jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Omar A. M. Abdelraouf | Xin Cai Wang | Ken Choon Hwa Goh | Chee Beng Lim Nelson | Siu Kit Ng | W.D. Wang | Xiao Renshaw Wang | Qi Jie Wang | Hong Liu
Source: Advanced Photonics Research (article, 2023-09-20)
Field: Materials Science — Materials Chemistry

All‐Optical Switching of Structural Color with a Fabry–Pérot Cavity Fine tuning the optical responses of thin‐film devices is highly attractive for emerging applications, such as optical memories, solar cells, nanophotonics, and photodetectors. Even though thin‐film technology is well established, dynamically switching the optical responses of thin films after fabrication remains challenging because of passive materials and device structures. This work demonstrates an approach for all‐optical switching of structural colors excited by a Fabry–Pérot (FP) cavity inside a metal–dielectric–metal (MDM) thin‐film stack. A low‐loss phase‐change material (PCM), that is, antimony trisulfide (Sb 2 S 3 ), which is embedded in the stack, enables efficient FP cavity resonance in the visible spectrum. 1) Color reflectivity of &gt;60%; 2) multistructural colors using a single MDM cavity; 3) a wide dynamic range of colors of up to ≈220 nm; and 4) a gamut coverage of more than 80% of standard RGB (sRGB) are achieved. The all‐optical switching is realized via the crystallization and reamorphization of Sb 2 S 3 using continuous‐wave and pulsed lasers, respectively. The findings provide a framework for the cost‐effective realization of dynamically responsive thin‐film‐based nanophotonic devices. Materials science ; Optoelectronics ; Nanophotonics ; Fabry–Pérot interferometer ; Thin film ; Stack (abstract data type) ; Optical switch ; Optical cavity ; Optics ; RGB color model ; Laser ; Computer science ; Nanotechnology ; Wavelength Phase-change materials and chalcogenides ; Chalcogenide Semiconductor Thin Films ; Liquid Crystal Research Advancements
Authors: Satyadeep Waiba | Kakoli Maji | Mamata Maiti | Biplab Maji
Source: Angewandte Chemie International Edition (article, 2023-01-11)
Field: Chemistry — Inorganic Chemistry

Sustainable Synthesis of α‐Hydroxycarboxylic Acids by Manganese Catalyzed Acceptorless Dehydrogenative Coupling of Ethylene Glycol and Primary Alcohols** Herein, we report a straightforward synthesis of valuable α-hydroxycarboxylic acid molecules via an acceptorless dehydrogenative coupling of ethylene glycol and primary alcohols. A bench-stable manganese complex catalyzed the reaction, which is scalable, with the product being isolated with high yields and selectivities under mild conditions. The protocol is environmentally benign, producing water and hydrogen gas as the only byproducts. Methanol can also be used as a C1 source for producing the platform molecule lactic acid, with a high turnover of >10<sup>4</sup> . The methodology was also used to functionalize alcohols derived from natural products and fatty acids. Furthermore, it was applied for synthesizing α-amino acid, α-thiocarboxylic acid, and several drugs and bioactive molecules, including endogenous metabolites, Danshensu, Enalapril, Lisinopril, and Rosmarinic acid. Preliminary mechanistic studies were performed to shed light on the mechanism involved in the reaction. Chemistry ; Ethylene glycol ; Manganese ; Catalysis ; Methanol ; Organic chemistry ; Primary (astronomy) ; Ethylene ; Lactic acid ; Combinatorial chemistry ; Alcohol ; Molecule ; Bacteria Asymmetric Hydrogenation and Catalysis ; Carbon dioxide utilization in catalysis ; Catalysis for Biomass Conversion
Authors: Mostafa Badreldin | Pedro Salas-Ambrosio | Élisabeth Garanger | Sébastien Lecommandoux | Simon Harrisson | Colin Bonduelle
Source: Progress in Polymer Science (article, 2023-10-22)
Field: Materials Science — Biomaterials

Thermoresponsive polymers: From natural proteins to amino acid based polymer synthesis Polymer ; Natural polymers ; Amino acid ; Polymerization ; Macromolecule ; Drug delivery ; Materials science ; Nanotechnology ; Chemistry ; Combinatorial chemistry ; Organic chemistry ; Biochemistry biodegradable polymer synthesis and properties ; Supramolecular Self-Assembly in Materials ; Chemical Synthesis and Analysis
Authors: Hao Xu | Duo‐Sheng Wang | Zhenyu Zhu | Arghya Deb | X. Peter Zhang
Source: Chem (article, 2023-10-11)
Field: Chemistry — Organic Chemistry

New mode of asymmetric induction for enantioselective radical N-heterobicyclization via kinetically stable chiral radical center Enantioselective synthesis ; Chemistry ; Steric effects ; Stereospecificity ; Asymmetric induction ; Ligand (biochemistry) ; Stereoselectivity ; Combinatorial chemistry ; Catalysis ; Reactivity (psychology) ; Radical cyclization ; Chiral ligand ; Stereochemistry ; Bicyclic molecule ; Organic chemistry ; Receptor Synthesis and Catalytic Reactions ; Catalytic C–H Functionalization Methods ; Radical Photochemical Reactions
Authors: Avirup Panja | Prasun Patra
Source: 4open (review, 2023-01-01)
Field: Materials Science — Materials Chemistry

A review on Quantum Dots (QDs) and their biomedical applications Quantum dots (QDs) are nanoscale semiconductor crystals that possess special characteristics, and they are used in various fields. The crystals are composed of elements that usually lie within the groups II-VI or III–V respectively. The diameter of these crystals is usually smaller than the Bohr excitation radius. These crystals have unique photochemical and photo-physical properties. There are several methods for synthesizing QDs, in which the high temperature co-ordinated solvents-based synthesis is one of the most important. The various synthesis procedures affect the size of these QDs, which determine their characteristics and consequently their applications. QDs are widely used in the fields of bio-imaging, photovoltaic, catalysis, light-emitting diodes, photoconductors, and photodetectors, respectively. The major factors which influence the use of QDs in the field of bio-imaging are their high luminescence, and narrow emission properties. In this review, we discuss various methods of QDs synthesis and their applications in different fields, specifically in today’s world of modern biology. Quantum dot ; Bohr radius ; Nanotechnology ; Materials science ; Luminescence ; Photodetector ; Diode ; Semiconductor ; Optoelectronics Quantum Dots Synthesis And Properties ; Carbon and Quantum Dots Applications ; Advanced biosensing and bioanalysis techniques
Authors: Qian‐Feng Qiu | Zhenhuan Sun | Danielle Joubran | Xiang Li | Joshua Wan | Klaus Schmidt‐Rohr | Grace G. D. Han
Source: Angewandte Chemie International Edition (article, 2023-01-23)
Field: Materials Science — Materials Chemistry

Optically Controlled Recovery and Recycling of Homogeneous Organocatalysts Enabled by Photoswitches We address a critical challenge of recovering and recycling homogeneous organocatalysts by designing photoswitchable catalyst structures that display a reversible solubility change in response to light. Initially insoluble catalysts are UV-switched to a soluble isomeric state, which catalyzes the reaction, then back-isomerizes to the insoluble state upon completion of the reaction to be filtered and recycled. The molecular design principles that allow for the drastic solubility change over 10 times between the isomeric states, 87 % recovery by the light-induced precipitation, and multiple rounds of catalyst recycling are revealed. This proof of concept will open up opportunities to develop highly recyclable homogeneous catalysts that are important for the synthesis of critical compounds in various industries, which is anticipated to significantly reduce environmental impact and costs. Homogeneous ; Solubility ; Catalysis ; Chemistry ; Precipitation ; Combinatorial chemistry ; Materials science ; Chemical engineering ; Nanotechnology ; Organic chemistry ; Thermodynamics ; Physics ; Engineering Photochromic and Fluorescence Chemistry ; Sulfur-Based Synthesis Techniques ; Synthesis of Indole Derivatives
Authors: Konstantin V. Deriabin | Sofia S. Filippova | Regina M. Islamova
Source: Biomimetics (review, 2023-07-03)
Field: Materials Science — Polymers and Plastics

Self-Healing Silicone Materials: Looking Back and Moving Forward This review is dedicated to self-healing silicone materials, which can partially or entirely restore their original characteristics after mechanical or electrical damage is caused to them, such as formed (micro)cracks, scratches, and cuts. The concept of self-healing materials originated from biomaterials (living tissues) capable of self-healing and regeneration of their functions (plants, human skin and bones, etc.). Silicones are ones of the most promising polymer matrixes to create self-healing materials. Self-healing silicones allow an increase of the service life and durability of materials and devices based on them. In this review, we provide a critical analysis of the current existing types of self-healing silicone materials and their functional properties, which can be used in biomedicine, optoelectronics, nanotechnology, additive manufacturing, soft robotics, skin-inspired electronics, protection of surfaces, etc. Self-healing ; Silicone ; Materials science ; Self-healing material ; Soft robotics ; Nanotechnology ; Soft materials ; Durability ; Regeneration (biology) ; Composite material ; Biomedical engineering ; Computer science ; Engineering ; Artificial intelligence ; Medicine Polymer composites and self-healing ; Advanced Sensor and Energy Harvesting Materials ; Electrospun Nanofibers in Biomedical Applications
Authors: Muhammad Saeed | Aswa Firdous | Muhammad Saleh Zaman | Fatima Izhar | Mubeshar Riaz | Sabah Haider | Muzamil Majeed | Shahzaib Tariq
Source: Journal of the Chinese Chemical Society (article, 2023-03-04)
Field: Chemistry — Inorganic Chemistry

<scp>MOFs</scp> for desulfurization of fuel oil: Recent advances and future insights Abstract Nowadays, desulfurization of fuel oil has raised concern globally because of strict industrial and environmental legislations. Albeit hydrodesulfurization (HDS) has been extensively used in oil refineries to produce low sulfur oil (&lt; 10 ppm) but not been proven as effective method for the removal of dibenzothiophene (DBT), benzothiophene (TH) and their derivatives. Subsequently, adsorptive desulfurization (ADS) and oxidative desulfurization (ODS) methods have been developed to achieve high removal efficiency. In the past decade, metal–organic frameworks (MOFs) and its composites as oxidative catalysts, as well as adsorbents, have attracted the researchers owing to high surface area, tunable properties, and reusable. The present review comprises use of MOFs and their composites for the removal of sulfur from fuel oil via ODS and ADS processes. Additionally, physicochemical properties of MOFs, mechanism, pros and cons of both process, regeneration, and future challenges have been discussed briefly. Moreover, current limitations and future prospective are also discussed. Dibenzothiophene ; Flue-gas desulfurization ; Benzothiophene ; Chemistry ; Oil refinery ; Hydrodesulfurization ; Sulfur ; Fuel oil ; Catalysis ; Waste management ; Chemical engineering ; Nanotechnology ; Organic chemistry ; Materials science ; Thiophene ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Catalysis and Hydrodesulfurization Studies ; Chemical Synthesis and Reactions
Authors: Aijaz A. Dar | Shaista H. Lone | Ishtiyaq Ahmad | Aadil A. Ahangar | Arshid A. Ganie | Cherumannil Femina
Source: Materials Advances (article, 2023-11-23)
Field: Materials Science — Materials Chemistry

Engineering the solid-state luminescence of organic crystals and cocrystals A crystal engineering approach has been used to investigate the integrated impact of functionalization and co-crystallization on the photophysical properties of organic solids. Luminescence ; Crystal engineering ; Surface modification ; Crystallization ; Solid-state ; Materials science ; Crystal (programming language) ; Chemical engineering ; Nanotechnology ; Crystal structure ; Crystallography ; Chemistry ; Supramolecular chemistry ; Physical chemistry ; Optoelectronics ; Computer science ; Engineering Luminescence and Fluorescent Materials ; Crystallography and molecular interactions ; Molecular Sensors and Ion Detection
Authors: Elias A. Halabi | Ralph Weissleder
Source: Journal of the American Chemical Society (article, 2023-04-05)
Field: Materials Science — Materials Chemistry

Light-Deactivated Fluorescent Probes (FLASH-Off) for Multiplexed Imaging Highly multiplexed, cyclic fluorescence imaging has advanced our understanding of the biology, evolution, and complexity of human diseases. Currently available cyclic methods still have considerable limitations including the need for long quenching times and extensive wash steps. Here, we report a new series of fluorochromes that can be efficiently inactivated by a single light pulse (∼405 nm) by means of a photo-immolating triazene linker. Upon UV-light irradiation, the rhodamines are cleaved off from the antibody conjugates and undergo a fast intramolecular spirocyclization that inherently switches off their fluorescence emission without the need to wash or add exogenous chemicals. We show that these switch-off probes are fast, highly controllable, biocompatible, and allow spatiotemporal quenching control of live and fixed samples. Fluorescence ; Chemistry ; Quenching (fluorescence) ; Multiplexing ; Linker ; Flash (photography) ; Fluorescence-lifetime imaging microscopy ; Biocompatible material ; Biophysics ; Nanotechnology ; Combinatorial chemistry ; Photochemistry ; Optics ; Biomedical engineering ; Computer science ; Materials science Photochromic and Fluorescence Chemistry ; Click Chemistry and Applications ; Photoreceptor and optogenetics research
Authors: Dan Zhao | Yan Rong | Dong Li | Chaoliang He | Xuesi Chen
Source: Regenerative Biomaterials (review, 2023-01-01)
Field: Chemistry — Organic Chemistry

Thermo-induced physically crosslinked polypeptide-based block copolymer hydrogels for biomedical applications Stimuli-responsive synthetic polypeptide-containing block copolymers have received considerable attention in recent years. Especially, unique thermo-induced sol-gel phase transitions were observed for elaborately-designed amphiphilic diblock copolypeptides and a range of poly(ethylene glycol) (PEG)-polypeptide block copolymers. The thermo-induced gelation mechanisms involve the evolution of secondary conformation, enhanced intramolecular interactions, as well as reduced hydration and increased chain entanglement of PEG blocks. The physical parameters, including polymer concentrations, sol-gel transition temperatures and storage moduli, were investigated. The polypeptide hydrogels exhibited good biocompatibility <i>in vitro</i> and <i>in vivo</i>, and displayed biodegradation periods ranging from 1 to 5 weeks. The unique thermo-induced sol-gel phase transitions offer the feasibility of minimal-invasive injection of the precursor aqueous solutions into body, followed by <i>in situ</i> hydrogel formation driven by physiological temperature. These advantages make polypeptide hydrogels interesting candidates for diverse biomedical applications, especially as injectable scaffolds for 3D cell culture and tissue regeneration as well as depots for local drug delivery. This review focuses on recent advances in the design and preparation of injectable, thermo-induced physically crosslinked polypeptide hydrogels. The influence of composition, secondary structure and chirality of polypeptide segments on the physical properties and biodegradation of the hydrogels are emphasized. Moreover, the studies on biomedical applications of the hydrogels are intensively discussed. Finally, the major challenges in the further development of polypeptide hydrogels for practical applications are proposed. Self-healing hydrogels ; Copolymer ; Block (permutation group theory) ; Materials science ; Nanotechnology ; Chemistry ; Polymer chemistry ; Polymer ; Composite material Advanced Polymer Synthesis and Characterization ; Hydrogels: synthesis, properties, applications ; biodegradable polymer synthesis and properties
Authors: Kevin Maik Jablonka | Philippe Schwaller | Andres Ortega‐Guerrero | Berend Smit
Source: ChemRxiv (preprint, 2023-02-14)
Field: Materials Science — Materials Chemistry

Is GPT-3 all you need for low-data discovery in chemistry? Machine learning has revolutionized many fields and has recently found applications in chemistry and materials science. The small datasets commonly found in chemistry lead to various sophisticated machine-learning approaches that incorporate chemical knowledge for each application and therefore require a lot of expertise to develop. Here, we show that large language models that have been trained on vast amounts of text extracted from the internet can easily be adapted to solve various tasks in chemistry and materials science by simply prompting them with chemical questions in natural language. We compared this approach with dedicated machine-learning models for many applications spanning properties of molecules and materials to the yield of chemical reactions. Surprisingly, we find this approach performs comparable to or even outperforms the conventional techniques, particularly in the low data limit. In addition, by simply inverting the questions, we can even perform inverse design successfully. The high performance, especially for small data sets, combined with the ease of use, can have a fundamental impact on how we leverage machine learning in the chemical and material sciences. Next to a literature search, querying a foundational model might become a routine way to bootstrap a project by leveraging the collective knowledge encoded in these foundational models. Computer science ; Leverage (statistics) ; Artificial intelligence ; Data science ; Machine learning ; Chemical space ; Drug discovery ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Various Chemistry Research Topics
Authors: Luke P. J. Gilligan | Matteo Cobelli | Valentin Taufour | Stefano Sanvito
Source: npj Computational Materials (article, 2023-12-13)
Field: Materials Science — Materials Chemistry

A rule-free workflow for the automated generation of databases from scientific literature In recent times, transformer networks have achieved state-of-the-art performance in a wide range of natural language processing tasks. Here we present a workflow based on the fine-tuning of BERT models for different downstream tasks, which results in the automated extraction of structured information from unstructured natural language in scientific literature. Contrary to existing methods for the automated extraction of structured compound-property relations from similar sources, our workflow does not rely on the definition of intricate grammar rules. Hence, it can be adapted to a new task without requiring extensive implementation efforts and knowledge. We test our data-extraction workflow by automatically generating a database for Curie temperatures and one for band gaps. These are then compared with manually curated datasets and with those obtained with a state-of-the-art rule-based method. Furthermore, in order to showcase the practical utility of the automatically extracted data in a material-design workflow, we employ them to construct machine-learning models to predict Curie temperatures and band gaps. In general, we find that, although more noisy, automatically extracted datasets can grow fast in volume and that such volume partially compensates for the inaccuracy in downstream tasks. Workflow ; Computer science ; Information extraction ; Natural language processing ; Artificial intelligence ; Data mining ; Transformer ; Database ; Volume (thermodynamics) ; Information retrieval ; Machine learning Machine Learning in Materials Science ; Software Engineering Research ; Topic Modeling
Authors: Mudasir Farooq | Haqnawaz Rafiq | A. Shah | Mir Hashim Rasool
Source: ECS Journal of Solid State Science and Technology (article, 2023-11-28)
Field: Materials Science — Materials Chemistry

Review— On the Development of Phosphors for Luminescent Materials: Synthesis, Characterization, Applications and Evolution of Phosphors as White-Light-Emitting Diodes The manuscript focuses on the concept of nano-phosphors, a remarkable type of material that has been widely explored because of their diverse promising applications. Progress in the development of such nano-phosphors as luminescent materials has received significant research attention. The white-light-emitting diodes (WLEDs) have grown dramatically and represent the most intriguing lighting source of the twenty-first century. The contribution of rare-Earth (RE) ions to lighting technology is explicitly addressed. The additional physical characteristics of white light that are addressed in the present manuscript comprise the correlated color temperature (CCT), the color rendering index (CRI), and the Commission International de’ Eclairage (CIE) chromaticity coordinates. Multiple synthesis methods employed around the globe to produce such industrially important nano-phosphors along with more specialized and impactful techniques to characterize all such materials are thus thoroughly explored. Also, the various technologically significant applications of these materials are described. The evolution of these potentially suitable luminescent materials for WLEDs and their white-light characteristics is also outlined. The manuscript presents a comprehensive overview of the advancement and innovation of nano-phosphors, their application fields and the significant milestones of artificial lighting toward modernization. Phosphor ; Color rendering index ; Chromaticity ; Materials science ; Luminescence ; White light ; Nanotechnology ; Diode ; Light-emitting diode ; Color temperature ; Optoelectronics ; Engineering physics ; Optics ; Engineering ; Physics Luminescence Properties of Advanced Materials ; Gas Sensing Nanomaterials and Sensors ; Advanced Photocatalysis Techniques
Authors: Zhen Liu | Yurii S. Moroz | Olexandr Isayev
Source: Chemical Science (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

The challenge of balancing model sensitivity and robustness in predicting yields: a benchmarking study of amide coupling reactions Accurate prediction of reaction yield is the holy grail for computer-assisted synthesis prediction, but current models have failed to generalize to large literature datasets. To understand the causes and inspire future design, we systematically benchmarked the yield prediction task. We carefully curated and augmented a literature dataset of 41 239 amide coupling reactions, each with information on reactants, products, intermediates, yields, and reaction contexts, and provided 3D structures for the molecules. We calculated molecular features related to 2D and 3D structure information, as well as physical and electronic properties. These descriptors were paired with 4 categories of machine learning methods (linear, kernel, ensemble, and neural network), yielding valuable benchmarks about feature and model performance. Despite the excellent performance on a high-throughput experiment (HTE) dataset (<i>R</i><sup>2</sup> around 0.9), no method gave satisfactory results on the literature data. The best performance was an <i>R</i><sup>2</sup> of 0.395 ± 0.020 using the stack technique. Error analysis revealed that <i>reactivity cliff</i> and <i>yield uncertainty</i> are among the main reasons for incorrect predictions. Removing reactivity cliffs and uncertain reactions boosted the <i>R</i><sup>2</sup> to 0.457 ± 0.006. These results highlight that yield prediction models must be sensitive to the reactivity change due to the subtle structure variance, as well as be robust to the uncertainty associated with yield measurements. Benchmarking ; Robustness (evolution) ; Amide ; Sensitivity (control systems) ; Coupling reaction ; Coupling (piping) ; Computer science ; Chemistry ; Combinatorial chemistry ; Engineering ; Organic chemistry ; Business ; Mechanical engineering ; Catalysis ; Electronic engineering ; Biochemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis