jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ping Yang | Shuangshuang Wu | Haonan Wu | Donglin Lu | Wenjing Zou | Luojing Chu | Yuanzhi Shao | Shanghua Wu
Source: Ceramics International (article, 2021-05-25)
Field: Materials Science — Ceramics and Composites

Prediction of bending strength of Si3N4 using machine learning Materials science ; Ceramic ; Silicon nitride ; Flexural strength ; Bending ; Sintering ; Composite material ; Boosting (machine learning) ; Silicon ; Machine learning ; Computer science ; Metallurgy Advanced ceramic materials synthesis ; Advanced Surface Polishing Techniques ; Metal and Thin Film Mechanics
Authors: Joy Sarkar | Zawad Hasan Prottoy | Md. Tanimul Bari | Md Abdullah Al Faruque
Source: Heliyon (article, 2021-09-01)
Field: Materials Science — Polymers and Plastics

Comparison of ANFIS and ANN modeling for predicting the water absorption behavior of polyurethane treated polyester fabric Nowadays, the polyurethane and its derivatives are highly applied as a surface modification material onto the textile substrates in different forms to enhance the functional properties of the textile materials. The primary purpose of this study is to develop prediction models to model the absorption property of the textile substrate using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods. In this study, polyurethane (PU) along with acrylic binder was applied on the dyed polyester knitted fabric to develop and validate the prediction models. Through the morphological study, it was evident that the solution prepared with the polyurethane and the acrylic binder was effectively coated onto the fabric surface. The ANFIS model was constructed by considering binder (ml) and PU (%) as input parameters, whereas absorbency (%) was the only output parameter. On the other hand, the system was trained with 70% data for constructing the ANN model whereas testing and validation were done with 15% data, respectively. To train the network, feed-forward backpropagation with Levenberg-Marquardt learning algorithm was used. The coefficient of determination (R<sup>2</sup>) was found to be 0.98 and 0.93 for ANFIS and ANN model, respectively. Both prediction models exhibited an excellent mean absolute error percentage (0.76% for the ANFIS model and 1.18% for the ANN model). Furthermore, an outstanding root-mean-square error (RMSE) of 0.61% and 1.28% for ANFIS and ANN models was observed. These results suggested an excellent performance of the developed models to predict the absorption property of the polyurethane and acrylic binder treated fabric. Besides, these models can be taken as a basis to develop prediction models for specific types of functional applications of the textile materials to eliminate heaps of trial and error efforts of the textile industries, which eventually be helpful in the scalable production of functional textiles. Adaptive neuro fuzzy inference system ; Polyurethane ; Mean squared error ; Materials science ; Coefficient of determination ; Polyester ; Composite material ; Artificial neural network ; Absorption (acoustics) ; Backpropagation ; Mean absolute percentage error ; Absorption of water ; Biological system ; Computer science ; Mathematics ; Artificial intelligence ; Machine learning ; Fuzzy logic ; Statistics ; Fuzzy control system Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Advanced Sensor and Energy Harvesting Materials
Authors: Magdalena Buszewska‐Forajta | Paweł Pomastowski | Fernanda Monedeiro | Justyna Walczak‐Skierska | Marcin Markuszewski | Marcin Matuszewski | Michał J. Markuszewski | Bogusław Buszewski
Source: Cancers (article, 2021-04-21)
Field: Chemistry — Spectroscopy

Lipidomics as a Diagnostic Tool for Prostate Cancer The main goal of this study was to explore the phospholipid alterations associated with the development of prostate cancer (PCa) using two imaging methods: matrix-assisted laser desorption ionization with time-of-flight mass spectrometer (MALDI-TOF/MS), and electrospray ionization with triple quadrupole mass spectrometer (ESI-QqQ/MS). For this purpose, samples of PCa tissue (<i>n</i> = 40) were evaluated in comparison to the controls (<i>n</i> = 40). As a result, few classes of compounds, namely phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), sphingomyelins (SMs), and phosphatidylethanolamines (PEs), were determined. The obtained results were evaluated by univariate (Mann-Whitney U-test) and multivariate statistical analysis (principal component analysis, correlation analysis, volcano plot, artificial neural network, and random forest algorithm), in order to select the most discriminative features and to search for the relationships between the responses of these groups of substances, also in terms of the used analytical technique. Based on previous literature and our results, it can be assumed that PCa is linked with both the synthesis of fatty acids and lipid oxidation. Among the compounds, phospholipids, namely PC 16:0/16:1, PC 16:0/18:2, PC 18:0/22:5, PC 18:1/18:2, PC 18:1/20:0, PC 18:1/20:4, and SM d18:1/24:0, were assigned as metabolites with the best discriminative power for the tested groups. Based on the results, lipidomics can be found as alternative diagnostic tool for CaP diagnosis. Lipidomics ; Mass spectrometry ; Principal component analysis ; Prostate cancer ; Chemistry ; Electrospray ionization ; Discriminative model ; Chromatography ; Univariate ; Computational biology ; Artificial intelligence ; Cancer ; Multivariate statistics ; Computer science ; Medicine ; Internal medicine ; Biology ; Biochemistry ; Machine learning Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Proteomics Techniques and Applications
Authors: Abhishek Sharan | Stephan Lany
Source: The Journal of Chemical Physics (article, 2021-06-17)
Field: Materials Science — Materials Chemistry

Computational discovery of stable and metastable ternary oxynitrides Materials design from first principles enables exploration of uncharted chemical spaces. Extensive computational searches have been performed for mixed-cation ternary compounds, but mixed-anion systems are gaining increased interest as well. Central to computational discovery is the crystal structure prediction, where the trade-off between reliance on prototype structures and size limitations of unconstrained sampling has to be navigated. We approach this challenge by letting two complementary structure sampling approaches compete. We use the kinetically limited minimization approach for high-throughput unconstrained crystal structure prediction in smaller cells up to 21 atoms. On the other hand, ternary-and, more generally, multinary-systems often assume structures formed by atomic ordering on a lattice derived from a binary parent structure. Thus, we additionally sample atomic configurations on prototype lattices with cells up to 56 atoms. Using this approach, we searched 65 different charge-balanced oxide-nitride stoichiometries, including six known systems as the control sample. The convex hull analysis is performed both for the thermodynamic limit and for the case of synthesis with activated nitrogen sources. We identified 34 phases that are either on the convex hull or within a viable energy window for potentially metastable phases. We further performed structure sampling for "missing" binary nitrides whose energies are needed for the convex hull analysis. Among these, we discovered metastable Ce<sub>3</sub>N<sub>4</sub> as a nitride analog of the tetravalent cerium oxide, which becomes stable under slightly activated nitrogen condition Δμ<sub>N</sub> > +0.07 eV. Given the outsize role of CeO<sub>2</sub> in research and application, Ce<sub>3</sub>N<sub>4</sub> is a potentially important discovery. Ternary operation ; Metastability ; Nitride ; Materials science ; Convex hull ; Crystal structure ; Chemical physics ; Crystallography ; Computer science ; Chemistry ; Nanotechnology ; Mathematics ; Regular polygon ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Electronic and Structural Properties of Oxides
Authors: Asbjørn Rasmussen | Thorsten Deilmann | Kristian S. Thygesen
Source: npj Computational Materials (article, 2021-01-29)
Field: Materials Science — Materials Chemistry

Towards fully automated GW band structure calculations: What we can learn from 60.000 self-energy evaluations Abstract We analyze a data set comprising 370 GW band structures of two-dimensional (2D) materials covering 14 different crystal structures and 52 chemical elements. The band structures contain a total of 61716 quasiparticle (QP) energies obtained from plane-wave-based one-shot G 0 W 0 @PBE calculations with full frequency integration. We investigate the distribution of key quantities, like the QP self-energy corrections and QP weights, and explore their dependence on chemical composition and magnetic state. The linear QP approximation is identified as a significant error source and we propose schemes for controlling and drastically reducing this error at low computational cost. We analyze the reliability of the 1/ N basis set extrapolation and find that is well-founded with a narrow distribution of coefficients of determination ( r 2 ) peaked very close to 1. Finally, we explore the accuracy of the scissors operator approximation and conclude that its validity is very limited. Our work represents a step towards the development of automatized workflows for high-throughput G 0 W 0 band structure calculations for solids. Extrapolation ; Set (abstract data type) ; Quasiparticle ; Electronic band structure ; Operator (biology) ; Distribution (mathematics) ; Reliability (semiconductor) ; Basis (linear algebra) 2D Materials and Applications ; Iron-based superconductors research ; Boron and Carbon Nanomaterials Research
Authors: Yury Shkryl | Tatiana Rusapetova | Yulia Yugay | A. Е. Egorova | V. E. Silant’ev | Valeria P. Grigorchuk | Aleksandr Karabtsov | Ya. О. Timofeeva | Elena Vasyutkina | Olesya Kudinova | V. V. Ivanov | Vadim Kumeiko | Victor P. Bulgakov
Source: International Journal of Molecular Sciences (article, 2021-08-27)
Field: Materials Science — Materials Chemistry

Biosynthesis and Cytotoxic Properties of Ag, Au, and Bimetallic Nanoparticles Synthesized Using Lithospermum erythrorhizon Callus Culture Extract The present study reports a green chemistry approach for the rapid and easy biological synthesis of silver (Ag), gold (Au), and bimetallic Ag/Au nanoparticles using the callus extract of <i>Lithospermum erythrorhizon</i> as a reducing and capping agent. The biosynthesized nanoparticles were characterized with ultraviolet-visible (UV-Vis) spectroscopy, X-ray diffraction (XRD) analysis, and transmission electron microscopy (TEM). Our results showed the formation of crystalline metal nanostructures of both spherical and non-spherical shape. Energy dispersive X-ray (EDX) spectroscopy showed the characteristic peaks in the silver and gold regions, confirming the presence of the corresponding elements in the monometallic particles and both elements in the bimetallic particles. Fourier-transform infrared (FTIR) spectroscopy affirmed the role of polysaccharides and polyphenols of the <i>L. erythrorhizon</i> extract as the major reducing and capping agents for metal ions. In addition, our results showed that the polysaccharide sample and the fraction containing secondary metabolites isolated from <i>L. erythrorhizon</i> were both able to produce large amounts of metallic nanoparticles. The biosynthesized nanoparticles demonstrated cytotoxicity against mouse neuroblastoma and embryonic fibroblast cells, which was considerably higher for Ag nanoparticles and for bimetallic Ag/Au nanoparticles containing a higher molar ratio of silver. However, fibroblast migration was not significantly affected by any of the nanoparticles tested. The obtained results provide a new example of the safe biological production of metallic nanoparticles, but further study is required to uncover the mechanism of their toxicity so that the biomedical potency can be assessed. Callus ; Bimetallic strip ; Chemistry ; Biosynthesis ; Cytotoxic T cell ; Nanoparticle ; Botany ; Traditional medicine ; Biochemistry ; Biology ; Nanotechnology ; Materials science ; In vitro ; Catalysis ; Gene ; Medicine Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanoparticle-Based Drug Delivery
Authors: Naresh Shahi | Eunji Lee | Byungjin Min | Dong‐Joo Kim
Source: Sensors (article, 2021-06-28)
Field: Materials Science — Biomaterials

Rice Husk-Derived Cellulose Nanofibers: A Potential Sensor for Water-Soluble Gases Cellulose and its derivatives have evoked much attention in sensor technology as host-matrices for conducting materials because of their versatility, renewability, and biocompatibility. However, only a few studies have dealt with the potential utilization of cellulose as a sensing material without a composite structure. In this study, cellulose nanofibers (CNF) and 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanofibers (TOCNF) extracted from rice husks by using ultrasonic-assisted methods are introduced as a potential gas sensing material with highly sensitive performance. To fabricate nanocellulose-based films, CNF, TOCNF, and TOCNF with glycerol (TOCNF/G) were dispersed in water and applied on polyimide substrate with digital electrodes to form self-standing thin films by a drop-casting method. A transparent coating layer on the surface of the plate after drying is used for the detection of water-soluble gases such as acetone, ammonia, methane, and hydrogen sulfide gases at room temperature at 52% relative humidity. The sensor prototypes exhibited high sensitivity, and the detection limit was between 1 ppm and 5 ppm, with less than 10 min response and recovery time. The results indicate that both the CNF- and the TOCNF-coated sensors show good sensitivity toward ammonia and acetone, compared to other gases. A TOCNF/G-coated sensor exhibited minimum time in regard to response/recovery time, compared to a CNF-coated sensor. In this study, nanocellulose-based sensors were successfully fabricated using a low-cost process and a bio-based platform. They showed good sensitivity for the detection of various gases under ambient conditions. Therefore, our study results should further propel in-depth research regarding various applications of cellulose-based sensors in the future. Nanocellulose ; Cellulose ; Materials science ; Nanofiber ; Chemical engineering ; Coating ; Acetone ; Composite material ; Chemistry ; Organic chemistry Advanced Cellulose Research Studies ; Nanocomposite Films for Food Packaging ; Advanced Sensor and Energy Harvesting Materials
Authors: Marek Tulej | N. F. W. Ligterink | Coenraad de Koning | Valentine Grimaudo | Rustam Lukmanov | Peter Keresztes Schmidt | Andreas Riedo | P. Wurz
Source: Applied Sciences (article, 2021-03-12)
Field: Chemistry — Spectroscopy

Current Progress in Femtosecond Laser Ablation/Ionisation Time-of-Flight Mass Spectrometry The last decade witnessed considerable progress in the development of laser ablation/ionisation time-of-flight mass spectrometry (LI-TOFMS). The improvement of both the laser ablation ion sources employing femtosecond lasers and the method of ion coupling with the mass analyser led to highly sensitive element and isotope measurements, minimisation of matrix effects, and reduction of various fractionation effects. This improvement of instrumental performance can be attributed to the progress in laser technology and accompanying commercialisation of fs-laser systems, as well as the availability of fast electronics and data acquisition systems. Application of femtosecond laser radiation to ablate the sample causes negligible thermal effects, which in turn allows for improved resolution of chemical surface imaging and depth profiling. Following in the footsteps of its predecessor ns-LIMS, fs-LIMS, which employs fs-laser ablation ion sources, has been developed in the last two decades as an important method of chemical analysis and will continue to improve its performance in subsequent decades. This review discusses the background of fs-laser ablation, overviews the most relevant instrumentation and emphasises their performance figures, and summarizes the studies on several applications, including geochemical, semiconductor, and bio-relevant materials. Improving the chemical analysis is expected by the implementation of laser pulse sequences or pulse shaping methods and shorter laser wavelengths providing current progress in mass resolution achieved in fs-LIMS. In parallel, advancing the methods of data analysis has the potential of making this technique very attractive for 3D chemical analysis with micrometre lateral and sub-micrometre vertical resolution. Laser ; Mass spectrometry ; Laser ablation ; Materials science ; Ablation ; Femtosecond ; Ionization ; Optics ; Optoelectronics ; Ion ; Chemistry ; Aerospace engineering ; Physics Mass Spectrometry Techniques and Applications ; Laser-induced spectroscopy and plasma ; Analytical chemistry methods development
Authors: Christian Niklas | Hainer Wackerbarth | Georgios Ctistis
Source: Sensors (review, 2021-03-02)
Field: Chemistry — Spectroscopy

A Short Review of Cavity-Enhanced Raman Spectroscopy for Gas Analysis The market of gas sensors is mainly governed by electrochemical, semiconductor, and non-dispersive infrared absorption (NDIR)-based optical sensors. Despite offering a wide range of detectable gases, unknown gas mixtures can be challenging to these sensor types, as appropriate combinations of sensors need to be chosen beforehand, also reducing cross-talk between them. As an optical alternative, Raman spectroscopy can be used, as, in principle, no prior knowledge is needed, covering nearly all gas compounds. Yet, it has the disadvantage of a low quantum yield through a low scattering cross section for gases. There have been various efforts to circumvent this issue by enhancing the Raman yield through different methods. For gases, in particular, cavity-enhanced Raman spectroscopy shows promising results. Here, cavities can be used to enhance the laser beam power, allowing higher laser beam-analyte interaction lengths, while also providing the opportunity to utilize lower cost equipment. In this work, we review cavity-enhanced Raman spectroscopy, particularly the general research interest into this topic, common setups, and already achieved resolutions. Raman spectroscopy ; Laser ; Raman scattering ; Spectroscopy ; Materials science ; Optoelectronics ; Optical cavity ; Semiconductor ; Optics ; Physics Spectroscopy and Laser Applications ; Photonic and Optical Devices ; Advanced Chemical Sensor Technologies
Authors: Damien Hudry | Annick De Backer | Radian Popescu | Dmitry Busko | Ian A. Howard | Sara Bals | Yang Zhang | Adrián Pedrazo‐Tardajos | Sandra Van Aert | Dagmar Gerthsen | Thomas Altantzis | Bryce S. Richards
Source: Small (article, 2021-10-25)
Field: Materials Science — Materials Chemistry

Interface Pattern Engineering in Core‐Shell Upconverting Nanocrystals: Shedding Light on Critical Parameters and Consequences for the Photoluminescence Properties Advances in controlling energy migration pathways in core-shell lanthanide (Ln)-based hetero-nanocrystals (HNCs) have relied heavily on assumptions about how optically active centers are distributed within individual HNCs. In this article, it is demonstrated that different types of interface patterns can be formed depending on shell growth conditions. Such interface patterns are not only identified but also characterized with spatial resolution ranging from the nanometer- to the atomic-scale. In the most favorable cases, atomic-scale resolved maps of individual particles are obtained. It is also demonstrated that, for the same type of core-shell architecture, the interface pattern can be engineered with thicknesses of just 1 nm up to several tens of nanometers. Total alloying between the core and shell domains is also possible when using ultra-small particles as seeds. Finally, with different types of interface patterns (same architecture and chemical composition of the core and shell domains) it is possible to modify the output color (yellow, red, and green-yellow) or change (improvement or degradation) the absolute upconversion quantum yield. The results presented in this article introduce an important paradigm shift and pave the way toward the emergence of a new generation of core-shell Ln-based HNCs with better control over their atomic-scale organization. Photoluminescence ; Nanocrystal ; Shell (structure) ; Materials science ; Interface (matter) ; Nanotechnology ; Core (optical fiber) ; Luminescence ; Optoelectronics ; Composite material ; Contact angle Luminescence Properties of Advanced Materials ; Quantum Dots Synthesis And Properties ; Carbon and Quantum Dots Applications
Authors: Lara G. Freidus | Pradeep Kumar | Thashree Marimuthu | Priyamvada Pradeep | Yahya E. Choonara
Source: Frontiers in Molecular Biosciences (article, 2021-05-20)
Field: Materials Science — Biomaterials

Theranostic Mesoporous Silica Nanoparticles Loaded With a Curcumin-Naphthoquinone Conjugate for Potential Cancer Intervention A novel theranostic molecule, derived from curcumin (Cur) and naphthoquinone (NQ), allowing for cancer targeting, detection and treatment was previously described and termed CurNQ. To allow for enhanced theranostic capabilities, advanced drug delivery techniques are required. To this end, mesoporous silica nanoparticles (MSN) were synthesized and CurNQ was loaded into its pores to form the novel nanosystem MSN_CurNQ. The formation of the nanosystem aimed to augment the drug delivery of CurNQ through the EPR effect and sustained release. Moreover, the loading of CurNQ into its pores, formed a fluorescent nanoparticle that can be tracked, detected and visualized. Herein, the synthesis of a novel nanosystem is described and its theranostic potential are explored <i>in vitro</i>. MSN with an average size of 108 d.nm, a zeta potential of -42 mV and a PDI of 0.150 were synthesized and were impregnated with CurNQ to form the novel nanosystem MSN_CurNQ. MSN_CurNQ was demonstrated to have pH-responsivity whereby after 96 h, at pH 7.4, 31.5% of CurNQ was released from the MSN compared to 57% release at pH 6.8, corresponding to an increase of 25.5% in release with a 0.6 pH drop. The innate fluorescence was then characterized through confocal and fluorescence microscopy. Microscopy images illustrated the distinct, high intensity innate fluorescence with a high background to target ratio, thus confirming detection capabilities and potentially extending MSN_CurNQ's application to molecular imaging purposes. Moreover, the chemotherapeutic potential of MSN_CurNQ was demonstrated as cell viability was reduced to below 50% in OVCAR-5, CACO-2, CHLA, and MCF-7 cell lines. Furthermore, MSN_CurNQ displayed tumor specific toxicity whereby the cell viability was reduced to a far greater extent in the cancer cell lines compared to a healthy fibroblast cell line (<i>p</i> = 0.000). Indeed, the novel MSN_CurNQ nanosystem has potential for applications in cancer targeting, detection and treatment. Curcumin ; Mesoporous silica ; Nanoparticle ; Nanotechnology ; Chemistry ; Fluorescence ; Cancer cell ; Mesoporous material ; Drug delivery ; Zeta potential ; Biophysics ; Conjugate ; Confocal microscopy ; Materials science ; Cancer ; Biochemistry Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; RNA Interference and Gene Delivery