jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ting An | Chongshan Yang | Jian Zhang | Zheli Wang | Yaoyao Fan | Shuxiang Fan | Wenqian Huang | Dandan Qi | Xi Tian | Changbo Yuan | Chunwang Dong
Source: Fermentation (article, 2023-10-07)
Field: Chemistry — Analytical Chemistry

Evaluation of the Black Tea Taste Quality during Fermentation Process Using Image and Spectral Fusion Features The rapid and intelligent evaluation of black tea taste quality during the fermentation process is an unsolved problem because of the complexity and hysteretic of the current taste evaluation method. Common infrared spectroscopy and machine vision technologies can rapidly evaluate the taste quality of black tea, but they can not obtain comprehensive sample information. To obtain comprehensive sample information and achieve the rapid evaluation of the taste quality of black tea, the fusion data from hyperspectral images of fermentation samples were applied to predict the taste quality. The successive projection algorithm (SPA) and ant colony optimization (ACO) were used to select effective bands for spectral data. Subsequently, the color images were synthesized using three carefully selected effective bands obtained through the SPA and ACO. The 18 image features were extracted from each synthesized color image and fused with spectral effective bands. The fusion data and three different algorithms, such as partial least squares regression (PLSR), support vector machine regression (SVR), and extreme learning machine (ELM), were employed to establish the regression model for taste quality. Specifically, the fusion-SPA-PLSR model exhibited the best performance. This study provides a novel method for the intelligent evaluation of taste quality during black tea fermentation and lays a theoretical foundation for the intelligent processing and control of black tea. Artificial intelligence ; Partial least squares regression ; Extreme learning machine ; Support vector machine ; Black tea ; Hyperspectral imaging ; Taste ; Computer science ; Ant colony optimization algorithms ; Pattern recognition (psychology) ; Quality (philosophy) ; Machine learning ; Mathematics ; Computer vision ; Artificial neural network ; Food science ; Chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Tea Polyphenols and Effects
Authors: Emmanouil Semidalas | Jan M. L. Martin
Source: Molecular Physics (article, 2023-09-29)
Field: Chemistry — Spectroscopy

Can G4-like composite <i>Ab Initio</i> methods accurately predict vibrational harmonic frequencies? Minimally empirical G4-like composite wavefunction theories [E. Semidalas and J. M. L. Martin, \textit{J. Chem. Theory Comput.} {\bf 16}, 4238-4255 and 7507-7524 (2020)] trained against the large and chemically diverse GMTKN55 benchmark suite have demonstrated both accuracy and cost-effectiveness in predicting thermochemistry, barrier heights, and noncovalent interaction energies. Here, we assess the spectroscopic accuracy of top-performing methods: G4-\textit{n}, cc-G4-\textit{n}, and G4-\textit{n}-F12, and validate them against explicitly correlated coupled cluster CCSD(T*)(F12*) harmonic vibrational frequencies and experimental data from the HFREQ2014 dataset, of small first- and second-row polyatomics. G4-T is three times more accurate than plain CCSD(T)/def2-TZVP, while G4-T$_{\rm ano}$ is two times superior to CCSD(T)/ano-pVTZ. Combining CCSD(T)/ano-pVTZ with MP2-F12 in a parameter-free composite scheme results to a root-mean-square deviation of ~5 cm$^{-1}$ relative to experiment, comparable to CCSD(T) at the complete basis set limit. Application to the harmonic frequencies of benzene reveals a significant advantage of composites with ANO basis sets -- MP2/ano-pV\textit{m}Z and [CCSD(T)-MP2]/ano-pVTZ (\textit{m} = Q or 5) -- over similar protocols based on CCSD(T)/def2-TZVP. Overall, G4-type composite energy schemes, particularly when combined with ANO basis sets in CCSD(T), are accurate and comparatively inexpensive tools for computational vibrational spectroscopy. Ab initio ; Harmonic ; Composite number ; Molecular physics ; Computational chemistry ; Physics ; Chemistry ; Atomic physics ; Materials science ; Quantum mechanics ; Composite material Molecular Spectroscopy and Structure ; Advanced Thermodynamic Systems and Engines ; Quantum, superfluid, helium dynamics
Authors: Ajeet Kaushik
Source: Neural Regeneration Research (article, 2023-10-02)
Field: Chemistry — Electrochemistry

Smart electrochemical sensing of amyloid-beta to manage total Alzheimer’s diseases NanoBioTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, FL, USA School of Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India *Correspondence to: Ajeet Kaushik, PhD, [email protected]. This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 4.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Library science ; Work (physics) ; Computer science ; Engineering ; Gerontology ; Medicine ; Mechanical engineering Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; EEG and Brain-Computer Interfaces
Authors: Patrick Taylor | G. J. Conduit
Source: Computational Materials Science (article, 2023-05-23)
Field: Materials Science — Materials Chemistry

Machine learning superalloy microchemistry and creep strength from physical descriptors We propose an element-agnostic set of descriptors to model superalloy properties with Gaussian process regression. Furthermore, we develop a correction method to deliver the best and most physical predictions for microchemistry in multi-phase alloys. The model’s performance in predictions is confirmed for superalloy microchemistry, microstructure, and strength properties. When including new, unseen elements in the test data, the models still give good predictions; such extrapolations into new chemical-space would be impossible with component-based descriptors. Superalloy ; Microchemistry ; Creep ; Microstructure ; Materials science ; Component (thermodynamics) ; Computer science ; Biological system ; Thermodynamics ; Metallurgy ; Chemistry ; Physics ; Chromatography ; Biology Machine Learning in Materials Science ; High Temperature Alloys and Creep ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Fuga Kumagai | Kazuhiro Gotoh | S. Miyamoto | Shinya Kato | Kentaro Kutsukake | Noritaka Usami | Yasuyoshi Kurokawa
Source: Discover Nano (article, 2023-03-13)
Field: Materials Science — Materials Chemistry

Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells Silicon quantum dot multilayer (Si-QDML) is a promising material for a light absorber of all silicon tandem solar cells due to tunable bandgap energy in a wide range depending on the silicon quantum dot (Si-QD) size, which is possible to overcome the Shockley-Queisser limit. Since solar cell performance is degenerated by carrier recombination through dangling bonds (DBs) in Si-QDML, hydrogen termination of DBs is crucial. Hydrogen plasma treatment (HPT) is one of the methods to introduce hydrogen into Si-QDML. However, HPT has a large number of process parameters. In this study, we employed Bayesian optimization (BO) for the efficient survey of HPT process parameters. Photosensitivity (PS) was adopted as the indicator to be maximized in BO. PS (σ<sub>p</sub>/σ<sub>d</sub>) was calculated as the ratio of photoconductivity (σ<sub>p</sub>) and dark conductivity (σ<sub>d</sub>) of Si-QDML, which allowed the evaluation of important electrical characteristics in solar cells easily without fabricating process-intensive devices. 40-period layers for Si-QDML were prepared by plasma-enhanced chemical vapor deposition method and post-annealing onto quartz substrates. Ten samples were prepared by HPT under random conditions as initial data for BO. By repeating calculations and experiments, the PS was successfully improved from 22.7 to 347.2 with a small number of experiments. In addition, Si-QD solar cells were fabricated with optimized HPT process parameters; open-circuit voltage (V<sub>OC</sub>) and fill factor (FF) values of 689 mV and 0.67, respectively, were achieved. These values are the highest for this type of device, which were achieved through an unprecedented attempt to combine HPT and BO. These results prove that BO is effective in accelerating the optimization of practical process parameters in a multidimensional parameter space, even for novel indicators such as PS. Quantum dot ; Bayesian optimization ; Plasma ; Bayesian probability ; Silicon ; Hydrogen ; Materials science ; Optoelectronics ; Computer science ; Physics ; Quantum mechanics ; Artificial intelligence Silicon Nanostructures and Photoluminescence ; Nanowire Synthesis and Applications ; Silicon and Solar Cell Technologies
Authors: Bienfait Kabuyaya Isamura | Paul L. A. Popelier
Source: AIP Advances (article, 2023-09-01)
Field: Materials Science — Materials Chemistry

Toward a simple yet efficient cost function for the optimization of Gaussian process regression model hyperparameters FFLUX is a novel machine-learnt force field using pre-trained Gaussian process regression (GPR) models to predict energies and multipole moments of quantum atoms in molecular dynamic simulations. At the heart of FFLUX lies the program FEREBUS, a Fortran90 and OpenMP-parallelized regression engine, which trains and validates GPR models of chemical accuracy. Training a GPR model is about finding an optimal set of model hyperparameters (θ). This time-consuming task is usually accomplished by maximizing the marginal/concentrated log-likelihood function LLy|x,θ, known as the type-II maximum likelihood approach. Unfortunately, this widespread approach can suffer from the propagation of numerical errors, especially in the noise-free regime, where the expected correlation betweenLLy|x,θ̂ [maximized value of theLLy|x,θfunction] and the models’ performance may no longer be valid. In this scenario, the LLy|x,θ function is no longer a reliable guide for model selection. While one could still rely on a pre-conditioner to improve the condition number of the covariance matrix, this choice is never unique and often comes with increased computational cost. Therefore, we have equipped FEREBUS with an alternatively simple, intuitive, viable, and less error-prone protocol called “iterative hold-out cross-validation” for the optimization of θ values. This protocol involves (1) a stratified random sampling of both training and validation sets, followed by (2) an iterative minimization of the predictive RMSE(θ) of intermediary models over a sufficiently large validation set. Its greatest asset is the assurance that the optimization process keeps reducing the generalization error of intermediary GPR models on unseen datasets, something that maximizing LLy|x,θ does not guarantee. Hyperparameter ; Kriging ; Computer science ; Gaussian process ; Algorithm ; Mathematical optimization ; Machine learning ; Gaussian ; Mathematics Machine Learning in Materials Science ; Mass Spectrometry Techniques and Applications ; Computational Drug Discovery Methods
Authors: Diego Alexander Gonzalez‐Casamachin | Qin Tian | Weimin Huang | Srinivas Rangarajan | Lihua Zhang | Jonas Baltrušaitis
Source: ACS Sustainable Chemistry & Engineering (article, 2023-12-22)
Field: Materials Science — Materials Chemistry

Actively Learned Optimal Sustainable Operation of Plasma-Catalyzed Methane Bireforming on La<sub>0.7</sub>Ce<sub>0.3</sub>NiO<sub>3</sub> Perovskite Catalyst Plasma-catalytic bireforming of methane was studied and actively optimized using a La<sub>0.7</sub>Ce<sub>0.3</sub>NiO<sub>3</sub> perovskite catalyst via experimentation in tandem with response surface modeling. Plasma power, inlet flow rate, temperature, CO<sub>2</sub>/CH<sub>4</sub> ratio, and steam concentration were tuned to maximize a variety of process- and sustainability-based metrics. Analysis of the optimal conditions (with respect to different metrics) with and without the catalyst reveals that dry reforming is driven largely via noncatalytic reactions, while steam reforming and water gas shift reactions require the catalyst. The experimental outcome demonstrated that under optimum reaction conditions using the La<sub>0.7</sub>Ce<sub>0.3</sub>NiO<sub>3</sub> catalyst it is possible to minimize global warming potential (GWP), in terms of inferred CO<sub>2</sub> footprint normalized to hydrogen throughput, resulting in maximizing hydrogen yield through steam reforming (and water gas shift reactions) at an SEI of ≈12 eV/molecule. Furthermore, the highest CH<sub>4</sub> conversion reached was 87% while the catalyst showed good activity stability in DBD plasma experiments.The actively learned iterative optimization procedure developed in this work allows for a direct juxtaposition of thermal (heat needed to make steam and heat the plasma reactor) and electrical (power requirement for plasma generation) carbon footprints in a highly nonlinear multivariate process. Furthermore, the corresponding GWP was calculated using a conventional electricity mix, wind electricity, and solar electricity, allowing a direct sustainability assessment in catalyst-assisted plasma conversion of carbonaceous feedstock to H<sub>2</sub> and CO. Catalysis ; Methane ; Perovskite (structure) ; Non-blocking I/O ; Materials science ; Plasma ; Inorganic chemistry ; Chemical engineering ; Chemistry ; Physics ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Oxidation Reactions
Authors: Leon A. Smook | Sissi de Beer
Source: ChemPhysChem (article, 2023-02-22)
Field: Materials Science — Surfaces, Coatings and Films

Electrostatic Fields Stimulate Absorption of Small Neutral Molecules in Gradient Polyelectrolyte Brushes Molecules can partition from a solution into a polymer coating, leading to a local enrichment. If one can control this enrichment via external stimuli, one can implement such coatings in novel separation technologies. Unfortunately, these coatings are often resource intensive as they require stimuli in the form changes of bulk solvent conditions such as acidity, temperature, or ionic strength. Electrically driven separation technology may provide an appealing alternative, as this will allow local, surface-bound stimuli instead of system-wide bulk stimuli to induce responsiveness. Therefore, we investigate via coarse grained molecular dynamics simulations the possibility of using coatings with charged moieties, specifically gradient polyelectrolyte brushes, to control the enrichment of the neutral target molecules near the surface with applied electric fields. We find that targets which interact more strongly with the brush show both more absorption and a larger modulation by electric fields. For the strongest interactions evaluated in this work, we obtained absorption changes of over 300 % between the collapsed and extended state of the coating. Polyelectrolyte ; Chemical physics ; Electric field ; Absorption (acoustics) ; Coating ; Molecule ; Polymer ; Brush ; Materials science ; Electrostatics ; Nanotechnology ; Solvent ; Chemistry ; Chemical engineering ; Organic chemistry ; Physical chemistry ; Composite material ; Physics Polymer Surface Interaction Studies ; Electrostatics and Colloid Interactions ; Microfluidic and Bio-sensing Technologies
Authors: Ekaterina S. Shchegravina | Sofia D. Usova | Dmitry S. Baev | Evgenii S. Mozhaitsev | Д. Н. Щербаков | S. V. Belenkaya | Ekaterina A. Volosnikova | V. Yu. Chirkova | Е. А. Шарлаева | E. V. Svirshchevskaya | I. P. Fonareva | Alsu R. Sitdikova | Нариман Ф. Салахутдинов | Оlga I. Yarovaya | Alexey Yu. Fedorov
Source: Russian Chemical Bulletin (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Synthesis of conjugates of (aR,7S)-colchicine with monoterpenoids and investigation of their biological activity Chemistry ; Colchicine ; Protease ; Conjugate ; Docking (animal) ; Alkaloid ; Cytotoxic T cell ; Stereochemistry ; Combinatorial chemistry ; Bicyclic molecule ; Biochemistry ; Enzyme ; In vitro Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Biological Evaluation
Authors: Julie Hyde | James S. Wright | Andi Xie
Source: Chemistry Education Research and Practice (article, 2023-10-16)
Field: Chemistry — Physical and Theoretical Chemistry

Progression from Chinese High School onto a TransNational Chinese-UK University joint BSc degree in chemistry; an international study focussing on laboratory practical skills An investigation was carried out into laboratory practical skills development and students’ specific challenges in transition from laboratory chemistry at Chinese High School (HS) to a fully English style university laboratory course. To the best of our knowledge this is the first study of its type investigating practical laboratory skills for a TransNational Education (TNE) Chemistry BSc (3 + 1) degree programme between the United Kingdom (UK) and the People's Republic of China (PRC). Internationalization of such courses have become popular in recent years. The two universities in this study are Nanjing Tech University (NJTech) and the University of Sheffield (UoS). Our study is exploratory with the aim to determine the level of practical laboratory skills the NJTech students gained from High School and the challenges they encountered as they joined a UK degree laboratory programme delivered in English. For this international study, a mixed-methods approach was followed using qualitative inductive and deductive methodologies. Using open-ended questions it was found that particular challenges in the transition were around the lack of prior laboratory experience and the development of many new skills, laboratory notebook documentation, laboratory safety, and studying laboratory chemistry in a second language. Students welcomed these challenges and felt they were developing into professional chemists. Specific recommendations are made for international TNE degrees with laboratory programmes, particularly for those students who progress from Chinese High School through the Chinese GaoKao system into a western university chemistry laboratory programme. The scaffolded/structured curriculum design allowed for total and successful integration of the NJTech with the Sheffield home students during the final year of their BSc in Chemistry. After graduation, having gained high class degrees and becoming fluent in English many of the students progressed into Industry, and onto Masters or PhD programmes in the UK and throughout the world, suggesting internationalisation of students on our TNE programme was successful. Curriculum ; Internationalization ; Documentation ; Medical education ; China ; Chemistry ; Mathematics education ; Pedagogy ; Engineering ; Psychology ; Political science ; Medicine ; Computer science Various Chemistry Research Topics ; Educational Strategies and Epistemologies ; Evaluation of Teaching Practices
Authors: Urban Senica | Sebastian Gloor | Paolo Micheletti | David Stark | Mattias Beck | Jérôme Faist | Giacomo Scalari
Source: APL Photonics (article, 2023-09-01)
Field: Chemistry — Spectroscopy

Broadband surface-emitting THz laser frequency combs with inverse-designed integrated reflectors THz quantum cascade lasers (QCLs) based on double metal waveguides feature broadband and high-temperature devices for their use in spectroscopy and sensing. However, their extreme field confinement produces poor output coupling efficiencies and divergent far-fields. Here, we present a planarized THz QCL with an inverse-designed end facet reflector coupled to a surface-emitting patch array antenna. All the components have been optimized for octave-spanning spectral bandwidths between 2 and 4 THz and monolithically integrated on the same photonic chip. We demonstrate this experimentally on broadband THz QCL frequency combs, with measured devices showing a seven-fold improvement in slope efficiency compared to devices with a cleaved facet. They feature a peak power of up to 13.5 mW with surface emission into a narrow beam with a divergence of (17.0° × 18.5°), while broadband fundamental and harmonic comb states spanning up to 800 GHz are observed. Broadband ; Terahertz radiation ; Optoelectronics ; Optics ; Materials science ; Laser ; Reflector (photography) ; Quantum cascade laser ; Frequency comb ; Physics Spectroscopy and Laser Applications ; Photonic and Optical Devices ; Advanced Fiber Laser Technologies
Authors: Jianliang Jiang | Junxue Zhai | Yanqing Chen | Dongqi Zhao | Yakai Feng
Source: International Journal of Smart and Nano Materials (article, 2023-09-20)
Field: Materials Science — Polymers and Plastics

A novel reprocessable chloroprene rubber based on dynamic disulfide metathesis For sustainable application of chloroprene rubber (CR), a new technology is developed by the vulcanization of CR using 2,2'dithiodipyridine (DPD) as a cross-linking agent with the reprocessing performance owing to disulfide metathesis.When DPD was incorporated into CR vulcanization, the Menschutkin reaction between allyl chloride group and pyridine group occurred with a maximum exothermic peak at 184C.The number of effective cross-linking bond at 0.5 phr DPD vulcanizate was higher than that at high DPD content.This vulcanizate showed high tensile strength (11.12 MPa) and elongation at break (1253 120%) owing to the exchangeable disulfide bond in the system.Under the catalysis of triphenylphosphine, the metathesis of disulfide compound was improved obviously, which endowed CR/DPD vulcanizates with good recyclability performance.Disulfide cross-linkage maintains its stability at low temperature, thus ensuring the mechanical stability of CR/ DPD vulcanizate under the ambient conditions.Vulcanization and reprocessing of CR/DPD vulcanizate can be conducted with common industrial rubber processing equipment.Such reprocessable chloroprene rubber could have potential application in CR industry, also serve to significantly improve environmental sustainability. Chloroprene ; Vulcanization ; Natural rubber ; Disulfide bond ; Materials science ; Polymer chemistry ; Metathesis ; Chemistry ; Chemical engineering ; Composite material ; Polymerization ; Polymer Polymer composites and self-healing ; Synthetic Organic Chemistry Methods ; Synthesis and properties of polymers