jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ling Zhou | Michal Slaný | Bingbing Bai | Weichao Du | Chengtun Qu | Jie Zhang | Ying Tang
Source: Nanomaterials (article, 2021-03-28)
Field: Materials Science — Materials Chemistry

Enhanced Removal of Sulfonated Lignite from Oil Wastewater with Multidimensional MgAl-LDH Nanoparticles In this study, hierarchical MgAl-LDH (layered double hydroxide) nanoparticles with a flower-like morphology were prepared under a hydrothermal condition by employing worm-like micelles formed by cetyltrimethylammonium bromide (CTAB) and salicylic acid (SA) as templates. The morphology and structure of the materials were characterized by Brunauer-Emmett-Teller (BET), SEM, and XRD analyses. The performance for the adsorption of sulfonated lignite (SL) was also investigated in detail. FTIR was used to detect the presence of active functional groups and determine whether they play important roles in adsorption. The results showed that the hierarchical MgAl-LDH nanoparticles with a specific surface area of 126.31 m<sup>2</sup>/g possessed a flower-like morphology and meso-macroporous structures. The adsorption capacity was high-its value was 1014.20 mg/g at a temperature of 298 K and an initial pH = 7, which was higher than traditional MgAl-LDH (86 mg/g). The adsorption process of sulfonated lignite followed the pseudo-second-order kinetics model and conformed to Freundlich isotherm model with a spontaneous exothermic nature. In addition, the hierarchical MgAl-LDH could be regenerated and used, and the adsorption was high after three adsorption cycles. The main adsorption mechanisms were electrostatic attraction and ion exchange between the hierarchical MgAl-LDH and sulfonated lignite. Adsorption ; Hydroxide ; Bromide ; Ion exchange ; Chemical engineering ; Freundlich equation ; Nanoparticle ; Fourier transform infrared spectroscopy ; Nuclear chemistry ; Chemistry ; Materials science ; Inorganic chemistry ; Organic chemistry ; Ion Layered Double Hydroxides Synthesis and Applications ; Phosphorus and nutrient management ; Catalysis and Hydrodesulfurization Studies
Authors: G. De Temmerman | K. Heinola | D. Borodin | S. Brezinsek | R.P. Doerner | M. Rubel | E. Fortuna-Zaleśna | Ch. Linsmeier | D. Nishijima | K. Nordlund | Michael Probst | J. Romazanov | E. Safi | T. Schwarz‐Selinger | A. Widdowson | Bastiaan J. Braams | Hyun-Kyung Chung | C. Hill
Source: Nuclear Materials and Energy (article, 2021-04-26)
Field: Materials Science — Materials Chemistry

Data on erosion and hydrogen fuel retention in Beryllium plasma-facing materials ITER will use beryllium as a plasma-facing material in the main chamber, covering a total surface area of about 620 m2. Given the importance of beryllium erosion and co-deposition for tritium retention in ITER, significant efforts have been made to understand the behaviour of beryllium under fusion-relevant conditions with high particle and heat loads. This paper provides a comprehensive report on the state of knowledge of beryllium behaviour under fusion-relevant conditions: the erosion mechanisms and their consequences, beryllium migration in JET, fuel retention and dust generation. The paper reviews basic laboratory studies, advanced computer simulations and experience from laboratory plasma experiments in linear simulators of plasma–wall interactions and in controlled fusion devices using beryllium plasma-facing components. A critical assessment of analytical methods and simulation codes used in beryllium studies is given. The overall objective is to review the existing set of data with a broad literature survey and to identify gaps and research needs to broaden the database for ITER. Beryllium ; Nuclear engineering ; Fusion power ; Plasma ; Materials science ; Erosion ; Hydrogen ; Environmental science ; Nuclear physics ; Chemistry ; Engineering ; Physics ; Geology Fusion materials and technologies ; Nuclear Materials and Properties ; Magnetic confinement fusion research
Authors: Helyati Abu Hassan Shaari | Muhammad Mahyiddin Ramli | Mohd Nazim Mohtar | Norizah Abdul Rahman | Azizan Ahmad
Source: Polymers (review, 2021-06-10)
Field: Materials Science — Polymers and Plastics

Synthesis and Conductivity Studies of Poly(Methyl Methacrylate) (PMMA) by Co-Polymerization and Blending with Polyaniline (PANi) Poly(methyl methacrylate) (PMMA) is a lightweight insulating polymer that possesses good mechanical stability. On the other hand, polyaniline (PANi) is one of the most favorable conducting materials to be used, as it is easily synthesized, cost-effective, and has good conductivity. However, most organic solvents have restricted potential applications due to poor mechanical properties and dispersibility. Compared to PANi, PMMA has more outstanding physical and chemical properties, such as good dimensional stability and better molecular interactions between the monomers. To date, many research studies have focused on incorporating PANi into PMMA. In this review, the properties and suitability of PANi as a conducting material are briefly reviewed. The major parts of this paper reviewed different approaches to incorporating PANi into PMMA, as well as evaluating the modifications to improve its conductivity. Finally, the polymerization condition to prepare PMMA/PANi copolymer to improve its conductivity is also discussed. Polyaniline ; Materials science ; Polymerization ; Methyl methacrylate ; Copolymer ; Conductivity ; Monomer ; Conductive polymer ; Polymer ; Chemical engineering ; Poly(methyl methacrylate) ; Polymer chemistry ; Composite material ; Chemistry Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Supercapacitor Materials and Fabrication
Authors: Kumar Vikrant | Ki‐Hyun Kim | Eilhann E. Kwon | Danil W. Boukhvalov
Source: Chemical Engineering Journal (article, 2021-11-09)
Field: Materials Science — Materials Chemistry

Reactive adsorption and catalytic oxidation of gaseous formaldehyde at room temperature by a synergistic copper-magnesium bimetal oxide biochar composite Chemistry ; Catalysis ; Adsorption ; Copper ; Bimetallic strip ; Inorganic chemistry ; Oxide ; Formaldehyde ; Biochar ; Metal ; Magnesium ; Organic chemistry ; Pyrolysis Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Industrial Gas Emission Control
Authors: Ana R. Cardoso | Manuela F. Frasco | Verónica Serrano | Elvira Fortunato | M. Goreti F. Sales
Source: Biosensors (review, 2021-05-13)
Field: Materials Science — Materials Chemistry

Molecular Imprinting on Nanozymes for Sensing Applications As part of the biomimetic enzyme field, nanomaterial-based artificial enzymes, or nanozymes, have been recognized as highly stable and low-cost alternatives to their natural counterparts. The discovery of enzyme-like activities in nanomaterials triggered a broad range of designs with various composition, size, and shape. An overview of the properties of nanozymes is given, including some examples of enzyme mimics for multiple biosensing approaches. The limitations of nanozymes regarding lack of selectivity and low catalytic efficiency may be surpassed by their easy surface modification, and it is possible to tune specific properties. From this perspective, molecularly imprinted polymers have been successfully combined with nanozymes as biomimetic receptors conferring selectivity and improving catalytic performance. Compelling works on constructing imprinted polymer layers on nanozymes to achieve enhanced catalytic efficiency and selective recognition, requisites for broad implementation in biosensing devices, are reviewed. Multimodal biomimetic enzyme-like biosensing platforms can offer additional advantages concerning responsiveness to different microenvironments and external stimuli. Ultimately, progress in biomimetic imprinted nanozymes may open new horizons in a wide range of biosensing applications. Biosensor ; Nanotechnology ; Molecularly imprinted polymer ; Artificial enzyme ; Molecular imprinting ; Nanomaterials ; Biochemical engineering ; Chemistry ; Materials science ; Catalysis ; Selectivity ; Engineering Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques
Authors: Daniel H. Weinland | Robert‐Jan van Putten | Gert‐Jan M. Gruter
Source: European Polymer Journal (article, 2021-12-24)
Field: Materials Science — Biomaterials

Evaluating the commercial application potential of polyesters with 1,4:3,6-dianhydrohexitols (isosorbide, isomannide and isoidide) by reviewing the synthetic challenges in step growth polymerization Plastic materials play a pivotal role in modern society. Finding sustainable alternatives to established fossil-based polymers is an important part of the effort to reduce the environmental impact of the materials sector. 1,4:3,6-dianhydrohexitols (isosorbide, isomannide and isoidide) are a group of biobased diol monomers that are promising for the synthesis of sustainable polyesters. Their rigid molecular structure imparts favorable material properties to polymers. Isosorbide is especially interesting due to its current commercial availability and synthesis from glucose. This potential is reflected in the large number of publications on polyesters with isosorbide in the past decade. Despite this, high molecular weight polyesters with high molar percentages of 1,4:3,6-dianhydrohexitols remain elusive due to the low reactivity of 1,4:3,6-dianhydrohexitols in (trans)esterification reactions. This review compares the efforts on the synthesis of polyesters with 1,4:3,6-dianhydrohexitols from both the academic and patent literature and puts them into perspective regarding industrial viability. Interesting synthesis strategies and possible future developments are highlighted together with material properties. Isosorbide ; Polyester ; Materials science ; Polymer ; Polymer science ; Reactivity (psychology) ; Monomer ; Biochemical engineering ; Organic chemistry ; Nanotechnology ; Chemistry ; Engineering biodegradable polymer synthesis and properties ; Catalysis for Biomass Conversion ; Carbon dioxide utilization in catalysis
Authors: Si Yin Tee | Enyi Ye
Source: Materials Advances (article, 2021-01-01)
Field: Chemistry — Electrochemistry

Recent advancements in coinage metal nanostructures and bio-applications In this review, the recent advances of coinage metals such as Cu, Ag, Au, and their bimetallic nanostructures are summarized, including synthetic methodologies and bio-applications of antibacterial, SERS-based detection, and electrochemical sensing. Nanotechnology ; Bimetallic strip ; Nanostructure ; Materials science ; Electrochemistry ; Metal ; Metallurgy ; Chemistry ; Electrode Electrochemical Analysis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Liwei Ye | Barry C. Thompson
Source: Journal of Polymer Science (article, 2021-09-15)
Field: Chemistry — Organic Chemistry

Improving the efficiency and sustainability of catalysts for direct arylation polymerization (DArP) Abstract In the past decade, direct arylation polymerization (DArP) has rapidly developed as a sustainable synthetic protocol for cost‐effective, atom‐economical preparation of conjugated polymers. By circumventing monomer functionalization with toxic transmetallating reagents such as organostannane and organoboron required for Stille‐Migita and Suzuki‐Miyaura polymerization methods, DArP proceeds through a metal‐catalyzed CH activation pathway for the preparation of high‐performance conjugated polymer materials. This review evaluates the development of several classes of efficient catalysts/catalytic systems from small‐molecule studies to polymerizations, including the mechanisms involved in these transformations and how they inspire catalyst and monomer design for defect‐free conjugated polymer synthesis. Recent advances in developing more sustainable first‐row transition metal catalysts for DArP are also highlighted, and the fundamental understanding of these efficient and sustainable catalysts should motivate the pursuit for the next generation of catalytic design to enable more effective and environmentally friendly conjugated polymer synthesis. Polymerization ; Conjugated system ; Polymer ; Monomer ; Catalysis ; Combinatorial chemistry ; Chemistry ; Organic chemistry ; Nanotechnology ; Materials science Catalytic Cross-Coupling Reactions ; Organoboron and organosilicon chemistry ; Covalent Organic Framework Applications
Authors: Teresa Gatti | Francesco Lamberti | Raffaello Mazzaro | Ilka Kriegel | Derck Schlettwein | Francesco Enrichi | Nicolò Lago | Eleonora Di Maria | Gaudenzio Meneghesso | Alberto Vomiero | Silvia Gross
Source: Advanced Energy Materials (article, 2021-07-02)
Field: Materials Science — Materials Chemistry

Opportunities from Doping of Non‐Critical Metal Oxides in Last Generation Light‐Conversion Devices Abstract The need to develop sustainable energy solutions is an urgent requirement for society, with the additional requirement to limit dependence on critical raw materials, within a virtuous circular economy model. In this framework, it is essential to identify new avenues for light‐conversion into clean energy and fuels exploiting largely available materials and green production methods. Metal oxide semiconductors (MOSs) emerge among other species for their remarkable environmental stability, chemical tunability, and optoelectronic properties. MOSs are often key constituents in next generation energy devices, mainly in the role of charge selective layers. Their use as light harvesters is hitherto rather limited, but progressively emerging. One of the key strategies to boost their properties involves doping, that can improve charge mobility, light absorption and tune band structures to maximize charge separation at heterojunctions. In this review, effective methods to dope MOSs and to exploit the derived benefits in relation to performance enhancement in different types of devices are identified and critically compared. The work is focused specifically on the best opportunities coming from the use of non‐critical raw materials, so as to contribute in defining an economically feasible roadmap for light conversion technologies based on these highly stable and widely available compounds. Materials science ; Heterojunction ; Exploit ; Nanotechnology ; Doping ; Semiconductor ; Energy transformation ; Engineering physics ; Optoelectronics ; Process engineering ; Computer science ZnO doping and properties ; Gas Sensing Nanomaterials and Sensors ; Electronic and Structural Properties of Oxides
Authors: Xiangfu Meng | Yunhui Xing | Jiawen Li | Cechuan Deng | Yifei Li | Xi Ren | Donghui Zhang
Source: Frontiers in Cell and Developmental Biology (review, 2021-04-21)
Field: Materials Science — Biomaterials

Rebuilding the Vascular Network: In vivo and in vitro Approaches As the material transportation system of the human body, the vascular network carries the transportation of materials and nutrients. Currently, the construction of functional microvascular networks is an urgent requirement for the development of regenerative medicine and <i>in vitro</i> drug screening systems. How to construct organs with functional blood vessels is the focus and challenge of tissue engineering research. Here in this review article, we first introduced the basic characteristics of blood vessels in the body and the mechanism of angiogenesis <i>in vivo</i>, summarized the current methods of constructing tissue blood vessels <i>in vitro</i> and <i>in vivo</i>, and focused on comparing the functions, applications and advantages of constructing different types of vascular chips to generate blood vessels. Finally, the challenges and opportunities faced by the development of this field were discussed. In vivo ; Vascular network ; Angiogenesis ; Regenerative medicine ; Blood vessel ; Tissue engineering ; Neuroscience ; Computer science ; Biology ; Medicine ; Biomedical engineering ; Cell biology ; Anatomy ; Biotechnology ; Stem cell ; Cancer research ; Internal medicine Electrospun Nanofibers in Biomedical Applications ; Tissue Engineering and Regenerative Medicine ; 3D Printing in Biomedical Research
Authors: Stephanie G. E. Amos | Diana Cavalli | Franck Le Vaillant | Jérôme Waser
Source: Angewandte Chemie International Edition (article, 2021-08-17)
Field: Chemistry — Organic Chemistry

Direct Photoexcitation of Ethynylbenziodoxolones: An Alternative to Photocatalysis for Alkynylation Reactions** Ethynylbenziodoxolones (EBXs) are commonly used as radical traps in photocatalytic alkynylations. Herein, we report that aryl-substituted EBX reagents can be directly activated by visible light irradiation. They act as both oxidants and radical traps, alleviating the need for a photocatalyst in several reported EBX-mediated processes, including decarboxylative and deboronative alkynylations, the oxyalkynylation of enamides and the C-H alkynylation of THF. Furthermore, the method could be applied to the synthesis of alkynylated quaternary centers from tertiary alcohols via stable oxalate salts and from tertiary amines via aryl imines. A photocatalytic process using 4CzIPN as an organic dye was also developed for the deoxyalkynylation of oxalates. Photocatalysis ; Alkynylation ; Oxalate ; Photoexcitation ; Reagent ; Chemistry ; Aryl ; Photochemistry ; Organic dye ; Visible spectrum ; Photoredox catalysis ; Combinatorial chemistry ; Organic chemistry ; Catalysis ; Materials science ; Chemical engineering ; Alkyl ; Excited state Radical Photochemical Reactions ; Sulfur-Based Synthesis Techniques ; Catalytic C–H Functionalization Methods
Authors: Noushin Omidvar | Hemanth Somarajan Pillai | Shih‐Han Wang | Tianyou Mou | Siwen Wang | Andy Athawale | Luke E. K. Achenie | Hongliang Xin
Source: The Journal of Physical Chemistry Letters (article, 2021-11-18)
Field: Materials Science — Materials Chemistry

Interpretable Machine Learning of Chemical Bonding at Solid Surfaces Understanding the nature of chemical bonding and its variation in strength across physically tunable factors is important for the development of novel catalytic materials. One way to speed up this process is to employ machine learning (ML) algorithms with online data repositories curated from high-throughput experiments or quantum-chemical simulations. Despite the reasonable predictive performance of ML models for predicting reactivity properties of solid surfaces, the ever-growing complexity of modern algorithms, e.g., deep learning, makes them black boxes with little to no explanation. In this Perspective, we discuss recent advances of interpretable ML for opening up these black boxes from the standpoints of feature engineering, algorithm development, and post hoc analysis. We underline the pivotal role of interpretability as the foundation of next-generation ML algorithms and emerging AI platforms for driving discoveries across scientific disciplines. Interpretability ; Machine learning ; Computer science ; Artificial intelligence ; Feature (linguistics) ; Throughput ; Perspective (graphical) ; Post hoc ; Process (computing) ; Quantum chemical ; Identification (biology) ; Chemistry ; Molecule Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Fuel Cells and Related Materials
Authors: Jacques A. Esterhuizen | Bryan R. Goldsmith | Suljo Linic
Source: Chem Catalysis (article, 2021-08-19)
Field: Materials Science — Materials Chemistry

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning Principal component analysis ; Electronic structure ; Chemisorption ; Metal ; Artificial intelligence ; Unsupervised learning ; Biological system ; Computer science ; Materials science ; Catalysis ; Pattern recognition (psychology) ; Chemistry ; Machine learning ; Computational chemistry ; Metallurgy Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Electrochemical Analysis and Applications
Authors: Xuhao Wan | Zhaofu Zhang | Wei Yu | Yuzheng Guo
Source: Materials Reports Energy (article, 2021-06-25)
Field: Materials Science — Materials Chemistry

A density-functional-theory-based and machine-learning-accelerated hybrid method for intricate system catalysis Being progressively applied in the design of highly active catalysts for energy devices, machine learning (ML) technology has shown attractive ability of dramatically reducing the computational cost of the traditional density functional theory (DFT) method, showing a particular advantage for the simulation of intricate system catalysis. Starting with a basic description of the whole workflow of the novel DFT-based and ML-accelerated (DFT-ML) scheme, and the common algorithms useable for machine learning, we presented in this paper our work on the development and performance test of a DFT-based ML method for catalysis program (DMCP) to implement the DFT-ML scheme. DMCP is an efficient and user-friendly program with the flexibility to accommodate the needs of performing ML calculations based on the data generated by DFT calculations or from materials database. We also employed an example of transition metal phthalocyanine double-atom catalysts as electrocatalysts for carbon reduction reaction to exhibit the general workflow of the DFT-ML hybrid scheme and our DMCP program. Density functional theory ; Workflow ; Flexibility (engineering) ; Computer science ; Catalysis ; Reduction (mathematics) ; Scheme (mathematics) ; Computational science ; Atom (system on chip) ; Chemistry ; Computational chemistry ; Mathematics ; Parallel computing Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; CO2 Reduction Techniques and Catalysts
Authors: Yilin Ning | Shengli Niu | Yongzheng Wang | Jianli Zhao | Chunmei Lu
Source: Renewable Energy (article, 2021-05-05)
Field: Materials Science — Biomaterials

Sono-modified halloysite nanotube with NaAlO2 as novel heterogeneous catalyst for biodiesel production: Optimization via GA_BP neural network Transesterification ; Biodiesel ; Biodiesel production ; Methanol ; Catalysis ; Halloysite ; Yield (engineering) ; Materials science ; Chemical engineering ; Pulp and paper industry ; Chemistry ; Organic chemistry ; Composite material ; Engineering Clay minerals and soil interactions ; Mesoporous Materials and Catalysis ; Biodiesel Production and Applications
Authors: Yijing Xu | Lu Jiang | Xiang Qi
Source: Computational Materials Science (article, 2021-06-08)
Field: Materials Science — Materials Chemistry

Machine learning in thermoelectric materials identification: Feature selection and analysis Thermoelectric effect ; Computer science ; Feature selection ; Thermoelectric materials ; Artificial intelligence ; Machine learning ; Feature (linguistics) ; Thermoelectric cooling ; Set (abstract data type) ; Data mining Advanced Thermoelectric Materials and Devices ; Machine Learning in Materials Science ; Thermal properties of materials