jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Richard Archibald | Jaron T. Krogel | Paul R. C. Kent
Source: The Journal of Chemical Physics (article, 2018-10-28)
Field: Materials Science — Materials Chemistry

Gaussian process based optimization of molecular geometries using statistically sampled energy surfaces from quantum Monte Carlo Optimization of atomic coordinates and lattice parameters remains a significant challenge to the wide use of stochastic electronic structure methods such as quantum Monte Carlo (QMC). Measurements of the forces and stress tensor by these methods contain statistical errors, challenging conventional gradient-based numerical optimization methods that assume deterministic results. Additionally, forces are not yet available for some methods, wavefunctions, and basis sets and when available may be expensive to compute to sufficiently high statistical accuracy near energy minima, where the energy surfaces are flat. Here, we explore the use of Gaussian process based techniques to sample the energy surfaces and reduce sensitivity to the statistical nature of the problem. We utilize Latin hypercube sampling, with the number of sampled energy points scaling quadratically with the number of optimized parameters. We show these techniques may be successfully applied to systems consisting of tens of parameters, demonstrating QMC optimization of a benzene molecule starting from a randomly perturbed, broken symmetry geometry. Latin hypercube sampling ; Maxima and minima ; Monte Carlo method ; Quantum Monte Carlo ; Statistical physics ; Gaussian ; Scaling ; Gaussian process ; Tensor (intrinsic definition) ; Ansatz ; Mathematics ; Computer science ; Mathematical optimization ; Physics ; Quantum mechanics ; Mathematical analysis ; Geometry ; Statistics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Mass Spectrometry Techniques and Applications
Authors: Babatunde Anifowose | Modupe T. Odubela
Source: Journal of Cleaner Production (article, 2018-03-21)
Field: Chemistry — Analytical Chemistry

Oil facility operations: A multivariate analyses of water pollution parameters Environmental science ; Multivariate statistics ; Pollution ; Multivariate analysis ; Water pollution ; Waste management ; Petroleum engineering ; Environmental engineering ; Engineering ; Statistics ; Mathematics ; Chemistry ; Environmental chemistry Petroleum Processing and Analysis
Authors: Peter D. Wentzell | Chelsi C. Wicks | Jez Willian Batista Braga | Liz F. Soares | Tereza Cristina Monteiro Pastore | Vera T.R. Coradin | Fabrice Davrieux
Source: Canadian Journal of Chemistry (article, 2018-05-22)
Field: Chemistry — Analytical Chemistry

Implications of measurement error structure on the visualization of multivariate chemical data: hazards and alternatives The analysis of multivariate chemical data is commonplace in fields ranging from metabolomics to forensic classification. Many of these studies rely on exploratory visualization methods that represent the multidimensional data in spaces of lower dimensionality, such as hierarchical cluster analysis (HCA) or principal components analysis (PCA). However, such methods rely on assumptions of independent measurement errors with uniform variance and can fail to reveal important information when these assumptions are violated, as they often are for chemical data. This work demonstrates how two alternative methods, maximum likelihood principal components analysis (MLPCA) and projection pursuit analysis (PPA), can reveal chemical information hidden from more traditional techniques. Experimental data to compare different methods consists of near-infrared (NIR) reflectance spectra from 108 samples of wood that are derived from four different species of Brazilian trees. The measurement error characteristics of the spectra are examined and it is shown that, by incorporating measurement error information into the data analysis (through MLPCA) or using alternative projection criteria (i.e., PPA), samples can be separated by species. These techniques are proposed as powerful tools for multivariate data analysis in chemistry. Principal component analysis ; Multivariate statistics ; Projection pursuit ; Visualization ; Exploratory data analysis ; Projection (relational algebra) ; Chemometrics ; Dimensionality reduction ; Data mining ; Multivariate analysis ; Hierarchical clustering ; Pattern recognition (psychology) ; Curse of dimensionality ; Statistics ; Computer science ; Chemistry ; Artificial intelligence ; Cluster analysis ; Algorithm ; Mathematics ; Machine learning Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Metabolomics and Mass Spectrometry Studies
Authors: Junming Chen | Haopeng Huang | Yi-Bing Zhang | Yonglu Wang | Fanyu Kong | Yanzhi Wang | Yunxia Jin | Peng Chen | Jiao Xu | Jianda Shao
Source: Scientific Reports (article, 2018-03-27)
Field: Materials Science — Surfaces, Coatings and Films

Reducing electric-field-enhancement in metal-dielectric grating by designing grating with asymmetric ridge Diffraction gratings are an essential optical component of high-power, short-pulse lasers. The maximum output of high-power pulsed lasers is always determined by laser resistance of gratings and this resistance is strongly dependent on the local near electric field intensity in the grating structure. We presented a novel method of reducing electric-field-enhancement in metal-dielectric grating by designing asymmetric grating ridge while maintaining high diffraction performance. Compared with the common isosceles trapezoidal grating, the grating with asymmetric ridge got a 0.04% reduction of diffraction efficiency in TE polarization at 1053 nm incident wavelength but a 21.3% reduction of maximal electric-field-enhancement in grating structure. This method can be applied to any surface-relief gratings to reduce the electric-field-enhancement for improving the laser induced damage threshold (LIDT) of grating and supporting the grating-based chirped pulse amplification (CPA) system to develop into higher peak-power levels. Grating ; Materials science ; Optics ; Ultrasonic grating ; Blazed grating ; Holographic grating ; Electric field ; Laser ; Optoelectronics ; Diffraction efficiency ; Diffraction ; Diffraction grating ; Dielectric ; Physics Optical Coatings and Gratings ; Advanced Surface Polishing Techniques ; Near-Field Optical Microscopy
Authors: Brian C. Searle | Lindsay K. Pino | Jarrett D. Egertson | Ying S. Ting | Robert Lawrence | Judit Villén | Michael J. MacCoss
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-03-07)
Field: Chemistry — Spectroscopy

Comprehensive peptide quantification for data independent acquisition mass spectrometry using chromatogram libraries ABSTRACT Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. We introduce a new experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in an experiment. These coordinates calibrate information in spectrum libraries or protein databases to a specific mass spectrometer and chromatography setup, and enable sensitive peptide detection in quantitative experiments. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect and quantify &gt;50% more peptides from DIA experiments than with DDA-based spectrum libraries alone. Mass spectrometry ; Chromatography ; Workflow ; Fragmentation (computing) ; Chemistry ; Peptide ; Proteomics ; Reproducibility ; Resolution (logic) ; Data acquisition ; Computer science ; Analytical Chemistry (journal) ; Database ; Artificial intelligence Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Pallavi Pawar | Sameer Talwar | D. Narasimha Reddy | Chandra Kanth Bandi | Huiquan Wu | Koushik Sowrirajan | Rick A. Friedman | Germán Drazer | James K. Drennen | Fernando J. Muzzio
Source: Journal of Pharmaceutical Sciences (article, 2018-08-10)
Field: Chemistry — Analytical Chemistry

A “Large-N” Content Uniformity Process Analytical Technology (PAT) Method for Phenytoin Sodium Tablets Chromatography ; Calibration ; Mean squared error ; Partial least squares regression ; Confidence interval ; Near-infrared spectroscopy ; Mathematics ; Analytical Chemistry (journal) ; Chemistry ; Materials science ; Statistics ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Drug Solubulity and Delivery Systems ; Analytical Methods in Pharmaceuticals
Authors: Maria Georgopoulou | Constantinos V. Chrysikopoulos
Source: Industrial & Engineering Chemistry Research (article, 2018-11-20)
Field: Materials Science — Materials Chemistry

Evaluation of Carbon Nanotubes and Quartz Sand for the Removal of Formaldehyde–(2,4-Dinitrophenylhydrazine) from Aqueous Solutions The assessment of the potential impact of engineered carbon nanotubes on the removal of synthetic chemical contaminants (e.g., pesticides, pharmaceuticals, and chemical reaction products) from aqueous solutions has become an increasingly important aspect of environmental research. This study has focused on the interaction of the reaction product of formaldehyde (FA) with 2,4-dinitrophenylhydrazine (2,4-DNPH) with multiwalled carbon nanotubes (MWCNTs) and quartz sand under static and dynamic conditions. Several batch adsorption experiments were conducted in test tubes, under controlled conditions and at laboratory room temperature (23 °C). The experimental results suggested that FA–(2,4-DNPH) has a low affinity for quartz sand but an enhanced potential for adsorption onto small quantities of MWCNTs. FA–(2,4-DNPH) adsorption onto quartz sand and MWCNTs was more pronounced under dynamic than static conditions, probably due to agitation improved mixing of the absorbent within the solution. The collected adsorption data were adequately described by a pseudo-second-order kinetic model and intraparticle diffusion model. On the basis of root-mean-square error (RMSE) values, better fitting of experimental data was achieved with the Weber-Morris intraparticle diffusion model. Our findings suggested that a rapid surface chemisorption of FA–(2,4-DNPH) onto available adsorption sites of sand and MWCNTs, followed by a slower intra-aggregate diffusion of FA–(2,4-DNPH) onto interstitial spaces of entangled MWCNTs, occurred. The observed FA–(2,4-DNPH) removal by combined MWCNTs and quartz sand was 78.1%. Thus, MWCNTs could be promising adsorbent materials for removal of complicated organic compounds from aqueous solutions and for groundwater remediation. Adsorption ; Aqueous solution ; Diffusion ; Carbon nanotube ; Formaldehyde ; Chemical engineering ; Quartz ; Chemisorption ; Chemistry ; Materials science ; Organic chemistry ; Composite material ; Thermodynamics Carbon Nanotubes in Composites ; Nanopore and Nanochannel Transport Studies ; Adsorption and biosorption for pollutant removal
Authors: K. B. Schaettle | Luis Ruiz Pestana | Teresa Head‐Gordon | Laura N. Lammers
Source: The Journal of Chemical Physics (article, 2018-02-20)
Field: Materials Science — Materials Chemistry

A structural coarse-grained model for clays using simple iterative Boltzmann inversion Cesium-137 is a major byproduct of nuclear energy generation and is environmentally threatening due to its long half-life and affinity for naturally occurring micaceous clays. Recent experimental observations of illite and phlogopite mica indicate that Cs<sup>+</sup> is capable of exchanging with K<sup>+</sup> bound in the anhydrous interlayers of layered silicates, forming sharp exchange fronts, leading to interstratification of Cs- and K-illite. We present here a coarse-grained (CG) model of the anhydrous illite interlayer developed using iterative Boltzmann inversion that qualitatively and quantitatively reproduces features of a previously proposed feedback mechanism of ion exchange. The CG model represents a 70-fold speedup over all-atom models of clay systems and predicts interlayer expansion for K-illite near ion exchange fronts. Contrary to the longstanding theory that ion exchange in a neighboring layer increases the binding of K in lattice counterion sites leading to interstratification, we find that the presence of neighboring exchanged layers leads to short-range structural relaxations that increase basal spacing and decrease cohesion of the neighboring K-illite layers. We also provide evidence that the formation of alternating Cs- and K-illite interlayers (i.e., ordered interstratification) is both thermodynamically and mechanically favorable compared to exchange in adjacent interlayers. Illite ; Anhydrous ; Ion ; Ion exchange ; Mineralogy ; Geology ; Materials science ; Chemistry ; Clay minerals Nuclear materials and radiation effects ; Soil and Unsaturated Flow ; Clay minerals and soil interactions
Authors: El Hassan Elkhattabi | Mohamed Lakraimi | M. Berraho | Ahmed Legrouri | Radouan Hammal | Layla El Gaini
Source: Applied Water Science (article, 2018-03-01)
Field: Materials Science — Materials Chemistry

Acid Green 1 removal from wastewater by layered double hydroxides The paper presents the removal of Acid Green 1 (AG1) from aqueous solutions by [Zn–Al–Cl]-layered double hydroxides (LDHs). The LDH was prepared by coprecipitation at constant pH. The affinity of this material for AG1 was studied as a function of contact time, pH of the solution, LDH dose and AG1/LDH mass ratio. It was found that 32 h are enough to reach the equilibrium with a maximum retention at pH 8 for an LDH dose of 100 mg and with an AG1/LDH mass ratio higher than 2. The adsorption isotherm is of L-type, as described by the Langmuir model. The results demonstrate that AG1 retention on LDHs occurs by adsorption on external surface when AG1/LDH mass ratio is equal or lower than 2 and by both adsorption and interlayer ion exchange for ratios higher than 2. A mechanism for the AG1 removal has been confirmed by X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetric–differential thermal analyses and scanning electron microscopy. Layered double hydroxides ; Adsorption ; Thermogravimetric analysis ; Coprecipitation ; Ion exchange ; Chemistry ; Fourier transform infrared spectroscopy ; Langmuir ; Aqueous solution ; Differential thermal analysis ; Langmuir adsorption model ; Scanning electron microscope ; Nuclear chemistry ; Inorganic chemistry ; Analytical Chemistry (journal) ; Materials science ; Chemical engineering ; Chromatography ; Ion ; Diffraction ; Composite material ; Organic chemistry Layered Double Hydroxides Synthesis and Applications ; Supercapacitor Materials and Fabrication ; Advanced Photocatalysis Techniques
Authors: Dawei Jiang | Zhongsheng Liu | Kaizhen Wu | Linlin Mou | Raquel Ovalle‐Robles | Kanzan Inoue | Yu Zhang | Ningyi Yuan | Jianning Ding | Jianhua Qiu | Yi Huang | Zunfeng Liu
Source: Polymers (article, 2018-03-28)
Field: Materials Science — Polymers and Plastics

Fabrication of Stretchable Copper Coated Carbon Nanotube Conductor for Non-Enzymatic Glucose Detection Electrode with Low Detection Limit and Selectivity The increasing demand for wearable glucose sensing has stimulated growing interest in stretchable electrodes. The development of the electrode materials having large stretchability, low detection limit, and good selectivity is the key component for constructing high performance wearable glucose sensors. In this work, we presented fabrication of stretchable conductor based on the copper coated carbon nanotube sheath-core fiber, and its application as non-enzymatic electrode for glucose detection with high stretchability, low detection limit, and selectivity. The sheath-core fiber was fabricated by coating copper coated carbon nanotube on a pre-stretched rubber fiber core followed by release of pre-stretch, which had a hierarchically buckled structure. It showed a small resistance change as low as 27% as strain increasing from 0% to 500% strain, and a low resistance of 0.4 Ω·cm<sup>-1</sup> at strain of 500%. This electrode showed linear glucose concentration detection in the range between 0.05 mM and 5 mM and good selectivity against sucrose, lactic acid, uric acid, acrylic acid in phosphate buffer saline solution, and showed stable signal in high salt concentration. The limit of detection (LOD) was 0.05 mM, for the range of 0.05⁻5 mM, the sensitivity is 46 mA·M<sup>-1</sup>. This electrode can withstand large strain of up to 60% with negligible influence on its performance. Detection limit ; Electrode ; Carbon nanotube ; Materials science ; Fabrication ; Electrical conductor ; Copper ; Conductor ; Nanotechnology ; Selectivity ; Biosensor ; Chemical engineering ; Optoelectronics ; Composite material ; Chemistry ; Chromatography ; Metallurgy ; Catalysis ; Organic chemistry Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Electrochemical sensors and biosensors
Authors: Anna Sandak | Jakub Sandak | Dominika Janiszewska | Salim Hızıroǧlu | Marta Petrillo | Paolo Grossi
Source: Journal of Spectroscopy (article, 2018-09-30)
Field: Chemistry — Analytical Chemistry

Prototype of the Near-Infrared Spectroscopy Expert System for Particleboard Identification The overall goal of this work was to develop a prototype expert system assisting quality control and traceability of particleboard panels on the production floor. Four different types of particleboards manufactured at the laboratory scale and in industrial plants were evaluated. The material differed in terms of panel type, composition, and adhesive system. NIR spectroscopy was employed as a pioneer tool for the development of a two-level expert system suitable for classification and traceability of investigated samples. A portable, commercially available NIR spectrometer was used for nondestructive measurements of particleboard panels. Twenty-five batches of particleboards, each containing at least three independent replicas, was used for the original system development and assessment of its performance. Four alternative chemometric methods (PLS-DA, kNN, SIMCA, and SVM) were used for spectroscopic data classification. The models were developed for panel recognition at two levels differing in terms of their generality. In the first stage, four among twenty-four tested combinations resulted in 100% correct classification. Discrimination precision with PLS-DA and SVMC was high (&gt;99%), even without any spectra preprocessing. SNV preprocessed spectra and SVMC algorithm were used at the second stage for panel batch classification. Panels manufactured by two producers were 100% correctly classified, industrial panels produced by different manufacturing plants were classified with 98.9% success, and the experimental panels manufactured in the laboratory were classified with 63.7% success. Implementation of NIR spectroscopy for wood-based product traceability and quality control may have a great impact due to the high versatility of the production and wide range of particleboards utilization. Traceability ; Process engineering ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Expert system ; Near-infrared spectroscopy ; Environmental science ; Engineering Spectroscopy and Chemometric Analyses ; Cultural Heritage Materials Analysis ; Advanced Chemical Sensor Technologies
Authors: Spencer Pfeifer | Balaji Sesha Sarath Pokuri | Pengfei Du | Baskar Ganapathysubramanian
Source: Materials Discovery (article, 2018-03-01)
Field: Materials Science — Materials Chemistry

Process optimization for microstructure-dependent properties in thin film organic electronics Computer science ; Modular design ; Organic electronics ; Electronics ; Fabrication ; Process (computing) ; Scalability ; Materials science ; Engineering ; Electrical engineering Machine Learning in Materials Science ; Organic Electronics and Photovoltaics ; Block Copolymer Self-Assembly
Authors: Tai-Danae Bradley
Source: arXiv (Cornell University) (preprint, 2018-09-16)
Field: Chemistry — Physical and Theoretical Chemistry

What is Applied Category Theory? This is a collection of introductory, expository notes on applied category theory, inspired by the 2018 Applied Category Theory Workshop, and in these notes we take a leisurely stroll through two themes (functorial semantics and compositionality), two constructions (monoidal categories and decorated cospans) and two examples (chemical reaction networks and natural language processing) within the field. Principle of compositionality ; Semantics (computer science) ; Computer science ; Field (mathematics) ; Category theory ; Linguistics ; Natural (archaeology) ; Natural language processing ; Artificial intelligence ; Programming language ; Mathematics ; Pure mathematics ; Philosophy ; History ; Archaeology History and advancements in chemistry
Authors: Linda Medlin
Source: Revista Brasileira de Botânica (article, 2018-02-14)
Field: Materials Science — Biomaterials

Mini review: Diatom species as seen through a molecular window It has been accepted that we know less than 10% of the identified diversity in the marine microbial world and the diatoms are no exception. Even the species that we think we can easily recognize are often cryptic species, and even less is known of their life histories and spatial and temporal trends in their abundance and distribution. With new molecular and analytical techniques, we can advance our knowledge of a species to understand its morphological range, biogeographies and reproductive isolation. Moreover, some of molecular techniques are very sensitive. Depending on the species-level question(s) being asked, the molecular tools appropriate to answer them differ greatly. Diatom ; Abundance (ecology) ; Range (aeronautics) ; Biology ; Isolation (microbiology) ; Ecology ; Evolutionary biology ; Bioinformatics Diatoms and Algae Research ; Microbial Community Ecology and Physiology ; Marine Biology and Ecology Research
Authors: Fengyi Wu | Zhongping Zhang | Zhifeng Zhu | Mingling Li | Wensheng Lü | Min Chen | Enze Xu | Li Wang | Yang Jiang
Source: CrystEngComm (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Fine-tuning the crystal structure of CdSe quantum dots by varying the dynamic characteristics of primary alkylamine ligands Primary alkylamines are generally used as ligands for the synthesis of colloidal II–VI group quantum dots (QDs). Quantum dot ; Primary (astronomy) ; Crystal (programming language) ; Chemistry ; Crystal structure ; Nanotechnology ; Materials science ; Optoelectronics ; Crystallography ; Physics ; Computer science ; Quantum mechanics Quantum Dots Synthesis And Properties ; Chalcogenide Semiconductor Thin Films ; Nanocluster Synthesis and Applications