jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Barbaro Zulueta | Sonia Tulyani | Phillip R. Westmoreland | Michael J. Frisch | E. James Petersson | George A. Petersson | John A. Keith
Source: ChemRxiv (preprint, 2022-04-07)
Field: Materials Science — Materials Chemistry

A Bond-Energy/Bond-Order and Populations Relationship We report an analytical Bond Energy from Bond Orders and Populations (BEBOP) model that provides intramolecular bond energy decompositions for chemical insight into the thermochemistry of molecules. The implementation reported here employs a minimum basis set Mulliken population analysis on well-conditioned Hartree-Fock orbitals to decompose total electronic energies into physically interpretable contributions. The model's parameterization scheme is based on atom-specific parameters for hybridization and atom pair-specific parameters for short-range repulsion and extended Huckel-type bond energy term fitted to reproduce CBS-QB3 thermochemistry data. The current implementation is suitable for molecules involving H, Li, Be, B, C, N, O, and F atoms, and it can be used to analyze intramolecular bond energies of molecular structures at optimized stationary points found from other computational methods. This first-generation model brings the computational cost of a Hartree-Fock calculation using a large triple-zeta basis set, and its atomization energies are comparable to those from widely used hybrid Kohn-Sham density functional theory (DFT, as benchmarked to 109 species from the G2/97 test set and an additional 83 reference species). This model should be useful for the community by interpreting overall \textit{ab initio} molecular energies in terms of physically insightful bond energy contributions, e.g. bond dissociation energies, resonance energies, molecular strain energies, and qualitative energetic contributions to the activation barrier in chemical reaction mechanisms. This work reports a critical benchmarking of this method as well as discussions of its strengths and weaknesses compared to hybrid DFT (i.e., B3LYP, M062X, PBE0, and APF methods), and other cost-effective approximate Hamiltonian semi-empirical quantum methods (i.e., AM1, PM6, PM7, and DFTB3). Intramolecular force ; Thermochemistry ; Chemistry ; Bond order ; Basis set ; Bond length ; Bond-dissociation energy ; Bond energy ; Computational chemistry ; Density functional theory ; Population ; Atomic physics ; Molecule ; Physics ; Dissociation (chemistry) ; Physical chemistry ; Stereochemistry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Crystallography and molecular interactions
Authors: Aqib Fawwaz Mohd Amidon | Noratikah Zawani Mahabob | Siti Mariatul Hazwa Mohd Huzir | Zakiah Mohd Yusoff | Nurlaila Ismail | Mohd Nasir Taib
Source: Journal of Electrical & Electronic Systems Research (article, 2022-11-01)
Field: Chemistry — Organic Chemistry

MSVM Modelling on Agarwood Oil Various Qualities Classification The aroma of agarwood oil is frequently connected with wealth and prestige. Because of its aroma, the oil is in great demand all over the world. Unfortunately, no standard method for classifying the quality of agarwood oil has been proposed to the world. This is essential to preserving the quality of agarwood oil and preventing fraudulent quality in the market. With that, for agarwood oil grading, a quality classification model must be developed. As part of the ongoing study for this standard's model development, an intelligent algorithm function has been implemented to ensure the model's capability is completely unquestionable. The intelligent algorithm used was Support Vector Machine (SVM) as main structure model. Then, the model has been added with Multiclass Classifier function by using One Verses One (OVO) strategy. The previous researcher's data was used in the analysis process, which included four classes of agarwood oil quality samples: low, medium low, medium high, and high quality. The result was a quality categorization of low, medium low, medium high or high quality, whereas the input was chemical abundances (percentages). The combination of both functions produced extremely good results for agarwood oil quality classification. The simulation platform was MATLAB software version r2020a, which was used for the desk study. The findings of this study will undoubtedly be useful in future agarwood oil research, particularly in the grade categorization section. Agarwood ; Mathematics ; Computer science ; Medicine Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection ; Image Processing and 3D Reconstruction
Authors: Stephen Chidera Nwafor | Sunday Ayoola Oke | Chris Abiodun Ayanladun
Source: Jurnal Ilmiah Teknik Industri (article, 2022-04-30)
Field: Materials Science — General Materials Science

FACTOR ANALYSIS APPROACH-TAGUCHI-PARETO METHOD TO CASTING A356 ALLOY COMPOSITE FOR LIGHTWEIGHT WHEEL RIM COVER OF VEHICLES The aspect of reinforcing re-usable A356 alloys with organic matters is a principal, success yet expanding in scope regarding new products development. Despite, the use of Taguchi-Pareto method has potentials for improvement. The purpose of this article is to examine the factor analysis- Taguchi-Pareto method at which identification of the key factors could be achieved while concurrently optimizing the factors. The point of integration is at the variance determination of the unrotated factor loadings and communality. The synergy between factor analysis and Taguchi-Pareto method provides practical assistance to foundry engineers to concurrently select key factors while optimising them. The factors were noted to be effective and responsive to the proposed method. The delta values are 0, 0.84 and 0 for LC1, WC1 and HC1, respectively while the ranks are WC1 as first while the second position is shared between LC1 and HC1. The optimal parametric settings are LC11 WC11 HC11, LC11 WC11 HC12, LC12 WC11 HC11 or LC12 WC11 HC12­. One of the optimal parametric settings is 0.280m of LC1 with 1.788kg of WC1 and 0.036m of HC1. The finding provides novel steps to the concurrent factor identification and optimisation in the choice of optimal parametric setting for the process. It is the first step towards sustainable foundry practice. Taguchi methods ; USable ; Foundry ; Parametric statistics ; Pareto principle ; Pareto analysis ; Orthogonal array ; Engineering ; Identification (biology) ; Manufacturing engineering ; Computer science ; Operations research ; Mechanical engineering ; Operations management ; Mathematics ; Statistics ; Machine learning Material Properties and Applications ; Manufacturing Process and Optimization ; Materials Engineering and Processing
Authors: Stephania Kossman | Arthur Hamieh | Freddy Ponchel | Denis Rémiens | Maxence Bigerelle
Source: Thin Solid Films (article, 2022-08-28)
Field: Materials Science — Materials Chemistry

Electromechanical properties of sodium bismuth titanate thin films Materials science ; Amorphous solid ; Annealing (glass) ; Composite material ; Crystallization ; Thin film ; Bismuth ; Bismuth titanate ; Piezoelectricity ; Lead zirconate titanate ; Piezoelectric coefficient ; Permittivity ; Elastic modulus ; Dielectric ; Relative permittivity ; Ferroelectricity ; Nanotechnology ; Chemical engineering ; Optoelectronics ; Metallurgy ; Crystallography Ferroelectric and Piezoelectric Materials ; Acoustic Wave Resonator Technologies ; Adhesion, Friction, and Surface Interactions
Authors: Ghaniya Rashid | Michael Kisangiri | Ernest R. Mbega
Source: International Journal of Advances in Scientific Research and Engineering (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Development of Optical-based and Imaging Technology Detection, Diagnosis and Prevention of Aflatoxin Contamination on Maize Crop Aflatoxins are mycotoxins produced naturally by some mold strains, such as Aspergillus flavus and Aspergillus parasiticus. Weather factors, notably moisture levels of more than 18 percent and temperatures of more than 32C, influence the proliferation of aflatoxin-producing fungus. Aflatoxin pollution is a danger to human and animal healthiness. As a result, there is a pressing need to control aflatoxin, particularly in crops like maize, in countries where aflatoxin susceptibility is high, such as Tanzania. Several aflatoxin management solutions are being developed, however, for them to be effective, accurate identification of fungus or aflatoxins contamination on grain surfaces is required. While the majority of the known solutions include growing and identifying the fungus responsible or using Higher-Performance Liquid Chromatography (HPCL), Thin Layer Chromatography (TLC), and Enzyme-Linked Immunosorbent Assays (ELISA) to detect aflatoxin early, this review underlines the prospect of employing computer-based techniques to detect aflatoxin early. Because of these options, producers will be able to quickly detect aflatoxin contamination and, as a result, make informed decisions about how to prevent and/or reduce aflatoxin contamination, hence enhancing maize quality and storability. Contamination ; Aflatoxin ; Crop ; Environmental science ; Agronomy ; Agricultural engineering ; Biotechnology ; Biology ; Engineering ; Ecology Spectroscopy and Chemometric Analyses
Authors: F. Angelini | Simone Santoro | F. Colao
Source: Chemosensors (article, 2022-07-27)
Field: Chemistry — Analytical Chemistry

Chemical Identification from Raman Peak Classification Using Fuzzy Logic and Monte Carlo Simulation In spite of the wide use of Raman spectroscopy for chemical analysis in different fields, not any automated identification of Raman spectra is universally adopted. However, the interest in this field is witnessed by the large number of papers published in the last decades. The problem of Raman-spectra classification becomes particularly challenging when low irradiation is requested, either for safety reasons or to avoid target photodegradation. This often leads to spectra characterized by a low signal-to-noise ratio, where methods based on correlation usually fail. For this reason, a method based on peak identification through FMFs is presented, discussed and validated over a large set of samples. In particular, a Monte Carlo simulation has been employed to determine the best parameters of the fuzzy membership functions based on the analysis of performances of the classification procedure. The ROC curves have been analyzed, and AUC and best accuracy are employed as key parameters to evaluate the classification performances on different amounts of ammonium nitrate (from 300 to 1500 μg) and different laser exposure levels (from 3.1 to 250 mJ/cm2). Raman spectroscopy ; Monte Carlo method ; Identification (biology) ; Fuzzy logic ; Artificial intelligence ; Computer science ; Noise (video) ; Pattern recognition (psychology) ; Mathematics ; Statistics ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Chuang Zhang | Samuel Huberman | Xinliang Song | Jin Zhao | Songze Chen | Lei Wu
Source: arXiv (Cornell University) (preprint, 2022-12-12)
Field: Materials Science — Materials Chemistry

Acceleration strategy of source iteration method for the stationary phonon Boltzmann transport equation Mesoscopic numerical simulation has become an important tool in thermal management and energy harvesting at the micro/nano scale, where the Fourier's law failed. However, it is not easy to efficiently solve the phonon Boltzmann transport equation (BTE) from ballistic to diffusive limit. In order to accelerate convergence, an implicit synthetic iterative scheme is developed for the stationary phonon BTE, in which a macroscopic moment equation is invoked and solved iteratively coupled with the typical source iteration of the kinetic equation. Different from previous numerical interpolation, the phonon BTE is solved again at the cell interface along the group velocity direction within a certain length when reconstructing the interfacial phonon distribution function. Fourier stability analysis shows that the present method could converge faster than the source iteration method in the (near) diffusive regime. Numerical results prove that the present scheme can capture the ballistic-diffusive effects correctly and efficiently. The present acceleration framework could be a powerful tool for simulating practical thermal engineering problems in the future. Boltzmann equation ; Phonon ; Convection–diffusion equation ; Acceleration ; Physics ; Fourier transform ; Mesoscopic physics ; Convergence (economics) ; Interpolation (computer graphics) ; Mathematical analysis ; Statistical physics ; Mathematics ; Classical mechanics ; Mechanics ; Quantum mechanics Thermal properties of materials ; Heat Transfer and Optimization ; Nanofluid Flow and Heat Transfer
Authors: Mitsalina Fildzah Arifah | Agustina Ari Murti Budi Hastuti | Abdul Rohman
Source: INDONESIAN JOURNAL OF PHARMACY (review, 2022-09-30)
Field: Chemistry — Analytical Chemistry

Application of Molecular spectroscopy and chemometrics for authentication and quality control of tea (Camellia sinensis L.): a review Tea, derived from Camellia sinensis L., is considered as the most popular beverages in the world. The quality of teas may vary depending on harvesting location and geographical origins, thus the traceability of teas according to their origins is very essential to assure tea’s quality. Due to economic reasons, high quality tea products may be added with foreign materials or adulterated with low quality ones, as a consequence, some analytical methods have been proposed and developed to quality control of tea. During the recent years, the application of molecular spectroscopic techniques (UV-Vis, Fluorescence, Near Infrared, Mid Infrared, Raman) in combination with multivariate data analysis has emerged as rapid and reliable analytical tool in the quality control of food, including food authentication. The objective of this review is to update the application of molecular spectroscopy (UV-Vis, fluorescence, infrared and Raman) for the quality control and authentication of tea products either geographical origins issue or detection of potential adulterants. The variables obtained during molecular spectral measurement involve hundreds or thousands of data, which make data analysis rather complex. Fortunately, the specific chemometrics tools can solve the problems arising from big data coming from analyte signals, spectral interferences and overlapping peaks. This review paper provides an overview of the recently developed approaches and latest research carried out in molecular spectroscopic techniques in combination with chemometrics for the quality control and for authentication of teas Chemometrics ; Traceability ; Camellia sinensis ; Quality (philosophy) ; Authentication (law) ; Food quality ; Counterfeit ; Computer science ; Raman spectroscopy ; Biochemical engineering ; Chemistry ; Mathematics ; Food science ; Geography ; Engineering ; Statistics ; Physics ; Botany ; Machine learning ; Biology ; Optics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Baohua Zhang | Qianqiu Tan | Shuwan Yu | Yuchen Liu | Yunmeng Ou | Wei Qiu
Source: Research Square (preprint, 2022-09-19)
Field: Chemistry — Analytical Chemistry

Gray mold and anthracnose disease detection on strawberry leaves using hyperspectral imaging Abstract Background Gray mold and anthracnose are the main factors affecting strawberry quality and yield. Accurate and rapid early disease identification is of great significance to achieve precise targeted spraying to avoid large-scale spread of diseases and improve strawberry yield and quality. However, the characteristics between early disease infected leaves and healthy leaves are very similar, making the early identification of strawberry anthracnose and gray mold still challenging. Results Based on hyperspectral imaging technology, this study explored the potential of combining spectral fingerprint features and vegetation indices for early detection of strawberry leaf diseases. The CARS algorithm and ReliefF algorithm were used for the extraction of spectral fingerprint features and vegetation indices, respectively. Three machine learning models, BPNN, SVM and ELM, were developed for the early identification of strawberry anthracnose and gray mold, using spectral fingerprint features, vegetation index features and their combined features as inputs respectively. The results showed that the combination of spectral fingerprint features and vegetation index features had better recognition accuracy compared with individual features as inputs, and the accuracies of the three classifiers were 97.78%, 94.44%, and 93.33%, respectively. This indicates that the fused features approach proposed in this study can effectively improve the early detection performance of strawberry leaf diseases. Conclusions This study provides a basis for the development of a rapid online detection and real-time monitoring system for fruit diseases. Hyperspectral imaging ; Artificial intelligence ; Gray level ; Fingerprint (computing) ; Support vector machine ; Spectral signature ; Grayscale ; Mold ; Pattern recognition (psychology) ; Computer science ; Horticulture ; Mathematics ; Biology ; Remote sensing ; Botany ; Pixel ; Geography Spectroscopy and Chemometric Analyses ; Plant Pathogens and Fungal Diseases ; Plant Disease Management Techniques
Authors: Zachariah Baird | Oliver Järvik | Vahur Oja
Source:  (preprint, 2022-01-28)
Field: Chemistry — Analytical Chemistry

The composition of kukersite shale oil Pyrolysis oils are usually considered as substitutes for crude oil; however, they can also be sources of valuable compounds. One such pyrolysis oil is shale oil obtained by pyrolysis of kukersite oil shale. K shale oil consists mainly of aromatic structures with straight alkyl side chains. For samples with comparable boiling point distributions, kukersite shale oil is more aromatic than petroleum and many other shale oils. Sulfur, nitrogen, and oxygen are often incorporated into the ring structures, with much of the oxygen also present as phenolic hydroxyl groups.To evaluate the potential for producing some specific compounds from kukersite shale oil foundational data on the composition is needed. Here we analyze new data on the elemental composition and infrared spectrum of kukersite shale oil to investigate its composition. To get detailed information on how the composition of the oil changes depending on the average molecular weight of the oil fraction, the shale oil was separated into narrow boiling fractions using distillation.The results show that the nitrogen content in kukersite shale oil increases with the boiling temperature, with the heaviest fractions containing about 0.3 wt%. Sulfur content reaches a maximum of almost 2 wt% for fractions boiling between 150 and 190 °C, and heavier fractions contain about 0.7 wt%. Similarly, the proportion of hydroxyl groups in kukersite shale oil peaks in the fraction boiling at about 320 °C, with heavier fractions containing more aromatic and alkyl functional groups. The elemental composition of kukersite shale oil is also compared to that of other shale oils. Oil shale ; Shale oil ; Pyrolysis ; Fraction (chemistry) ; Distillation ; Chemistry ; Boiling point ; Sulfur ; Composition (language) ; Oil shale gas ; Boiling ; Alkyl ; Nitrogen ; Vacuum distillation ; Shale oil extraction ; Synthetic crude ; Organic chemistry ; Petroleum ; Geology Petroleum Processing and Analysis ; Hydrocarbon exploration and reservoir analysis ; Phase Equilibria and Thermodynamics
Authors: Bert Debusschere | Daniel Seidl | Timothy Berg | Kyung Won Chang | Rosemary Leone | Laura Swiler | Paul Mariner
Source:  (article, 2022-11-01)
Field: Materials Science — Materials Chemistry

Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository. Abstract not provided. Process (computing) ; Computer science ; Radioactive waste ; Process engineering ; Machine learning ; Reliability engineering ; Artificial intelligence ; Waste management ; Engineering ; Operating system Graphite, nuclear technology, radiation studies ; Fault Detection and Control Systems
Authors: Filipe Pereira | Alexandre José Macêdo | Leandro Ferreira‐Pinto | Filomena Soares | Rosa Vasconcelos | José Machado | Vı́tor Carvalho
Source: Preprints.org (preprint, 2022-11-30)
Field: Materials Science — Polymers and Plastics

Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some yarn characteristic parameters. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation and standard hairiness deviation, as well as performs spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology. Yarn ; Mechatronics ; Standard deviation ; Quality (philosophy) ; Volume (thermodynamics) ; Computer science ; Artificial intelligence ; Engineering ; Engineering drawing ; Mechanical engineering ; Mathematics ; Statistics Textile materials and evaluations ; Industrial Vision Systems and Defect Detection
Authors: Mingfu He | Amir Ali | Minghui Chen
Source: Progress in Nuclear Energy (article, 2022-04-05)
Field: Materials Science — Materials Chemistry

Experimental investigations of Critical Heat Flux re-occurrence on post-CHF surfaces Materials science ; Inconel ; Cladding (metalworking) ; Critical heat flux ; Boiling ; Scanning electron microscope ; Composite material ; Thermal ; Heat flux ; Heat transfer ; Thermodynamics Nuclear Materials and Properties ; Heat Transfer and Boiling Studies ; Heat transfer and supercritical fluids
Authors: Leilei Gu | Shusheng Xie | Ying Zhang | Yule Huang | Yaojun He | Hongzhan Liu | Zhongchao Wei | Jian Ping Guo
Source: Research Square (preprint, 2022-03-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Plasmonic Metamaterials Absorbers Design Based on XGBoost and LightGBM Algorithms Metamaterial ; Plasmon ; Inverse ; Boosting (machine learning) ; Computer science ; Zoom ; Inverse problem ; Optics ; Algorithm ; Physics ; Artificial intelligence ; Mathematics ; Geometry ; Lens (geology) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Polydiacetylene-based materials and applications