS substrates with high performance and reproducibility. Common methods, such as ion beam and colloidal lithography, provide high-quality substrates but are often limited by high costs, complex processes, and challenges associated with mass manufacturing. Triboelectrification-driven self-assembly of dry colloidal powder offers a promising dry approach to attain ordered monolayer colloidal particles in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo><</mml:mo> <mml:mn>20</mml:mn></mml:mrow> <mml:annotation>$<20$</mml:annotation></mml:semantics> </mml:math> s rapidly. Here, we use this approach to produce high-performance SERS substrates with reproducible signals. By optimizing particle size and gold coating thickness, we found that self-assembled 500 nm particles with a 50 and 65 nm Au layer achieved a maximum enhancement factor (EF) of 1 × 10, and limit of detection (LOD) of 33-36 nM, in our initial characterization study without coordinate translation. Compared with commercial substrates (Silmeco; Hamamatsu) under matched conditions, this corresponds to 20-24 × lower LOD (33-36 nM vs. 680-800 nM) and 10-100 × higher maximum EF. These results highlight triboelectrification's ability to efficiently and cost-effectively produce homogeneous monolayers, offering a promising alternative to more complex or expensive methods and unlocking the opportunity for large-scale SERS substrate production with biosensing, diagnostics, and chemical detection applications. Fabrication ; Substrate (aquarium) ; Raman spectroscopy ; Surface-enhanced Raman spectroscopy ; Colloid ; Monolayer ; Particle (ecology) ; Coating Gold and Silver Nanoparticles Synthesis and Applications ; Pickering emulsions and particle stabilization ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Cecilia García-Guzmán | Stefano Cinti | Eduardo Coutiño‐González | Eden Morales‐Narváez
Source: Chemical Communications (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Silver clusters embedded within zeolites for innovative (bio)sensing platforms Silver clusters embedded within zeolites combine the molecular-like optical and electrochemical properties of sub-nanometric clusters with the structural robustness, porosity, and ion-exchange capacity of crystalline frameworks. Their unique features, such as tunable emission with high quantum yields, large Stokes shifts, redox activity, electrocatalytic behavior, and sensitivity to external stimuli, enable versatile sensing capabilities. These composites have already demonstrated remarkable versatility, enabling optical detection of water vapor, volatile amines, oxygen, and biomolecules, as well as electrochemical sensing of hydrogen peroxide, tryptophan, and chloride ions. Their integration into immunosensors, optical hydration switches, and electrochemical paper-based strips highlights their disruptive potential for portable and wearable devices. However, key challenges remain, including controlled nucleation, tailoring excitation-emission properties, and ensuring stability after biorecognition functionalization and device integration. This review discusses the structure-property relationships that govern the optical and electrochemical responses of silver clusters embedded within zeolites, summarizes recent advances in (bio)sensing applications, and outlines the challenges that must be overcome for their translation into scalable, robust, and sustainable devices. With continued progress in material design, surface functionalization, and integration within microfluidic and data analysis platforms, silver cluster-zeolite composites hold strong promise to evolve from laboratory prototypes into portable technologies for diagnostics and environmental monitoring, displaying significant promises for next-generation point-of-care and wearable sensors. Wearable computer ; Electrochemistry ; Wearable technology ; Microfluidics ; Surface modification ; Optical sensing ; Quantum dot Nanocluster Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Carbon and Quantum Dots Applications
Authors: Songül OĞLAKÇI | Cevat Aksu | Murat Çanli | Nihat Arikan
Source: Journal of Electronic Materials (article, 2026-03-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ab Initio Modeling of MgXIr2 (X = Al, Ga, In, Si): A Multifaceted Study on Physical Properties Abstract We present a comprehensive ab initio investigation of the structural, electronic, mechanical, thermodynamic, and vibrational properties of Mg X Ir 2 ( X = Al, Ga, In, Si) full-Heusler compounds using density functional theory (DFT). Structural optimization reveals that all four compounds stabilize in the cubic Fm3m phase, with lattice parameters showing a monotonic increase from X = Si to In. Electronic band structure calculations demonstrate metallic behavior, characterized by Ir- d orbital dominance near the Fermi level. Mechanical properties, including elastic constants (C 11 , C 12 , C 44 ), confirm thermodynamic stability and ductile behavior, with MgSiIr 2 exhibiting the highest bulk modulus (218 GPa). Phonon dispersion spectra show no imaginary frequencies, verifying dynamic stability across all compositions. Thermodynamic analysis via quasi-harmonic approximation predicts Debye temperatures ranging from 420 K (MgInIr 2 ) to 580 K (MgSiIr 2 ), correlating with bond stiffness trends. Vibrational modes indicate distinct optical phonon splitting is the highest in MgSiIr 2 owing to mass contrast. The Grüneisen parameters suggest anharmonic effects are most pronounced in MgInIr 2 . Comparative analysis highlights MgSiIr 2 as the most promising candidate for high-temperature applications, balancing mechanical strength and thermal stability. This work provides foundational insights into experimental synthesis and targeted applications in catalysis or spintronics. Given magnesium’s osteogenic properties, these alloys also hold significant potential in regenerative medicine, particularly for repairing osseous defects triggered by degenerative disorders or bone cancer. Phonon ; Anharmonicity ; Ab initio ; Debye model ; Density functional theory ; Bulk modulus ; Electronic band structure ; Ab initio quantum chemistry methods ; MAX phases ; Fermi level Heusler alloys: electronic and magnetic properties ; Boron and Carbon Nanomaterials Research ; MXene and MAX Phase Materials
Authors: Fahad Abdullah Alotaibi | Fatimah I Alqannas | Abdullah H. Alluhayb | Rehan Ali | Sayed M. Saleh
Source: JOURNAL of QASSIM UNIVERSITY FOR SCIENCE (article, 2026-02-24)
Field: Materials Science — Materials Chemistry

Green Synthesis of Silver Nanoparticles from Desert Plant Extracts from the Qassim Region for Optical Sensing Applications: A Comprehensive Review The synthesis of luminous metal nanoclusters (MNCs) from natural plant sources is a long-lasting and cost-effective approach to developing improved optical sensors. This thorough study examines the potential of two desert plant species native to the Qassim region of Saudi Arabia as biomediators for the green synthesis of silver nanoclusters (AgNCs) for optical sensing. Desert plants accumulate a wide range of secondary metabolites, such as flavonoids, phenolic compounds, and tannins, that are effective at stabilizing and reducing MNCs. Silver nanoclusters exhibit strong photoluminescence, significant Stokes shifts, and high selectivity for heavy metal ions, making them ideal for building inexpensive, easy-to-use optical sensors. This review brings together what we know about (1) the botanical and phytochemical properties of plant extracts from the Qassim region, (2) the principles and mechanisms of green synthesis of AgNCs using plant extracts, (3) the optical properties and sensing mechanisms of luminescent AgNCs, (4) recent advances in AgNC-based fluorescence sensors for finding toxic metal ions and biomolecules, and (5) the possible scale-up and practical use of plant-derived AgNCs in clinical and environmental settings. The focus is on creating optical sensors that are sensitive, selective, and reversible, with detection limits in the nanomolar range, by employing fluorescence quenching and amplification methods. The combination of traditional ethnobotanical knowledge with current analytical chemistry and nanotechnology demonstrates that it is possible to develop new optical biosensing platforms using plants native to Saudi Arabia. Nanoclusters ; Silver nanoparticle ; Fluorescence ; Plant species ; Phytochemical ; Optical sensing Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Boron and Carbon Nanomaterials Research
Authors: H. Bu | Wenwu Jiang | Penghua Ying | Ting Liang | Zheyong Fan | Wengen Ouyang
Source: Journal of the Mechanics and Physics of Solids (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Modular hybrid machine learning and physics-based potentials for scalable modeling of Van der Waals heterostructures van der Waals force ; Stacking ; Heterojunction ; Scalability ; Thermal ; Decoupling (probability) ; Bilayer ; Boron nitride ; Modular design 2D Materials and Applications ; Machine Learning in Materials Science ; Graphene research and applications
Authors: Darshan Chikkanayakanahalli Mukunda | Ritam Dadhara | Rishikesh Pandey | Ram Prasad | Surya Pratap Singh
Source: Nanotechnology Reviews (article, 2026-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Nanoparticles as SERS substrates: recent progress in hormone sensing Abstract Surface-enhanced Raman spectroscopy (SERS) has enabled the, ultrasensitive, and real-time monitoring of clinically significant hormones and related health abnormalities such as diabetes, thyroid dysfunction, infertility, stress etc. Plasmonic nanoparticles (PNPs) specifically, silver (Ag) and gold (Au), provide the foundation for signal enhancement due to their localized surface plasmon resonance (LSPR) and tunable shapes (e.g. spherical, rod, wire, triangle etc.). Recent studies have demonstrated the potential applications of non-plasmonic NPs (Silicon and graphene) and their composites in sensitive detection of hormones in complex biological matrices. Together, the SERS, can detect a wide range of hormones such as insulin, cortisol, dopamine (DA), serotonin (ST), progesterone (P4), etc. at nanomolar (nM) to attomolar (aM) concentrations in complex biological fluids [saliva, blood plasma, serum, sweat (transdermal), cell lysate) and cells. Bimetallic NPs (Ag@Au, Au@Ag), nanocomposites (Si@Ag, Si@Au) have been strategically fabricated to generate high-density electromagnetic hotspots. Further, coupling these substrates with molecularly imprinted polymers (MIPs), antibodies (Ab), aptamers, Raman reporter molecules (RRM) and flexible supports (silicon wafers, paper, PVC/SEBS, PDMS, electrodes) have improved specificity, biocompatibility, and point-of-care (POC) utility of SERS. Thus, the current review evaluates the future diagnostic potential of NPs as SERS substrates for hormone biosensing, highlighting rational nanostructure design, selective surface functionalization, validation in complex matrices and quantitative comparison, reference standards, and clinically translatable SERS platforms across studies. Nanoparticle ; Surface plasmon resonance ; Surface-enhanced Raman spectroscopy ; Plasmon ; Nanostructure ; Hormone ; Silver nanoparticle ; Raman spectroscopy ; Colloidal gold Gold and Silver Nanoparticles Synthesis and Applications ; Melamine detection and toxicity ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Md Imran Hossain | Dong Kee Yi | Sanghyo Kim
Source: Applied Sciences (article, 2026-01-09)
Field: Materials Science — Materials Chemistry

Recent Advances in Nanomaterial-Based and Colorimetric Technologies for Detecting Illicit Drugs and Environmental Toxins The global surge in illicit drug use has intensified the demand for rapid, portable, and reliable on-site detection technologies. Traditional analytical approaches, such as laboratory-based instrumentation and biological sample assays, while accurate, are often constrained by high costs, long processing times, and the need for specialized equipment, rendering them unsuitable for field applications. This review highlights recent progress in chemical sensor technologies designed for the detection of widely misused drugs such as methamphetamine, cocaine, fentanyl, and heroin. Parallel advancements in the detection of environmental contaminants, particularly concerning micro- and nanoplastics, are also discussed. Emerging sensing platforms employing nanoparticle functionalization, graphene nanosheets, MXenes, metal–organic frameworks (MOFs), and supramolecular colorimetric assays demonstrate significant potential for achieving high sensitivity, selectivity, and operational simplicity in portable formats. These innovations enable real-time detection with minimal user expertise, thereby advancing applications in forensic analysis, environmental monitoring, and public health protection. The review also addresses current limitations related to detection accuracy, reagent stability, and matrix interferences and proposes future directions for optimizing sensor robustness and performance under diverse field conditions. Emerging technologies ; Drug detection ; Human health ; Rendering (computer graphics) ; Robustness (evolution) ; Instrumentation (computer programming) Luminescence and Fluorescent Materials ; Forensic Toxicology and Drug Analysis ; Carbon and Quantum Dots Applications
Authors: Rafita Erli Adhawiyah | Jungchul Lee
Source: Micro and Nano Systems Letters (article, 2026-02-16)
Field: Chemistry — Electrochemistry

Nanomaterial-enhanced sensors for trace heavy metal ion detection: a review of electrochemical and optical methods Heavy metal ions (HMIs), such as mercury (Hg), lead (Pb), cadmium (Cd), arsenic (As), and chromium (Cr), are a serious environmental issue due to their toxicity, bioaccumulation, and long-term persistence, making it necessary to develop sensitive and selective detection technologies. Laboratory-based methods, such as atomic absorption spectroscopy, provide high accuracy, but their point-of-need deployment is limited by their reliance on large equipment and complicated sample preparation. This review highlights the critical role of nanomaterial in sensing platforms in overcoming these limitations and advancements across electrochemical and optical detection techniques. The integration of nanomaterials-including carbon-based, metallic-based, silicon-based, and quantum dots-is shown to significantly enhance sensor performance through increased surface area, electron transfer efficiency, and plasmonic effects. Despite this progress, challenges such as matrix interference, ensuring signal reproducibility, and developing scalable fabrication methods remain. Future research will focus on developing hybrid, multiplexed, and antifouling sensor architectures integrated with digital technologies like the Internet of Things (IoT) to realize next-generation, ultra-sensitive HMIs monitoring platforms. Software deployment ; Arsenic ; Fabrication ; Nanomaterials ; Mercury (programming language) ; Scalability ; Microscale chemistry ; Electrochemistry ; Nanosensor Electrochemical Analysis and Applications ; Analytical Chemistry and Sensors ; Molecular Sensors and Ion Detection