jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tobias Greisager Rehfeldt | Konrad Krawczyk | Simon Gregersen Echers | Paolo Marcatili | Pawel Palczynski | Richard Röttger | Veit Schwämmle
Source: GigaScience (article, 2022-12-28)
Field: Chemistry — Spectroscopy

Variability analysis of LC-MS experimental factors and their impact on machine learning Our findings show significantly higher levels of homogeneity within a project than between projects, which indicates that it is important to construct datasets most closely resembling future test cases, as transferability is severely limited for unseen datasets. We also found that transfer learning, although it did increase model performance, did not increase model performance compared to a non-pretrained model. Computer science ; Data science Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Proteomics Techniques and Applications
Authors: Jinsong Yang
Source: Polymers (article, 2022-05-18)
Field: Materials Science — Polymers and Plastics

Molecular Dynamics Simulation of Oxidative Aging Effect on Diffusion Behaviors of Oxygen and Cyclohexane in NBR The influences of thermal-oxidative aging on the diffusion behaviors of oxygen and cyclohexane in nitrile-butadiene rubber (NBR) at the micro-scale were investigated by molecular dynamics (MD) simulation. The two types of aged rubber models were established on the basis of rubber oxidative chains modified by the introduction of hydroxyl groups and carbonyl groups in rubber chains. The diffusion behaviors of oxygen and cyclohexane in NBR under different conditions were characterized by the fractional free volume (<i>FFV</i>), mean square displacement (<i>MSD</i>), diffusion coefficients, and diffusion trajectory. It turns out that the elevated temperature contributed to the increase in the free volume and diffusion range of oxygen and cyclohexane, while the compressive stress showed the reverse influence. Additionally, the introduction of oxidative polar functional groups (hydroxyl groups and carbonyl groups) in rubber chains lowered the flexibility of the rubber chains and promoted the formation of strong polar interaction, which further inhibits the diffusion of oxygen and cyclohexane. Cyclohexane ; Natural rubber ; Diffusion ; Oxygen ; Molecular dynamics ; Chemistry ; Polymer chemistry ; Materials science ; Organic chemistry ; Computational chemistry ; Thermodynamics ; Physics Polymer Nanocomposites and Properties ; Polymer crystallization and properties ; Polymer composites and self-healing
Authors: Audrey R. N. Ndukwe | Sandra Wiedbrauk | Nathan R. B. Boase | Kathryn E. Fairfull‐Smith
Source: Chemistry - An Asian Journal (review, 2022-03-29)
Field: Chemistry — Organic Chemistry

Strategies to Improve the Potency of Oxazolidinones towards Bacterial Biofilms Biofilms are part of the natural lifecycle of bacteria and are known to cause chronic infections that are difficult to treat. Most antibiotics are developed and tested against bacteria in the planktonic state and are ineffective against bacterial biofilms. The oxazolidinones, including the last resort drug linezolid, are one of the main classes of synthetic antibiotics progressed to clinical use in the last 50 years. They have a unique mechanism of action and only develop low levels of resistance in the clinical setting. With the aim of providing insight into strategies to design more potent antibiotic compounds with activity against bacterial biofilms, we review the biofilm activity of clinically approved oxazolidinones and report on structural modifications to oxazolidinones and their delivery systems which lead to enhanced anti-biofilm activity. Potency ; Biofilm ; Microbiology ; Chemistry ; Biology ; Bacteria ; Biochemistry ; In vitro ; Genetics Antimicrobial agents and applications ; Bacterial biofilms and quorum sensing ; Nosocomial Infections in ICU
Authors: Rhoda Afriyie Mensah | Alva Vennström | Vigneshwaran Shanmugam | Michael Försth | Zhiwei Li | Ágoston Restás | Rasoul Esmaeely Neisiany | De­nis Sokol | Manjusri Misra | Amar K. Mohanty | Mikael S. Hedenqvist | Oisik Das
Source: Composites Part C Open Access (article, 2022-10-01)
Field: Materials Science — Polymers and Plastics

Influence of biochar and flame retardant on mechanical, thermal, and flammability properties of wheat gluten composites The use of environmentally friendly materials such as bio-sourced plastics is being driven by increased awareness of environmental issues caused by synthetic plastics. However, bio-sourced plastics have poor fire behaviour that limits their application. The addition of a flame retardant to these plastics is one effective way to increase the fire resistance property; however, the flame retardant should not interfere with the mechanical performance of the plastic. Most flame retardants act as stress concentration points, reducing tensile strength. Hence, to create a balance between tensile strength and fire resistance, biochar (to conserve strength) and lanosol (to improve fire resistance) were added to wheat gluten bioplastic in various ratios and the optimal ratio was identified. Wheat gluten composites were fabricated using compression moulding at four different concentrations of lanosol (2, 4, 6, and 8 wt.%) and biochar (2, 4, 6, and 8 wt.%). From the test results, the composite with 4 wt.% lanosol and 6 wt.% biochar exhibited a good balance between the mechanical and fire properties; it conserved the strength and improved the fire properties (39 % reduction in peak heat release rate). Fire retardant ; Flammability ; Biochar ; Materials science ; Ultimate tensile strength ; Composite material ; Fire resistance ; Composite number ; Fire test ; Waste management ; Pyrolysis Natural Fiber Reinforced Composites ; Flame retardant materials and properties ; Fire dynamics and safety research
Authors: Pedro Escárate | Gonzalo Farías | Paulina Naranjo | Juan Pablo Zóffoli
Source: Sensors (article, 2022-08-14)
Field: Chemistry — Analytical Chemistry

Estimation of Soluble Solids for Stone Fruit Varieties Based on Near-Infrared Spectra Using Machine Learning Techniques The quality control for fruit maturity inspection is a key issue in fruit packaging and international trade. The quantification of Soluble Solids (SS) in fruits gives a good approximation of the total sugar concentration at the ripe stage, and on the other hand, SS alone or in combination with acidity is highly related to the acceptability of the fruit by consumers. The non-destructive analysis based on Visible (VIS) and Near-Infrared (NIR) spectroscopy has become a popular technique for the assessment of fruit quality. To improve the accuracy of fruit maturity inspection, VIS−NIR spectra models based on machine learning techniques are proposed for the non-destructive evaluation of soluble solids in considering a range of variations associated with varieties of stones fruit species (peach, nectarine, and plum). In this work, we propose a novel approach based on a Convolutional Neural Network (CNN) for the classification of the fruits into species and then a Feedforward Neural Network (FNN) to extract the information of VIS−NIR spectra to estimate the SS content of the fruit associated to several varieties. A classification accuracy of 98.9% was obtained for the CNN classification model and a correlation coefficient of Rc>0.7109 for the SS estimation of the FNN models was obtained. The results reported show the potential of this method for a fast and on-line classification of fruits and estimation of SS concentration. Convolutional neural network ; Sugar ; Artificial neural network ; Artificial intelligence ; Near-infrared spectroscopy ; Correlation coefficient ; Machine learning ; Biological system ; Computer science ; Mathematics ; Pattern recognition (psychology) ; Horticulture ; Chemistry ; Food science ; Physics ; Biology ; Optics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Water Quality Monitoring and Analysis
Authors: S. Muthukumaran | P. Geetha | E. Ramaraj
Source: Intelligent Automation & Soft Computing (article, 2022-06-06)
Field: Chemistry — Analytical Chemistry

Multi-Objective Optimization with Artificial Neural Network Based Robust Paddy Yield Prediction Model Agriculture plays a vital role in the food production process that occupies nearly one-third of the total surface of the earth. Rice is propagated from the seeds of paddy and it is a stable food almost used by fifty percent of the total world population. The extensive growth of the human population alarms us to ensure food security and the country should take proper food steps to improve the yield of food grains. This paper concentrates on improving the yield of paddy by predicting the factors that influence the growth of paddy with the help of Evolutionary Computation Techniques. Most of the researchers used to relay on historical records of meteorological parameters to predict the yield of paddy. There is a lack in analyzing the day to day impact of meteorological parameters such as direction of wind, relative humidity, Instant Wind Speed in paddy cultivation. The real time meteorological data collected and analysis the impact of weather parameters from the day of paddy sowing to till the last day of paddy harvesting with regular time series. A Robust Optimized Artificial Neural Network (ROANN) Algorithm with Genetic Algorithm (GA) and Multi Objective Particle Swarm Optimization Algorithm (MOPSO) proposed to predict the factors that to be concentrated by farmers to improve the paddy yield in cultivation. A real time paddy data collected from farmers of Tamilnadu and the meteorological parameters were matched with the cropping pattern of the farmers to construct the database. The input parameters were optimized either by using GA or MOPSO optimization algorithms to reconstruct the database. Reconstructed database optimized by using Artificial Neural Network Back Propagation Algorithm. The reason for improving the growth of paddy was identified using the output of the Neural Network. Performance metrics such as Accuracy, Error Rate etc were used to measure the performance of the proposed algorithm. Comparative analysis made between ANN with GA and ANN with MOPSO to identify the recommendations for improving the paddy yield. Particle swarm optimization ; Food security ; Computer science ; Artificial neural network ; Agriculture ; Agricultural engineering ; Cropping ; Population ; Paddy field ; Wind speed ; Algorithm ; Machine learning ; Meteorology ; Agronomy ; Engineering ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Fault Detection and Control Systems
Authors: Shota Ono | Kobayashi Daigo
Source: Scientific Reports (article, 2022-05-04)
Field: Materials Science — Materials Chemistry

Role of the M point phonons for the dynamical stability of B2 compounds Although many binary compounds have the B2 (CsCl-type) structure in the thermodynamic phase diagram, an origin of the dynamical stability is not understood well. Here, we focus on 416 compounds in the B2 structure extracted from the Materials Project, and study the dynamical stability of those compounds from first principles. We demonstrate that the dynamical stability of the B2 compounds lies in whether the lowest frequency phonons around the M point in the Brillouin zone are endowed with a positive frequency, except for VRu. We show that the interatomic interactions up to the fourth nearest neighbor atoms are necessary for stabilizing such phonon modes, which should determine the minimum cutoff radius for constructing the interatomic potentials of binary compounds with guaranteed accuracy. Phonon ; Point (geometry) ; Stability (learning theory) ; Computer science ; Statistical physics ; Physics ; Condensed matter physics ; Mathematics ; Machine learning ; Geometry Boron and Carbon Nanomaterials Research ; Advanced ceramic materials synthesis ; Intermetallics and Advanced Alloy Properties
Authors: Henri Vahabi | M.Z. Naser | Mohammad Reza Saeb
Source: Fire Technology (article, 2022-01-04)
Field: Materials Science — Materials Chemistry

Fire Protection and Materials Flammability Control by Artificial Intelligence Flammability ; Poison control ; Fire safety ; Fire protection ; Forensic engineering ; Engineering ; Environmental science ; Occupational safety and health ; Medical emergency ; Materials science ; Civil engineering ; Medicine ; Composite material Machine Learning in Materials Science ; Risk and Safety Analysis
Authors: Chitnarong Sirisathitkul | Yaowarat Sirisathitkul
Source: Inventions (article, 2022-08-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent Developments in 3D Printing of Rare-Earth-Free Permanent Magnets This article reviews the advances in additive manufacturing of magnetic ceramics and alloys without rare-earth elements. Near-net-shaped permanent magnets with varying shapes and dimensions overcome traditional limitations of the cast, sintered, and bonded magnets. The published articles are categorized based on material types and 3D printing techniques. Selective laser melting and electron beam melting were predominantly used to produce alnico magnets. In addition to the electron beam melting, manganese aluminium-based alloys were successfully printed by fuse filament fabrication. By incorporating magnetic powders in polymers and then printing via extrusion, the fuse filament fabrication was also used to produce strontium ferrite magnets. Moreover, hard ferrites were printed by stereolithography and extrusion free-forming, without drawing composites into filaments. Magnetic properties in some cases are comparable to those of conventional magnets with the same compositions. Currently, available software packages can simulate magnetic fields for designing magnets and optimize the integration in electrical machines. These developments open up opportunities for next-generation permanent magnet applications. Magnet ; Materials science ; Alnico ; Extrusion ; Neodymium magnet ; Fabrication ; 3D printing ; Ceramic ; Ferrite (magnet) ; Fused filament fabrication ; Mechanical engineering ; Composite material ; Metallurgy Magnetic Properties of Alloys ; Electromagnetic wave absorption materials ; Metallic Glasses and Amorphous Alloys
Authors: Jonas Schaub | Julian Zander | Achim Zielesny | Christoph Steinbeck
Source: Journal of Cheminformatics (article, 2022-11-10)
Field: Chemistry — Physical and Theoretical Chemistry

Scaffold Generator: a Java library implementing molecular scaffold functionalities in the Chemistry Development Kit (CDK) The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day. Scaffold ; Java ; Computer science ; Generator (circuit theory) ; Chemistry ; Software engineering ; World Wide Web ; Programming language Various Chemistry Research Topics ; Chemistry and Chemical Engineering ; Computational Drug Discovery Methods
Authors: Huiming Yao | Jiapeng Yang | Han Li | Jianchun Xu | Ke Bi
Source: Research Square (preprint, 2022-12-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimal Design of Multilayer Radar Absorbing Materials: A Simulation-Optimization Approach Abstract Multilayer radar absorbing materials with light weight, strong absorption, and wide absorption bandwidth are urgently demanded with the increase of electromagnetic pollution. However, the current design methods with only simulation operation or optimization strategy are not comprehensive. Here, a simulation-optimization approach including electromagnetic simulation and numerical calculation is proposed based on the interaction between different software, in which the homogeneous medium substitution method is presented to simplify the complicated structures. Besides, return loss and impedance matching of different layer structures are investigated. From the simulated results, it can be found that the structures with better impedance matching have superior absorbing performance. The optimal method shows the advantages of fast and efficient, which has tremendous potential for various applications, such as military stealth and electromagnetic wave elimination. Radar ; Impedance matching ; Bandwidth (computing) ; Software ; Computer science ; Electrical impedance ; Simulation software ; Electromagnetic simulation ; Matching (statistics) ; Return loss ; Optimal design ; Electronic engineering ; Absorption (acoustics) ; Homogeneous ; Computer simulation ; Acoustics ; Simulation ; Engineering ; Telecommunications ; Physics ; Electrical engineering ; Mathematics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Electromagnetic Scattering and Analysis
Authors: Bo Hu | Chang Liu | Yuan Yang | Bin Wang | Dan Cai | Weifeng Xu
Source: IEEE Access (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Adaptive Internal Model Control of SCR Denitration System Based on Multi-Objective Optimization Many thermal power plants use selective catalytic reduction (SCR) systems to complete flue gas denitration. The system has the characteristics of large inertia, large delay and nonlinearity. At the same time, it is difficult to use the controller under a single working condition to meet the control task of the system under the full working conditions. In order to solve the above control difficulties, This paper proposes a two-degree-of-freedom internal model control (2-DOF-IMC) method based on controller parameter adaptation and multi-model adaptation to realize the control of the full working conditions of the SCR system. First, the intelligent identification method based on Differential evolution quantum particle swarm optimization (DEQPSO) is used to obtain the sub-model of ammonia injection-SCR outlet Nitrogen Oxide (NOx) concentration in typical working conditions. A 2-DOF-IMC controller under each sub-model is established. Then, aiming at system set point tracking performance, anti-disturbance performance, and control energy consumption, the Pareto optimal solution of each controller is obtained by using the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) algorithm based on chaotic mutation. Finally, the controller parameter adaptive strategy is designed based on the Takagi-Sugeno (T-S) fuzzy model, and the multi-model adaptive strategy is designed based on the recursive bayesian probability weighting. Through the dynamic performance test and the anti-disturbance performance test, it is verified that the 2-DOF-IMC based on controller parameter adaptation and multi-model adaptation has good control performance and adaptability to all working conditions. The method proposed in this paper combines the advantages of multi-parameter and multi-model strategies, further improves the control quality, and provides a new solution for the control of thermal power plant SCR system. Control theory (sociology) ; Controller (irrigation) ; Computer science ; Particle swarm optimization ; Control engineering ; Engineering Catalytic Processes in Materials Science ; Industrial Gas Emission Control ; Advanced Control Systems Optimization
Authors: Rajender Kumar | Puneet Katyal | Kamal Kumar | Y Joung | H Han | S Loffredo | I Jun | J Edwards | Y Kim | H Seok | F Witte | D Mantovani | S Glyn-Jones | C Tai | H Lo | C Liaw | Y Huang | K Yang | C Huang | S Huang | H Shen | T Lin | C Lu | V Singh | P Katyal | K Kumar | R Kumar | Y Chen | Z Xu | C Smith | J Sankar | Abdel Gawad | M Usman | C Shunmugasamy | V Karaman | I Mansoor | B | G Song | U Riaz | I Shabib | W Haider | S Kumar | R Chaudhary | G Sharma | P Satsangi | N Sharma | Y Yang | X Xiong | J Chen | X Peng | D Chen | F Pan | M Uddin | H Rosman | C Hall | P Murphy | A Promila; Kumar | S Silla | A Sarova | H Gkkaya | G Santhanakrishnan | R Krishnamurthy | S Malhotra | Al Hazza | M Adesta | E | M Nurhaniza | M Ariffin | F Mustapha | B Baharudin | R Walter | M Kannan | Y He | A Sandham | R Gill | U Batra | N Singh | A Mahapatro | K Goyal | R Gupta | S Gupta | D Rani | D Kumar | V Sharma | G Selvakumar
Source: Biointerface Research in Applied Chemistry (article, 2022-06-05)
Field: Materials Science — Biomaterials

Effect of End Milling Process Parameters and Corrosion Behaviour of ZE41A Magnesium Alloy using Taguchi Based GRA The purpose of the study is to optimize the machining characteristics for milling ZE41A Mg alloy on a CNC milling by Taguchi-based Grey relational analysis (GRA) to achieve the maximum material removal rate (MRR), lowest corrosion rate (CR), and surface roughness (SR). After one week of immersion in simulated body fluid (SBF), weighing samples determined the corrosion rate. The process attributes, which include tool rotation cutting speed, feed rate, and depth of cut, are opted. The experiments were conducted using a Taguchi L16 orthogonal array (OA). Additionally, variance analysis (ANOVA) was used to determine the influence of process parameters on the responses. The study discusses the significance of machining process parameters concerning the degradation behavior of biomedical implant materials in a simulated body fluid (SBF). According to the current study, the most influential parameters in multi-objective optimization are the tool rotation cutting speed and feed rate. Thus, the results obtained with GRA of MRR: 492.25mm3/min, SR: 0.3112µm, and CR: 6.386mm/year with the experimental confirmatory test were close to the expected values. ZE41A Mg alloy machined samples at optimum end-milling parameters enhanced performance in reduced surface roughness and low in-vitro corrosion rate for ZE41A Mg alloy. Taguchi methods ; Materials science ; Grey relational analysis ; Surface roughness ; Machining ; Corrosion ; Rotational speed ; Alloy ; Simulated body fluid ; Metallurgy ; Orthogonal array ; Magnesium alloy ; Surface finish ; Composite material ; Mechanical engineering ; Scanning electron microscope ; Engineering ; Mathematics Magnesium Alloys: Properties and Applications ; Tribology and Lubrication Engineering ; Surface Treatment and Coatings