jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ayoub Koufi | Younes Ziat | Hamza Belkhanchi | Noureddine Elmeskini
Source: Hydrogen (article, 2026-03-12)
Field: Materials Science — Materials Chemistry

Physical Characteristics of Hydride Perovskites XZrH3 (X = Mg, Ca, Sr, and Ba) as Materials for Hydrogen Storage: A First-Principles Investigation In this study, density functional theory (DFT) within the generalized gradient approximation (GGA) is employed to investigate the structural, electronic, mechanical, and thermoelectric properties of perovskite hydrides XZrH3 (X = Mg, Ca, Sr, Ba). Mechanical stability and ductility are evaluated through the Cauchy pressure, Pugh’s ratio, and Poisson’s ratio, all of which point to ductile behavior with a dominant ionic-bonding character. Electronic structure calculations reveal metallic behavior arising from band overlap at the Fermi level. Equilibrium energy–volume data are fitted with the Murnaghan equation of state, and transport coefficients are extracted using the BoltzTraP package as implemented in WIEN2k. The absence of a band gap and the overlap between valence and conduction bands confirm conductor-like behavior. Lattice thermal conductivity for MgZrH3, CaZrH3, SrZrH3, and BaZrH3 increases monotonically with temperature. Overall, the results identify MgZrH3 in particular as a promising candidate for thermoelectric devices and solid-state hydrogen storage, thereby supporting progress toward a sustainable hydrogen economy. Thermoelectric effect ; Hydrogen ; Density functional theory ; Perovskite (structure) ; Hydride ; Electronic band structure ; Fermi level ; Electronic structure ; Electrical resistivity and conductivity Hydrogen Storage and Materials ; Thermal Expansion and Ionic Conductivity ; Heusler alloys: electronic and magnetic properties
Authors: Tamanna Yakub | Anupama Asthana | Sunita Sanwaria | Ajaya Kumar Singh
Source: ChemistrySelect (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Graphene–ZnO–β‐Cyclodextrin Nanohybrid: Synthesis, Photocatalytic, and Antimicrobial Properties ABSTRACT This study reports the synthesis and characterization of a novel GO/ZnO/β‐CD nanocomposite for efficient photocatalytic degradation of methylene blue (MB) dye and antibacterial applications. The nanocomposite was synthesized via a facile hydrothermal method and extensively characterized through FTIR, XRD, SEM, TEM, EDX, and BET analyses, confirming successful integration of all components with characteristic functional groups preserved. XRD patterns revealed the hexagonal wurtzite crystalline structure of ZnO nanoparticles with average crystallite size of 27–32 nm, while SEM and TEM imaging demonstrated hierarchical morphology with uniformly distributed ZnO nanoparticles (15–30 nm) anchored onto crumpled GO. EDX analysis confirmed optimal elemental composition of 65.8 wt% Zn, 22.1 wt% O, and 11.21 wt% C. The GO/ZnO/β‐CD nanocomposite exhibited superior photocatalytic performance, achieving 99% MB degradation within 60 min under UV irradiation at optimal conditions (MB concentration: 15 ppm, catalyst loading: 0.03 g/20 mL), significantly outperforming GO/ZnO (97%) and GO (95%) alone. Kinetic analysis revealed the degradation process follows pseudo‐second‐order kinetics ( k 2 = 0.0289 g mg −1 min −1 , R 2 = 0.993) compared to pseudo‐first‐order ( k 1 = 0.035 min −1 , R 2 = 0.995), confirming chemisorption as the predominant mechanism. The nanocomposite demonstrated remarkable antibacterial activity against both Escherichia coli and Staphylococcus aureus , producing inhibition zones of 19 and 22 mm respectively, surpassing penicillin control against S. aureus . Recyclability studies indicated sustained performance over four consecutive cycles, maintaining 68% efficiency in the fourth cycle. Nanocomposite ; Wurtzite crystal structure ; Crystallite ; Photocatalysis ; Hydrothermal circulation ; Methylene blue ; Nanoparticle ; Catalysis Nanoparticles: synthesis and applications ; Advanced Photocatalysis Techniques ; TiO2 Photocatalysis and Solar Cells
Authors: Jean-François Dechézelles | Yaoyao Feng | Kang Wang | Marc Pera-Titus | Véronique NARDELLO-RATAJ
Source: National Science Review (article, 2026-03-11)
Field: Materials Science — Materials Chemistry

Hybrid Pickering emulsifiers (HYPIEs) via synergistic water/oil interfacial interactions: enhanced properties and applications Abstract Emulsions stabilized by surface-active solid particles, known as Pickering emulsions, offer advantages over conventional emulsions, including enhanced stability, biocompatibility, and the potential recyclability of particles. These attributes underpin their growing use in cosmetics, food, catalysis, enhanced oil recovery, and pharmaceuticals. However, single-particle emulsifiers often lack the versatility required to precisely control emulsion formation, stability, and morphology. To address these limitations, hybrid Pickering emulsifiers (HYPIEs), which combine solid particles with secondary emulsifiers, have emerged as a powerful alternative. By improving interfacial wettability and adsorption, HYPIEs exhibit superior performance compared with their individual components and enable the co-adsorption of species with antagonistic properties, facilitating the design of smart emulsifying systems. This review categorizes HYPIEs based on synergistic combinations, including particle-particle (i.e. ‘hard’-‘hard’, ‘hard’-‘soft’, ‘soft’-‘soft’), particle-(bio)surfactant and particle-(bio)polymer systems. We elucidate the mechanisms underlying their enhanced interfacial behavior and highlight the diverse interfacial architectures that can be achieved. Finally, we discuss emerging applications of HYPIEs in shaping oil–water interfaces for catalysis, biomedicine, cosmetics, personal care, and food products, and outline current challenges and future perspectives, including strategies for tailoring synergistic functionalities and computational approaches for in silico HYPIE design. Pickering emulsion ; Wetting ; Emulsion ; Solid surface Pickering emulsions and particle stabilization ; Innovative Microfluidic and Catalytic Techniques Innovation ; Proteins in Food Systems
Authors: Daniel Chukwuma Okolo | JohnKennedy Anumudu | NICODEMUS CHIDERA OMEKAWUM | Agha Inya Ndukwe
Source: Discover Electrochemistry. (article, 2026-04-06)
Field: Materials Science — Materials Chemistry

Fundamental and sustainability of nanoengineered green corrosion inhibitors Corrosion of industrial metals remains a critical economic and environmental challenge, with traditional inhibitors often posing toxicity and non-degradability risks. This review quantitatively examines the synergy between nanotechnology and green chemistry in developing nanoengineered green corrosion inhibitors (NGIs). Electrochemical analyses reveal that the integration of plant extracts with nanomaterials enhances inhibition efficiency significantly: non-nano plant extracts achieve efficiencies of approximately 69–96.41%, while nanoengineered systems consistently reach approximately 85–99% in aggressive media (e.g., HCl, H2SO4). For instance, green-synthesized silver nanoparticles (AgNPs) from tobacco extract provide 98% protection for carbon steel in 0.5 M HCl, while SiO2 nanoparticles from rice husk ash achieve 99% inhibition. These improvements are attributed to increased surface coverage, enhanced charge transfer resistance (e.g., from 200 to 359.3Ω·cm2 with ZnO-NPs), and reduced corrosion current densities. Nanocoatings and nanocomposites further improve barrier properties, reducing porosity and extending service life. However, challenges in scalability, nanoparticle dispersion, and long-term durability under real-world conditions remain. This review highlights the > 90% efficiency trends of NGIs, supported by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), and surface characterization data, positioning them as sustainable, high-performance alternatives to conventional inhibitors. Sustainability ; Corrosion ; Human health ; Renewable energy Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Electrodeposition and Electroless Coatings
Authors: DEEPIKA | YOGITA TYAGI | Srishti Morris | ARTI KORI
Source: International Journal of Applied Pharmaceutics (article, 2026-01-07)
Field: Materials Science — Materials Chemistry

RECENT ADVANCES IN NANO SPONGE TECHNOLOGY: FROM SYNTHESIS TO APPLICATIONS Nanosponges (NSs) are an emerging class of advanced nanomaterials with wide-ranging applications in healthcare, environmental protection, catalysis, and sensing. Composed of polymers, inorganic compounds, or hybrid structures, they possess a large surface area, adjustable pore size, and tunable chemical properties, allowing precise adaptation to various environments. These features make them highly effective for drug delivery, pollutant adsorption, and catalytic processes. Notably, NSs exhibit exceptional drug loading efficiencies, reaching up to 98%, such as 95% for cyclodextrin-based formulations encapsulating the anticancer drug doxorubicin. Their enhanced performance is primarily due to their porous network and ability to form stable inclusion complexes with hydrophobic molecules. In environmental applications, mesoporous silica NSs have shown high efficacy in removing toxic heavy metals like chromium (VI) and lead (II) from wastewater. To achieve optimal performance, several advanced characterization techniques are employed. In Situ transmission electron microscopy (TEM) allows real-time visualization of structural evolution, while X-ray diffraction (XRD) provides data on crystallinity and phase transitions. Dynamic light scattering (DLS) determines particle size distribution and stability, and Zeta Potential Analysis assesses surface charge interactions. Moreover, fourier transform infrared (FT-IR) Spectroscopy identifies chemical bonding and drug–carrier interactions, whereas thermogravimetric analysis (TGA) provides insights into thermal stability and composition. Ongoing research continues to refine the synthesis, functionalization, and application of nano sponges, enabling the development of more efficient, sustainable, and multifunctional nanostructures that address critical challenges in medicine, environmental remediation, and advanced materials science. Thermogravimetric analysis ; Nanomaterials ; Characterization (materials science) ; Drug delivery ; Mesoporous silica ; Nanoparticle ; Nanostructure ; Mesoporous material ; Thermal stability Mesoporous Materials and Catalysis ; Aerogels and thermal insulation ; Magnesium Oxide Properties and Applications
Authors: Dr. Prity Sharma | Dr. Chandan Singh | Teena Pareek
Source: INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

NANOCARBON ARCHITECTURES FOR SUSTAINABLE ENERGY SYSTEMS: GRAPHENE, CARBON NANOTUBES, AND CARBON QUANTUM DOTS IN STORAGE AND CONVERSION TECHNOLOGIES UGC-CARE list, New UGC-CARE Reference List, UGC CARE Journals, ugc care list of journal, ugc care list, UGC Approved list, list of ugc approved journal, ugc approved journal,IJRAR - international Research Journal,IJRAR.ORG,Ijrar.org, International Journal of Research and Analytical Reviews (IJRAR) , UGC Approved journal, ugc approved,ugc, ugc certify, publish free of cost, free publication, UGC and ISSN Approved , International Peer Reviewed, Open Access Journal , e ISSN 2348 –1269, Print ISSN 2349-5138, ISSN: 2348 –1269, Impact Factor : 5.75 , E- journal, Low Cost INR 500, Free Publication Quantum dot ; Carbon fibers ; Sustainable energy ; Carbon quantum dots ; Energy transformation ; Energy storage ; Carbon nanotube Carbon Nanotubes in Composites ; Chemical and Physical Properties of Materials ; Boron and Carbon Nanomaterials Research
Authors: Jinfeng Ji | Jinfeng Zhang | Haitao Zhou | Congcong Li | Xiaolong Zhao | Fei Xiao | Gang Tang
Source: Journal of Applied Polymer Science (article, 2026-02-10)
Field: Materials Science — Polymers and Plastics

Development of Phosphorus‐Doped Carbon Nitride‐Coated Ammonium Polyphosphate Flame Retardant and Its Effect on the Fire Safety of Epoxy Resins ABSTRACT Epoxy resin (EP) is widely used in fields such as building materials, aerospace, and transportation; however, its high fire risk is considered the main factor limiting its practical use. To address this issue, ammonium polyphosphate (APP) is coated with phosphorus‐doped graphitic carbon nitride (PCN) to prepare PCN@APP. When compared with pure EP, the composite with high‐loading APP is observed to exhibit reduced mechanical properties. In contrast, the composite containing modified APP is shown to demonstrate enhanced mechanical performance. Specifically, the flexural strength and tensile strength are increased by 9.13% and 45.09%, respectively. With the incorporation of 20 wt% PCN@APP, significant reductions are achieved in key fire parameters: the peak heat release rate (PHRR), total heat release (THR), peak smoke production rate (PSPR), total smoke production (TSP), peak CO production (PCOP), and peak CO 2 production (PCO 2 P) are lowered by 66.6%, 66.2%, 71.8%, 78.7%, 65.5%, and 68.6%, respectively. TG‐IR results indicate that after adding the PCN@APP filler, the absorbance of CO and NO is reduced by 80.2% and 67.9%, respectively, demonstrating significant suppression of fire toxicity. This work is considered to provide valuable inspiration for the straightforward design of APP‐based flame retardants, thereby enhancing their flame‐retardant efficiency. Ammonium polyphosphate ; Fire retardant ; Smoke ; Epoxy ; Flexural strength ; Ultimate tensile strength ; Composite number ; Fire safety Flame retardant materials and properties ; Fiber-reinforced polymer composites ; Fire dynamics and safety research
Authors: Alemayehu Kidanemariam | SungBo Cho
Source: Sensors (article, 2026-01-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design and Applications of MOF-Based SERS Sensors in Agriculture and Biomedicine Metal-organic framework (MOF)-based surface-enhanced Raman scattering (SERS) sensors have emerged as a versatile platform for high-sensitivity and selective detection in agricultural, environmental, and biomedical applications. By integrating plasmonic nanostructures with tunable MOF architectures, these hybrid systems combine ultrahigh signal enhancement with molecular recognition, analyte preconcentration, and controlled hotspot distribution. This review provides a comprehensive overview of the fundamental principles underpinning MOF-SERS performance, including EM and chemical enhancement mechanisms, and highlights strategies for substrate design, such as metal-MOF composites, plasmon-free frameworks, ligand functionalization, and hierarchical or core-shell architectures. We further examine their applications in environmental monitoring, pesticide and contaminant detection, pathogen identification, biomarker analysis, and theranostics, emphasizing real-sample performance, molecular selectivity, and emerging integration with portable Raman devices and AI-assisted data analysis. Despite notable advances, challenges remain in reproducibility, quantitative reliability, matrix interference, scalability, and biocompatibility. Future developments are likely to focus on rational MOF design, sustainable fabrication, intelligent spectral interpretation, and multifunctional integration to enable robust, field-deployable sensors. Overall, MOF-based SERS platforms represent a promising next-generation analytical tool poised to bridge laboratory innovation and practical, real-world applications. Biomedicine ; Underpinning ; Raman scattering ; Plasmon ; Scalability ; Chemical sensor ; Scope (computer science) Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Nanomaterials in Catalysis
Authors: P. Durgadevi | Koyeli Girigoswami | Chandni Thakkar | Agnishwar Girigoswami
Source: Photochem (article, 2026-03-25)
Field: Materials Science — Materials Chemistry

Fluorescence-Based Neurotransmitter Detection: Nanomaterial Engineering and Bioanalytical Advances at the Nano–Neuro Interface All forms of neural communications, from cognition to emotion, are regulated by neurotransmitters, which are otherwise the chemical language of the brain. Precise detection of these neurotransmitters is essential for the perception of neurophysiology and diagnosis of neurodegenerative diseases as well. Among the existing techniques for the detection of these molecules, fluorescence sensing is evolving as a powerful approach in terms of high sensitivity, rapid response, and real-time visualization of the chemical events occurring in the neural system. In recent years, nanomaterials have transformed this field by integrating tunable optical properties, excellent photostability, and modifiable surface chemistry into biocompatible nanostructures. We summarize the recent advances of these architectures to show how the material type and dimensionality, as well as the surface functionality, play roles in sensing through the mechanisms of Förster resonance energy transfer (FRET), photoinduced electron transfer (PET), inner filter effect (IFE), and aggregation-induced emission (AIE). The discussion has also been extended to the correlation of fluorescence modulation with the selectivity and sensitivity in the mechanism-to-function relationship. The potential utility of such innovative technologies, including artificial intelligence, spectral deconvolution analysis via big data algorithms, and chip-integrated sensing, was explored as a means to enable real-time neurochemical detection. This converging area of nanotechnology and neuroscience leaves a mark not just in analytical accuracy, but also parallels human brain rhythms. Biocompatible material ; Nanomaterials ; Interface (matter) ; Bioanalysis ; Biosensor ; Förster resonance energy transfer Luminescence and Fluorescent Materials ; Quantum Dots Synthesis And Properties ; Carbon and Quantum Dots Applications
Authors: Fraser Birks | Matthew Nutter | Thomas D. Swinburne | James R. Kermode
Source: npj Computational Materials (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

Efficient and accurate spatial mixing of machine learned interatomic potentials for materials science Machine-learned interatomic potentials can offer near first-principles accuracy but are computationally expensive, limiting their application to large-scale molecular dynamics simulations. Inspired by quantum mechanics/molecular mechanics methods, we present ML-MIX, a CPU- and GPU-compatible LAMMPS package to accelerate simulations by spatially mixing interatomic potentials of different complexities, allowing deployment of modern MLIPs even under restricted computational budgets. We demonstrate our method for ACE, UF3, SNAP and MACE potential architectures and demonstrate how linear 'cheap' potentials can be distilled from a given 'expensive' potential, allowing close matching in relevant regions of configuration space. The functionality of ML-MIX is demonstrated through tests on point defects in Si, Fe and W-He, in which speedups of up to 11× over ~8000 atoms are demonstrated, without sacrificing accuracy. The scientific potential of ML-MIX is demonstrated via two case studies in W, measuring the mobility of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>b</mml:mi> <mml:mo>=</mml:mo> <mml:mfrac><mml:mrow><mml:mn>1</mml:mn></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:mfrac> <mml:mo>〈</mml:mo> <mml:mn>111</mml:mn> <mml:mo>〉</mml:mo></mml:mrow> </mml:math> screw dislocations with ACE/ACE mixing and the implantation of He with MACE/SNAP mixing. The latter returns He reflection coefficients which (for the first time) match experimental observations up to an He incident energy of 80 eV-demonstrating the benefits of deploying state-of-the-art models on large, realistic systems. Interatomic potential ; Mixing (physics) ; Reflection (computer programming) ; Limiting ; Point (geometry) ; Molecular dynamics ; Matching (statistics) Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; Electrocatalysts for Energy Conversion
Authors: Osman Mamun | Chenlu Yang | Shuwen Yue
Source: Digital Discovery (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Deep graph kernel learning for material &amp; atomic level uncertainty quantification in adsorption energy prediction Deep graph kernel learning combines GNN backbones with Gaussian processes to deliver calibrated, atomic-level uncertainty quantification for adsorption energy prediction, outperforming ensemble and evidential methods for catalyst discovery. Uncertainty quantification ; Artificial neural network ; Density functional theory ; Energy (signal processing) ; Kernel (algebra) ; Graph ; Measurement uncertainty Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; CO2 Reduction Techniques and Catalysts
Authors: Jinlei Cui | Yuting Li | Da-Jiang Liu | Marco Mais | Jie M. Zhang | Long Qi | Aaron D. Sadow | Takeshi Kobayashi
Source: Inorganic Chemistry Frontiers (article, 2026-01-01)
Field: Chemistry — Organic Chemistry

Solid-state NMR and theoretical studies illuminate lanthanum borohydride C–H borylation catalysts confined within a zeolite Solid-state NMR and machine-learning MD showed that zeolite-supported La borohydride, which generates species catalyzing C–H borylation, adopts a bidentate, ligand-exchangeable, low-coordination state due to Brønsted acid binding and confinement. Borylation ; Lanthanum ; Catalysis ; Zeolite ; Borohydride ; Organoboron compounds Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Organoboron and organosilicon chemistry
Authors: Seung Won Kim | Shuting Fu | K.J. Lin | J. T. Lee
Source: Reviews in Chemical Engineering (article, 2026-03-19)
Field: Materials Science — Polymers and Plastics

Control of chlorine migration in catalytic co-pyrolysis of PVC with other plastics Abstract Polyvinyl chloride (PVC) present in mixed plastic waste poses a significant challenge to chemical recycling processes. This is due to the potential release of chlorine as HCl and its subsequent migration into oils, solids, and catalysts in both inorganic and organic forms. This review deals with the current understanding of chlorine behavior during the co-pyrolysis of PVC with major polymer classes, focusing on (i) dechlorination pathways and the phase-wise distribution of chlorine, (ii) interaction mechanisms in representative blends (PVC/polyolefins, PVC/PS, and PVC/PET), and (iii) catalytic and process-engineering strategies for chlorine management. Research within the field suggests that polyolefins can postpone the apparent dehydrochlorination process through mechanisms of melt encapsulation and transport limitation. In contrast, aromatic or polar matrices may enhance chlorine retention in condensable products via radical-mediated or functional-group-assisted pathways. The most consistent results in mitigation are observed with staged (two-stage/stepwise) approaches that separate low-temperature dehydrochlorination from high-temperature catalytic upgrading. This is particularly effective when combined with appropriate sorbents and specifically designed zeolite catalysts, such as ZSM-5. These findings reveal the synergistic and antagonistic roles of polymer mixtures and catalysts in governing chlorine migration, thereby offering practical insights for developing cleaner and more efficient PVC valorization routes. Chlorine ; Catalysis ; Zeolite ; Polymer ; Chloride ; Chemical industry Polymer Science and PVC ; Toxic Organic Pollutants Impact ; Microplastics and Plastic Pollution