jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qiang Zhu | Suxi Wang | Xizu Wang | Ady Suwardi | Ming Hui Chua | Xiang Yun Debbie Soo | Jianwei Xu
Source: Nano-Micro Letters (review, 2021-05-03)
Field: Materials Science — Materials Chemistry

Bottom-Up Engineering Strategies for High-Performance Thermoelectric Materials The recent advancements in thermoelectric materials are largely credited to two factors, namely established physical theories and advanced materials engineering methods. The developments in the physical theories have come a long way from the "phonon glass electron crystal" paradigm to the more recent band convergence and nanostructuring, which consequently results in drastic improvement in the thermoelectric figure of merit value. On the other hand, the progresses in materials fabrication methods and processing technologies have enabled the discovery of new physical mechanisms, hence further facilitating the emergence of high-performance thermoelectric materials. In recent years, many comprehensive review articles are focused on various aspects of thermoelectrics ranging from thermoelectric materials, physical mechanisms and materials process techniques in particular with emphasis on solid state reactions. While bottom-up approaches to obtain thermoelectric materials have widely been employed in thermoelectrics, comprehensive reviews on summarizing such methods are still rare. In this review, we will outline a variety of bottom-up strategies for preparing high-performance thermoelectric materials. In addition, state-of-art, challenges and future opportunities in this domain will be commented. Thermoelectric effect ; Materials science ; Engineering physics ; Systems engineering ; Engineering ; Mechanical engineering ; Physics Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Heusler alloys: electronic and magnetic properties
Authors: Xin Geng | Shuwei Li | Lalani Mawella-Vithanage | Tao Ma | Mohamed Kilani | Bingwen Wang | Lu Ma | Chathuranga C. Hewa‐Rahinduwage | Alina Shafikova | Eranda Nikolla | Guangzhao Mao | Stephanie L. Brock | Liang Zhang | Long Luo
Source: Nature Communications (article, 2021-08-12)
Field: Materials Science — Materials Chemistry

Atomically dispersed Pb ionic sites in PbCdSe quantum dot gels enhance room-temperature NO2 sensing Atmospheric NO<sub>2</sub> is of great concern due to its adverse effects on human health and the environment, motivating research on NO<sub>2</sub> detection and remediation. Existing low-cost room-temperature NO<sub>2</sub> sensors often suffer from low sensitivity at the ppb level or long recovery times, reflecting the trade-off between sensor response and recovery time. Here, we report an atomically dispersed metal ion strategy to address it. We discover that bimetallic PbCdSe quantum dot (QD) gels containing atomically dispersed Pb ionic sites achieve the optimal combination of strong sensor response and fast recovery, leading to a high-performance room-temperature p-type semiconductor NO<sub>2</sub> sensor as characterized by a combination of ultra-low limit of detection, high sensitivity and stability, fast response and recovery. With the help of theoretical calculations, we reveal the high performance of the PbCdSe QD gel arises from the unique tuning effects of Pb ionic sites on NO<sub>2</sub> binding at their neighboring Cd sites. Quantum dot ; Ionic bonding ; Materials science ; Nanotechnology ; Ion ; Chemical physics ; Chemical engineering ; Chemistry Quantum Dots Synthesis And Properties ; Gas Sensing Nanomaterials and Sensors ; ZnO doping and properties
Authors: Wan‐Chen Cindy Lee | Duo‐Sheng Wang | Congzhe Zhang | Jingjing Xie | Bo Li | X. Peter Zhang
Source: Chem (article, 2021-03-29)
Field: Chemistry — Organic Chemistry

Asymmetric radical cyclopropanation of dehydroaminocarboxylates: Stereoselective synthesis of cyclopropyl α-amino acids Cyclopropanation ; Stereoselectivity ; Catalysis ; Enantioselective synthesis ; Chemistry ; In situ ; Combinatorial chemistry ; Organic chemistry ; Stereochemistry Cyclopropane Reaction Mechanisms ; Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions
Authors: Francisco Garnes–Portolés | Rossella Greco | Judit Oliver–Meseguer | Jorge Castellanos-Soriano | M. Consuelo Jiménez | Miguel López‐Haro | Juan Carlos Hernández‐Garrido | Mercedes Boronat | Raúl Pérez–Ruíz | Antonio Leyva‐Pérez
Source: Nature Catalysis (article, 2021-04-15)
Field: Chemistry — Organic Chemistry

Regioirregular and catalytic Mizoroki–Heck reactions Chemistry ; Aryl ; Heck reaction ; Intramolecular force ; Palladium ; Regioselectivity ; Steric effects ; Coupling reaction ; Photochemistry ; Ligand (biochemistry) ; Combinatorial chemistry ; Organic chemistry ; Catalysis ; Alkyl Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods ; Radical Photochemical Reactions
Authors: Jia‐Jun Jiang | Man‐Kin Wong
Source: Chemistry - An Asian Journal (review, 2021-01-02)
Field: Chemistry — Organic Chemistry

Recent Advances in the Development of Chiral Gold Complexes for Catalytic Asymmetric Catalysis Abstract Asymmetric gold catalysis has been rapidly developed in the past ten years. Breakthroughs have been made by rational design and meticulous selection of chiral ligands. This review summarizes newly developed gold‐catalyzed enantioselective organic transformations and recent progress in ligand design (since 2016), organized according to different types of chiral ligands, including bisphosphine ligands, monophosphine ligands, phosphite‐derived ligands, and N‐heterocyclic carbene ligands for asymmetric gold(I) catalysis as well as heterocyclic carbene ligands and oxazoline ligands for asymmetric gold(III) catalysis. Enantioselective synthesis ; Catalysis ; Oxazoline ; Carbene ; Combinatorial chemistry ; Rational design ; Ligand (biochemistry) ; Chemistry ; Organic chemistry ; Nanotechnology ; Materials science ; Receptor Catalytic Alkyne Reactions ; Asymmetric Hydrogenation and Catalysis ; Synthetic Organic Chemistry Methods
Authors: Aditya Nandy | Chenru Duan | Heather J. Kulik
Source: Current Opinion in Chemical Engineering (article, 2021-12-17)
Field: Materials Science — Materials Chemistry

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery Computer science ; Fidelity ; Property (philosophy) ; Quality (philosophy) ; Machine learning ; Scarcity ; High fidelity ; Artificial intelligence ; Data science ; Data quality ; Data mining ; Metric (unit) ; Engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Anas Karuth | Amirhadi Alesadi | Wenjie Xia | Bakhtiyor Rasulev
Source: Polymer (article, 2021-02-05)
Field: Materials Science — Polymers and Plastics

Predicting glass transition of amorphous polymers by application of cheminformatics and molecular dynamics simulations Cheminformatics ; Molecular dynamics ; Glass transition ; Polymer ; Molecular descriptor ; Quantitative structure–activity relationship ; Intermolecular force ; Materials science ; Amorphous solid ; Molecular model ; Computational chemistry ; Chemical physics ; Chemistry ; Thermodynamics ; Molecule ; Computer science ; Machine learning ; Organic chemistry ; Physics ; Composite material Polymer crystallization and properties ; Material Dynamics and Properties ; Polymer Nanocomposites and Properties
Authors: Yujie Li | Benxue Ma | Cong Li | Guowei Yu
Source: Computers and Electronics in Agriculture (article, 2021-12-31)
Field: Chemistry — Analytical Chemistry

Accurate prediction of soluble solid content in dried Hami jujube using SWIR hyperspectral imaging with comparative analysis of models Hyperspectral imaging ; Remote sensing ; Environmental science ; Geology Spectroscopy and Chemometric Analyses ; Ziziphus Jujuba Studies and Applications ; Remote Sensing and Land Use
Authors: Pikee Priya | N. R. Aluru
Source: npj Computational Materials (article, 2021-06-10)
Field: Materials Science — Materials Chemistry

Accelerated design and discovery of perovskites with high conductivity for energy applications through machine learning Abstract We use machine learning tools for the design and discovery of ABO 3 -type perovskite oxides for various energy applications, using over 7000 data points from the literature. We demonstrate a robust learning framework for efficient and accurate prediction of total conductivity of perovskites and their classification based on the type of charge carrier at different conditions of temperature and environment. After evaluating a set of &gt;100 features, we identify average ionic radius, minimum electronegativity, minimum atomic mass, minimum formation energy of oxides for all B-site, and B-site dopant ions of the perovskite as the crucial and relevant predictors for determining conductivity and the type of charge carriers. The models are validated by predicting the conductivity of compounds absent in the training set. We screen 1793 undoped and 95,832 A-site and B-site doped perovskites to report the perovskites with high conductivities, which can be used for different energy applications, depending on the type of the charge carriers. Electronegativity ; Perovskite (structure) ; Dopant ; Conductivity ; Materials science ; Doping ; Charge carrier ; Charge (physics) ; Ionic radius ; Ionic conductivity ; Computer science ; Machine learning ; Ion ; Optoelectronics ; Chemistry ; Physics ; Physical chemistry ; Crystallography ; Electrolyte Machine Learning in Materials Science ; Advancements in Solid Oxide Fuel Cells ; Electronic and Structural Properties of Oxides
Authors: Nor Qhairul Izzreen Mohd Noor | Rina Syafinaz Razali | Nur Khairina Ismail | Rabiatul Amirah Ramli | Umi Hartina Mohamad Razali | Ahmad Riduan Bahauddin | Nazikussabah Zaharudin | Rozzamri Ashari | Jamilah Bakar | Sharifudin Md. Shaarani
Source: Processes (review, 2021-12-09)
Field: Materials Science — Biomaterials

Application of Green Technology in Gelatin Extraction: A Review Growing demands for green and sustainable processing that eliminates the utilization of toxic chemicals and increases efficiency has encouraged the application of novel extraction technologies for the food industry. This review discusses the principles and potential application of several green technology for gelatin extraction. Several novel technologies and their processing efficiency are discussed in this review. Furthermore, factors that affect the quality of the gelatin produced from different sources are also highlighted. The potential application of ultrasound-assisted extraction (UAE), subcritical water extraction, high-pressure processing, and microwave-assisted extraction (MAE) to improve gelatin extraction are addressed. These technologies have the potential to become an efficient extraction method compared to the conventional extraction technologies. Several combinations of green and conventional technologies have been reported to yield promising results. These combinations, especially using conventional pre-treatment and green technologies for extraction, have been found to be more effective in producing gelatin. Since gelatin could be produced from various sources, it exhibits different characteristics; thus, different approaches and extraction method should be identified for specific types of gelatin. Although these technologies have limitations, such as overhydration and sophisticated systems explicitly designed for large-scale production, they are nonetheless more efficient in the long run to safeguard the environment as they reduce solvent usage and carbon footprint along the way. Gelatin ; Extraction (chemistry) ; Process engineering ; Biochemical engineering ; Carbon footprint ; Computer science ; Engineering ; Chromatography ; Chemistry ; Greenhouse gas Collagen: Extraction and Characterization ; Meat and Animal Product Quality ; Protein Hydrolysis and Bioactive Peptides
Authors: Mengyu Chen | Lihua Lu | Hui Yu | Cheng Li | Ni Zhao
Source: Advanced Science (review, 2021-07-28)
Field: Materials Science — Materials Chemistry

Integration of Colloidal Quantum Dots with Photonic Structures for Optoelectronic and Optical Devices Colloidal quantum dot (QD), a solution-processable nanoscale optoelectronic building block with well-controlled light absorption and emission properties, has emerged as a promising material system capable of interacting with various photonic structures. Integrated QD/photonic structures have been successfully realized in many optical and optoelectronic devices, enabling enhanced performance and/or new functionalities. In this review, the recent advances in this research area are summarized. In particular, the use of four typical photonic structures, namely, diffraction gratings, resonance cavities, plasmonic structures, and photonic crystals, in modulating the light absorption (e.g., for solar cells and photodetectors) or light emission (e.g., for color converters, lasers, and light emitting diodes) properties of QD-based devices is discussed. A brief overview of QD-based passive devices for on-chip photonic circuit integration is also presented to provide a holistic view on future opportunities for QD/photonic structure-integrated optoelectronic systems. Quantum dot ; Photonics ; Materials science ; Optoelectronics ; Nanotechnology ; Colloid ; Chemistry Quantum Dots Synthesis And Properties ; Photonic Crystals and Applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Isabell Bludau | Max Frank | Christian Dörig | Yujia Cai | Moritz Heusel | George Rosenberger | Paola Picotti | Ben C. Collins | Hannes Röst | Ruedi Aebersold
Source: Nature Communications (article, 2021-06-21)
Field: Chemistry — Spectroscopy

Systematic detection of functional proteoform groups from bottom-up proteomic datasets To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene - so-called proteoforms - that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation data as well as to more typical protein abundance vs. sample data matrices, demonstrating the systematic detection of assembly- and tissue-specific proteoform groups, respectively, in either dataset. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets. Computer science ; Proteomics ; Computational biology ; Functional diversity ; Coding (social sciences) ; Biology ; Gene ; Genetics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Machine Learning in Bioinformatics
Authors: Yun Zhang | Xiaojie Xu
Source: International Journal of Materials Research (formerly Zeitschrift fuer Metallkunde) (article, 2021-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Predicting doped Fe-based superconductor critical temperature from structural and topological parameters using machine learning Abstract Recently, Fe-based superconductors have shown promising properties of high critical temperature and high upper critical fields, which are prerequisites for applications in high-field magnets. Critical temperature, T c , is an important characteristic correlated with crystallographic and electronic structures. By doping with foreign ions in the crystal structure, T c can be modified, which however requires significant manpower and resources for materials synthesis and characterizations. In this study, we develop the Gaussian process regression model to predict T c of doped Fe-based superconductors based on structural and topological parameters, including the lattice constants, volume, and bonding parameter topological index H 31 . The model is stable and accurate, contributing to fast T c estimations. Superconductivity ; Materials science ; Doping ; Condensed matter physics ; Topology (electrical circuits) ; Crystal structure ; Lattice constant ; Crystallography ; Physics ; Combinatorics ; Quantum mechanics ; Mathematics ; Optoelectronics Iron-based superconductors research ; Rare-earth and actinide compounds ; Machine Learning in Materials Science
Authors: Naveed Ahmed Khan | Muhammad Bilal Khan Niazi | Farooq Sher | Zaib Jahan | Tayyaba Nооr | Ofaira Azhar | Tazien Rashid | Naseem Iqbal
Source: Polymers (article, 2021-07-14)
Field: Materials Science — Biomaterials

Metal Organic Frameworks Derived Sustainable Polyvinyl Alcohol/Starch Nanocomposite Films as Robust Materials for Packaging Applications Bio-nanocomposites-based packaging materials have gained significance due to their prospective application in rising areas of packaged food. This research aims to fabricate biodegradable packaging films based upon polyvinyl alcohol (PVA) and starch integrated with metal-organic frameworks (MOFs) or organic additives. MOFs offer unique features in terms of surface area, mechanical strength, and chemical stability, which make them favourable for supporting materials used in fabricating polymer-based packaging materials. zeolitic imidazolate frameworks (ZIFs) are one of the potential candidates for this application due to their highly conductive network with a large surface area and high porosity. Present research illustrates a model system based on ZIF-67 (C<sub>8</sub>H<sub>10</sub>N<sub>4</sub>Co) bearing 2-10 wt.% loading in a matrix of PVA/starch blend with or without pyrolysis to probe the function of intermolecular interaction in molecular packing, tensile properties, and glass transition process. ZIF-67 nanoparticles were doped in a PVA/starch mixture, and films were fabricated using the solution casting method. It was discovered through scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and Fourier transform infrared spectroscopy (FTIR) that addition of ZIF-67 and pyrolyzed ZIF-67 changed and enhanced the thermal stability of the membrane. Moreover, 2-10 wt.% loading of ZIF-67 effected the thermal stability, owing to an interlayer aggregation of ZIF-67. The membranes containing pyrolyzed ZIF-67 showed mechanical strength in the order of 25 MPa in a moderate loading of pyrolyzed ZIF-67 (i.e., at 4 wt.%). The crystallinity enhanced by an increment in ZIF-67 loading. On the other hand, pyrolyzed ZIF-67 carbon became amorphous because of the inert environment and elevated temperature. The surface area also increased after the pyrolysis, which helped to increase the strength of the composite films. Materials science ; Thermogravimetric analysis ; Nanocomposite ; Thermal stability ; Zeolitic imidazolate framework ; Polyvinyl alcohol ; Chemical engineering ; Crystallinity ; Fourier transform infrared spectroscopy ; Pyrolysis ; Polymer ; Dynamic mechanical analysis ; Composite material ; Metal-organic framework ; Organic chemistry ; Chemistry ; Adsorption biodegradable polymer synthesis and properties ; Nanocomposite Films for Food Packaging ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Sarah I. Bukhari | Syed Sarim Imam | Mohammad Zaki Ahmad | Parameswara Rao Vuddanda | Sultan Alshehri | Wael A. Mahdi | Javed Ahmad
Source: Pharmaceutics (review, 2021-06-07)
Field: Materials Science — Biomaterials

Recent Progress in Lipid Nanoparticles for Cancer Theranostics: Opportunity and Challenges Cancer is one of the major leading causes of mortality in the world. The implication of nanotherapeutics in cancer has garnered splendid attention owing to their capability to efficiently address various difficulties associated with conventional drug delivery systems such as non-specific biodistribution, poor efficacy, and the possibility of occurrence of multi-drug resistance. Amongst a plethora of nanocarriers for drugs, this review emphasized lipidic nanocarrier systems for delivering anticancer therapeutics because of their biocompatibility, safety, high drug loading and capability to simultaneously carrying imaging agent and ligands as well. Furthermore, to date, the lack of interaction between diagnosis and treatment has hampered the efforts of the nanotherapeutic approach alone to deal with cancer effectively. Therefore, a novel paradigm with concomitant imaging (with contrasting agents), targeting (with biomarkers), and anticancer agent being delivered in one lipidic nanocarrier system (as cancer theranostics) seems to be very promising in overcoming various hurdles in effective cancer treatment. The major obstacles that are supposed to be addressed by employing lipidic theranostic nanomedicine include nanomedicine reach to tumor cells, drug internalization in cancer cells for therapeutic intervention, off-site drug distribution, and uptake via the host immune system. A comprehensive account of recent research updates in the field of lipidic nanocarrier loaded with therapeutic and diagnostic agents is covered in the present article. Nevertheless, there are notable hurdles in the clinical translation of the lipidic theranostic nanomedicines, which are also highlighted in the present review along with plausible countermeasures. Nanocarriers ; Nanomedicine ; Drug delivery ; Nanotechnology ; Medicine ; Cancer ; Biodistribution ; Cancer therapy ; Drug ; Pharmacology ; Nanoparticle ; Materials science ; Biology ; Biotechnology Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; RNA Interference and Gene Delivery
Authors: Mark R. Gilbert | Kazuto Arakawa | Zachary Bergstrom | M.J. Caturla | S. L. Dudarev | Fei Gao | Alexandra M. Goryaeva | Shenyang Hu | Xunxiang Hu | Richard J. Kurtz | A. Litnovsky | Jaime Marian | Mihai‐Cosmin Marinica | Enrique Martínez | Emmanuelle A. Marquis | Daniel R. Mason | Ba Nghiep Nguyen | Pär Olsson | Yuri Osetskiy | David J. Senor | Wahyu Setyawan | Michael P. Short | Tomoaki Suzudo | Jason R. Trelewicz | Tomohito Tsuru | Gary S. Was | Brian D. Wirth | Yang Liu | Yunyan Zhang | S.J. Zinkle
Source: Journal of Nuclear Materials (article, 2021-06-08)
Field: Materials Science — Materials Chemistry

Perspectives on multiscale modelling and experiments to accelerate materials development for fusion Computer science ; Fusion ; Replicate ; Fusion power ; Systems engineering ; Biochemical engineering ; Data science ; Engineering ; Physics Fusion materials and technologies ; Nuclear Materials and Properties ; Microstructure and mechanical properties