jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Paolo Pegolo | Federico Grasselli
Source: Frontiers in Materials (article, 2024-03-06)
Field: Materials Science — Ceramics and Composites

Thermal transport of glasses via machine learning driven simulations Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the chemical and morphological complexity of glasses calls for atomistic simulations where the interatomic potentials are able to capture the variety of local environments, composition, and (dis)order that typically characterize glassy phases. Machine-learning potentials (MLPs) are emerging as a valid alternative to computationally expensive ab initio simulations, inevitably run on very small samples which cannot account for disorder at different scales, as well as to empirical force fields, fast but often reliable only in a narrow portion of the thermodynamic and composition phase diagrams. In this article, we make the point on the use of MLPs to compute the thermal conductivity of glasses, through a review of recent theoretical and computational tools and a series of numerical applications on vitreous silica and vitreous silicon, both pure and intercalated with lithium. Thermal conductivity ; Interatomic potential ; Silicon ; Thermal ; Materials science ; Phase diagram ; Computer science ; Silicate glass ; Statistical physics ; Lithium (medication) ; Phase (matter) ; Computational science ; Nanotechnology ; Molecular dynamics ; Thermodynamics ; Physics ; Chemistry ; Computational chemistry ; Composite material Glass properties and applications ; Phase-change materials and chalcogenides ; Material Dynamics and Properties
Authors: Xi‐Guan Zhao | Qi Yang | Ying Xu | Qing‐Yu Liu | Ziyu Li | Xiao-Xiao Liu | Yan‐Xia Zhao | Sheng‐Gui He
Source: Journal of the American Chemical Society (article, 2024-04-23)
Field: Materials Science — Materials Chemistry

Machine Learning for Experimental Reactivity of a Set of Metal Clusters toward C–H Activation Understanding the mechanisms of C-H activation of alkanes is a very important research topic. The reactions of metal clusters with alkanes have been extensively studied to reveal the electronic features governing C-H activation, while the experimental cluster reactivity was qualitatively interpreted case by case in the literature. Herein, we prepared and mass-selected over 100 rhodium-based clusters (Rh<sub><i>x</i></sub>V<sub><i>y</i></sub>O<sub><i>z</i></sub><sup>-</sup> and Rh<sub><i>x</i></sub>Co<sub><i>y</i></sub>O<sub><i>z</i></sub><sup>-</sup>) to react with light alkanes, enabling the determination of reaction rate constants spanning six orders of magnitude. A satisfactory model being able to quantitatively describe the rate data in terms of multiple cluster electronic features (average electron occupancy of valence s orbitals, the minimum natural charge on the metal atom, cluster polarizability, and energy gap involved in the agostic interaction) has been constructed through a machine learning approach. This study demonstrates that the general mechanisms governing the very important process of C-H activation by diverse metal centers can be discovered by interpreting experimental data with artificial intelligence. Chemistry ; Reactivity (psychology) ; Set (abstract data type) ; Metal ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Zheng Jia | Hai-Cheng Yi | Zhu‐Hong You
Source: IEEE Journal of Biomedical and Health Informatics (article, 2024-11-04)
Field: Chemistry — Organic Chemistry

Equivariant 3D-Conditional Diffusion Model for <i>De Novo</i> Drug Design De novo drug design speeds up drug discovery, mitigating its time and cost burdens with advanced computational methods. Previous work either insufficiently utilized the 3D geometric structure of the target proteins, or generated ligands in an order that was inconsistent with real physics. Here we propose an equivariant 3D-conditional diffusion model, named DiffFBDD, for generating new pharmaceutical compounds based on 3D geometric information of specific target protein pockets. DiffFBDD overcomes the underutilization of geometric information by integrating full atomic information of pockets to backbone atoms using an equivariant graph neural network. Moreover, we develop a diffusion approach to generate drugs by generating ligand fragments for specific protein pockets, which requires fewer computational resources and less generation time (65.98% 96.10% lower). DiffFBDD offers better performance than state-of-the-art models in generating ligands with strong binding affinity to specific protein pockets, while maintaining high validity, uniqueness, and novelty, with clear potential for exploring the drug-like chemical space. Computer science ; Equivariant map ; Diffusion ; Algorithm ; Artificial intelligence ; Theoretical computer science ; Mathematics ; Physics ; Pure mathematics Microwave-Assisted Synthesis and Applications ; Injection Molding Process and Properties ; Veterinary medicine and infectious diseases
Authors: Fanghui Chen | Xingyue Liu | Chengchen Lu | Mingxiu Ruan | Yujing Wen | Shaodong Wang | Youhong Song | Lin Li | Liang Zhou | Haiyang Jiang | Leiming Wu
Source: Bioresource Technology (article, 2024-09-23)
Field: Chemistry — Analytical Chemistry

High-throughput prediction of stalk cellulose and hemicellulose content in maize using machine learning and Fourier transform infrared spectroscopy Hemicellulose ; Stalk ; Cellulose ; Fourier transform infrared spectroscopy ; Infrared spectroscopy ; Throughput ; Infrared ; Papermaking ; Spectroscopy ; Lignin ; Fourier transform ; Content (measure theory) ; Materials science ; Chemistry ; Pulp and paper industry ; Artificial intelligence ; Computer science ; Chemical engineering ; Composite material ; Engineering ; Mathematics ; Optics ; Physics ; Biology ; Horticulture ; Organic chemistry Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Food composition and properties
Authors: Cheng Cui | Jingzhu Wu | Qian Zhang | Le Yu | Xiaorong Sun | Cuiling Liu | Yi Yang
Source: Infrared Physics & Technology (article, 2024-02-20)
Field: Chemistry — Analytical Chemistry

Maturity detection of single maize seeds based on hyperspectral imaging and transfer learning Hyperspectral imaging ; Maturity (psychological) ; Computer science ; Remote sensing ; Artificial intelligence ; Geology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Zhipeng Ding | Wei Su | Lipengan Ye | Wenlong Li | Yuanhang Zhou | Bin Tang | Jianfei Zou | Hongbing Yao
Source: Solar Energy (article, 2024-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Deep learning based inverse design of metasurface absorber for maximizing solar spectral absorption Absorption (acoustics) ; Materials science ; Optoelectronics ; Solar energy ; Photovoltaics ; Broadband ; Thermal ; Optics ; Solar cell ; Range (aeronautics) ; Engineering physics ; Photovoltaic system ; Computer science ; Physics ; Meteorology ; Composite material ; Electrical engineering ; Engineering Metamaterials and Metasurfaces Applications ; Thermal Radiation and Cooling Technologies ; Advanced Antenna and Metasurface Technologies
Authors: Panagiotis D. Kolokathis | Evangelos Voyiatzis | Nikolaos K. Sidiropoulos | Andreas Tsoumanis | Georgia Melagraki | Kaido Tämm | Iseult Lynch | Antreas Afantitis
Source: Computational and Structural Biotechnology Journal (article, 2024-03-12)
Field: Materials Science — Materials Chemistry

ASCOT: A web tool for the digital construction of energy minimized Ag, CuO, TiO2 spherical nanoparticles and calculation of their atomistic descriptors ASCOT (an acronym derived from Ag-Silver, Copper Oxide, Titanium Oxide) is a user-friendly web tool for digital construction of electrically neutral, energy-minimized spherical nanoparticles (NPs) of Ag, CuO, and TiO<sub>2</sub> (both Anatase and Rutile forms) in vacuum, integrated into the Enalos Cloud Platform (https://www.enaloscloud.novamechanics.com/sabydoma/ascot/). ASCOT calculates critical atomistic descriptors such as average potential energy per atom, average coordination number, common neighbour parameter (used for structural classification in simulations of crystalline phases), and hexatic order parameter (which measures how closely the local environment around a particle resembles perfect hexatic symmetry) for both core (over 4 Å from the surface) and shell (within 4 Å of the surface) regions of the NPs. These atomistic descriptors assist in predicting the most stable NP size based on lowest per atom energy and serve as inputs for developing machine learning models to predict the toxicity of these nanomaterials. ASCOT's automated backend requires minimal user input in order to construct the digital NPs: inputs needed are the material type (Ag, CuO, TiO<sub>2</sub>-Anatase, TiO<sub>2</sub>-Rutile), target diameter, a Force-Field from a pre-validated list, and the energy minimization parameters, with the tool providing a set of default values for novice users. Anatase ; Rutile ; Materials science ; Nanoparticle ; Atom (system on chip) ; Surface energy ; Nanotechnology ; Molecular dynamics ; Energy (signal processing) ; Shell (structure) ; Nanomaterials ; Computer science ; Chemistry ; Physics ; Chemical engineering ; Computational chemistry ; Composite material ; Engineering Machine Learning in Materials Science ; Copper-based nanomaterials and applications ; Quantum Dots Synthesis And Properties
Authors: Dhananjay Ambre | Manaf Sheyyab | Patrick T. Lynch | Eric Mayhew | Kenneth Brezinsky
Source: Talanta (article, 2024-01-09)
Field: Chemistry — Analytical Chemistry

A Raman spectroscopy based chemometric approach to predict the derived cetane number of hydrocarbon jet fuels and their mixtures Cetane number ; Jet fuel ; Chemistry ; Chemometrics ; Combustion ; Raman spectroscopy ; Analytical Chemistry (journal) ; Hydrocarbon mixtures ; Ignition system ; Hydrocarbon ; Organic chemistry ; Optics ; Thermodynamics ; Chromatography ; Physics ; Biodiesel Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Pesticide Residue Analysis and Safety
Authors: N. Navya | B.R. Radha Krushna | Saurabh Sharma | Vijay Kumar | Srikant Sahoo | R. Sudarmani | K. Suresh Babu | K. Manjunatha | Sheng Yun Wu | Hsin‐Hao Chiu | G. K. Vinayak | H. Nagabhushana
Source: Inorganic Chemistry Communications (article, 2024-10-31)
Field: Materials Science — Materials Chemistry

A facile approach towards large-scale synthesis of TiO2 nanoparticles derived from egg shell waste with enhanced UV shielding, nano priming and fingerprint real time object detection through YOLOv8x Fingerprint (computing) ; Electromagnetic shielding ; Priming (agriculture) ; Radiation shielding ; Materials science ; Nanoparticle ; Shell (structure) ; Nano- ; Nanotechnology ; Object (grammar) ; Chemical engineering ; Computer science ; Engineering ; Composite material ; Artificial intelligence Advanced Nanomaterials in Catalysis ; Biosensors and Analytical Detection
Authors: Jiayi Xu | Colton J. Lund | Prajay Patel | Yu Lim Kim | Cong Liu
Source: Catalysts (article, 2024-03-28)
Field: Materials Science — Materials Chemistry

Recent Advances on Computational Modeling of Supported Single-Atom and Cluster Catalysts: Characterization, Catalyst–Support Interaction, and Active Site Heterogeneity To satisfy the need for catalyst materials with high activity, selectivity, and stability for energy conversion, material design and discovery guided by theoretical insights are a necessity. In the past decades, the rise in theoretical investigations into the properties of catalyst materials, reaction mechanisms, and catalyst design principles has shed light on the catalysis field. Quantitative structure–activity relationships have been developed through incorporating spectroscopic simulations, electronic structure calculations, and reaction mechanistic studies. In this review, we report the state-of-the-art computational approaches to catalyst materials characterization for supported single-atom and cluster catalysts utilizing spectroscopic simulations, i.e., XANES simulation, and material properties investigation via electronic-structure calculations. Furthermore, approaches regarding reaction mechanisms, focusing on active site heterogeneity, are also discussed. Catalysis ; Characterization (materials science) ; Cluster (spacecraft) ; Nanotechnology ; Materials science ; Atom (system on chip) ; Chemical physics ; Computational chemistry ; Chemistry ; Computer science ; Organic chemistry Catalytic Processes in Materials Science ; Advanced Photocatalysis Techniques ; Machine Learning in Materials Science
Authors: Md. Ibrahim Abdullah | Mohammad Saidur Rahman | Mohammad Obayedullah | Sawda Ahmed Musfika
Source: Heliyon (review, 2024-08-24)
Field: Materials Science — Materials Chemistry

RETRACTED: Prospect and challenges of borophene bandgap formation: A comprehensive review A two-dimensional crystalline allotrope of boron, Borophene, has attracted much interest lately because of its unique electrical characteristics and possible uses in electronic devices. This thorough analysis examines the opportunities and difficulties related to the bandgap creation in boron, which is essential for its incorporation into semiconductor technologies. An introduction to the structural features of Borophene is given at the outset of the text, emphasizing its fascinating hexagonal lattice and tunable electronic properties. The review thoroughly explores the range of techniques used in synthesizing Borophene, covering both theoretical and experimental methods. It assesses how growth conditions, post-synthesis treatments, and substrate interactions affect the establishment of the bandgap in Borophene. The study also looks at how strain engineering, flaws, and impurities affect the bandgap, highlighting the necessity of exact control over these elements to get desirable electrical properties. We go into great length about the difficulties in Borophene bandgap engineering, including stability, scalability, and repeatability problems. The study critically evaluates the current body of knowledge, pointing out knowledge gaps and suggesting possible directions for further research. In addition, the paper discusses how external elements like humidity and temperature affect the stability of Borophene electrical characteristics, which complicates practical application. To sum up, this thorough analysis offers insightful information about the development of the borophene bandgap formation and a road map for scientists and engineers hoping to utilize borophene to its maximum potential in the future generation of electronic devices. The difficulties in synthesis and the complex interaction of several factors influencing bandgap creation highlight the necessity of ongoing multidisciplinary work to realize the technological potential of borophene. Borophene ; Nanotechnology ; Materials science ; Engineering physics ; Engineering ethics ; Engineering ; Graphene Boron and Carbon Nanomaterials Research ; Semiconductor materials and interfaces ; MXene and MAX Phase Materials
Authors: Farah Murtaza | Naseem Akhter | Muhammad Azam Qamar | Asma Yaqoob | Anis Ahmad Chaudhary | Bhagyashree R. Patil | Salah-Ud-Din Khan | Nasir Adam Ibrahim | Nosiba S. Basher | Mohammed S. Aleissa | Iqra Kanwal | Mohd Imran
Source: Crystals (article, 2024-05-27)
Field: Materials Science — Materials Chemistry

Syzygium aromaticum Bud Extracted Core–Shell Ag–Fe Bimetallic Nanoparticles: Phytotoxic, Antioxidant, Insecticidal, and Antibacterial Properties Today, there is the roar of sustainable material development around the globe. Green nanotechnology is one of the extensions of sustainability. Due to its sustainable approach, the green fabrication of nanoparticles has recently surpassed their classical synthesis in popularity. Among metal nanoparticles, contemporary findings have demonstrated that bimetallic nanoparticles possess more potential for different applications than monometallic nanoparticles due to the synergistic effects of the two metals. So, we are presenting facile, one-vessel, and one-step phyto-fabrication of Ag–Fe BMNPs using the bud extract of Syzygiumaromaticum. The synthesized nanoparticles were characterized by UV-VIS, XRD, EDX, FTIR, and SEM. The synthesized NPs and the extract underwent biological studies. The radical scavenging potential of the NPs and the extract was found to be 64% and 73%, and the insecticidal potential was found to be 80% and 100%, respectively. Similarly, the NPs and the extract both exhibited good antibacterial activity. The zone of inhibition using 100 mg/mL of extract and NPs was found to be 1 cm against all bacterial species, i.e., K. pneumonia, E. coli, and S. aureus. It was 1.5 cm, 1.3 cm, and 1 cm against K. pneumonia, E. coli, and S. aureus, respectively, showing that the antibacterial activity of the extract is higher than that of the NPs. So, this study unlocks the synthesis of Ag–Fe bimetallic nanoparticles using eco-safe, cost-effective, facile, and least-harmful green methodology with potential applications of both NPs and SA extract in medical and agricultural fields, a step towards sustainability. Syzygium ; Bimetallic strip ; Shell (structure) ; Nanoparticle ; Antioxidant ; Eugenol ; Traditional medicine ; Chemistry ; Core (optical fiber) ; Antibacterial activity ; Nuclear chemistry ; Materials science ; Biology ; Botany ; Nanotechnology ; Organic chemistry ; Bacteria ; Composite material ; Medicine Nanoparticles: synthesis and applications ; Moringa oleifera research and applications ; Piperaceae Chemical and Biological Studies
Authors: Priyadarshi K. Ray | Kulamani Parida
Source: Materials Advances (article, 2024-11-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Achievements, challenges, and stability of layer double hydroxide and carbon nanotube hybrid electrode materials for clean and sustainable energy storage supercapacitor application: an extensive review The graphical abstract illustrates the use of LDH/CNT: a low cost, flexible and sustainable rapid energy storage and release supercapacitor. Supercapacitor ; Carbon nanotube ; Materials science ; Energy storage ; Nanotechnology ; Electrode ; Layer (electronics) ; Hydroxide ; Carbon fibers ; Chemical engineering ; Composite number ; Capacitance ; Composite material ; Engineering ; Chemistry ; Physics ; Power (physics) Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Electrochemical sensors and biosensors
Authors: Safdar Ali Amur | Bharat Prasad Sharma | Najaf Ali Soomro | Quratulain Khuhro | Muhammad Atif Tariq | Hao Liang | Mohsin Kazi | Mohammad Nur‐e‐Alam
Source: Applied Organometallic Chemistry (article, 2024-11-06)
Field: Chemistry — Organic Chemistry

Synthesis, Characterization, Density Functional Theory Study, Antibacterial Activity and Molecular Docking of Zeolitic Imidazolate Framework‐8 ABSTRACT In this study, Zeolitic Imidazolate Framework‐8 (ZIF‐8) nanomaterials were synthesized using a co‐precipitation one‐pot method that uses ethanol, methanol, and water as solvents for the precursors (2‐methylimidazole and Zinc nitrate hexahydrate), resulting in yields of 66.77%, 73.14%, and 68.12%, respectively. The as‐synthesized ZIF‐8 nanomaterials were thoroughly characterized by X‐ray diffraction analysis, transmission electron microscopy, ultraviolet–visible spectroscopy, and Fourier‐transform infrared spectroscopy. The X‐ray diffraction analysis showed that the crystallite size of ethanol‐based ZIF‐8 (24.76 ± 1.67 nm) was smaller than those synthesized in water (26.92 ± 1.89 nm) and methanol (31.39 ± 1.03 nm). However, methanol‐based ZIF‐8 exhibited lower crystallinity (85.93%) than water‐based ZIF‐8 (91.48%) and ethanol‐based ZIF‐8 (92.71%). Zeta potential studies revealed that ethanol‐based ZIF‐8 had a larger surface charge (+37 mV) than water‐based ZIF‐8 (+35 mV) or methanol‐based ZIF‐8 (+24 mV) |SPINPDF101. Transmission electron microscopy analysis confirmed particle sizes of 54.35 ± 2.11 nm for ethanol‐based ZIF‐8, 57.91 ± 2.26 nm for water‐based ZIF‐8, and 63.25 ± 4.12 nm for methanol‐based ZIF‐8. Thermogravimetric analysis indicated thermal stability up to 800 °C, with mass losses of 55.98% for ethanol‐ZIF‐8, 50.12% for water‐based ZIF‐8, and 65.36% for methanol‐based ZIF‐8 by 600 °C. In antibacterial studies, water‐based ZIF‐8 exhibited the largest zone of growth inhibition (17.30 ± 0.26 mm) against Escherichia coli compared to ethanol‐based ZIF‐8 (15.57 ± 0.32 mm) and methanol‐based ZIF‐8 (14.70 ± 0.20 mm). Pearson's correlation study revealed that zeta potential, crystallinity, and antibacterial activity are positively related. Furthermore, water‐based ZIF‐8, with a minimum inhibitory concentration of 50 μg/100 μL, confirmed evident cell membrane disruption. Molecular docking experiments revealed ZIF‐8's significant binding affinity for the E. coli protein 5AZC, supporting its robust antibacterial activity. Chemistry ; Zeolitic imidazolate framework ; Density functional theory ; Docking (animal) ; Computational chemistry ; Imidazolate ; Antibacterial activity ; Combinatorial chemistry ; Stereochemistry ; Organic chemistry ; Metal-organic framework ; Bacteria ; Adsorption Synthesis and biological activity ; Multicomponent Synthesis of Heterocycles ; Computational Drug Discovery Methods
Authors: Al Mojahid Afridi | Mahbuba Aktary | Syed Shaheen Shah | Sheikh Sharif Iqbal | Gazi Jahirul Islam | M. Nasiruzzaman Shaikh | Md. Abdul Aziz
Source: The Chemical Record (review, 2024-11-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advancing Electrical Engineering with Biomass‐derived Carbon Materials: Applications, Innovations, and Future Directions The ongoing global shift towards sustainability in electrical engineering necessitates novel materials that offer both ecological and technical benefits. Biomass-derived carbon materials (BCMs) are emerging as cornerstones in this transition due to their sustainability, cost-effectiveness, and versatile properties. This review explores the expansive role of BCMs across various electrical engineering applications, emphasizing their transformative impact and potential in fostering a sustainable technological ecosystem. The fundamentals of BCMs are investigated, including their unique structures, diverse synthesis procedures, and significant electrical and electrochemical properties. A detailed examination of recent innovations in BCM applications for energy storage, such as batteries and supercapacitors, and their pivotal role in developing advanced electronic components like sensors, detectors, and electromagnetic interference shielding composites has been covered. BCMs offer superior electrical conductivities, tunable surface chemistries, and mechanical properties compared to traditional carbon sources. These can be further enhanced through innovative doping and functionalization techniques. Moreover, this review identifies challenges related to scalability and uniformity in properties and proposes future research directions to overcome these hurdles. By integrating insights from recent studies with a forward-looking perspective, this paper sets the stage for the next generation of electrical engineering solutions powered by biomass-derived materials, aligning technological advancement with environmental stewardship. Supercapacitor ; Sustainability ; Nanotechnology ; Expansive ; Surface engineering ; Systems engineering ; Computer science ; Materials science ; Engineering ; Capacitance ; Ecology Supercapacitor Materials and Fabrication ; Graphene research and applications ; Advancements in Battery Materials