jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jessica Mauriello | Romain Maury | Yohann Guillaneuf | Didier Gigmès
Source: Advanced Materials Technologies (article, 2023-05-24)
Field: Chemistry — Organic Chemistry

3D/4D Printing of Polyurethanes by Vat Photopolymerization Abstract Vat photopolymerization relies on the light‐induced polymerization of liquid photopolymer to produce the targeted structure. Among all the polymers prepared by vat photopolymerization, due to their numerous properties polyurethanes have recently gained great attention in the industrial and academic fields. In this review article, recent progress in printing techniques, resin compositions, and applications related to 3D/4D printing by vat photopolymerization of polyurethanes are highlighted. Photopolymer ; Polymerization ; 3D printing ; Polymer science ; Polymer ; Materials science ; Polyurethane ; Polymer chemistry ; Composite material Photopolymerization techniques and applications ; Additive Manufacturing and 3D Printing Technologies ; 3D Printing in Biomedical Research
Authors: Zhipeng Zhao | Huizeng Li | Quan Liu | An Li | Luanluan Xue | Renxuan Yuan | Xinye Yu | Rujun Li | Xiao Deng | Yanlin Song
Source: Droplet (article, 2023-03-16)
Field: Materials Science — Surfaces, Coatings and Films

Regulating droplet impact symmetry by surface engineering Abstract Droplet impact on solid surfaces is essential both in nature and industry. Precisely regulating the dynamic behavior of droplet impact is of great significance for energy harvesting, anti‐icing, inkjet printing, pesticide spraying, and many other fields. Various rebounding behaviors (deposition, rebounding, rotation, instability control, and so on) and rebounding intrinsic parameters (such as contact time) after droplets impacting on solid surfaces can be regulated by surface engineering. This paper reviews the advances in regulating droplet impact behavior from the perspective of symmetry by modifying solid surfaces from the following aspects: chemical modification and physical structure regulation, in which the symmetry is discussed from mirror symmetry and rotational symmetry. Firstly, the symmetry of the droplet impact dynamics and its influencing factors are introduced. Then the modulation of droplet impact symmetry, using homogeneous and heterogeneous chemically modified solid surfaces, is summarized. The following presents the influence of physical structures, from micro to macro scale compared to the droplet size, on the droplet impact symmetry. Finally, the future challenges and opportunities of the droplet impact behavior regulation are discussed. Symmetry (geometry) ; Rotational symmetry ; Mechanics ; Homogeneous ; Rotation (mathematics) ; Materials science ; Nanotechnology ; Chemical physics ; Physics ; Computer science ; Statistical physics ; Mathematics ; Geometry Surface Modification and Superhydrophobicity ; Fluid Dynamics and Heat Transfer ; Plant Surface Properties and Treatments
Authors: Markus J. Buehler
Source: Journal of the Mechanics and Physics of Solids (article, 2023-10-11)
Field: Materials Science — Materials Chemistry

MeLM, a generative pretrained language modeling framework that solves forward and inverse mechanics problems Automatic summarization ; Computer science ; Generative grammar ; Set (abstract data type) ; Artificial intelligence ; Programming language Machine Learning in Materials Science ; Calcium Carbonate Crystallization and Inhibition ; Advanced Electron Microscopy Techniques and Applications
Authors: Rita de Jesus | Kerstin Hiesinger | Manuel van Gemmeren
Source: Angewandte Chemie International Edition (review, 2023-06-07)
Field: Chemistry — Organic Chemistry

Preparative Scale Applications of C−H Activation in Medicinal Chemistry C-H activation is an attractive methodology to increase molecular complexity without requiring substrate prefunctionalization. In contrast to well-established cross-coupling methods, C-H activation is less explored on large scales and its use in the production of pharmaceuticals faces substantial hurdles. However, the inherent advantages, such as shorter synthetic routes and simpler starting materials, motivate medicinal chemists and process chemists to overcome these challenges, and exploit C-H activation steps for the synthesis of pharmaceutically relevant compounds. In this review, we will cover examples of drugs/drug candidates where C-H activation has been implemented on a preparative synthetic scale (range between 355 mg and 130 kg). The optimization processes will be described, and each example will be examined in terms of its advantages and disadvantages, providing the reader with an in-depth understanding of the challenges and potential of C-H activation methodologies in the production of pharmaceuticals. Scale (ratio) ; Chemistry ; Environmental chemistry ; Geography ; Cartography Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Chemical Reactions and Isotopes
Authors: Shimaa I. Sayed | Korany R. Mahmoud | Roaa I. Mubarak
Source: Scientific Reports (article, 2023-07-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design and optimization of broadband metamaterial absorber based on manganese for visible applications Metamaterial absorbers have been extensively researched due to their potential applications in photonics. This paper presents a highly efficient Broadband Metamaterial Absorber (BMA) based on a Manganese-Silica-Manganese three layer structure with a shaped pattern at the top layer. For maximum absorption efficiency, the geometrical parameters of the proposed absorber have been optimized based on Particle Swarm Optimization (PSO). The optimal structure with a thickness of 190 nm, can achieve more than 94% absorption spanning visible band (400-800) nm with 98.72% average absorption, and more than 90% absorption over the range from 365 to 888 nm. In the range from 447 to 717 nm, the design presented above 99% absorptivity, providing an ultra-wide bandwidth of 270 nm. The physical mechanism of absorption is illustrated through the exploration of the electric and magnetic field distributions. Additionally, the proposed structure maintains 85% absorption stability for wide incident angles up to 70° for both the TE and TM polarizations under oblique incidence. Further, the optimized absorber structure with excellent absorption capabilities makes it suitable for various applications, including optical sensors, thermal emitters, and color imaging applications. Metamaterial absorber ; Materials science ; Metamaterial ; Absorption (acoustics) ; Molar absorptivity ; Optoelectronics ; Broadband ; Optics ; Particle swarm optimization ; Computer science ; Physics ; Composite material ; Tunable metamaterials Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Thermal Radiation and Cooling Technologies
Authors: Xi Cheng | Yangyanbing Liao | Lei Zhao | Jie Li | Xiaolei Fan | Xin Xiao
Source: Journal of Membrane Science (article, 2023-01-25)
Field: Chemistry — Inorganic Chemistry

Multi-scale design of MOF-based membrane separation for CO2/CH4 mixture via integration of molecular simulation, machine learning and process modeling and simulation Metal-organic framework (MOF) membranes have demonstrated high efficiency for CO2 capture due to their wide range of pore sizes, high surface area, high porosity, and open metal sites. In this work, we propose a multi-scale design framework of MOF-based membrane separation for CO2/CH4 mixture via integration of molecular simulation, machine learning, and process modelling and simulation. The GCMC and MD molecular simulation is first used to evaluate adsorption isotherms, isosteric adsorption heat, self-diffusivity, activation energy, permeability, and selectivity of a MOF-based membrane (e.g., IRMOF-1) for CO2/CH4 separation at different operating conditions. It is found that the simulated isotherms at 298 K are consistent with experimental results. CO2 permeability can range from 4.090 × 104 to 3.818 × 105 barrer with variation in operating conditions. The same phenomenon is also reflected in the selectivity. We then establish prediction models of adsorption capacity and self-diffusivity using machine learning methods such as artificial neural network (ANN), which are used to calculate the permeability. The mean squared error is 0.0086, and the coefficient of determination is 0.9822. The proposed ANN models are integrated with the tanks-in-series model of a hollow fiber membrane separation process, which is simulated using the finite volume method. Three case studies illustrate the feasibility and superiority of the proposed integrated framework. Thermal diffusivity ; Adsorption ; Membrane ; Separation process ; Materials science ; Porosity ; Selectivity ; Permeability (electromagnetism) ; Gas separation ; Work (physics) ; Barrer ; Artificial neural network ; Metal-organic framework ; Biological system ; Thermodynamics ; Chemical engineering ; Computer science ; Chemistry ; Chromatography ; Artificial intelligence ; Engineering ; Physical chemistry ; Physics ; Composite material ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Carbon Dioxide Capture Technologies
Authors: Daniel R. Cassar
Source: Ceramics International (article, 2023-08-25)
Field: Materials Science — Ceramics and Composites

GlassNet: A multitask deep neural network for predicting many glass properties Liquidus ; Viscosity ; Materials science ; Python (programming language) ; Surface tension ; Artificial neural network ; Software ; Dielectric ; Computer science ; Thermodynamics ; Artificial intelligence ; Mineralogy ; Composite material ; Geology ; Optoelectronics ; Physics Glass properties and applications ; Phase-change materials and chalcogenides ; Pigment Synthesis and Properties
Authors: Hong Meng | Wei Peng | Zhongyu Tang | Hulei Yu | Yanhui Chu
Source: Journal of Materiomics (article, 2023-12-20)
Field: Materials Science — Materials Chemistry

Data-driven discovery of formation ability descriptors for high-entropy rare-earth monosilicates Herein we establish formation ability descriptors of high-entropy rare-earth monosilicates (HEREMs) via the data-driven discovery based on the high-throughput solid-state reaction and machine learning (ML) methods. Specifically, adequate high-quality data are generated with 132 samples synthesized by the self-developed high-throughput solid-state reaction apparatuses, and 30 potential descriptors are considered in ML simultaneously. Two classifications are proposed to study the phase formation of HEREMs via the ML approach combined with the genetic algorithm: (Ⅰ) to distinguish pure HEREMs (X) from other phases and (Ⅱ) to categorize the detail phases of HEREMs (X2, X1, or X2+X1). Four formation ability descriptors (rMe¯, EF¯, δEg, and δZ∗) with a high validation accuracy (96.2%) are proposed as the optimal combination for Classification Ⅰ, where a smaller rMe¯ is determined to have the most significant influence on the formation of HEREMs. For Classification Ⅱ, a 100% validation accuracy is achieved by using only two formation ability descriptors (rion¯ and δZ∗), where the rion¯ is analyzed to be the dominant feature and a lower rion¯ is beneficial to the formation of X2-HEREMs. Based on our established formation ability descriptors, 6,045 unreported multicomponent silicates are explored, and 3,478 new HEREMs with 2,700 X2-and 423 X1-HEREMs are predicted. Rare earth ; Materials science ; Nanotechnology ; Astrobiology ; Physics ; Metallurgy Machine Learning in Materials Science ; High Entropy Alloys Studies ; Intermetallics and Advanced Alloy Properties
Authors: Jonas Köhler | Yaoyi Chen | Andreas Krämer | Cecilia Clementi | Frank Noé
Source: Journal of Chemical Theory and Computation (article, 2023-01-20)
Field: Materials Science — Materials Chemistry

Flow-Matching: Efficient Coarse-Graining of Molecular Dynamics without Forces Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time and length scales inaccessible to all-atom simulations. Parametrizing CG force fields to match all-atom simulations has mainly relied on force-matching or relative entropy minimization, which require many samples from costly simulations with all-atom or CG resolutions, respectively. Here we present <i>flow-matching</i>, a new training method for CG force fields that combines the advantages of both methods by leveraging normalizing flows, a generative deep learning method. Flow-matching first trains a normalizing flow to represent the CG probability density, which is equivalent to minimizing the relative entropy without requiring iterative CG simulations. Subsequently, the flow generates samples and forces according to the learned distribution in order to train the desired CG free energy model via force-matching. Even without requiring forces from the all-atom simulations, flow-matching outperforms classical force-matching by an order of magnitude in terms of data efficiency and produces CG models that can capture the folding and unfolding transitions of small proteins. Granularity ; Flow (mathematics) ; Matching (statistics) ; Dynamics (music) ; Molecular dynamics ; Computer science ; Statistical physics ; Biological system ; Physics ; Mechanics ; Chemistry ; Mathematics ; Computational chemistry ; Biology ; Statistics Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Protein Structure and Dynamics
Authors: Luca Mascaretti | Yuheng Chen | Olivier Henrotte | Ömer Yeşilyurt | Vladimir M. Shalaev | Alberto Naldoni | Alexandra Boltasseva
Source: ACS Photonics (article, 2023-12-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Designing Metasurfaces for Efficient Solar Energy Conversion Metasurfaces have recently emerged as a promising technological platform, offering unprecedented control over light by structuring materials at the nanoscale using two-dimensional arrays of subwavelength nanoresonators. These metasurfaces possess exceptional optical properties, enabling a wide variety of applications in imaging, sensing, telecommunication, and energy-related fields. One significant advantage of metasurfaces lies in their ability to manipulate the optical spectrum by precisely engineering the geometry and material composition of the nanoresonators' array. Consequently, they hold tremendous potential for efficient solar light harvesting and conversion. In this Review, we delve into the current state-of-the-art in solar energy conversion devices based on metasurfaces. First, we provide an overview of the fundamental processes involved in solar energy conversion, alongside an introduction to the primary classes of metasurfaces, namely, plasmonic and dielectric metasurfaces. Subsequently, we explore the numerical tools used that guide the design of metasurfaces, focusing particularly on inverse design methods that facilitate an optimized optical response. To showcase the practical applications of metasurfaces, we present selected examples across various domains such as photovoltaics, photoelectrochemistry, photocatalysis, solar-thermal and photothermal routes, and radiative cooling. These examples highlight the ways in which metasurfaces can be leveraged to harness solar energy effectively. By tailoring the optical properties of metasurfaces, significant advancements can be expected in solar energy harvesting technologies, offering new practical solutions to support an emerging sustainable society. Photovoltaics ; Energy harvesting ; Plasmon ; Solar energy ; Metamaterial ; Nanotechnology ; Energy transformation ; Photovoltaic system ; Materials science ; Optoelectronics ; Computer science ; Engineering physics ; Energy (signal processing) ; Physics ; Engineering ; Electrical engineering Metamaterials and Metasurfaces Applications ; Thermal Radiation and Cooling Technologies ; Plasmonic and Surface Plasmon Research
Authors: Jun Zhang | Chaohui Wang | Shasha Huang | Xuepeng Xiang | Yaoxu Xiong | Biao Xu | Shihua Ma | Haijun Fu | Ji‐Jung Kai | Xiongwu Kang | Shijun Zhao
Source: Joule (article, 2023-07-03)
Field: Materials Science — Materials Chemistry

Design high-entropy electrocatalyst via interpretable deep graph attention learning Electrocatalyst ; Graph ; Artificial intelligence ; Computer science ; Theoretical computer science ; Chemistry ; Electrode ; Physical chemistry ; Electrochemistry Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Fuel Cells and Related Materials
Authors: Lina Liu | Jing Dai | Sonali Das | Yaolin Wang | Han Yu | Shibo Xi | Zhikun Zhang | Xin Tu
Source: JACS Au (article, 2023-02-17)
Field: Materials Science — Materials Chemistry

Plasma-Catalytic CO<sub>2</sub> Reforming of Toluene over Hydrotalcite-Derived NiFe/(Mg, Al)O<sub><i>x</i></sub> Catalysts The removal of tar and CO<sub>2</sub> in syngas from biomass gasification is crucial for the upgrading and utilization of syngas. CO<sub>2</sub> reforming of tar (CRT) is a potential solution which simultaneously converts the undesirable tar and CO<sub>2</sub> to syngas. In this study, a hybrid dielectric barrier discharge (DBD) plasma-catalytic system was developed for the CO<sub>2</sub> reforming of toluene, a model tar compound, at a low temperature (∼200 °C) and ambient pressure. Periclase-phase (Mg, Al)O <sub><i>x</i></sub> nanosheet-supported NiFe alloy catalysts with various Ni/Fe ratios were synthesized from ultrathin Ni-Fe-Mg-Al hydrotalcite precursors and employed in the plasma-catalytic CRT reaction. The result demonstrated that the plasma-catalytic system is promising in promoting the low-temperature CRT reaction by generating synergy between DBD plasma and the catalyst. Among the various catalysts, Ni4Fe1-R exhibited superior activity and stability because of its highest specific surface area, which not only provided sufficient active sites for the adsorption of reactants and intermediates but also enhanced the electric field in the plasma. Furthermore, the stronger lattice distortion of Ni4Fe1-R provided more isolated O<sup>2-</sup> for CO<sub>2</sub> adsorption, and having the most intensive interaction between Ni and Fe in Ni4Fe1-R restrained the catalyst deactivation induced by the segregation of Fe from the alloy to form FeO <sub><i>x</i></sub> . Finally, in situ Fourier transform infrared spectroscopy combined with comprehensive catalyst characterization was used to elucidate the reaction mechanism of the plasma-catalytic CRT reaction and gain new insights into the plasma-catalyst interfacial effect. Catalysis ; Syngas ; Hydrotalcite ; Bimetallic strip ; Materials science ; Chemical engineering ; Dielectric barrier discharge ; Inorganic chemistry ; Chemistry ; Organic chemistry ; Dielectric Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Hydrodesulfurization Studies
Authors: Kriti Kapil | Arman Moini Jazani | Grzegorz Szczepaniak | Hironobu Murata | Mateusz Olszewski | Krzysztof Matyjaszewski
Source: Macromolecules (article, 2023-02-20)
Field: Chemistry — Organic Chemistry

Fully Oxygen-Tolerant Visible-Light-Induced ATRP of Acrylates in Water: Toward Synthesis of Protein-Polymer Hybrids Over the last decade, photoinduced ATRP techniques have been developed to harness the energy of light to generate radicals. Most of these methods require the use of UV light to initiate polymerization. However, UV light has several disadvantages: it can degrade proteins, damage DNA, cause undesirable side reactions, and has low penetration depth in reaction media. Recently, we demonstrated green-light-induced ATRP with dual catalysis, where eosin Y (EYH<sub>2</sub>) was used as an organic photoredox catalyst in conjunction with a copper complex. This dual catalysis proved to be highly efficient, allowing rapid and well-controlled aqueous polymerization of oligo(ethylene oxide) methyl ether methacrylate without the need for deoxygenation. Herein, we expanded this system to synthesize polyacrylates under biologically relevant conditions using Cu<sup>II</sup>/Me<sub>6</sub>TREN (Me<sub>6</sub>TREN = tris[2-(dimethylamino)ethyl]amine) and EYH<sub>2</sub> at ppm levels. Water-soluble oligo(ethylene oxide) methyl ether acrylate (average <i>M</i> <sub>n</sub> = 480, OEOA<sub>480</sub>) was polymerized in open reaction vessels under green light irradiation (520 nm). Despite continuous oxygen diffusion, high monomer conversions were achieved within 40 min, yielding polymers with narrow molecular weight distributions (1.17 ≤ <i>D̵</i> ≤ 1.23) for a wide targeted DP range (50-800). In situ chain extension and block copolymerization confirmed the preserved chain end functionality. In addition, polymerization was triggered/halted by turning on/off a green light, showing temporal control. The optimized conditions also enabled controlled polymerization of various hydrophilic acrylate monomers, such as 2-hydroxyethyl acrylate, 2-(methylsulfinyl)ethyl acrylate), and zwitterionic carboxy betaine acrylate. Notably, the method allowed the synthesis of well-defined acrylate-based protein-polymer hybrids using a straightforward reaction setup without rigorous deoxygenation. Polymerization ; Acrylate ; Polymer chemistry ; Ethylene oxide ; Chemistry ; Monomer ; Copolymer ; Methacrylate ; Polymer ; Photochemistry ; Organic chemistry Advanced Polymer Synthesis and Characterization ; Photopolymerization techniques and applications ; Click Chemistry and Applications
Authors: Ahmed Mohamed Radwan | Manosh C. Paul
Source: International Journal of Hydrogen Energy (article, 2023-10-27)
Field: Materials Science — Materials Chemistry

Plasma assisted NH3 combustion and NOx reduction technologies: Principles, challenges and prospective Combustion is the cornerstone for generating energy in various sectors and applications. The predominance of hydrocarbons combustion causes several environmental and human health issues. The ever-increasing demand for decarbonization of combustion technologies in order to reduce or eliminate undesirable emissions has created a major challenge, putting tremendous pressure on the international research community to develop alternative fuels. Ammonia has recently been explored as a promising carbon-free fuel and a great alternative to hydrocarbon fuels to achieve zero-carbon emissions. However, despite its advantages over hydrogen, ammonia combustion has some drawbacks including low burning velocity, flame stability, and high NOx emissions. This review begins with energy and environmental issues before moving on to hydrogen and ammonia as promising potential solutions, their advantages and drawbacks, and ammonia combustion kinetics. It summarises the principles of chemical kinetics of both ammonia combustion and NOx reduction coupled with the chemistry, kinetic mechanisms and impact of plasma on ammonia combustion. The effects of plasma on ammonia combustion and NOx reduction are also discussed, with a comparison of NOx reduction mechanisms and plasma approach. Finally, the review discusses the perspectives and challenges of using plasma in ammonia combustion. Combustion ; NOx ; Ammonia ; Chemistry ; Ammonia production ; Waste management ; Hydrogen ; Environmental science ; Process engineering ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Plasma Applications and Diagnostics