jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: M. Brennan Pecha | Kristiina Iisa | Michael B. Griffin | Calvin Mukarakate | Richard J. French | Bruce D. Adkins | Vivek S. Bharadwaj | Meagan Crowley | Thomas D. Foust | Joshua A. Schaidle | Peter N. Ciesielski
Source: Reaction Chemistry & Engineering (article, 2020-10-15)
Field: Chemistry — Inorganic Chemistry

<i>Ex situ</i> upgrading of pyrolysis vapors over PtTiO<sub>2</sub>: extraction of apparent kinetics <i>via</i> hierarchical transport modeling Chemical reaction kinetics enable predictive scaling studies and process sensitivity analyses that can substantially accelerate commercial deployment of new catalytic transformation technologies. Kinetics ; Pyrolysis ; Extraction (chemistry) ; Chemical kinetics ; Chemistry ; Scaling ; Chemical engineering ; Catalysis ; In situ ; Process (computing) ; Process engineering ; Materials science ; Chromatography ; Computer science ; Organic chemistry ; Engineering ; Physics ; Mathematics Zeolite Catalysis and Synthesis ; Thermochemical Biomass Conversion Processes ; Catalytic Processes in Materials Science
Authors: Wei Zheng | Yawei Shi | Guozhu Liu | Bin Zhao | Liang Wang
Source: RSC Advances (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Heteroatom-doped highly porous carbons prepared by <i>in situ</i> activation for efficient adsorptive removal of sulfamethoxazole Using organic salts as precursors, heteroatom-doped porous carbons prepared by <i>in situ</i> activation had surface areas of up to 2703 m<sup>2</sup> g<sup>-1</sup>. These porous carbons have been found to be effective adsorbents for adsorption of sulfamethoxazole (SMX) from water. The effects of precursor type, calcination temperature, pH and ionic strength as well as the regeneration properties were investigated. The different adsorption performances of porous carbons were related to their textural structures and chemical properties, and a reasonable adsorption mechanism was proposed. The effects of different heteroatom functional groups on the adsorption of SMX were also analyzed in detail. For potential practical applications, the performance of the porous carbon for removing SMX from real water was also tested. Heteroatom ; In situ ; Porosity ; Doping ; Chemistry ; Chemical engineering ; Nuclear chemistry ; Materials science ; Organic chemistry ; Ring (chemistry) Nanomaterials for catalytic reactions ; Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal
Authors: Srdjan Simunovic | Theodore M. Besmann | Emily E. Moore | Max Poschmann | M.H.A. Piro | Kevin Clarno | Jake Mcmurray | William Wieselquist
Source: Journal of Nuclear Materials (article, 2020-06-03)
Field: Materials Science — Materials Chemistry

Modeling and simulation of oxygen transport in high burnup LWR fuel Burnup ; Nuclear transmutation ; Thermochemistry ; Nuclear fuel ; Nuclear engineering ; Fission products ; Oxygen ; Chemistry ; MOX fuel ; Uranium dioxide ; Nuclear physics ; Thermodynamics ; Uranium ; Radiochemistry ; Plutonium ; Nuclear chemistry ; Physics ; Neutron ; Physical chemistry Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Radioactive element chemistry and processing
Authors: Mikhail Vasin | Владимир Лебедев
Source: Journal of Non-Crystalline Solids (article, 2020-05-25)
Field: Materials Science — Materials Chemistry

To understanding of slow and non-monotonic relaxation in Al–Y eutectic melts Eutectic system ; Spinodal decomposition ; Thermodynamics ; Instability ; Relaxation (psychology) ; Slowdown ; Spinodal ; Materials science ; Diffusion ; Monotonic function ; Statistical physics ; Phase (matter) ; Chemistry ; Physics ; Mechanics ; Microstructure ; Mathematics ; Metallurgy Material Dynamics and Properties ; Solidification and crystal growth phenomena ; Metallic Glasses and Amorphous Alloys
Authors: Yisu Peng | Shantanu Jain | Yong Fuga Li | Michal Greguš | Alexander R. Ivanov | Olga Vitek | Predrag Radivojac
Source: Bioinformatics (article, 2020-09-08)
Field: Chemistry — Spectroscopy

New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics Supplementary data are available at Bioinformatics online. False discovery rate ; Computer science ; Decoy ; Algorithm ; Data mining Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Identification and Quantification in Food
Authors: Giuseppe Ermondi | Vasanthanathan Poongavanam | Maura Vallaro | Jan Kihlberg | Giulia Caron
Source: ADMET & DMPK (article, 2020-07-08)
Field: Materials Science — Materials Chemistry

Solubility prediction in the bRo5 chemical space: where are we right now? Modelling the solubility of compounds in the "beyond Rule of 5" (bRo5) chemical space is in its infancy and to date only a few studies have been reported in the literature. Based on our own results, and those already published, we conclude that consideration of conformational flexibility and chameleon like behaviour is important, but quantitative models that account for these properties remain to be developed. Inclusion of 3D information appears to be somewhat less important than for cell permeability and extremely challenging due to the difficulties of accurate conformational sampling in the bRo5 space. Currently, methods for modelling of solubility will have to be tailored to the set of investigated compounds. Chemical space ; Solubility ; Flexibility (engineering) ; Space (punctuation) ; Formalism (music) ; Computer science ; Chemistry ; Computational chemistry ; Statistical physics ; Mathematics ; Physics ; Organic chemistry ; Statistics ; Drug discovery Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Organometallic Complex Synthesis and Catalysis
Authors: Anna Kryshchyshyn‐Dylevych | Danylo Kaminskyy | O Román | Róbert Královics | Olexandr Karpenko | Roman Lesyk
Source: The Ukrainian Biochemical Journal (article, 2020-04-17)
Field: Chemistry — Organic Chemistry

Synthesis and anti-leukemic activity of pyrrolidinedione-thiazolidinone hybrids A series of novel 2-(5-ylidene-4-oxo-2-thioxo-thiazolidin-3-yl)-succinimides and 5-ylidene-3-(1-arylpyrrolidine-2,5-dione)-thiazolidine-2,4-diones were synthesized. An efficient simple protocol for rhodanine-pyrrolidinedione hybrids synthesis which allows avoiding the step of anhydride formation was proposed. Following the previous data on antileukemic properties of related thiazolidinone derivatives, the activity of 19 target compounds was investigated towards four leukemia cell lines: Dami, HL-60, Jurkat, and K562. Among the tested compounds, 3-[5-(4-chloro-benzylidene)-4-oxo-2-thioxo-thiazolidin-3-yl]-1-phenyl-pyrrolidine-2,5-dione (Compound 1) possessed good and selective antiproliferative action against Dami and HL-60 cell lines and satisfactory toxicity level (acute toxicity evaluated in vivo in mice). Hybrid ; Chemistry ; Traditional medicine ; Pharmacology ; Toxicology ; Biology ; Medicine ; Botany Synthesis and biological activity ; Synthesis of heterocyclic compounds ; Synthesis and Reactivity of Sulfur-Containing Compounds
Authors: Jangwon Lee | Jesus Flores‐Cerrillo | Jin Wang | Q. Peter He
Source: Industrial & Engineering Chemistry Research (article, 2020-02-06)
Field: Chemistry — Analytical Chemistry

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. The new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data. Consistency (knowledge bases) ; Key (lock) ; Selection (genetic algorithm) ; Computer science ; Feature selection ; Variable (mathematics) ; Data mining ; Chemistry ; Biochemical engineering ; Machine learning ; Artificial intelligence ; Mathematics ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Samuel K. Kwofie | Emmanuel Broni | Bismark Dankwa | Kweku S. Enninful | Joshua Teye | Cedar R. Davidson | Josephine B. Nimely | J. Chioma Orizu | Prakasha Kempaiah | Brijesh Rathi | Whelton A. Miller
Source: Journal of Chemistry (article, 2020-05-20)
Field: Chemistry — Organic Chemistry

Review of Atypical Organometallic Compounds as Antimalarial Drugs Organometallic compounds are molecules that contain at least one metal-carbon bond. Due to resistance of the Plasmodium parasite to traditional organic antimalarials, the use of organometallic compounds has become widely adopted in antimalarial drug discovery. Ferroquine, which was developed due to the emergence of chloroquine resistance, is currently the most advanced organometallic antimalarial drug and has paved the way for the development of new organometallic antimalarials. In this review, a general overview of organometallic antimalarial compounds and their antimalarial activity in comparison to purely organic antimalarials are presented. Furthermore, recent developments in the field are discussed, and future applications of this emerging class of therapeutics in antimalarial drug discovery are suggested. Chemistry ; Antimalarial Agent ; Malaria ; Drug discovery ; Plasmodium falciparum ; Group 2 organometallic chemistry ; Combinatorial chemistry ; Organic chemistry ; Molecule ; Biochemistry ; Biology ; Immunology Ferrocene Chemistry and Applications ; Synthesis and Biological Evaluation ; Chemical Synthesis and Analysis
Authors: Zhong-Xuan Li | Haiping Huang
Source: Petroleum Science (article, 2020-09-12)
Field: Chemistry — Analytical Chemistry

Bulk and molecular composition variations of gold-tube pyrolysates from severely biodegraded Athabasca bitumen Abstract Gold-tube pyrolysis experiments were performed on two Athabasca oil sand bitumens at 300 °C to 525 °C with 2 °C/h rate and 25 °C step under 50 MPa. Pyrolysis temperature of 425 °C is critical for weight loss of bulk bitumen and hydrocarbon generation and destruction. Polar compounds are the main source of saturated and aromatic hydrocarbon, gas and coke fractions. Molecular compositions in pyrolyzates vary systematically with increasing pyrolysis temperatures. High molecular weight n -alkanes (C 26 + ) are gradually destructed during pyrolysis due to thermal cracking. Moderate molecular weight n -alkanes (C 21 –C 25 ) show the highest thermal stability in designed pyrolysis temperatures. The loss of low molecular weight n -alkanes (C 20 − ) might be caused by volatilization during pyrolysis, which may alter commonly used molecular parameters such as ∑ n -C 20 − /∑ n -C 21 + , Pr/ n -C 17 and Ph/ n -C 18 . Aromatic hydrocarbons were generated from 300 to 425 °C, then condensation and dealkylation have been initiated at 425 °C as evidenced by decreased summed alkylnaphthalenes to alkylphenanthrenes ratios and increased unsubstituted aromatics to substituted homologs ratios in higher temperatures. The occurrence of anthracene and benz[a]anthracene in pyrolysates indicates pyrogenic origin, while fluoranthene shows unexpected behaviors during pyrolysis. Ratios derived from them are not always reliable for pyrogenic source input diagnosis in environmental samples. Pyrolysis ; Anthracene ; Chemistry ; Hydrocarbon ; Volatilisation ; Fluoranthene ; Cracking ; Organic chemistry ; Tube furnace ; Polycyclic aromatic hydrocarbon ; Condensation ; Coke Petroleum Processing and Analysis ; Hydrocarbon exploration and reservoir analysis ; Toxic Organic Pollutants Impact
Authors: Mariano Romero | Dominique Mombrú | Fernando Pignanelli | Ricardo Faccio | Álvaro W. Mombrú
Source: Frontiers in Chemistry (review, 2020-07-14)
Field: Materials Science — Polymers and Plastics

Mini-Review: Mixed Ionic–Electronic Charge Carrier Localization and Transport in Hybrid Organic–Inorganic Nanomaterials In this mini-review, a comprehensive discussion on the state of the art of hybrid organic-inorganic mixed ionic-electronic conductors (<i>hOI</i>-MIECs) is given, focusing on conducting polymer nanocomposites comprising inorganic nanoparticles ranging from ceramic-in-polymer to polymer-in-ceramic concentration regimes. First, a brief discussion on fundamental aspects of mixed ionic-electronic transport phenomena considering the charge carrier transport at bulk regions together with the effect of the organic-inorganic interphase of hybrid nanocomposites is presented. We also make a recount of updated instrumentation techniques to characterize structure, microstructure, chemical composition, and mixed ionic-electronic transport with special focus on those relevant for <i>hOI</i>-MIECs. Raman imaging and impedance spectroscopy instrumentation techniques are particularly discussed as relatively simple and versatile tools to study the charge carrier localization and transport at different regions of <i>hOI</i>-MIECs including both bulk and interphase regions to shed some light on the mixed ionic-electronic transport mechanism. In addition, we will also refer to different device assembly configurations and <i>in situ/operando</i> measurements experiments to analyze mixed ionic-electronic conduction phenomena for different specific applications. Finally, we will also review the broad range of promising applications of <i>hOI</i>-MIECs, mainly in the field of energy storage and conversion, but also in the emerging field of electronics and bioelectronics. Bioelectronics ; Ionic bonding ; Nanotechnology ; Materials science ; Charge carrier ; Nanomaterials ; Ionic conductivity ; Nanocomposite ; Organic electronics ; Chemical physics ; Ion ; Chemistry ; Electrode ; Optoelectronics ; Electrical engineering ; Electrolyte ; Biosensor ; Physical chemistry ; Organic chemistry Conducting polymers and applications ; Advanced Battery Materials and Technologies ; Ionic liquids properties and applications
Authors: Junhui Zhang | Lixiong Dai | Alexandra M. Webster | Wesley Ting Kwok Chan | Lewis E. MacKenzie | Róbert Pál | Steven L. Cobb | Ga‐Lai Law
Source: Angewandte Chemie (article, 2020-09-22)
Field: Materials Science — Materials Chemistry

Unusual Magnetic Field Responsive Circularly Polarized Luminescence Probes with Highly Emissive Chiral Europium(III) Complexes Abstract Chirality is ubiquitous within biological systems where many of the roles and functions are still undetermined. Given this, there is a clear need to design and develop sensitive chiral optical probes that can function within a biological setting. Here we report the design and synthesis of magnetically responsive Circularly Polarized Luminescence (CPL) complexes displaying exceptional photophysical properties (quantum yield up to 31 % and |g lum | up to 0.240) by introducing chiral substituents onto the macrocyclic scaffolds. Magnetic CPL responses are observed in these chiral Eu III complexes, promoting an exciting development to the field of magneto‐optics. The |g lum | of the 5 D 0 → 7 F 1 transition increases by 20 % from 0.222 (0 T) to 0.266 (1.4 T) displaying a linear relationship between the Δg lum and the magnetic field strength. These Eu III complexes with magnetic CPL responses, provides potential development to be used in CPL imaging applications due to improved sensitivity and resolution. Chirality (physics) ; Luminescence ; Europium ; Magnetic field ; Circular polarization ; Quantum yield ; Circular dichroism ; Magnetic circular dichroism ; Chemistry ; Materials science ; Nanotechnology ; Crystallography ; Optoelectronics ; Optics ; Physics ; Fluorescence Lanthanide and Transition Metal Complexes ; Magnetism in coordination complexes ; Luminescence and Fluorescent Materials
Authors: Chris John | Cheriyacheruvakkara Owais | Anto James | Rotti Srinivasamurthy Swathi
Source: The Journal of Physical Chemistry C (article, 2020-12-28)
Field: Materials Science — Materials Chemistry

Swarm Intelligence Steers a Global Minima Search of Clusters Bound on Carbon Nanostructures A detailed exploration of the energy landscape is a necessary criterion for an efficient structure prediction. Although computational power has increased many-folds in recent decades, a full analysis of the potential energy surfaces (PESs) for complex chemical systems is still computationally elusive. Locating the most stable geometry of a system from a highly complex PES necessitates the use of metaheuristic techniques. Particle swarm optimization (PSO), a nature-inspired metaheuristic technique falling under the general ambit of artificial intelligence, has proven to be a promising approach for structure prediction. Through social networking, the swarm attains a collective intelligence leading to an effective search of the PESs for the most stable configurations. The PESs associated with the noncovalent interactions involving carbon nanostructures and atomic or molecular clusters are often rugged, with a large number of local minima hindering the tracking down of the global minima. In this Perspective, we demonstrate that an amalgamation of PSO with the continuum approximation, an approximation that exploits the symmetry of carbon nanostructures, serves as a robust methodology for unraveling the interactions of Lennard-Jones clusters with carbon nanostructures. The putative global minima geometries obtained from our methodology can provide fruitful insights on the structural and energetic aspects of cluster binding on carbon nanostructures and can offer excellent initial configurations for first-principles calculations. Maxima and minima ; Swarm behaviour ; Cluster (spacecraft) ; Swarm intelligence ; Metaheuristic ; Computer science ; Energy landscape ; Particle swarm optimization ; Statistical physics ; Nanotechnology ; Mathematical optimization ; Physics ; Materials science ; Algorithm ; Artificial intelligence ; Mathematics Machine Learning in Materials Science ; Complex Network Analysis Techniques ; Advanced Chemical Physics Studies
Authors: Bineet Sharma | Yutao Ma | Andrew L. Ferguson | Allen P. Liu
Source: Soft Matter (review, 2020-01-01)
Field: Materials Science — Biomaterials

In search of a novel chassis material for synthetic cells: emergence of synthetic peptide compartment Giant lipid vesicles have been used extensively as a synthetic cell model to recapitulate various life-like processes, including in vitro protein synthesis, DNA replication, and cytoskeleton organization. Cell-sized lipid vesicles are mechanically fragile in nature and prone to rupture due to osmotic stress, which limits their usability. Recently, peptide vesicles have been introduced as a synthetic cell model that would potentially overcome the aforementioned limitations. Peptide vesicles are robust, reasonably more stable than lipid vesicles and can withstand harsh conditions including pH, thermal, and osmotic variations. This mini-review summarizes the current state-of-the-art in the design, engineering, and realization of peptide-based chassis materials, including both experimental and computational work. We present an outlook for simulation-aided and data-driven design and experimental realization of engineered and multifunctional synthetic cells. Chassis ; Vesicle ; Artificial cell ; Synthetic biology ; Peptide ; Compartment (ship) ; Lipid vesicle ; Cell biology ; Chemistry ; Nanotechnology ; Computational biology ; Biophysics ; Biology ; Biochemistry ; Materials science ; Engineering ; Membrane Supramolecular Self-Assembly in Materials ; Lipid Membrane Structure and Behavior ; Polydiacetylene-based materials and applications
Authors: Yomei Tokuda | Misa Fujisawa | Daniel M. Packwood | Mei Kambayashi | Yoshikatsu Ueda
Source: AIP Advances (article, 2020-10-01)
Field: Materials Science — Ceramics and Composites

Data-driven design of glasses with desirable optical properties using statistical regression In this study, we used a data-driven approach to build models for assisting the design of new glasses with high refractive index and low dispersion. Our models, which are based on multiple linear regression and kernel ridge regression, achieved high accuracy in predicting optical properties of glasses based on their composition alone. Using the predictions of these models as a guide, we fabricated new glasses in our laboratory. In agreement with model predictions, these glasses had promising optical properties. This work therefore demonstrates a successful example of data-driven materials design and can be used as a template for designing glasses or other materials with other desirable properties. Refractive index ; Optical glass ; Dispersion (optics) ; Materials science ; Regression ; Computer science ; Linear regression ; Regression analysis ; Kernel (algebra) ; Ridge ; Optics ; Mathematics ; Machine learning ; Statistics ; Physics ; Optoelectronics ; Composite material ; Geology Glass properties and applications ; Pigment Synthesis and Properties ; Phase-change materials and chalcogenides