jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hongxi Luo | Fangwei Cheng | Luke Huelsenbeck | Natalie Smith
Source: ChemRxiv (preprint, 2020-12-17)
Field: Chemistry — Inorganic Chemistry

Comparison Between Conventional Solvothermal and Aqueous Solution-based Production of UiO-66-NH2: Life Cycle Assessment, Techno-economic Assessment, and Implications for CO2 Capture and Storage Metal-organic frameworks (MOFs) are a new class of materials that has shown great potential in catalysis, sensing, separations, and carbon capture and storage. Conventionally, MOFs are synthesized at lab-scale using organic solvent-based systems, leading to high environmental burdens and high operating costs, which ultimately hinders the large-scale production and application of MOFs. Aqueous synthesis of MOFs overcomes such difficulty by eliminating the organic solvent, which makes it an environmentalfriendlier and economically-favorable alternative to the current production method. However, further quantitative analysis is required to compare the environmental and economic performances of the two methods. Here, we used life cycle assessment (LCA) coupled with techno-economic analysis (TEA) to evaluate the environmental and economic performances of different UiO-66-NH2 production methods. When the solvothermal method was replaced by the aqueous solution-based method, the LCA and TEA results suggest the environmental burdens and cost of UiO-66-NH2 production were reduced by up to 91% and 84%, respectively. By using aqueous solution-based method, the cradle to gate carbon footprint and production cost of UiO-66-NH2 were estimated to be 43 kg CO2 eq/kg and $15.8/kg, respectively. We further applied our LCA results to reassess the role of UiO-66-NH2 in carbon capture and storage (CCS) and compare its environmental performance with current benchmark (amine-based solvent). Our results show that UiO-66-NH2 could potentially have better environmental performance than the amine-based solvent if the number of regeneration cycles is greater than 1513. This work is the first comprehensive LCA-TEA study that quantifies the substantial environmental and economic benefits of using the aqueous solution-based systems to produce UiO-66-NH2, and the analysis in this work is intended to be a starting point for further systematic studies on the full life-cycle impacts of MOFs. Life-cycle assessment ; Aqueous solution ; Amine gas treating ; Process engineering ; Carbon footprint ; Production (economics) ; Environmental science ; Metal-organic framework ; Solvent ; Waste management ; Materials science ; Computer science ; Biochemical engineering ; Chemistry ; Environmental engineering ; Organic chemistry ; Greenhouse gas ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science ; Carbon Dioxide Capture Technologies
Authors: Zachary D. McClure | Alejandro Strachan
Source: JOM (preprint, 2020-11-10)
Field: Materials Science — Materials Chemistry

Expanding Materials Selection Via Transfer Learning for High-Temperature Oxide Selection Oxide ; Stability (learning theory) ; Computer science ; Melting temperature ; Scale (ratio) ; Materials science ; Thermal diffusivity ; Selection (genetic algorithm) ; Thermodynamics ; Machine learning ; Physics Machine Learning in Materials Science ; Metallurgical Processes and Thermodynamics ; X-ray Diffraction in Crystallography
Authors: Bonnie L. Buss | Miyake, Garret | Bailey, Travis | Shi, Yian | Herrera-Alonso, Margarita
Source: Digital Collections of Colorado (Colorado State University) (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Mechanistically-guided advancement of photoinduced organocatalyzed atom transfer radical polymerization Photoinduced organocatalyzed atom transfer radical polymerization (O-ATRP) is a promising polymerization methodology which leverages radical reactivity to afford macromolecular products with a high degree of control over polymer molecular weights and molecular weight distributions, paired with the added benefit of spatial and temporal control over polymerization. This process, a metal-free approach, relies on photoexcitation of an organic photoredox catalyst which stringently mediates the radical activation and deactivation steps of an oxidative quenching catalytic cycle. To successfully operate this cycle, and thus control the polymerization, the rate of deactivation must be faster than both the rates of radical activation and monomer propagation. Central to the initial development of O-ATRP has been the design and study of strongly reducing organic photocatalysts, particularly in the context of methacrylate monomer polymerizations. However, as a burgeoning methodology, the full scope of O-ATRP has not yet been established. In this dissertation, efforts in addressing three key challenges in O-ATRP, including reaction scalability, complex architecture synthesis, and polymerization of challenging monomers, through manipulation of features of the oxidative quenching mechanistic cycle is presented. To address these challenges diverse approaches were employed, including adaptation to continuous-flow reactors, implementation of multifunctional initiating systems, and rational design of a new family of organic photocatalysts, ultimately facilitating progression of O-ATRP to a scalable and efficient approach in the well-defined synthesis of industrially-relevant materials. Atom-transfer radical-polymerization ; Chemistry ; Polymerization ; Photochemistry ; Polymer ; Organic chemistry Advanced Polymer Synthesis and Characterization ; Photopolymerization techniques and applications ; Photochromic and Fluorescence Chemistry
Authors: Stephen R. Johnson | Weifan Zheng
Source: UNC Libraries (article, 2020-11-09)
Field: Chemistry — Spectroscopy

Recent progress in the computational prediction of aqueous solubility and absorption The computational prediction of aqueous solubility and/or human absorption has been the goal of many researchers in recent years. Such an in silico counterpart to the biopharmaceutical classification system (BCS) would have great utility. This review focuses on recent developments in the computational prediction of aqueous solubility, P-glycoprotein transport, and passive absorption. We find that, while great progress has been achieved, models that can reliably affect chemistry and development are still lacking. We briefly discuss aspects of emerging scientific understanding that may lead to breakthroughs in the computational modeling of these properties. Solubility ; Aqueous solution ; Absorption (acoustics) ; Materials science ; Chemistry ; Chemical engineering ; Computer science ; Engineering physics ; Physical chemistry ; Engineering ; Composite material Analytical Chemistry and Chromatography ; Water Quality Monitoring and Analysis ; Process Optimization and Integration
Authors: S. Molnár
Source: University of Debrecen Electronic Archive (University of Debrecen) (article, 2020-09-21)
Field: Materials Science — Materials Chemistry

Radiation- and Thermally Stimulated Changes in Amorphous Chalcogenide Layers and Nanocomposites A disszertáció kiválasztott amorf kalkogenid rétegek és nanokompozitok sugárzás- és hőstimulált változásainak kutatásán alapul, és célja, hogy jobban megértsük a háttérben zajló fizikai folyamatokat, és ezáltal továbbfejleszthessük ezen anyagok felhasználását az optikában és az optoelektronikában. Amorphous solid ; Chalcogenide ; Materials science ; Nanocomposite ; Optoelectronics ; Nanotechnology ; Chemistry ; Crystallography Phase-change materials and chalcogenides ; Glass properties and applications
Authors: Ravi Shankar | Sofia Marchesini | Erich A. Müller | Camille Petit
Source: ChemRxiv (preprint, 2020-11-11)
Field: Materials Science — Materials Chemistry

Gas Adsorption in Amorphous Porous Boron Oxynitride: Grand Canonical Monte Carlo Simulations and Experimental Determination Amorphous boron nitride doped with oxygen, boron oxynitride, BNO, is a porous material stable at high pressures and elevated temperatures with potential uses in adsorption-based separation processes at the industrial scale. We present here a molecular model capable of accurately predicting gas sorption in porous BNO solely from the knowledge of the basic experimental characteristics, i.e. overall chemical composition and porosity. With this information, the adsorbent is described atomistically by a complex 3-D pore network built by random packing of nanoflakes. The adsorption may then be evaluated by employing Grand Canonical Monte Carlo with classical forcefields. We report sorption isotherms for CO2, N2 and CH4 on BNO at low (< 1 bar) and high (0 – 20 bar) pressures, across a range of temperatures (283 – 313 K), which are well predicted by the molecular model. While the experimental measurement of multi-component isotherms under such conditions is a challenging task, molecular simulations provide predictions without the need of additional information. As an example, CO2/N2 and CO2/CH4 binary mixture isotherms, at conditions relevant to post combustion CO2 capture and natural gas sweetening, are computed. Overall, the model provides fundamental insight, which is useful in the design and optimization of porous BNObased adsorbents for molecular separations. Adsorption ; Boron nitride ; Sorption ; Amorphous solid ; Monte Carlo method ; Porosity ; Materials science ; Porous medium ; Boron ; Thermodynamics ; Chemistry ; Physical chemistry ; Nanotechnology ; Organic chemistry ; Physics ; Composite material ; Mathematics Thermal properties of materials ; Boron and Carbon Nanomaterials Research ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Egon Heuson | Rénato Froidevaux | Ivaldo Itabaiana | Robert Wojcieszak | Mickaël Capron | Franck Dumeignil
Source: SPIRE - Sciences Po Institutional REpository (preprint, 2020-01-01)
Field: Materials Science — Materials Chemistry

Des réactions multi-catalytiques au concept de catalyse hybride L’efficacité des catalyseurs chimiques et biologiques pour la réalisation de réactions chimiques au niveau industriel n’est plus à démontrer. Leur spécificité et sélectivité en font des outils essentiels à de nombreux procédés, et ils représentent à ce titre un outil majeur dans l’établissement de l’industrie de demain.&#13;\n&#13;\nHistoriquement, les catalyseurs ont été très majoritairement utilisés de manière unitaire, les procédés en faisant intervenir plusieurs s’inscrivant le plus souvent dans des stratégies multi-étapes. Cependant, les deux dernières décennies ont vu un essor de la recherche autour des réactions multi-catalytiques qui combinent deux catalyseurs ou plus afin de bénéficier d’effets collaboratifs.&#13;\n&#13;\nSi des catalyseurs de natures différentes ne sont que très rarement mis en jeu ensemble, la combinaison d’un catalyseur chimique et d’un biocatalyseur, appelée « catalyse hybride », représente très probablement le type de réaction multi-catalytique le plus prometteur de par la diversité et l’efficacité inédites permises. Elle n’en demeure pas moins la plus complexe à mettre en œuvre, faisant appel à des compétences de domaines différents (chimie, biologie, matériaux, etc.). Les perspectives offertes donnent lieu à des travaux pionniers qui poussent les chercheurs à mettre au point de nouvelles stratégies permettant de contourner les limitations et inhibitions qui ne manquent pas d’apparaitre lorsque l’on force ces deux types de catalyseurs à travailler de concert. Catalysis ; Chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysis and Hydrodesulfurization Studies
Authors: Asfaw G. Yohannes
Source: Repository KITopen (Karlsruhe Institute of Technology) (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Computational Study on Small Pt Clusters: Structure of Pt$_n^-$ Clusters and Elementary Steps in Nanocatalysis Cluster (spacecraft) ; Chemistry ; Nanotechnology ; Computer science ; Materials science Nanocluster Synthesis and Applications ; Machine Learning in Materials Science ; Catalytic Processes in Materials Science
Authors: Ravi Shankar | Sofia Marchesini | Erich A. Müller | Camille Petit
Source: ChemRxiv (preprint, 2020-07-29)
Field: Materials Science — Materials Chemistry

Gas Adsorption in Amorphous Porous Boron Oxynitride: Grand Canonical Monte Carlo Simulations and Experimental Determination Amorphous boron nitride doped with oxygen, boron oxynitride, BNO, is a porous material stable at high pressures and elevated temperatures with potential uses in adsorption-based separation processes at the industrial scale. We present here a molecular model capable of accurately predicting gas sorption in porous BNO solely from the knowledge of the basic experimental characteristics, i.e. overall chemical composition and porosity. With this information, the adsorbent is described atomistically by a complex 3-D pore network built by random packing of nanoflakes. The adsorption may then be evaluated by employing Grand Canonical Monte Carlo with classical forcefields. We report sorption isotherms for CO2, N2 and CH4 on BNO at low (< 1 bar) and high (0 – 20 bar) pressures, across a range of temperatures (283 – 313 K), which are well predicted by the molecular model. While the experimental measurement of multi-component isotherms under such conditions is a challenging task, molecular simulations provide predictions without the need of additional information. As an example, CO2/N2 and CO2/CH4 binary mixture isotherms, at conditions relevant to post combustion CO2 capture and natural gas sweetening, are computed. Overall, the model provides fundamental insight, which is useful in the design and optimization of porous BNObased adsorbents for molecular separations. Monte Carlo method ; Porosity ; Adsorption ; Amorphous solid ; Boron ; Materials science ; Statistical physics ; Chemical physics ; Physics ; Chemistry ; Physical chemistry ; Crystallography ; Mathematics ; Composite material ; Nuclear physics ; Statistics Thermal properties of materials ; Boron and Carbon Nanomaterials Research ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Daniel Quevedo Becerra
Source: Deep Blue (University of Michigan) (article, 2020-01-01)
Field: Materials Science — Biomaterials

Design, Applications, and Processing of Synthetic Protein Nanoparticles Nanomedicine- where a therapeutic is loaded into nanoparticles to increase therapeutic efficiency and improve patient outcomes- has long had the potential to revolutionize medicine. With all of their promise, nanoparticle carrier technologies have yet to make a significant clinical impact, emphasizing the need for new technologies and approaches. In this dissertation, electrohydrodynamic (EHD) co-jetting was used to develop various methods to create novel Synthetic Protein Nanoparticles (SPNPs), which were then applied to the delivery of therapeutic enzymes, and characterized using a microfluidic technique. It was found that SPNPs can be made from various proteins, such as Human Transferrin, Hemoglobin, and others, and that various macromers can be selected, such as a stimuli responsive NHS-Ester based macromer that can detect oxidative environments and show signs of degradation after being taken up by HeLa cells. SPNPs were then loaded with medically relevant enzymes, such as the antioxidant enzyme catalase. The enzymes showed high activity retention rates, with catalase SPNPs maintaining up to 82% of their original enzymatic activity. Additionally, antibody-targeted catalase SPNPs were able to protect REN cells in an inflammatory disease model. Next, an electrokinetic microfluidic system was adapted for the characterization of SPNPs based on their protein composition and anisotropy. The method was able to differentiate bicompartmental particles made from two different proteins from single compartment SPNPs made of an equivalent isotropic mixture of the same two proteins, with a significant voltage difference between the two particle types. Finally, preliminary work was conducted on using a small targeting molecule, meta-acetylenbenzylguanidine (MABG), for the treatment of neuroblastoma, and a system for validating MABG targeting in SK-N-BE(2) cells (a neuroblastoma cell line) was developed. Work done in this dissertation presents the development of multifunctional protein nanocarriers and lays the groundwork for the targeted delivery of active therapeutics using these particles. Nanoparticle ; Nanotechnology ; Computer science ; Materials science Nanoparticle-Based Drug Delivery ; Polymer Surface Interaction Studies ; Quantum Dots Synthesis And Properties
Authors: Robert Pollice
Source: Faculty of 1000 Research Ltd (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Referee report. For: GoodVibes: automated thermochemistry for heterogeneous computational chemistry data [version 1; peer review: 1 approved with reservations] Thermochemistry ; Computational model ; Computational complexity theory ; Experimental data Chemical Thermodynamics and Molecular Structure ; Phase Equilibria and Thermodynamics ; thermodynamics and calorimetric analyses
Authors: Thibaud Rossel | Bing Zhang | R. Gobat
Source: ChemRxiv (preprint, 2020-04-08)
Field: Chemistry — Organic Chemistry

Solving an X-Ray Structure of a Bio-Artificial Neurotransmitter Receptor Designed for the Naked-Eye Recognition of Dopamine The literature is constellated with a wide variety of chemosensors against a plethora of analytes.﻿ This seminal library is used to inspire chemists to improve them using chemical synthesis. However, their optimization via chemical synthesis is a difficult task which takes time without the guarantee of final success.﻿We show here that combinatorial chemistry﻿,the use of first and second coordination spheres and the displacement of indicators united within a protein cavity﻿ offers an easy-to-assemble colorimetric bio-chemical sensor. It consists only of commercial chemicals. This colorimetric sensor is highly modular, cheap and evolvable. Its X-ray structure reveals the composition of its active site. This allows to design it rationally for the recognition of dopamine with the naked eye. Our bio-sensor therefore resembles a biological receptor for the recognition of neurotransmitters. Its immediate high adaptability and ability to be evolved can be useful for the selective detection of a wide variety of analytes going from small molecules to microorganisms. This discovery therefore makes it possible to dream of new biotechnological or new immunotherapeutic applications. Naked eye ; Modular design ; Computer science ; Nanotechnology ; Molecular recognition ; Variety (cybernetics) ; Artificial intelligence ; Biochemical engineering ; Computational biology ; Combinatorial chemistry ; Chemistry ; Materials science ; Biology ; Molecule ; Engineering Click Chemistry and Applications ; Chemical Synthesis and Analysis ; Receptor Mechanisms and Signaling
Authors: Sebastian Kozuch
Source: ChemRxiv (preprint, 2020-12-04)
Field: Chemistry — Physical and Theoretical Chemistry

How Scientific is Chemistry? ϕ for philosophy, χ for chemistry. Is there a connection? Is there any interaction? Do chemists have something useful to learn from philosophers? Do philosophers from chemists? How can we define if chemistry is a science, or at least trustworthy? Which disciplines, styles and personalities are progressive in chemistry? Which ones are truth-seekers, progress-seekers or profit-seekers? Is there a point in asking these questions? Is there even an answer to them? Trustworthiness ; Seekers ; Chemistry ; Epistemology ; Computer science ; Philosophy History and advancements in chemistry
Authors: Qiyuan Zhao | Brett M. Savoie
Source: ChemRxiv (article, 2020-10-12)
Field: Materials Science — Materials Chemistry

More and Faster: Simultaneously Improving Reaction Coverage and Computational Cost in Automated Reaction Prediction Tasks &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation. Although substantial progress has been made in predicting specific reaction pathways and resolving mechanisms, the computational cost and inconsistent reaction coverage of automated prediction are still obstacles to exploring deep reaction networks without using heuristics. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straight- forward modifications of the reaction enumeration, geometry initialization, and transition state convergence algorithms that are common to many emerging prediction methodologies. These changes are implemented in the context of Yet Another Reaction Program (YARP), our reaction prediction package, for which we report a head-to-head comparison with prevailing methods for two benchmark reaction prediction tasks. In all cases, we observe near perfect recapitulation of established reaction pathways and products by YARP, without the use of heuristics or other domain knowledge to guide reaction selection. In addition, YARP also discovers many new kinetically relevant pathways and products reported here for the first time. This is achieved while simultaneously reducing the cost of reaction characterization nearly 100-fold and increasing transition state success rates and intended rates over 2-fold and 10-fold, respectively, compared with recent benchmarks. This combination of ultra-low cost and high reaction-coverage creates opportunities to explore the reactivity of larger sys- tems and more complex reaction networks for applications like chemical degradation, where approaches based on domain heuristics fail. &lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; Computer science ; Initialization ; Heuristics ; Benchmark (surveying) ; Context (archaeology) ; Reaction conditions ; Reaction rate ; Algorithm ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Thermal and Kinetic Analysis
Authors: 東北大学流体科学研究所
Source: Institutional Repositories DataBase (IRDB) (article, 2020-01-20)
Field: Materials Science — Materials Chemistry

研究活動報告書 平成30年度 A.23 A.24 A.25 B.1 () B.2 B.3 B.4 () B.5 B.6 B.7 B.8 C.1 C Boron and Carbon Nanomaterials Research ; Superconductivity in MgB2 and Alloys ; Boron Compounds in Chemistry