jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Safa Radmehr | Mina Sabzevari | Mehrorang Ghaedi | Mohammad Hossein Ahmadi Azqhandi | Farzaneh Marahel
Source: Journal of environmental chemical engineering (article, 2021-07-10)
Field: Chemistry — Organic Chemistry

Adsorption of nalidixic acid antibiotic using a renewable adsorbent based on Graphene oxide from simulated wastewater Adsorption ; Graphene ; Materials science ; Nalidixic acid ; Response surface methodology ; Oxide ; Scanning electron microscope ; Nanocomposite ; Langmuir adsorption model ; Adaptive neuro fuzzy inference system ; Nuclear chemistry ; Central composite design ; Chemical engineering ; Chemistry ; Nanotechnology ; Composite material ; Chromatography ; Organic chemistry ; Computer science ; Fuzzy logic Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Nils Bäumer | Jonas Matern | Gustavo Fernández
Source: Chemical Science (review, 2021-01-01)
Field: Materials Science — Biomaterials

Recent progress and future challenges in the supramolecular polymerization of metal-containing monomers The self-assembly of discrete molecular entities into functional nanomaterials has become a major research area in the past decades. The library of investigated compounds has diversified significantly, while the field as a whole has matured. The incorporation of metal ions in the molecular design of the (supra-)molecular building blocks greatly expands the potential applications, while also offering a promising approach to control molecular recognition and attractive and/or repulsive intermolecular binding events. Hence, supramolecular polymerization of metal-containing monomers has emerged as a major research focus in the field. In this perspective article, we highlight recent significant advances in supramolecular polymerization of metal-containing monomers and discuss their implications for future research. Additionally, we also outline some major challenges that metallosupramolecular chemists (will) have to face to produce metallosupramolecular polymers (MSPs) with advanced applications and functionalities. Monomer ; Perspective (graphical) ; Supramolecular chemistry ; Polymerization ; Nanotechnology ; Metal ; Materials science ; Chemistry ; Polymer chemistry ; Computer science ; Organic chemistry ; Polymer ; Molecule Supramolecular Self-Assembly in Materials ; Supramolecular Chemistry and Complexes
Authors: Zachary Brounstein | Chris M. Yeager | Andrea Labouriau
Source: Polymers (article, 2021-02-15)
Field: Materials Science — Biomaterials

Development of Antimicrobial PLA Composites for Fused Filament Fabrication In addition to possessing the desirable properties of being a biodegradable and biocompatible polymer fabricated from renewable resources, poly (lactic acid) (PLA) has useful mechanical and thermal attributes that has enabled it to be one of the most widely-used plastics for medicine, manufacturing, and agriculture. Yet, PLA composites have not been heavily explored for use in 3D-printing applications, and the range of feasible materials for the technology is limited, which inhibits its potential growth and industry adoption. In this study, tunable, multifunctional antimicrobial PLA composite filaments for 3D-printing have been fabricated and tested via chemical, thermal, mechanical, and antimicrobial experiments. Thermally stable antimicrobial ceramics, ZnO and TiO<sub>2</sub>, were used as fillers up to 30 wt%, and poly (ethylene glycol) (PEG) was used as a plasticizer to tune the physical material properties. Results demonstrate that the PLA composite filaments exhibit the thermal phase behaviors and thermal stability suitable for 3D-printing. Additionally, PEG can be used to tune the mechanical properties while not affecting the antimicrobial efficacy that ZnO and TiO<sub>2</sub> imbue. Materials science ; Ethylene glycol ; Thermal stability ; Polymer ; Fabrication ; Composite material ; Composite number ; Antimicrobial ; Ceramic ; Plasticizer ; 3D printing ; Fused filament fabrication ; Chemical engineering ; Organic chemistry ; Chemistry biodegradable polymer synthesis and properties ; Additive Manufacturing and 3D Printing Technologies ; Bone Tissue Engineering Materials
Authors: Toshihiko Mandai | Yong Youn | Yoshitaka Tateyama
Source: Materials Advances (article, 2021-01-01)
Field: Chemistry — Inorganic Chemistry

Remarkable electrochemical and ion-transport characteristics of magnesium-fluorinated alkoxyaluminate–diglyme electrolytes for magnesium batteries One specific magnesium battery electrolyte composed of Mg[Al(HFIP) 4 ] 2 and G2 exhibits outstanding electrochemical activity owing to the enhanced mass transport combined with favorable interfacial kinetics. Diglyme ; Magnesium ; Electrolyte ; Electrochemistry ; Battery (electricity) ; Inorganic chemistry ; Mass transport ; Kinetics ; Ion ; Chemistry ; Materials science ; Electrode ; Metallurgy ; Thermodynamics ; Organic chemistry ; Physical chemistry Inorganic Chemistry and Materials ; Inorganic Fluorides and Related Compounds ; Layered Double Hydroxides Synthesis and Applications
Authors: Yingfen Wu | Diane C. Darland | Julia Xiaojun Zhao
Source: Sensors (review, 2021-07-31)
Field: Materials Science — Materials Chemistry

Nanozymes—Hitting the Biosensing “Target” Nanozymes are a class of artificial enzymes that have dimensions in the nanometer range and can be composed of simple metal and metal oxide nanoparticles, metal nanoclusters, dots (both quantum and carbon), nanotubes, nanowires, or multiple metal-organic frameworks (MOFs). They exhibit excellent catalytic activities with low cost, high operational robustness, and a stable shelf-life. More importantly, they are amenable to modifications that can change their surface structures and increase the range of their applications. There are three main classes of nanozymes including the peroxidase-like, the oxidase-like, and the antioxidant nanozymes. Each of these classes catalyzes a specific group of reactions. With the development of nanoscience and nanotechnology, the variety of applications for nanozymes in diverse fields has expanded dramatically, with the most popular applications in biosensing. Nanozyme-based novel biosensors have been designed to detect ions, small molecules, nucleic acids, proteins, and cancer cells. The current review focuses on the catalytic mechanism of nanozymes, their application in biosensing, and the identification of future directions for the field. Biosensor ; Nanotechnology ; Nanoclusters ; Nanowire ; Chemistry ; Materials science Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Nils Lennart Frye | Constantin G. Daniliuc | Armido Studer
Source: Angewandte Chemie International Edition (article, 2021-12-27)
Field: Chemistry — Organic Chemistry

Radical 1‐Fluorosulfonyl‐2‐alkynylation of Unactivated Alkenes Sulfonyl fluorides have found widespread use in chemical biology and drug discovery. The development of synthetic methods for the introduction of the sulfonyl fluoride moiety is therefore of importance. Herein, a transition-metal-free radical 1,2-difunctionalization of unactivated alkenes via FSO<sub>2</sub> -radical addition with subsequent vicinal alkynylation to access β-alkynyl-fluorosulfonylalkanes is presented. Alkynyl sulfonyl fluorides are introduced as highly valuable bifunctional radical trapping reagents that also serve as FSO<sub>2</sub> -radical precursors. The β-alkynyl-fluorosulfonylalkanes obtained in these transformations can be readily diversified by using SuFEx click chemistry to obtain sulfonates and sulfonamides. Sulfonyl ; Alkynylation ; Moiety ; Chemistry ; Fluoride ; Combinatorial chemistry ; Radical ; Drug discovery ; Organic chemistry ; Catalysis ; Inorganic chemistry ; Biochemistry Sulfur-Based Synthesis Techniques ; Radical Photochemical Reactions ; Fluorine in Organic Chemistry
Authors: Sabina Halappanavar | Penny Nymark | Harald F. Krug | Martin J. D. Clift | Barbara Rothen‐Rutishauser | Ulla Vogel
Source: Small (review, 2021-02-09)
Field: Materials Science — Materials Chemistry

Non‐Animal Strategies for Toxicity Assessment of Nanoscale Materials: Role of Adverse Outcome Pathways in the Selection of Endpoints Faster, cheaper, sensitive, and mechanisms-based animal alternatives are needed to address the safety assessment needs of the growing number of nanomaterials (NM) and their sophisticated property variants. Specifically, strategies that help identify and prioritize alternative schemes involving individual test models, toxicity endpoints, and assays for the assessment of adverse outcomes, as well as strategies that enable validation and refinement of these schemes for the regulatory acceptance are needed. In this review, two strategies 1) the current nanotoxicology literature review and 2) the adverse outcome pathways (AOPs) framework, a systematic process that allows the assembly of available mechanistic information concerning a toxicological response in a simple modular format, are presented. The review highlights 1) the most frequently assessed and reported ad hoc in vivo and in vitro toxicity measurements in the literature, 2) various AOPs of relevance to inhalation toxicity of NM that are presently under development, and 3) their applicability in identifying key events of toxicity for targeted in vitro assay development. Finally, using an existing AOP for lung fibrosis, the specific combinations of cell types, exposure and test systems, and assays that are experimentally supported and thus, can be used for assessing NM-induced lung fibrosis, are proposed. Adverse Outcome Pathway ; Toxicity ; Computer science ; Risk assessment ; Risk analysis (engineering) ; Nanotoxicology ; Adverse effect ; Computational biology ; Biochemical engineering ; Bioinformatics ; Medicine ; Nanotechnology ; Pharmacology ; Biology ; Materials science ; Engineering Nanoparticles: synthesis and applications ; Environmental Toxicology and Ecotoxicology ; Inhalation and Respiratory Drug Delivery
Authors: Masoud Shahrokhi | Pascal Raybaud | Tangui Le Bahers
Source: ACS Applied Materials & Interfaces (article, 2021-07-26)
Field: Materials Science — Materials Chemistry

2D MoO<sub>3–<i>x</i></sub>S<i><sub>x</sub></i>/MoS<sub>2</sub>van der Waals Assembly: A Tunable Heterojunction with Attractive Properties for Photocatalysis Two-dimensional (2D) van der Waals (vdW) heterostructures currently have attracted much attention in widespread research fields where semiconductor materials are key. With the aim of gaining insights into photocatalytic materials, we use density functional theory (DFT) calculations within the HSE06 functional to analyze the evolution of optoelectronic properties and high-frequency dielectric constant profiles of various 2D MoO<sub>3-<i>x</i></sub>S<i><sub>x</sub></i>/MoS<sub>2</sub> heterostructures modified by chemical and physical approaches. Although the MoO<sub>3</sub>/MoS<sub>2</sub> heterostructure is a type III heterojunction associated with a metallic character, we found that exchanging the terminal oxo atoms of the MoO<sub>3-<i>x</i></sub>S<i><sub>x</sub></i> single layer (SL) with sulfur enables shifting its CB position above the VB position of the MoS<sub>2</sub> SL. This trend gives rise to a type II heterojunction where the band gap and charge transfer within the two layers are driven continuously by the S concentration in the MoO<sub>3-<i>x</i></sub>S<i><sub>x</sub></i> SL. This fine-tuning leads to a versatile type II heterostructure proposed to provide a direct Z-scheme system valuable for photocatalytic water splitting. Heterojunction ; Materials science ; van der Waals force ; Photocatalysis ; Semiconductor ; Density functional theory ; Dielectric ; Band gap ; Optoelectronics ; Nanotechnology ; Chemical physics ; Computational chemistry ; Molecule ; Physics ; Chemistry ; Quantum mechanics 2D Materials and Applications ; Advanced Photocatalysis Techniques ; MXene and MAX Phase Materials
Authors: Jia Guo | Rong Xiang | Ting Cheng | Shigeo Maruyama | Yan Li
Source: ACS Nanoscience Au (review, 2021-11-08)
Field: Materials Science — Materials Chemistry

One-Dimensional van der Waals Heterostructures: A Perspective As a new frontier in low-dimensional material research, van der Waals (vdW) heterostructures, represented by 2D heterostructures, have attracted tremendous attention due to their unique properties and potential applications. The emerging 1D heterostructures open new possibilities for the field with expectant unconventional properties and yet more challenging preparation pathways. This Perspective aims to give an overall understanding of the state-of-the-art growth strategies and fantastic properties of the 1D heterostructures and provide an outlook for further development based on the controlled preparation, which will bring up a variety of applications in high-performance electronic, optoelectronic, magnetic, and energy storage devices. A quick rise of the fundamentals and application study of 1D heterostructures is anticipated. Heterojunction ; Perspective (graphical) ; Nanotechnology ; van der Waals force ; Frontier ; Materials science ; Engineering physics ; Computer science ; Physics ; Optoelectronics ; Political science ; Quantum mechanics 2D Materials and Applications ; MXene and MAX Phase Materials ; Graphene research and applications
Authors: Brielle Stawicki | Tyler Schacher | Hyunah Cho
Source: Gels (review, 2021-05-26)
Field: Materials Science — Biomaterials

Nanogels as a Versatile Drug Delivery System for Brain Cancer Chemotherapy and radiation remain as mainstays in the treatment of a variety of cancers globally, yet some therapies exhibit limited specificity and result in harsh side effects in patients. Brain tissue differs from other tissue due to restrictions from the blood-brain barrier, thus systemic treatment options are limited. The focus of this review is on nanogels as local and systemic drug delivery systems in the treatment of brain cancer. Nanogels are a unique local or systemic drug delivery system that is tailorable and consists of a three-dimensional polymeric network formed via physical or chemical assembly. For example, thermosensitive nanogels show promise in their ability to incorporate therapeutic agents in nano-structured matrices, be applied in the forms of sprays or sols to the area from which a tumor has been removed, form adhesive gels to fill the cavity and deliver treatment locally. Their usage does come with complications, such as handling, storage, chemical stability, and degradation. Despite these limitations, the current ongoing development of nanogels allows patient-centered treatment that can be considered as a promising tool for the management of brain cancer. Drug delivery ; Cancer treatment ; Cancer ; Drug ; Nanotechnology ; Blood–brain barrier ; Cancer therapy ; Brain cancer ; Medicine ; Materials science ; Central nervous system ; Pharmacology ; Internal medicine Nanoparticle-Based Drug Delivery ; Glioma Diagnosis and Treatment ; Nanoplatforms for cancer theranostics
Authors: Ruiqi Zhang | Christopher Lane | Bahadur Singh | Johannes Nokelainen | Bernardo Barbiellini | Robert S. Markiewicz | Arun Bansil | Jianwei Sun
Source: Communications Physics (article, 2021-06-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Magnetic and f-electron effects in LaNiO2 and NdNiO2 nickelates with cuprate-like $$3{d}_{{x}^{2}-{y}^{2}}$$ band Abstract Recent discovery of superconductivity in the doped infinite-layer nickelates has renewed interest in understanding the nature of high-temperature superconductivity more generally. The low-energy electronic structure of the parent compound NdNiO 2 , the role of electronic correlations in driving superconductivity, and the possible relationship between the cuprates and the nickelates are still open questions. Here, by comparing LaNiO 2 and NdNiO 2 systematically within a parameter-free, all-electron first-principles density-functional theory framework, we reveal the role of Nd 4 f electrons in shaping the ground state of pristine NdNiO 2 . Strong similarities are found between the electronic structures of LaNiO 2 and NdNiO 2 , except for the effects of the 4 f electrons. Hybridization between the Nd 4 f and Ni 3 d orbitals is shown to significantly modify the Fermi surfaces of various magnetic states. In contrast, the competition between the magnetically ordered phases depends mainly on the gaps in the Ni $$3{d}_{{x}^{2}-{y}^{2}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mn>3</mml:mn> <mml:msub> <mml:mrow> <mml:mi>d</mml:mi> </mml:mrow> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>x</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> <mml:mo>−</mml:mo> <mml:msup> <mml:mrow> <mml:mi>y</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:msub> </mml:math> band. Our estimated value of the on-site Hubbard U in the nickelates is similar to that in the cuprates, but the value of the Hund’s coupling J H is found to be sensitive to the Nd magnetic moment. In contrast with the cuprates, NdNiO 2 presents 3D magnetism with competing antiferromagnetic and (interlayer) ferromagnetic exchange, which may explain why the T c is lower in the nickelates. Antiferromagnetism ; Cuprate ; Superconductivity ; Ferromagnetism ; Magnetism ; Ground state ; Electronic structure ; Electronic band structure ; Fermi level Magnetic and transport properties of perovskites and related materials ; Rare-earth and actinide compounds ; Iron-based superconductors research
Authors: Arghya Bhowmik | Maitane Berecibar | Montse Casas‐Cabanas | Gábor Cśanyi | Robert Dominko | Kersti Hermansson | M. Rosa Palacín | Helge S. Stein | Tejs Vegge
Source: Advanced Energy Materials (article, 2021-11-23)
Field: Materials Science — Materials Chemistry

Implications of the BATTERY 2030+ AI‐Assisted Toolkit on Future Low‐TRL Battery Discoveries and Chemistries Abstract BATTERY 2030+ targets the development of a chemistry neutral platform for accelerating the development of new sustainable high‐performance batteries. Here, a description is given of how the AI‐assisted toolkits and methodologies developed in BATTERY 2030+ can be transferred and applied to representative examples of future battery chemistries, materials, and concepts. This perspective highlights some of the main scientific and technological challenges facing emerging low‐technology readiness level (TRL) battery chemistries and concepts, and specifically how the AI‐assisted toolkit developed within BIG‐MAP and other BATTERY 2030+ projects can be applied to resolve these. The methodological perspectives and challenges in areas like predictive long time‐ and length‐scale simulations of multi‐species systems, dynamic processes at battery interfaces, deep learned multi‐scaling and explainable AI, as well as AI‐assisted materials characterization, self‐driving labs, closed‐loop optimization, and AI for advanced sensing and self‐healing are introduced. A description is given of tools and modules can be transferred to be applied to a select set of emerging low‐TRL battery chemistries and concepts covering multivalent anodes, metal‐sulfur/oxygen systems, non‐crystalline, nano‐structured and disordered systems, organic battery materials, and bulk vs. interface‐limited batteries. Battery (electricity) ; Materials science ; Nanotechnology ; Systems engineering ; Engineering physics ; Engineering ; Physics ; Thermodynamics Machine Learning in Materials Science ; Advancements in Battery Materials ; Advanced Battery Technologies Research
Authors: Jerrit Wagner | Christian G. Berger | Xiaoyan Du | Tobias Stubhan | Jens A. Hauch | Christoph J. Brabec
Source: Journal of Materials Science (article, 2021-07-23)
Field: Materials Science — Materials Chemistry

The evolution of Materials Acceleration Platforms: toward the laboratory of the future with AMANDA Abstract The development of complex functional materials poses a multi-objective optimization problem in a large multi-dimensional parameter space. Solving it requires reproducible, user-independent laboratory work and intelligent preselection of experiments. However, experimental materials science is a field where manual routines are still predominant, although other domains like pharmacy or chemistry have long used robotics and automation. As the number of publications on Materials Acceleration Platforms (MAPs) increases steadily, we review selected systems and fit them into the stages of a general material development process to examine the evolution of MAPs. Subsequently, we present our approach to laboratory automation in materials science. We introduce AMANDA (Autonomous Materials and Device Application Platform - www.amanda-platform.com ), a generic platform for distributed materials research comprising a self-developed software backbone and several MAPs. One of them, LineOne (L1), is specifically designed to produce and characterize solution-processed thin-film devices like organic solar cells (OSC). It is designed to perform precise closed-loop screenings of up to 272 device variations per day yet allows further upscaling. Each individual solar cell is fully characterized, and all process steps are comprehensively documented. We want to demonstrate the capabilities of AMANDA L1 with OSCs based on PM6:Y6 with 13.7% efficiency when processed in air. Further, we discuss challenges and opportunities of highly automated research platforms and elaborate on the future integration of additional techniques, methods and algorithms in order to advance to fully autonomous self-optimizing systems—a paradigm shift in functional materials development leading to the laboratory of the future. Automation ; Process (computing) ; Robotics ; Field (mathematics) ; Acceleration ; Software ; Materials processing ; Solar cell Machine Learning in Materials Science ; Organic Electronics and Photovoltaics ; Perovskite Materials and Applications
Authors: Gabriel R. Schleder | Bruno Focassio | A. Fazzio
Source: Applied Physics Reviews (article, 2021-08-03)
Field: Materials Science — Materials Chemistry

Machine learning for materials discovery: Two-dimensional topological insulators One of the main goals and challenges of materials discovery is to find the best candidates for each interest property or application. Machine learning rises in this context to efficiently optimize this search, exploring the immense materials space, consisting of simultaneously the atomic, compositional, and structural spaces. Topological insulators, presenting symmetry-protected metallic edge states, are a promising class of materials for different applications. However, further development is limited by the scarcity of viable candidates. Here we present and discuss machine learning–accelerated strategies for searching the materials space for two-dimensional topological materials. We show the importance of detailed investigations of each machine learning component, leading to different results. Using recently created databases containing thousands of ab initio calculations of 2D materials, we train machine learning models capable of determining the electronic topology of materials, with an accuracy of over 90%. We can then generate and screen thousands of novel materials, efficiently predicting their topological character without the need for a priori structural knowledge. We discover 56 non-trivial materials, of which 17 are novel insulating candidates for further investigation, for which we corroborate their topological properties with density functional theory calculations. This strategy is 10× more efficient than the trial-and-error approach while a few orders of magnitude faster and is a proof of concept for guiding improved materials discovery search strategies. Topological insulator ; Materials science ; Topology (electrical circuits) ; Computer science ; Physics ; Mathematics ; Condensed matter physics ; Combinatorics Machine Learning in Materials Science ; Graphene research and applications ; Topological Materials and Phenomena