jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jiabao WANG | Xiaohong Wu | Jun Zheng | Bin Wu
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Rapid identification of green tea varieties based on FT-NIR spectroscopy and LDA/QR There are many substances beneficial to human body in tea. In this study, we put forward innovative strategies to quickly and harmlessly identify Chinese green tea varieties. Near-infrared (NIR) spectrometer was used to collect NIR spectral data of tea samples, and the data were preprocessed by Savitzky-Golay (SG) filter to eliminate noise of spectral data. Three feature extraction algorithms: principal component analysis (PCA) combined with linear discriminant analysis (LDA), LDA/QR, generalize singular value decomposition (GSVD) were performed to decrease the dimension and compress the spectral data. Finally, k-nearest neighbor (kNN) classifier was utilized to classify the samples according to the NIR spectra of the samples. PCA combined with LDA, GSVD and LDA/QR had the classification accuracy rates 94.19%, 91.86% and 98.84%, respectively. So, LDA/QR showed the highest classification accuracy in classification of NIR spectra of tea samples. We believe that the combination of NIR spectroscopy and feature extraction algorithms can quickly identify the types of tea samples. This method may have the potential to identify other varieties of food. Linear discriminant analysis ; Principal component analysis ; Pattern recognition (psychology) ; Artificial intelligence ; Near-infrared spectroscopy ; Mathematics ; Classifier (UML) ; Computer science ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Tea Polyphenols and Effects
Authors: Laine Longacre | Emily Wu | Chelsea Yang | Miles Zhang | Sneha Sinha | Advika Varadharajan | William E. Acree
Source: Liquids (article, 2022-09-22)
Field: Materials Science — Materials Chemistry

Development of Abraham Model Correlations for Solute Transfer into the tert-Butyl Acetate Mono-Solvent and Updated Equations for Both Ethyl Acetate and Butyl Acetate Experimental solubilities were determined for 31 solid nonelectrolyte organic compounds dissolved in tert-butyl acetate at 298.15 K. Results of the experimental measurements were combined with published mole fraction solubility data for two lipid-lowering medicinal compounds (lovastatin and simvastatin) in order to derive Abraham model expressions for solute transfer into the tert-butyl acetate mono-solvent. The derived correlations provided an accurate mathematical description of the observed experimental data. As part of the current study, previously published Abraham model solvent correlations for both ethyl acetate and butyl acetate were updated using much larger datasets that contained an additional 64 and 35 experimental data points, respectively. The mathematical correlations presented in the current study describe the observed solubility ratios of solutes dissolved in tert-butyl acetate, ethyl acetate, and butyl acetate to within an overall standard deviation of 0.15 log units or less. Ethyl acetate ; Solubility ; Solvent ; Butyl acetate ; Chemistry ; Organic chemistry Crystallization and Solubility Studies ; Chemistry and Chemical Engineering ; Computational Drug Discovery Methods
Authors: Alexander J. Grooms | Benjamin J. Burris | Abraham K. Badu‐Tawiah
Source: Mass Spectrometry Reviews (review, 2022-12-16)
Field: Chemistry — Spectroscopy

Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body. Metabolomics ; Metabolome ; Computational biology ; Tandem mass spectrometry ; Instrumentation (computer programming) ; Proteome ; Biomarker discovery ; Chemistry ; Metabolite ; Bioinformatics ; Proteomics ; Mass spectrometry ; Computer science ; Biology ; Chromatography ; Biochemistry Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Metabolism and Genetic Disorders
Authors: Thomas E. Gartner | Kelly M. Hunter | Eleftherios Lambros | Alessandro Caruso | Marc Riera | Gregory R. Medders | Athanassios Z. Panagiotopoulos | Pablo G. Debenedetti | Francesco Paesani
Source: ChemRxiv (preprint, 2022-02-25)
Field: Materials Science — Materials Chemistry

The Anomalies and Local Structure of Liquid Water from Boiling to the Supercooled Regime as Predicted by the Many-Body MB-pol Model For the last 50 years, researchers have sought molecular models that can accurately reproduce water’s microscopic structure and thermophysical properties across broad ranges of its complex phase diagram. Herein, molecular dynamics simulations with the many-body MB-pol model are performed to monitor the thermodynamic response functions and local structure of liquid water from the boiling point down to deeply supercooled temperatures at ambient pressure. The isothermal compressibility and isobaric heat capacity show maxima near 223 K, in excellent agreement with recent experiments, and the liquid density exhibits a minimum at ~208 K. A local tetrahedral arrangement, where each water molecule accepts and donates two hydrogen bonds, is found to be the most probable hydrogen-bonding topology at all temperatures. This work suggests that MB-pol may provide predictive capability for studies of liquid wa- ter’s physical properties across broad ranges of thermodynamic states, including the so-called water’s “no man’s land” which is difficult to probe experimentally. Supercooling ; Thermodynamics ; Phase diagram ; Heat capacity ; Liquid water ; Water model ; Isobaric process ; Compressibility ; Hydrogen bond ; Molecular dynamics ; Work (physics) ; Boiling ; Isothermal process ; Materials science ; Chemistry ; Molecule ; Physics ; Phase (matter) ; Computational chemistry Material Dynamics and Properties ; Phase Equilibria and Thermodynamics ; Theoretical and Computational Physics
Authors: Jae-Hyang Kim | Seung-Hoon Han
Source: Buildings (article, 2022-02-24)
Field: Materials Science — Polymers and Plastics

Indoor Daylight Performances of Optimized Transmittances with Electrochromic-Applied Kinetic Louvers Windows with low visible light transmittance (VLT) and g-values are preferred to reduce the building’s energy consumption. However, low VLT and g-value can create an unpleasant indoor daylight environment. A glass with freely adjustable VLT and g-value as required has been developed and is called smart glass. In this study, the recently developed VLT adjustable smart glass is targeted. Some studies were conducted on the VLT adjustment status of smart windows to create an appropriate indoor lighting environment. Although research on smart glass has been conducted through ecofriendly building certification systems such as LEED in the US, BREEAM in the UK, CASBEE in Japan, and GSEED in South Korea, it was pointed out that there is a limit to creating a uniformity. Therefore, the previous study analyzed the VLT conditions to create a minimal indoor daylight environment. The purpose of this study is to propose and analyze a louver-type electrochromic façade that can create a uniform indoor illuminance. A simulation method was used, and a range of changes in indoor illuminance that could be controlled through an electrochromic louver was derived. The simulation was performed using the Rhino 6′s Grasshopper program based on the Radiance engine. Electrochromic is a class of smart glass with high VLT variable range and durability. The conditions for deriving the optimal daylight environment according to the composition, VLT, and angle of the electrochromic louver were analyzed. The evaluation was made against the criteria of LEED v4.1. Data on the composition, VLT, and angle adjustment of the electrochromic louver that can obtain a high LEED v4.1 daylight score were derived, and organized in tables. Considering the composition and angle, it was found that the daylight environment of the electrochromic louver adjusted with a VLT of 25% to 45% was excellent in composition. Louver ; Daylight ; Electrochromism ; Glazing ; Radiance ; Illuminance ; Environmental science ; Transmittance ; Computer science ; Materials science ; Simulation ; Optics ; Engineering ; Optoelectronics ; Mechanical engineering ; Physics ; Composite material Transition Metal Oxide Nanomaterials ; Urban Heat Island Mitigation ; Building Energy and Comfort Optimization
Authors: Arnaud Allera | Fabienne Ribeiro | Michel Perez | David Rodney
Source: Physical Review Materials (article, 2022-01-18)
Field: Materials Science — Materials Chemistry

Carbon-induced strengthening of bcc iron at the atomic scale In steels, the interaction between screw dislocations and carbon solutes has a great influence on the yield strength. Fe-C potentials used in molecular dynamics (MD) simulations yield a poor description of screw dislocation properties---their core structure and Peierls barrier---compared to ab initio calculations. Here we combine two EAM potentials from the literature, which greatly improves dislocation property accuracy in FeC alloys. Using this hybrid potential, MD simulations of dislocation glide in random solid solutions confirm a powerful solute strengthening, caused by complex interaction processes. We analyze these processes in a model geometry, where a row of carbon atoms is inserted in the dislocation core with varying separations. We use a combination of MD simulations, minimum-energy path calculations, and a statistical model based on the harmonic transition state theory to explain the strengthening induced by carbon. We unveil that carbon disrupts the glide process, as unpinning requires the successive nucleation of two kink pairs. When solute separation is below about 100 Burgers vectors, the activation enthalpy of both kink pairs are markedly increased compared to pure iron, resulting in a strong dependence of the unpinning stress on solute spacing. Our simulations also suggest an effect of carbon spacing on the kink-pair activation entropy. This work provides elementary processes and parameters that will be useful for larger-scale models and, in particular, kinetic Monte Carlo simulations. Materials science ; Molecular dynamics ; Nucleation ; Dislocation ; Atomic units ; Carbon fibers ; Work (physics) ; Kinetic Monte Carlo ; Yield (engineering) ; Transition state theory ; Enthalpy ; Thermodynamics ; Monte Carlo method ; Chemistry ; Computational chemistry ; Physics ; Kinetics ; Metallurgy ; Classical mechanics Microstructure and mechanical properties ; Microstructure and Mechanical Properties of Steels
Authors: Etienne Palos | Eleftherios Lambros | Steven Swee | Jie Hu | Saswata Dasgupta | Francesco Paesani
Source: ChemRxiv (preprint, 2022-01-17)
Field: Materials Science — Materials Chemistry

Assessing the Interplay Between Functional-Driven and Density-Driven Errors in DFT Models of Water We investigate the interplay between functional-driven and density-driven errors in different density functional theory (DFT) approximations, and the implications of these errors for simulations of water with DFT-based data-driven many-body potentials. Specifically, we quantify density-driven errors in two widely used dispersion-corrected functionals derived within the generalized gradient approximation (GGA), namely BLYP-D3 and revPBE-D3, and two modern meta-GGA functionals, namely SCAN and B97M-rV. The effects of functional-driven and density-driven errors on the interaction energies are assessed for the water clusters of the BEGDB dataset. Further insight into the nature of functional-driven errors is gained from applying the absolutely localized molecular orbital energy decomposition analysis (ALMO- EDA) to the interaction energies, which demonstrates that functional-driven errors are strongly correlated with the nature of the interactions. We discuss cases where density-corrected DFT (DC-DFT) models display higher accuracy than the original DFT models, and cases where reducing the density-driven errors leads to larger deviations from the reference energies due to the presence of large functional-driven errors. Finally, molecular dynamics simulations are performed with data-driven many-body potentials derived from DFT and DC-DFT data to determine the effect that minimizing density-driven errors has on the description of liquid water. Besides rationalizing the performance of widely used DFT models of water, we believe that our findings unveil fundamental relations between the shortcomings of some common DFT approximations and the requirements for accurate descriptions of molecular interactions, which will aid the development of a consistent, DFT-based framework for data-driven simulations of condensed-phase systems. Density functional theory ; Statistical physics ; Orbital-free density functional theory ; Hybrid functional ; Physics ; Dispersion (optics) ; Computational physics ; Computer science ; Quantum mechanics Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Quantum, superfluid, helium dynamics
Authors: Rong Zhao | Bin Zhou | Jianyong Zhang | Ruixue Cheng | Qi Liu | Minglu Dai | Bubin Wang | Yihong Wang
Source: Case Studies in Thermal Engineering (article, 2022-12-20)
Field: Chemistry — Spectroscopy

A stability and spatial-resolution enhanced laser absorption spectroscopy tomographic sensor for complex combustion flame diagnosis A novel stable laser absorption spectroscopy (LAS) tomographic sensor with enhanced stability and spatial resolution is developed and applied to complex combustion flame diagnosis. The sensor reduces the need for laser collimation and alignment even in extremely harsh environments and improves the stability of the received laser signal. Furthermore, a new miniaturized laser emission module was designed to achieve multi-degree of freedom adjustment. The full optical paths can be sampled by 8 receivers, with such arrangement, the equipment cost can be greatly reduced, at the same time, the spatial resolution is improved. In fact, 100 emitted laser paths are realized in a limited space of 200mm×200 mm with the highest spatial resolution of 1.67mm×1.67 mm. The stability and penetrating spatial resolution of the LAS tomographic sensor were validated by both simulation and field experiments on the afterburner flames. Tests under two representative experiment states, i.e., the main combustion and the afterburner operation states, were conducted. Results show that the error under the main combustion state was about 4.32% and, 5.38% at the afterburner operation state. It has been proven that this proposed sensor can provide better tomographic measurements for combustion diagnosis, as an effective tool for improving performances of afterburners. Combustion ; Laser ; Image resolution ; Spectroscopy ; Tomographic reconstruction ; Optics ; Materials science ; Absorption (acoustics) ; Resolution (logic) ; Tunable diode laser absorption spectroscopy ; Collimated light ; SIGNAL (programming language) ; Tomography ; Environmental science ; Computer science ; Physics ; Tunable laser ; Chemistry ; Artificial intelligence Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Atmospheric Ozone and Climate
Authors: Anasua Chatterjee | Fabio Ansaloni | Torbjørn Rasmussen | Bertram Brovang | Federico Fedele | Heorhii Bohuslavskyi | Oswin Krause | Ferdinand Kuemmeth
Source: Physical Review Applied (article, 2022-12-14)
Field: Materials Science — Materials Chemistry

Autonomous Estimation of High-Dimensional Coulomb Diamonds from Sparse Measurements In spin-based quantum processors, each quantum dot of a qubit is populated by exactly one electron, which requires careful tuning of each gate voltage such that it lies inside the charge-stability region (the ``Coulomb diamond'') associated with the dot array. However, mapping the boundary of a multidimensional Coulomb diamond by traditional dense raster scanning would take years, so the authors develop a sparse acquisition technique that autonomously learns Coulomb-diamond boundaries from a small number of measurements. Here we have hardware-triggered line searches in the gate-voltage space of a silicon quadruple dot, with smart search directions proposed by an active-learning algorithm. Coulomb ; Estimation ; Materials science ; Physics ; Economics ; Quantum mechanics ; Electron Electronic and Structural Properties of Oxides ; Diamond and Carbon-based Materials Research ; Advanced materials and composites
Authors: Lenka Rouhová | Hana Sehadová | Lucie Pauchová | Miluše Hradilová | Martina Žurovcová | Michal Šerý | Michal Rindoš | Michal Žurovec
Source: Frontiers in Molecular Biosciences (article, 2022-08-11)
Field: Materials Science — Biomaterials

Using the multi-omics approach to reveal the silk composition in Plectrocnemia conspersa Similar to Lepidoptera, the larvae of Trichoptera are also capable of producing silk. <i>Plectrocnemia conspersa</i>, a predatory species belonging to the suborder Annulipalpia, builds massive silken retreats with preycapturing nets. In this study, we describe the silk glands of <i>P. conspersa</i> and use the multi-omics methods to obtain a complete picture of the fiber composition. A combination of silk gland-specific transcriptome and proteomic analyses of the spun-out fibers yielded 27 significant candidates whose full-length sequences and gene structures were retrieved from the publicly available genome database. About one-third of the candidates were completely novel proteins for which there are no described homologs, including a group of five pseudofibroins, proteins with a composition similar to fibroin heavy chain. The rest were homologs of lepidopteran silk proteins, although some had a larger number of paralogs. On the other hand, <i>P. conspersa</i> fibers lacked some proteins that are regular components in moth silk. In summary, the multi-omics approach provides an opportunity to compare the overall composition of silk with other insect species. A sufficient number of such studies will make it possible to distinguish between the basic components of all silks and the proteins that represent the adaptation of the fibers for specific purposes or environments. Fibroin ; SILK ; Biology ; Composition (language) ; Computational biology ; Lepidoptera genitalia ; Evolutionary biology ; Ecology ; Computer science Silk-based biomaterials and applications ; Insect and Arachnid Ecology and Behavior ; Silkworms and Sericulture Research
Authors: Lorenzo Marchi | I. V. Krylov | Robert T. Roginski | Barry M. Wise | Francesca Di Donato | Sonia Nieto‐Ortega | José F. Q. Pereira | Rasmus Bro
Source: Journal of Chemometrics (article, 2022-11-03)
Field: Chemistry — Analytical Chemistry

Automatic hierarchical model builder Abstract When building classification models of complex systems with many classes, the traditional chemometric approaches such as discriminant analysis or soft independent modeling of class analogy often fail. Some people resort to advanced deep neural network, but this is only an option if there is access to very many samples. Another alternative often used is to build hierarchical models where subclasses are sort of peeled off one or a few at a time. Such approaches often outperform classical classification as well as deep neural network on small multi‐class problems. The downside though is that it is very cumbersome to build such hierarchies of models. It requires substantial work of a skilled person. In this paper, we develop a fully automated approach for building hierarchical models and test the performance on a number of classification problems. Computer science Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Water Quality Monitoring and Analysis
Authors: Henrik M. Hammarén | Eva‐Maria Geissen | Clément M. Potel | Martin Beck | Mikhail M. Savitski
Source: Nature Communications (article, 2022-12-02)
Field: Chemistry — Spectroscopy

Protein-Peptide Turnover Profiling reveals the order of PTM addition and removal during protein maturation Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods relying on pulsed metabolic labeling are popular to quantify turnover rates on a proteome-wide scale. Such data have traditionally been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a protein's lifetime-a fundamentally different metric. This is due to interconversion of the measured proteoform species. Using this framework, we identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results thus allow tying PTMs to the age of the modified proteins. Protein turnover ; Chemistry ; Phosphorylation ; Stable isotope labeling by amino acids in cell culture ; Proteome ; Isotopic labeling ; Posttranslational modification ; Peptide ; Context (archaeology) ; Protein degradation ; Biochemistry ; Isobaric labeling ; Protein phosphorylation ; Proteomics ; Protein biosynthesis ; Quantitative proteomics ; Biology ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Enzyme Structure and Function