jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Paulo Pereira | Luana Fernandes | Liziane Beatriz Ubirajara Santos | Kelly Cristina Coelho de Carvalho Benini | Bárbara Pereira | Heitor Luiz Ornaghi | Maria Odila Hilário Cioffi
Source: Research Square (preprint, 2021-06-10)
Field: Materials Science — Biomaterials

Different sequential chemical treatments used to obtain bleached cellulose from orange bagasse Bagasse ; Cellulose ; Orange (colour) ; Pulp and paper industry ; Chemistry ; Mathematics ; Food science ; Organic chemistry ; Engineering Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Enzyme-mediated dye degradation
Authors: Duangdao Aht‐Ong
Source: Scholarworks (University of Massachusetts Amherst) (article, 2021-11-01)
Field: Materials Science — General Materials Science

https://scholarworks.umass.edu/dissertations_1/989/ Gelatin has been used as a binder or dispersing agent for light-sensitive and non-light-sensitive photographic layers. The ability to keep the silver halide crystals finely dispersed and to protect the silver halide crystals and other additives from abrasion and other mechanical and chemical influences make gelatin desirable in photographic applications. However, gelatin is very sensitive to changes in humidity. Although this sensitivity to moisture is favorable when the film must be processed, it is also a drawback to the use of gelatin in an emulsion layer. The absorption of moisture can induce swelling stresses, causing dimensional instability commonly observed as bending or curling in the photographic films. This dissertation focuses on the effects of moisture on the state of stress and dimensional stability of gelatin coatings. The hygroscopic effects on the thermal, mechanical, and transport properties were also investigated. Two types of polymer latices, poly(ethyl acrylate) and poly(ethyl methacrylate), were studied as additives to gelatin. The effects of latex concentration, latex particle size, drying condition at vitrification, and gelatin concentration at set point were examined as a function of relative humidity. The goal is to develop an understanding of these properties and assist in controlling or selecting conditions which will minimize the dimensional instability of photographic films over a wide range of use conditions. A vibrational holographic interferometry method and a thermomechanical analyzer were adopted to measure the stresses and dimensional changes as a function of relative humidity. The incorporation of a polymer latex can reduce the moisture sensitivity, and hence increases the dimensional stability of the emulsion layer exposed to the moisture. Composite theories for an isotropic composite filled with spherical particles were applied to determine the humidity expansion coefficient and elastic moduli of the gelatin-latex films. The experimental data were in excellent agreement with the theories. The decrease in swelling stress with an addition of the polymer latex was explained by the incremental linear elasticity theory. Based on this theory, the best material (i.e., minimum swelling stress, lowest Eβ value) was found to be the gelatin film with 40 parts PEA and 15% gelatin concentration at set point, and was dried at the LMERH condition (130F/5.5% RH). Gelatin ; Composite material ; Moisture ; Stress (linguistics) ; Materials science ; Chemistry Material Properties and Applications
Authors: Min‐Sik Park | Dongseon Lee | Youngchun Kwon | Eunji Kim | Youn-Suk Choi
Source: Research Square (preprint, 2021-05-18)
Field: Materials Science — Materials Chemistry

Efficient Data Undersampling for Rule-Based Retrosynthetic Planning Abstract Computer-aided retrosynthetic planning for organic molecules, which is based on a large synthetic database, is a significant part of the recent development of an autonomous robotic chemist. As in other AI fields, however, the class imbalance problem in the dataset affects the prediction performance of retrosynthetic paths. Here, we demonstrate that applying undersampling methods to the imbalanced reaction dataset can improve the prediction of retrosynthetic rules for target molecules. We report improvements in the top-1 and top-10 prediction accuracies by 13.8% (13.1, 5.4%) and 8.8% (6.9, 2.4%) for the undersampling based on the similarity (random, dissimilarity) clustering of molecular structures of products, respectively. These results demonstrate the importance of a deep understanding of the statistical distribution, internal structure, and sampling for the training dataset. For practical application, the target-oriented undersampling method is proposed and confirmed by the improved prediction performance of 9.3 and 4.2% for top-1 and top-10 accuracies, respectively. Undersampling ; Retrosynthetic analysis ; Computer science ; Data mining ; Cluster analysis ; Artificial intelligence ; Sampling (signal processing) ; Machine learning ; Similarity (geometry) ; Pattern recognition (psychology) ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Gamze D. Tetik | Ejebay Jumageldiyeva | Ayşe Ebru Tayyar
Source: Pamukkale University Journal of Engineering Sciences (article, 2021-01-01)
Field: Materials Science — Biomaterials

Production of nanofiber textile surfaces with β-arbutin via electrospinning method Bu çalışmada, cilt lekeleri azaltıcı etkisi bilinen β-arbutin ilave edilmiş polimer çözeltisinden nanoliflerin elektrolif çekim yöntemi ile üretimi amaçlanmıştır. Bu amaçla %2, %5 ve %10 (w/v) oranlarında β-arbutin, formik asit ile hazırlanmış poliamid 6 çözeltisine ilave edilerek, çözeltilerin elektrolif çekimleri gerçekleştirilmiş ve gerçekleştirilen taramalı elektron mikroskobu (SEM) analizi ile optimum elektrolif çekim parametreleri belirlenmeye çalışılmıştır. SEM görüntüleri, en düzgün morfolojili nanoliflerin %2 (w/v)'lik β-arbutin Electrospinning ; Nanofiber ; Textile ; Arbutin ; Materials science ; Pulp and paper industry ; Composite material ; Chemistry ; Chromatography ; Engineering ; Polymer Electrospun Nanofibers in Biomedical Applications ; Silk-based biomaterials and applications
Authors: Diana Hodyna | Vasyl Kovalishyn | Volodymyr Blagodatnyi | S. P. Bondarenko | Galyna P. Mrug | M. S. Frasinyuk | Larysa Metelytsia
Source: Ukrainica Bioorganica Acta (article, 2021-12-30)
Field: Chemistry — Organic Chemistry

Cytisine derivatives as new anti-Escherichia coli agents: in silico and in vitro studies QSAR analysis of a 5143 compounds set of previously synthesized compounds tested against multi-drug resistant (MDR) clinical isolate Escherichia coli strains was done by using Online Chemical Modeling Environment (OCHEM).The predictive ability of the regression models was tested through cross-validation, giving coefficient of determination q2=0.72-0.8. The validation of the models using an external test set proved that the models can be used to predict the activity of newly designed compounds with reasonable accuracy within the applicability domain (q2=0.74-0.8). The models were applied to screen a virtual chemical library of cytisine derivatives, which was designed to have antibacterial activity. The QSAR modeling results allowed to identify a number of cytisine derivatives as effective antibacterial agents against antibiotic-resistant E. coli strains. Seven compounds were selected for synthesis and biological testing. In vitro investigation of the selected cytisine derivatives have shown that all studied compounds are potential antibacterial agents against MDR E. coli strains Cytisine ; In silico ; Quantitative structure–activity relationship ; Escherichia coli ; Antibacterial activity ; Combinatorial chemistry ; Chemistry ; Stereochemistry ; Biology ; Biochemistry ; Bacteria Synthesis and Biological Evaluation ; Computational Drug Discovery Methods ; Phenothiazines and Benzothiazines Synthesis and Activities
Authors: Ashvinder K. Rana | Vijay Kumar Thakur | A. S. Singha
Source: e-Polymers (article, 2021-01-01)
Field: Materials Science — Polymers and Plastics

Towards the use of acrylic acid graft-copolymerized plant biofiber in sustainable fortified composites: Manufacturing and characterization Abstract In this study, the impact of particle form of the Cannabis indica plant biofibers and the fiber’s surface tailoring on the physical, thermal, dielectric, and mechanical properties of unsaturated polyester composite specimens manufactured utilizing nonconventional materials were investigated. The mechanical properties such as compressive, flexural, and tensile strengths of the composite specimens were noticed to increase after functionalization of biofiber with acrylic acid and maximum enhancement was found at 20% of biofiber sacking. The physical characterization was concentrated on the assurance of the dielectric constant, dielectric strength, dielectric loss, moisture absorption, chemical resistance, percentage of swelling, limiting oxygen index, and biodegradation of polymer composites under red soil. An increase in dielectric strength from 28 to 29 kV, limiting oxygen index values from 19% to 23%, and moisture/water absorption behavior was noted for resulted bio-composites after surface tailoring of biofiber. To assess the deterioration of the polymeric materials with the temperature, differential scanning calorimetric and the thermogravimetric tests were carried out and enhancement in thermal stability was noted after fortification of polyester composites with functionalized biofiber. Materials science ; Composite material ; Limiting oxygen index ; Thermogravimetric analysis ; Flexural strength ; Absorption of water ; Ultimate tensile strength ; Dielectric ; Thermal stability ; Composite number ; Surface modification ; Fiber ; Polyester ; Chemical engineering ; Pyrolysis Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging
Authors: Lucile Nuez
Source: theses.fr (ABES) (preprint, 2021-07-12)
Field: Materials Science — Polymers and Plastics

Contribution to the multi-scale study of elementary flax fibres and xylem for composite material reinforcement Coming from a local production in France, flax has genuine attributes for its use in composite materials, in particular due to the excellent specific mechanical properties of its fibres and to the numerous co-products resulting from its culture. Flax shives make up more than 50 % of the produced biomass following flax scutching, and the diversification in its uses is an important issue for scutching companies. A better understanding of flax shives from its origin as the stem’s xylem tissue to its use as composite reinforcement is the topic of this research. A microstructural and mechanical property analysis of the xylem cell walls is carried out, followed by the characterization of flax shives after different fragmentation modes in comparison with other co-products of flax scutching, dusts. The mechanical properties of the injection moulded composites reinforced with the various considered materials are then studied. The consequences of the processing steps on the flax shives granulometry are investigated, as well as the nature of the co-products or of the thermoplastic matrix used. The main goal is a better understanding of the reinforcing mechanisms of flax shives in injection moulded composites. At the scale of elementary fibres, two important bottlenecks are tackled. The consequences of various hygroscopic conditions on the internal organisation of cellulose microfibrils during tensile tests are studied by X-ray diffraction from Soleil synchrotron. Finally, the effects of a vascular disease caused by the Verticillium dahliae fungi is investigated on the mechanical properties of both cell walls and flax elementary fibres. Reinforcement ; Xylem ; Composite number ; Composite material ; Scale (ratio) ; Materials science ; Botany ; Physics ; Biology Natural Fiber Reinforced Composites
Authors: Krittanon Prathepha | Worawat Sa-Ngiamvibool
Source: EUREKA Physics and Engineering (article, 2021-11-18)
Field: Materials Science — Materials Chemistry

The investigation of natural-rubber for improving self-powered heat detector based on thermoelectric generators Fire hazard has destroyed humanity creations. Fire detectors have been developed by using different techniques. Thermoelectric generator (TEG) is a part of energy harvesting which is able to convert heat into electricity because of temperature difference between hot and cold side of thermoelectric device (TE). Different materials are used for thermoelectric generators which depend on the characteristics of the heat source, heat sink and the design of the thermoelectric generator. Many thermoelectric generator materials are currently undergoing research. This paper presented an investigation of seeking an alternative way of detecting fire hazard by developing architecture prototype of a fire detection technique using natural rubber. The thermoelectric prototype used self-powered device which improved the temperature difference gap and stabilized the cold side of TE alongside natural rubber as the cooling material. The technique is relatively simple system realization based on three viable components, i.e. a heat sensor, a low-power RF-transmitter and a RF-receiver. The heat sensor is designed and fabricated by thermoelectric and heat sink with natural rubber (NR) coating. The NR coating is heat absorption reduction. Therefore, the temperature difference is wildly resulting in the higher TE output voltage. The voltage is also supplied to the low-power RF transmitter module. In case of fire hazard, the temperature increases from 26 to 100 °C , the prototype can operate successfully. This technique will solve potentially the power supply issue in fluctuated situations. The rubber coating from rubber trees in Thailand would be a value chain added for bio-economy, supporting a sustainable development goal of the country Thermoelectric generator ; Heat sink ; Thermoelectric effect ; Materials science ; Thermoelectric materials ; Nuclear engineering ; Thermoelectric cooling ; Electrical engineering ; Mechanical engineering ; Coating ; Voltage ; Environmental science ; Optoelectronics ; Process engineering ; Automotive engineering ; Engineering ; Composite material ; Thermal conductivity ; Physics Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Innovative Energy Harvesting Technologies
Authors: Neelmani Neelmani | R. Sarathi | Hisayuki Suematsu | Toshikatsu Tanaka
Source: Revue des composites et des matériaux avancés (article, 2021-08-31)
Field: Materials Science — Materials Chemistry

Influence of Nanofiller Dispersion on Electrical and Mechanical Properties of Epoxy Alumina Nanocomposites The electrical and mechanical properties of the epoxy alumina nanocomposites depend on the uniform dispersion of the nanofiller in the epoxy matrix. Epoxy alumina nanocomposites were prepared using 1, 3, and 5 wt% of alumina nanofiller, and electrical and mechanical properties were analyzed using experimental and modelling studies. Water droplet initiated corona inception voltage (CIV) was identified using fluorescence fiber technique and by Ultra High Frequency (UHF) technique, under AC and DC voltages. The CIV formed due to water droplet have reduced drastically with increase in number of droplets and fluorescent fiber technique found to be more sensitive to identify water droplet initiated discharges. A micro mechanical model was proposed to analyse the combined effect of the interphase and agglomeration properties of the alumina nanoparticles on the tensile strength of epoxy alumina nanocomposites. Variation in ϕagg, Eagg, and E were analysed by adopting the non-parametric distribution of alumina nanoparticles and Young’s modulus increased with the increment in the alumina nanofiller dispersion level. The presence of aggregated particles exhibits a negative effect on the tensile properties of nanocomposites. Materials science ; Epoxy ; Composite material ; Nanocomposite ; Ultimate tensile strength ; Dispersion (optics) ; Nanoparticle ; Nanotechnology High voltage insulation and dielectric phenomena ; Advanced Sensor and Energy Harvesting Materials ; Dielectric materials and actuators
Authors: Chintan Patel | R. R. Patel
Source: International Journal of Materials Engineering Innovation (article, 2021-11-01)
Field: Materials Science — Materials Chemistry

Quantification of Surface Erosion in Polymeric Insulating Material under Electrical Stress using FTIR, SEM, and Edge Detection Silicon rubber (polymeric) insulators are extensively preferred in overhead power transmission networks due to their superior performance over the conventional insulators. The surface degradation is an important concern for the insulators as it is organic in nature. The degradation may be caused by a variety of factors like electrical and environmental stresses which will result in the failure of the insulator. This paper discusses the surface erosion study of silicon rubber by applying 3.5 kV voltages (AC and DC with both the polarities) as per IEC 60587. To quantify the surface erosion, Fourier transform infrared (FTIR) and scanning electron microscopy (SEM) have been used. Further, the results are verified by edge detection techniques using Sobel and Prewitt edge detection algorithm. The study revealed that the surface erosion is more with positive DC voltage than AC and negative DC which demands the introduction of appropriate filler materials to enhance the surface properties of the silicon rubber. Materials science ; Fourier transform infrared spectroscopy ; Composite material ; Enhanced Data Rates for GSM Evolution ; Erosion ; Stress (linguistics) ; Polymer ; Chemical engineering High voltage insulation and dielectric phenomena ; Infrastructure Maintenance and Monitoring ; Non-Destructive Testing Techniques
Authors: Ahmet Onur Pehlivan
Source: Cement Wapno Beton (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Mechanical properties of magnesium phosphate cement incorporating basalt fibers In this experimental study, the effect of basalt fibers on the mechanical properties of magnesium phosphate cement [MPC] was investigated. Compressive strength, splitting tensile strength, flexural strength and modulus of elasticity, were introduced. It was observed that mechanical properties were significantly enhanced with the addition of silica fume, especially splitting tensile and flexural strength were enhanced with the increase of basalt fibers. However, for mixtures without silica fume addition, high content of fibers adversely affected the mechanical properties. Silica fume addition was found to be significant in increasing the bonding mechanism between basalt fibers and the MPC matrix. Thus, combined usage of silica fume and basalt fibers was found to be effective. A molar ratio of magnesia to ammonium dihydrogen phosphate of 8 was observed to have better results with respect to a molar ratio of 6, however, this distinction was not very apparent, when silica fume was added to both mixtures. Silica fume ; Flexural strength ; Materials science ; Ultimate tensile strength ; Composite material ; Compressive strength ; Magnesium phosphate ; Cement ; Basalt fiber ; Young's modulus ; Magnesium ; Fiber ; Metallurgy Magnesium Oxide Properties and Applications ; Bone Tissue Engineering Materials ; Magnesium Alloys: Properties and Applications
Authors: Heikki Lappalainen
Source: Aaltodoc (Aalto University) (article, 2021-08-24)
Field: Materials Science — Materials Chemistry

Data-driven materials science: reaction databases for machine learning assisted catalyst design Storing computational data in materials science databases in a consistent and generalized way is crucial for the advance of data-driven materials science. Development is required especially in storing chemical reaction data, as it is much more complex to represent in a generalized data format. Open access to databases containing curated and generalized chemical reaction data would accelerate the development of data-driven approaches also in catalysis research.&#13;\n&#13;\nIn this work, catalysis reaction data was queried from available databases, and applied on machine learning models to predict activation energies. Acquiring and pre-processing the data was found to involve a lot of pitfalls that need to be addressed when establishing chemical reaction databases. The data was found to be un-curated and inconsistent in notation and composition.&#13;\n&#13;\nAfter parsing and cleaning, descriptors were built for 1826 reactions that were acquired from the Catalysis-hub and CatApp databases. Atomic structures were provided in some of the reactions, but building descriptors directly from the structural data proved to be quite complicated, and were left out of the main data set. The data set was used to train kernel ridge regression and random forest regressor models. The models were able to predict the activation energies with over 90% accuracy, suggesting that such data-driven methods can provide valuable tools for catalysis research.&#13;\n&#13;\nAs a case study, the correlation of reaction energy and adsorption energy was investigated by using a small data set where the reaction energy was replaced with adsorption energy. The predicted activation energies showed large variation in the errors, and the results suggest that using adsorption energies directly to predict activation energies should be considered critically in catalyst screening. Catalysis ; Database ; Computer science ; Chemistry ; Organic chemistry Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Zeolite Catalysis and Synthesis
Authors: Houchen Zuo | Yongquan Jiang | Yan Yang | Jie Hu
Source: arXiv (Cornell University) (preprint, 2021-09-20)
Field: Materials Science — Materials Chemistry

Prediction of properties of metal alloy materials based on machine learning Density functional theory and its optimization algorithm are the main methods to calculate the properties in the field of materials. Although the calculation results are accurate, it costs a lot of time and money. In order to alleviate this problem, we intend to use machine learning to predict material properties. In this paper, we conduct experiments on atomic volume, atomic energy and atomic formation energy of metal alloys, using the open quantum material database. Through the traditional machine learning models, deep learning network and automated machine learning, we verify the feasibility of machine learning in material property prediction. The experimental results show that the machine learning can predict the material properties accurately. Machine learning ; Artificial intelligence ; Property (philosophy) ; Computer science ; Field (mathematics) ; Computational learning theory ; Alloy ; Energy (signal processing) ; Materials science ; Active learning (machine learning) ; Metallurgy ; Mathematics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Computational Drug Discovery Methods