jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Aabid Hussain Shaik | Saboor Shaik | Sparsh Goyal | Mohammed Rehaan Chandan | Ibham Veza | Abdulrajak Buradi | Ibrahim M. Alarifi
Source: Journal of Nanomaterials (review, 2022-01-01)
Field: Materials Science — Materials Chemistry

A Review on Environmental and Economic Impact of 2D Nanomaterials‐Based Heat Transfer Fluids 2D nanomaterials‐based heat transfer fluids show excellent thermal properties due to their large specific surface area; hence, they find large‐scale applications in automobile industries and cooling processes. Therefore, it is very essential to study the environmental and economic aspects of these 2D nanomaterial‐based nanofluids. In this review, we have discussed the environmental impact of 2D nanomaterial‐based heat transfer nanofluids under various conditions. The environmental impact analysis of these materials has shown excellent capability in reducing the energy consumption for heat transfer operations. Moreover, the possibility of nanomaterials and base fluid recovery makes it a sustainable alternative. In addition, health risk assessment on humans, cytotoxicity, and life cycle analysis have also been explored. The price‐performance index has been successfully used to study the economic impact of 2D nanomaterial‐based heat transfer fluids. The overall economic impact of 2D nanomaterial‐based heat transfer nanofluids provides an optimistic perspective over conventional heat transfer fluids. Moreover, graphene production, market trend, and commercialization obstacles were also discussed. Nanofluid ; Nanomaterials ; Heat transfer ; Commercialization ; Materials science ; Nanotechnology ; Biochemical engineering ; Business ; Nanoparticle ; Engineering ; Thermodynamics Graphene research and applications ; Solar-Powered Water Purification Methods ; Membrane Separation Technologies
Authors: Madan Kumar Lakshmanan | Birte Boelt | René Gislum
Source: Journal of Near Infrared Spectroscopy (article, 2022-12-13)
Field: Chemistry — Analytical Chemistry

A chemometric method for the viability analysis of spinach seeds by near infrared spectroscopy with variable selection using successive projections algorithm This paper proposes a chemometric method for evaluating the viability of spinach seeds using near infrared (NIR) spectroscopy and successive projections algorithms (SPA). An essential step of the procedure is to apply the SPA to optimize the choice of variables for multivariate classification. Variable selection using SPA has been described as an optimization problem in which a cost function is minimized. Selecting the correct variables makes the chemometric models more complete, precise, accurate, and less complex. The NIR spectra were processed using the Savitzky-Golay and multiplicative scatter correction techniques. After that, the best wavelength subset was selected using SPA. Different classification techniques are then applied to the dimension-reduced data to determine the seeds’ viability. The results show that the proposed method is less complex compared to existing canonical variance methods (1.7% miscalculation error in the proposed way) and is also easier to implement. Feature selection ; Algorithm ; Chemometrics ; Near-infrared spectroscopy ; Selection (genetic algorithm) ; Multiplicative function ; Mathematics ; Computer science ; Dimension (graph theory) ; Multivariate statistics ; Pattern recognition (psychology) ; Statistics ; Artificial intelligence ; Machine learning ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Smart Agriculture and AI
Authors: S. N. Igidov | I. A. Gorbunova | A. Yu. Turyshev | D. A. Shipilovskikh | Danil A. Kozlov | Anna Rogova | Р. Р. Махмудов | P. S. Silaichev | Н. М. Игидов
Source: Chimica Techno Acta (article, 2022-12-01)
Field: Chemistry — Organic Chemistry

Synthesis, recyclization under the action of methanol and analgetic activity of N'-(5-aryl-2-oxofuran-3(2<i>H</i>)-ylidene)furan-2-carbohydrazides New methyl 5-aryl-1-(furan-2-carbonyl)-1H-pyrazole-3-carboxylates were obtained via decyclization reaction of N'-(5-aryl-2-oxofuran-3(2H)-ylidene)furan-2-carbohydrazides under the action of methanol. Starting N'-(5-aryl-2-oxofuran-3(2H)-ylidene)furan-2-carbohydrazides were obtained by intramolecular cyclization of substituted 4-aryl-2-[2-(furan-2-ylcarbonyl)hydrazinylidene]-4-oxobutanoic acids in propionic anhydride. The structure of the compounds obtained was confirmed by the 1H NMR spectroscopy, IR spectrometry and elemental analysis methods. Analgesic activity of some obtained compounds was studied by the “hot plate” method on outbred white mice of both sexes with intraperitoneal injection. Furan ; Chemistry ; Aryl ; Methanol ; Intramolecular force ; Elemental analysis ; Proton NMR ; Medicinal chemistry ; Organic chemistry Chemical synthesis and pharmacological studies ; Synthesis and Reactions of Organic Compounds ; Synthesis and Characterization of Pyrroles
Authors: Seth‐Frerich Fobian | Melissa Petzer | Melissa Vetten | Vanessa Steenkamp | Mary Gulumian | Werner Cordier
Source: Journal of Pharmacy and Pharmacology (article, 2022-02-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Mechanisms facilitating the uptake of carboxyl–polythene glycol-functionalized gold nanoparticles into multicellular spheroids Although poor uptake was observed, a multicellular spheroid model of A549 alveolar carcinoma cells was established, allowing for similar future uptake assessment of various NPs. Colloidal gold ; Multicellular organism ; Nanoparticle ; Chemistry ; Nanotechnology ; Materials science ; Biochemistry Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticle-Based Drug Delivery ; Advanced Nanomaterials in Catalysis
Authors: Yongling Ai | Harsha P. Gunawardena | Xuanwen Li | Yong-Ick Kim | Howard D. Dewald | Hao Chen
Source: Analytical Chemistry (article, 2022-08-26)
Field: Chemistry — Spectroscopy

Standard-Free Absolute Quantitation of Antibody Deamidation Degradation and Host Cell Proteins by Coulometric Mass Spectrometry Proteomic absolute quantitation strategies mainly rely on the use of synthetic stable isotope-labeled peptides or proteins as internal standards, which are highly costly and time-consuming to synthesize. To circumvent this limitation, we recently developed a coulometric mass spectrometry (CMS) approach for absolute quantitation of proteins without the use of standards, based on the electrochemical oxidation of oxidizable surrogate peptides, followed by mass spectrometry measurement of the peptide oxidation yield. Previously, CMS was only applied for single-protein quantitation. In this study, first, we demonstrated absolute quantitation of multiple proteins in a mixture (e.g., β-lactoglobulin B, α-lactalbumin, and carbonic anhydrase) by CMS in one run, without using any standards. The CMS quantitation result was validated with a traditional isotope dilution method. Second, CMS can be used for absolute quantitation of a low-level target protein in a mixture; for instance, 500 ppm of PLBL2, a problematic host cell protein (HCP), in the presence of a highly abundant monoclonal antibody (mAb) was successfully quantified by CMS with no use of standards. Third, taking one step further, this study demonstrated the unprecedented quantitative analysis of deamidated peptide products arising from the mAb heavy chain deamidation reaction. In particular, absolute quantitation of the deamidation succinimide intermediate which had not been performed before due to the lack of standard was conducted by CMS, for the first time. Overall, our data suggest that CMS has potential utilities for quantitative proteomics and biotherapeutic drug discovery. Deamidation ; Chemistry ; Quantitative proteomics ; Chromatography ; Mass spectrometry ; Isobaric labeling ; Peptide ; Succinimide ; Quantitative analysis (chemistry) ; Proteomics ; Selected reaction monitoring ; Tandem mass spectrometry ; Biochemistry ; Protein mass spectrometry ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development
Authors: Zhipeng Wu | Xiang Cai | Chengyun Zhang | Haoran Qiao | Yejian Wu | Yun Zhang | Xinqiao Wang | Xie Hai-ying | Feng Luo | Hongliang Duan
Source: Journal of Chemical Information and Modeling (article, 2022-09-21)
Field: Materials Science — Materials Chemistry

Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios In the face of low-resource reaction training samples, we construct a chemical platform for addressing small-scale reaction prediction problems. Using a self-supervised pretraining strategy called MAsked Sequence to Sequence (MASS), the Transformer model can absorb the chemical information of about 1 billion molecules and then fine-tune on a small-scale reaction prediction. To further strengthen the predictive performance of our model, we combine MASS with the reaction transfer learning strategy. Here, we show that the average improved accuracies of the Transformer model can reach 14.07, 24.26, 40.31, and 57.69% in predicting the Baeyer-Villiger, Heck, C-C bond formation, and functional group interconversion reaction data sets, respectively, marking an important step to low-resource reaction prediction. Transformer ; Computer science ; Sequence (biology) ; Reaction conditions ; Scale (ratio) ; Artificial intelligence ; Construct (python library) ; Machine learning ; Chemistry ; Engineering ; Organic chemistry ; Catalysis Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning in Bioinformatics
Authors: Cristian Ștefan Dumitriu | Alina Bărbulescu
Source: Materials (article, 2022-09-27)
Field: Materials Science — Materials Chemistry

Artificial Intelligence Models for the Mass Loss of Copper-Based Alloys under Cavitation Cavitation is a physical process that produces different negative effects on the components working in conditions where it acts. One is the materials' mass loss by corrosion-erosion when it is introduced into fluids under cavitation. This research aims at modeling the mass variation of three samples (copper, brass, and bronze) in a cavitation field produced by ultrasound in water, using four artificial intelligence methods-SVR, GRNN, GEP, and RBF networks. Utilizing six goodness-of-fit indicators (R<sup>2</sup>, MAE, RMSE, MAPE, CV, correlation between the recorded and computed values), it is shown that the best results are provided by GRNN, followed by SVR. The novelty of the approach resides in the experimental data collection and analysis. Cavitation ; Copper ; Materials science ; Metallurgy ; Mechanics ; Physics Metallurgy and Material Science ; Aluminum Alloy Microstructure Properties ; Material Properties and Applications
Authors: van der Oord | Matthias Sachs | Dávid Péter Kovács | Christoph Ortner | Gábor Csányi
Source: arXiv (Cornell University) (preprint, 2022-10-09)
Field: Materials Science — Materials Chemistry

Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials Data-driven interatomic potentials have emerged as a powerful class of surrogate models for {\it ab initio} potential energy surfaces that are able to reliably predict macroscopic properties with experimental accuracy. In generating accurate and transferable potentials the most time-consuming and arguably most important task is generating the training set, which still requires significant expert user input. To accelerate this process, this work presents \text{\it hyperactive learning} (HAL), a framework for formulating an accelerated sampling algorithm specifically for the task of training database generation. The key idea is to start from a physically motivated sampler (e.g., molecular dynamics) and add a biasing term that drives the system towards high uncertainty and thus to unseen training configurations. Building on this framework, general protocols for building training databases for alloys and polymers leveraging the HAL framework will be presented. For alloys, ACE potentials for AlSi10 are created by fitting to a minimal HAL-generated database containing 88 configurations (32 atoms each) with fast evaluation times of &lt;100 microsecond/atom/cpu-core. These potentials are demonstrated to predict the melting temperature with excellent accuracy. For polymers, a HAL database is built using ACE, able to determine the density of a long polyethylene glycol (PEG) polymer formed of 200 monomer units with experimental accuracy by only fitting to small isolated PEG polymers with sizes ranging from 2 to 32. Computer science ; Interatomic potential ; Task (project management) ; Process (computing) ; Set (abstract data type) ; Ab initio ; Work (physics) ; Molecular dynamics ; Materials science ; Chemistry ; Thermodynamics ; Physics ; Computational chemistry Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Computational Drug Discovery Methods
Authors: Jia Wen | Tingjun Chen | Jiayao Wang | Xiaohang Tuo | Yumei Gong | Jing Guo
Source: Journal of Applied Polymer Science (article, 2022-08-30)
Field: Materials Science — Polymers and Plastics

Study on the healing performance of poly(<i>ε</i>‐caprolactone) filled ultraviolet‐curable <scp>3D</scp> printed cyclic trimethylolpropane formal acrylate shape memory polymers Abstract The research and application of ultraviolet‐curable 3D printed shape memory polymers have been focused on artificial intelligence, bionic engineering, and medical devices, and so forth. However, this photopolymer has the disadvantages of low toughness and easy to be damaged. As a healing agent and toughening agent, the thermoplastic polymer polycaprolactone (PCL) is used to improve the utility value of 3D printed cyclic trimethylolpropane formal acrylate (CTFA) shape memory composites. The filling content of PCL is evaluated through multiscale observation, mechanical test, thermal analysis and comparison before and after healing. PCL with 5% filling content not only improves the flexibility and scratch healing ability of 3D printed samples, but also maintains the shape memory characteristics of the samples. The blending structure constructed by PCL and CTFA polymers plays an important role in balancing the various properties of the 3D printed composites. Materials science ; Polycaprolactone ; Trimethylolpropane ; Composite material ; Polymer ; Acrylate ; Toughness ; TMPTA ; Prepolymer ; Caprolactone ; Shape-memory polymer ; Polymerization ; Copolymer ; Polyurethane Polymer composites and self-healing ; Photopolymerization techniques and applications ; Additive Manufacturing and 3D Printing Technologies
Authors: Frederic Felsen | Karsten Reuter | Christoph Scheurer
Source: Chemical Engineering Journal (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

A model-free sparse approximation approach to robust formal reaction kinetics Accurate and transferable models of reaction kinetics are of key importance for chemical reactors on both laboratory and industrial scale. Usually, setting up such models requires a detailed mechanistic understanding of the reaction process and its interplay with the reactor setup. We present a data driven approach which analyzes the influence of process parameters on the reaction rate to identify locally approximated effective rate laws without prior knowledge and assumptions. The algorithm we propose determines relevant model terms from a polynomial ansatz employing well established statistical methods. For the optimization of the model parameters special emphasize is put on the robustness of the results by taking not only the quality of the fit but also the distribution of errors into account in a multi-objective optimization. We demonstrate the flexibility of this approach based on artificial kinetic data sets from microkinetic models. This way, we show that the kinetics of both the classical HBr reaction and a prototypical catalytic cycle are automatically reproduced. Further, combining our approach with experimental screening designs we illustrate how to efficiently explore kinetic regimes by using the example of the catalytic oxidation of CO. Robustness (evolution) ; Ansatz ; Flexibility (engineering) ; Computer science ; Chemical kinetics ; Process (computing) ; Reaction rate ; Experimental data ; Mathematical optimization ; Biological system ; Kinetics ; Biochemical engineering ; Chemistry ; Catalysis ; Mathematics ; Physics ; Engineering Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms ; Computational Drug Discovery Methods
Authors: Fangfang Chen | Dingwen Cao | Juanjuan Li | Yong Yan | Di Wu | Cheng Zhang | Lenan Gao | Zhaowei Guo | Shihong Ma | Huihui Yu | Pei Lin
Source: Frontiers in Chemistry (article, 2022-10-13)
Field: Materials Science — Materials Chemistry

Solution-processed thickness engineering of tellurene for field-effect transistors and polarized infrared photodetectors Research on elemental 2D materials has been experiencing a renaissance in the past few years. Of particular interest is tellurium (Te), which possesses many exceptional properties for nanoelectronics, photonics, and beyond. Nevertheless, the lack of a scalable approach for the thickness engineering and the local properties modulation remains a major obstacle to unleashing its full device potential. Herein, a solution-processed oxidative etching strategy for post-growth thickness engineering is proposed by leveraging the moderate chemical reactivity of Te. Large-area ultrathin nanosheets with well-preserved morphologies could be readily obtained with appropriate oxidizing agents, such as HNO<sub>2</sub>, H<sub>2</sub>O<sub>2</sub>, and KMnO<sub>4</sub>. Compared with the conventional physical thinning approaches, this method exhibits critical merits of high efficiency, easy scalability, and the capability of site-specific thickness patterning. The thickness reduction leads to substantially improved gate tunability of field-effect transistors with an enhanced current switching ratio of ∼10<sup>3</sup>, promoting the applications of Te in future logic electronics. The response spectrum of Te phototransistors covers the full range of short-wave infrared wavelength (1-3 μm), and the room-temperature responsivity and detectivity reach 0.96 AW<sup>-1</sup> and 2.2 × 10<sup>9</sup> Jones at the telecom wavelength of 1.55 μm, together with a favorable photocurrent anisotropic ratio of ∼2.9. Our study offers a new approach to tackling the thickness engineering issue for solution-grown Te, which could help realize the full device potential of this emerging p-type 2D material. Optoelectronics ; Materials science ; Responsivity ; Photocurrent ; Photonics ; Photodetector ; Electronics ; Transistor ; Nanotechnology ; Nanoelectronics ; Field-effect transistor ; Infrared ; Optics ; Electrical engineering ; Physics ; Engineering 2D Materials and Applications ; Perovskite Materials and Applications ; Advanced Thermoelectric Materials and Devices
Authors: Hyun Woo Park | Eunyeong Cho | Yun Zou | Sea‐Hoon Lee | Jae Ryung Choi | Sang‐Bok Lee | Kyeongwoon Chung | Se‐Hun Kwon | Jeonghun Kim | Hee Jung Lee
Source: Nanomaterials (article, 2022-12-21)
Field: Chemistry — Inorganic Chemistry

Synthesis of Yttria-Stabilized Zirconia Nanospheres from Zirconium-Based Metal–Organic Frameworks and the Dielectric Properties Yttria-stabilized zirconia (YSZ) nanospheres were synthesized by calcination at 900 °C after the adsorption of Y<sup>3+</sup> ions into the pores of a zirconium-based metal-organic framework (MOF). The synthesized 3YSZ (zirconia doped with 3 mol% Y<sub>2</sub>O<sub>3</sub>), 8YSZ (8 mol% Y<sub>2</sub>O<sub>3</sub>), and 30YSZ (30 mol% Y<sub>2</sub>O<sub>3</sub>) nanospheres were found to exhibit uniform sizes and shapes. Complex permittivity and complex permeability were carried out in K-band (i.e., 18-26.5 GHz) to determine their suitability for use as low-k materials in 5G communications. The real and imaginary parts of the permittivity of the sintered 3YSZ were determined to be 21.24 and 0.12, respectively, while those of 8YSZ were 22.80 and 0.16, and those of 30YSZ were 7.16 and 0.38. Control of the real part of the permittivity in the sintered YSZ was facilitated by modifying the Y<sub>2</sub>O<sub>3</sub> content, thereby rendering this material an electronic ceramic with potential for use in high-frequency 5G communications due to its excellent mechanical properties, high chemical resistance, and good thermal stability. In particular, it could be employed as an exterior material for electronic communication products requiring the minimization of information loss. Materials science ; Yttria-stabilized zirconia ; Zirconium ; Cubic zirconia ; Permittivity ; Ceramic ; Calcination ; Dielectric ; Chemical engineering ; Composite material ; Optoelectronics ; Metallurgy ; Organic chemistry ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; MXene and MAX Phase Materials
Authors: Xinying Liu | Weidong Ge
Source: Frontiers in Medicine (review, 2022-02-22)
Field: Materials Science — Biomaterials

The Emerging Role of Ultrasonic Nanotechnology for Diagnosing and Treatment of Diseases Nanotechnology has been commonly used in a variety of applications in recent years. Nanomedicine has also gotten a lot of attention in the medical and treatment fields. Ultrasonic technology is already being used in research as a powerful tool for manufacturing nonmaterial and in the decoration of catalyst supports for energy applications and material processing. For the development of nanoparticles and the decoration of catalytic assisted powders with nanoparticles, low or high-frequency Ultrasonic are used. The Ultrasonic is frequently used in joint venture with the nanotechnology from the past few years and bring tremendous success in various diseases diagnosing and treatment. Numerous kinds of nanoparticles are fabricated with desired capabilities and targeted toward different targets. This review first highlights the Ultrasonic Treatment and processing of Nanoparticles for Pharmaceuticals. Next, we explain various nanoparticles with ultrasonic technology for different diagnosing and treatment of various diseases. Finally, we explain the challenges face by current approaches for their translation in clinics. Nanomedicine ; Nanotechnology ; Ultrasonic sensor ; Applications of nanotechnology ; Nanoparticle ; Materials science ; Computer science ; Medicine Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Gold and Silver Nanoparticles Synthesis and Applications