jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shiwei Li | Zhiqiang Liu | Xiangfeng Wei | Hao Wu | H. C. van der Mei | Jiehua Liu
Source: Metals (article, 2025-07-06)
Field: Materials Science — Materials Chemistry

Advanced Strategies for Suppressing the Self-Corrosion of the Anode in Al–Air Batteries Aluminum–air batteries are highly promising energy storage systems due to their high theoretical energy density, environmental friendliness, and cost-effectiveness. However, the self-corrosion of aluminum anodes in alkaline electrolytes remains a critical issue that significantly limits their practical application and commercialization. This review paper comprehensively examined various advanced strategies aimed at suppressing the self-corrosion of anodes in Al–air batteries. We summarized the fundamental principles of these approaches, their advantages and disadvantages, and provided an in-depth analysis of their effectiveness, supported by experimental and theoretical evidence. Specifically, this review systematically analyzes six major strategies for suppressing anode self-corrosion: anode alloying, electrolyte additives, novel electrolytes, anode surface treatment, battery structural design, and computer-aided investigation. Furthermore, we proposed the challenges and future research directions in this field. Overall, this review aimed to offer valuable insights and guidance for the development of high-performance, long-lasting Al–air batteries. Anode ; Corrosion ; Materials science ; Metallurgy ; Galvanic anode ; Environmental science ; Cathodic protection ; Chemistry ; Electrode Corrosion Behavior and Inhibition ; Advancements in Battery Materials ; Hydrogen Storage and Materials
Authors: Han Wang | Jinna Chen | Biao Huang | Chenlong Xue | Jinbo Kuang | Longqing Cong | Perry Ping Shum | Yiyao Ge
Source: Microstructures (article, 2025-06-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent progress on synthesis and application of plasmonic metal heterostructures In the past decade, plasmonic metal heterostructures have been widely studied for their unique plasmon-enhanced effects and synergistic effects between different constituents. The intriguing properties of plasmonic metal heterostructures arise from the synergistic and/or complementary interactions of their components and the nanoscale interfaces between different materials. In addition, plasmonic metal heterostructures exhibit interesting optical and catalytic properties depending on their composition, shape, size, and architecture. This review provides an overview of the recent progress on the synthesis of plasmonic metal heterostructures including core-shell, core-satellites, Janus, and other typical structures, and then introduces some of the latest applications including surface-enhanced Raman scattering, sensing, and electrocatalysis of these plasmonic metal heterostructures. Finally, the challenges and prospects for the development of novel high-performance plasmonic metal heterostructures in the future are presented. Plasmon ; Heterojunction ; Nanotechnology ; Materials science ; Metal ; Optoelectronics ; Metallurgy Gold and Silver Nanoparticles Synthesis and Applications ; Copper-based nanomaterials and applications ; ZnO doping and properties
Authors: Kasala Prabhakar Reddy | Jeongjin Kim | Hojoon Lim | Arephin Islam | Irene Barba-Nieto | Xiao Tong | Adrian Hunt | Iradwikanari Waluyo | José A. Rodríguez
Source: The Journal of Physical Chemistry C (article, 2025-01-24)
Field: Materials Science — Materials Chemistry

The Surface Chemistry of Methanol on Cu<sub>3</sub>Pd(111): Effects of Metal Alloying and Reaction with Hydrogen Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu3Pd(111) model surface. The composition and morphological properties of the pristine Cu3Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu3Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with 3-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd–Pd distances of 2.7–2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. The valence band spectrum of Cu3Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu3Pd(111) at 300 K mainly produced CH3O, CO, and CHx species. AP-XPS showed that most Pd atoms in the surface of the Cu3Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CHx, C, and PdCx species from Cu3Pd(111) at moderate (<450 K) temperatures and prevented a CHx → C transformation. If the stability of adsorbed CH3O is used as a descriptor for the hydrogenation of CO2 to methanol, Cu3Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites. Metal ; Methanol ; Hydrogen ; Inorganic chemistry ; Chemistry ; Materials science ; Metallurgy ; Organic chemistry Catalytic Processes in Materials Science ; nanoparticles nucleation surface interactions ; Advanced Chemical Physics Studies
Authors: Gabriel Reynald Da Silva | João Paulo Cerqueira Felix | Celso R. C. Rêgo | Alexandre C. Dias | Carlos M. O. Bastos | Maurício J. Piotrowski | Diego Guedes‐Sobrinho
Source: Scientific Reports (article, 2025-01-14)
Field: Materials Science — Materials Chemistry

Workflow-driven catalytic modulation from single-atom catalysts to Au–alloy clusters on graphene Gold-based (Au) nanostructures are efficient catalysts for CO oxidation, hydrogen evolution (HER), and oxygen evolution (OER) reactions, but stabilizing them on graphene (Gr) is challenging due to weak affinity from delocalized [Formula: see text] carbon orbitals. This study investigates forming metal alloys to enhance stability and catalytic performance of Au-based nanocatalysts. Using ab initio density functional theory, we characterize [Formula: see text] sub-nanoclusters (M = Ni, Pd, Pt, Cu, and Ag) with atomicities [Formula: see text], both in gas-phase and supported on Gr. We find that M atoms act as "anchors," enhancing binding to Gr and modulating catalytic efficiency. Notably, [Formula: see text]/Gr shows improved stability, with segregation tendencies mitigated upon adsorption on Gr. The d-band center ([Formula: see text]) model indicates catalytic potential, correlating an optimal [Formula: see text] range of [Formula: see text] eV for HER and OER catalysts. Incorporating Au into [Formula: see text] adjusts [Formula: see text] closer to the Fermi level, especially for Group-10 alloys, offering designs with improved stability and efficiency comparable to pure Au nanocatalysts. Our methodology leveraged SimStack, a workflow framework enabling modeling and analysis, enhancing reproducibility, and accelerating discovery. This work demonstrates SimStack's pivotal role in advancing the understanding of composition-dependent stability and catalytic properties of Au-alloy clusters, providing a systematic approach to optimize metal-support interactions in catalytic applications. Catalysis ; Nanoclusters ; Nanomaterial-based catalyst ; Graphene ; Delocalized electron ; Density functional theory ; Materials science ; Atom (system on chip) ; Nanotechnology ; Chemistry ; Chemical physics ; Crystallography ; Computational chemistry ; Computer science Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Nanocluster Synthesis and Applications
Authors: Muhammad Hamza | S. Haq | Nashrah Saleem | Nisar Hussain | Sana Tayyeb | Shahzaib Khan | Farah Ahmad | N. Ayub | Abid Ali
Source: Scholars Academic Journal of Biosciences (article, 2025-06-27)
Field: Materials Science — Materials Chemistry

Biochemically Inspired Synthesis and Semiconductor-Integrated Interface Engineering of Metal Oxide–Graphene Nanohybrids for High-Performance, Flexible, and Next-Generation Energy Storage Systems Addressing the urgent need for advanced energy storage technologies, this study introduces a pioneering strategy that synergistically integrates biochemically inspired synthesis with semiconductor-engineered interfaces to fabricate high-performance metal oxide–graphene nanohybrids. Metal oxides (e.g., nickel oxide) are synthesized in situ using plant-based reducing agents, offering a sustainable and eco-friendly alternative to conventional chemical methods. These oxides are uniformly anchored onto functionalized graphene oxide sheets, forming robust 2D/2D heterostructures with exceptional mechanical resilience—crucial for maintaining structural integrity under operational stress. Crucially, tailored semiconductor interlayers are strategically integrated to enhance charge transport and minimize interface resistance within the composite framework. The developed hybrids demonstrate outstanding performance metrics, including a high specific capacitance of 150 Fg⁻¹ at a current density of 0.5 A g⁻¹ and exceptional long-term stability with 96% capacitance retention over 10,000 charge–discharge cycles. Comprehensive microscopic and spectroscopic characterization unequivocally confirms uniform dispersion, effective reduction of graphene oxide, and pristine nanoscale crystallinity throughout the hybrid matrix. Beyond their exceptional electrochemical performance, these composites hold immense potential for scalable integration into flexible and wearable next-generation energy storage systems. This synergistic strategy, uniquely bridging green chemistry, advanced nanotechnology, and semiconductor engineering, not only sets a new benchmark for sustainable material design but also paves the way for fundamentally cleaner, more efficient, and truly flexible power solutions for the future. Graphene ; Materials science ; Oxide ; Interface (matter) ; Nanotechnology ; Semiconductor ; Energy storage ; Metal ; Optoelectronics ; Metallurgy ; Composite material Advanced Nanomaterials in Catalysis ; Microbial Fuel Cells and Bioremediation ; Graphene and Nanomaterials Applications
Authors: Aqshat Seth | Rutvij Pankaj Kulkarni | Gopalakrishnan Sai Gautam
Source: ACS Materials Au (article, 2025-02-05)
Field: Materials Science — Materials Chemistry

Investigating Ionic Diffusivity in Amorphous LiPON using Machine-Learned Interatomic Potentials Due to its immense importance as an amorphous solid electrolyte in thin-film devices, lithium phosphorus oxynitride (LiPON) has garnered significant scientific attention. However, investigating Li<sup>+</sup> transport within the LiPON framework, especially across a Li||LiPON interface, has proven challenging due to its amorphous nature and varying stoichiometry, necessitating large supercells and long time scales for computational models. Notably, machine-learned interatomic potentials (MLIPs) can combine the computational speed of classical force fields with the accuracy of density functional theory (DFT), making them the ideal tool for modeling such amorphous materials. Thus, in this work, we train and validate the neural equivariant interatomic potential (NequIP) framework on a comprehensive DFT-based data set consisting of 13,454 chemically relevant structures to describe LiPON. With optimized training (validation) energy and force mean absolute errors of 5.5 (6.1) meV/atom and 13.6 (13.2) meV/Å, respectively, we employ the trained potential to model Li transport in both bulk LiPON and across Li||LiPON interfaces. Amorphous LiPON structures generated by the optimized potential resemble those generated by <i>ab initio</i> molecular dynamics, with N being incorporated on nonbridging apical and bridging sites. Subsequent analysis of Li<sup>+</sup> diffusivity in the bulk LiPON structures indicates broad agreement with prior computational and experimental literature. Further, we investigate the anisotropy in Li<sup>+</sup> transport across the Li(110)||LiPON and Li(111)||LiPON interface, where we observe Li transport across the interface to be one order of magnitude slower than Li motion within the bulk Li and LiPON phases. Nevertheless, we note that this anisotropy of Li transport across the interface is minor, and we do not expect it to cause any significant impedance buildup. Finally, our work highlights the efficiency of MLIPs in enabling high-fidelity modeling of complex noncrystalline systems over large length and time scales. Amorphous solid ; Thermal diffusivity ; Materials science ; Molecular dynamics ; Ab initio ; Interatomic potential ; Lithium (medication) ; Chemistry ; Thermodynamics ; Computational chemistry ; Physics ; Crystallography Machine Learning in Materials Science ; Advanced Battery Materials and Technologies ; Advancements in Battery Materials
Authors: Gyu Jin Choi | Jeong Won Ryu | Ha‐Bin Jeon | Rajneesh Kumar Mishra | Yoonseuk Choi | Jin Seog Gwag
Source: Sensors (review, 2025-06-12)
Field: Materials Science — Materials Chemistry

Emerging Role of Nb2CTx MXene in Sensors: The Roadmap from Synthesis to Health and Environmental Monitoring The rise of two-dimensional (2D) materials has transformed gas sensing, with Nb<sub>2</sub>CT<sub>x</sub> MXene drawing significant interest due to its distinct physicochemical behaviors. As part of the MXene family, Nb<sub>2</sub>CT<sub>x</sub> MXene demonstrates a remarkable combination of high electrical conductivity, adjustable surface chemistry, and exceptional mechanical flexibility, positioning it as a promising candidate for next-generation gas sensors. This review explores the synthesis techniques for Nb<sub>2</sub>CT<sub>x</sub> MXene, highlighting etching methods and post-synthesis adjustments to achieve the tailored surface terminations and structural qualities essential for gas detection. A comprehensive examination of the crystal structure, morphology, and electronic characteristics of Nb<sub>2</sub>CT<sub>x</sub> MXene is presented to clarify its outstanding sensing capabilities. The application of Nb<sub>2</sub>CT<sub>x</sub> MXene for detecting gases, including NH<sub>3</sub>, humidity, NO<sub>2</sub>, and volatile organic compounds (VOCs), is assessed, showcasing its sensitivity, selectivity, and low detection limits across various environmental settings. Furthermore, the integration of Nb<sub>2</sub>CT<sub>x</sub> MXene with other nanostructures in sensor platforms is reviewed. Lastly, challenges related to scalability, stability, and long-term performance are addressed, along with future prospects for Nb<sub>2</sub>CT<sub>x</sub> MXene-based gas sensors. This review offers significant insights into the potential of Nb<sub>2</sub>CT<sub>x</sub> MXene as a pioneering material for enhancing gas sensing technologies. Nanotechnology ; Flexibility (engineering) ; Scalability ; Computer science ; Materials science MXene and MAX Phase Materials ; Gas Sensing Nanomaterials and Sensors ; Advanced Memory and Neural Computing
Authors: Christian W. Schmitt | Liam James Dodd | Julia Walz | Leon Deterding | Patrick Lott | Alexander P. Grimm | Michael P. Shaver | Tom Hasell | Patrick Théato
Source: RSC Sustainability (review, 2025-01-01)
Field: Materials Science — Polymers and Plastics

A critical review on the sustainability of inverse vulcanised polymers This review takes a closer look at the life-cycle of inverse vulcanized polymers and if they can be more sustainable alternatives to commodity materials in energy storage, remediation technology, agriculture or construction. Sustainability ; Inverse ; Computer science ; Mathematics ; Biology ; Ecology Synthesis and properties of polymers
Authors: Nastaran Parsafard | Zaidoon M. Shakor
Source: Discover Applied Sciences (article, 2025-04-28)
Field: Chemistry — Inorganic Chemistry

Advancements in zeolite-based catalysts for the isomerization of n-alkanes: mechanistic insights and future directions In recent years, the isomerization of n-alkanes has garnered significant attention due to its pivotal role in enhancing the octane number of gasoline and producing valuable chemicals. This study delves into the advancements in zeolite-based catalysts, specifically tailored for the isomerization of n-alkanes, offering mechanistic insights and outlining future research directions. Leveraging a combination of experimental and computational approaches, we systematically investigate the influence of zeolite framework topology, active site configuration, and reaction conditions on catalytic performance. Our findings underscore the critical role of acid–base properties and pore architecture in dictating selectivity and conversion rates. Notably, we identify a novel class of hierarchical zeolites that exhibit superior activity and stability compared to conventional counterparts, attributed to enhanced mass transport and optimized active site accessibility. Additionally, we elucidate the underlying mechanisms governing the isomerization process over these catalysts, revealing intricate relationships between structural characteristics and reactivity patterns. Based on these insights, we propose strategic modifications to zeolite catalysts that could lead to breakthroughs in efficiency and sustainability of n-alkane isomerization processes. Looking ahead, we discuss potential pathways for integrating these advanced catalysts into industrial settings, alongside challenges and opportunities for future research in the realm of zeolite-catalyzed reactions. This work not only contributes to the fundamental understanding of zeolite catalysis but also paves the way for the development of next-generation catalysts for energy-efficient chemical transformations. Isomerization ; Zeolite ; Catalysis ; Chemistry ; Organic chemistry Zeolite Catalysis and Synthesis ; Catalysis and Hydrodesulfurization Studies ; Catalytic Processes in Materials Science
Authors: Astha Tripathi | Saumya Singh Rautela | Pratibha Kumari
Source: RSC Advances (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

Graphene-based nanozymes for revolutionizing biomedical research Nanozymes, with nanoscale dimensions and enzyme-like properties, have garnered substantial interest as they can overcome the downsides of conventional enzymes, including fragility, high cost, tedious isolation, and expensive manufacturing. Over the past decade, a diverse range of nanomaterials have demonstrated the ability to mimic enzyme-like activity by incorporating multivalent elements into nanostructures. Notably, graphene-based nanomaterials, such as graphene, graphene oxide, and reduced graphene oxide, with their precisely controlled scaffolds and electronic properties, have emerged as promising substitutes for traditional enzymes by emulating the intricately evolved catalytic centers of natural enzymes, including oxidase, peroxidase, catalase, and superoxide dismutase. The distinct electronic, mechanical, thermal, and optical properties enable graphene-based nanozymes to provide multifunctional platforms for various biomedical applications, including wound healing, tissue regeneration, cancer treatment therapies, antibacterial activity, and biosensing applications. This in-depth review examines the enzymatic features and recent advancements of graphene-based nanozymes, highlighting their significant contributions to biomedicine. Biosensor ; Graphene ; Nanomaterials ; Biocompatible material Advanced Nanomaterials in Catalysis ; Graphene and Nanomaterials Applications ; Electrochemical sensors and biosensors
Authors: Ayush Jain | Ashutosh Srivastava | Rampi Ramprasad
Source: Chemistry of Materials (article, 2025-09-11)
Field: Materials Science — Materials Chemistry

A Learning Framework for Atomic-Level Polymer Structure Generation Synthetic polymeric materials underpin fundamental technologies in the energy, electronics, consumer goods, and medical sectors, yet their development still suffers from prolonged design timelines. Although polymer informatics tools have supported speedup, polymer simulation protocols continue to face significant challenges in the on-demand generation of realistic 3D atomic structures that respect the conformational diversity of polymers. Generative algorithms for 3D structures of inorganic crystals, biopolymers, and small molecules exist, but have not addressed synthetic polymers because of challenges in representation and data set constraints. In this work, we introduce polyGen, a generative model designed specifically for 3D polymer structures that operates from minimal inputs such as the repeat unit chemistry alone. polyGen combines graph-based encodings with a latent diffusion transformer using positional biased attention for realistic conformation generation. Given the limited data set of 3,855 DFT-optimized polymer structures, we incorporate joint training with small molecule data to enhance generation quality. We also establish structure matching criteria to benchmark our approach on this novel problem. polyGen overcomes the limitations of traditional crystal structure prediction methods for polymers, successfully generating realistic and diverse linear and branched conformations, with promising performance even on challenging large repeat units. As an atomic-level proof-of-concept capturing intrinsic polymer flexibility, it marks a transformative capability in material structure generation. Polymer ; Set (abstract data type) ; Representation (politics) ; Generative grammar ; Benchmark (surveying) ; Generative model ; Benchmarking ; Generative Design Machine Learning in Materials Science ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Woodrow N. Wilson | John Lane | Chinmoy Saha | Sony Severin | Vivek S. Bharadwaj | Neeraj Rai
Source: Catalysis Science & Technology (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Nature of molybdenum carbide surfaces for catalytic hydrogen dissociation using machine-learned potentials: an ensemble-averaged perspective Unique surface chemistries of molybdenum carbide phases for H 2 dissociation with MLIP-based reactive molecular dynamics. Dissociation (chemistry) ; Catalysis ; Molybdenum ; Carbide ; Hydrogen ; Perspective (graphical) ; Materials science ; Chemistry ; Inorganic chemistry ; Physical chemistry ; Computer science ; Metallurgy ; Artificial intelligence ; Organic chemistry Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Hydrodesulfurization Studies