jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Christian Ieritano | Arthur Lee | Jeff Crouse | Zack Bowman | Nour Mashmoushi | Paige M. Crossley | Benjamin P. Friebe | J. Larry Campbell | W. Scott Hopkins
Source: Analytical Chemistry (article, 2021-06-16)
Field: Chemistry — Spectroscopy

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (<i>m</i>/<i>z</i>: 86-683 Da and CCS 110-236 Å<sup>2</sup>) was measured in a N<sub>2</sub> environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's <i>m</i>/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform. Ion-mobility spectrometry ; Chemistry ; Calibration ; Ion ; Analytical Chemistry (journal) ; Analyte ; Differential (mechanical device) ; Collision ; Voltage ; Mass spectrometry ; Computational physics ; Chromatography ; Computer science ; Statistics ; Physics Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Analytical Chemistry and Chromatography
Authors: Taoreed O. Owolabi | Tawfik A. Saleh | Olubosede Olusayo | Miloud Souiyah | Oluwatoba Emmanuel Oyeneyin
Source: Journal of Nanomaterials (article, 2021-08-18)
Field: Materials Science — Materials Chemistry

Modeling the Specific Surface Area of Doped Spinel Ferrite Nanomaterials Using Hybrid Intelligent Computational Method Spinel ferrites nanomaterials are magnetic semiconductors with excellent chemical, magnetic, electrical, and optical properties which have rendered the materials useful in many technological driven applications such as solar hydrogen production, data storage, magnetic sensing, converters, inductors, spintronics, and catalysts. The surface area of these nanomaterials contributes significantly to their targeted applications as well as the observed physical and chemical features. Experimental doping has shown a great potential in enhancing and tuning the specific surface area of spinel ferrite nanomaterials while the attributed experimental challenges call for viable theoretical model that can estimate the surface area of doped spinel ferrite nanomaterials with high degree of precision. This work develops stepwise regression (STWR) and hybrid genetic algorithm-based support vector regression (GBSVR) intelligent model for estimating specific surface area of doped spinel ferrite nanomaterials using lattice parameter and the size of nanoparticle as descriptors to the models. The developed hybrid GBSVR model performs better than STWR model with the performance improvement of 7.51% and 22.68%, respectively, using correlation coefficient and root mean square error as performance metrics when validated with experimentally measured specific surface area of doped spinel ferrite nanomaterials. The developed GBSVR model investigates the influence of nickel, yttrium, and lanthanum nanoparticles on the specific surface area of different classes of spinel ferrite nanomaterials, and the obtained results agree excellently well with the measured values. The accuracy and precision characterizing the developed model would be of immense importance in enhancing specific surface area of doped spinel ferrite nanomaterial prediction with circumvention of experimental stress coupled with reduced cost. Materials science ; Nanomaterials ; Spinel ; Ferrite (magnet) ; Doping ; Specific surface area ; Nanotechnology ; Response surface methodology ; Optoelectronics ; Computer science ; Composite material ; Metallurgy ; Machine learning ; Catalysis Magnetic Properties and Synthesis of Ferrites ; Machine Learning and ELM
Authors: Olivier Guillon
Source: International Journal of Ceramic Engineering & Science (article, 2021-03-19)
Field: Materials Science — Ceramics and Composites

Ceramic materials for energy conversion and storage: A perspective Abstract Advanced ceramic materials with tailored properties are at the core of established and emerging energy technologies. Applications encompass high‐temperature power generation, energy harvesting, and electrochemical conversion and storage. New opportunities for material design, the importance of processing and material integration, and the need for long‐term testing under realistic conditions are highlighted in the present perspective. Electrochemical energy storage ; Energy storage ; Ceramic ; Perspective (graphical) ; Energy transformation ; Materials science ; Process engineering ; Electrochemical energy conversion ; Nanotechnology ; Systems engineering ; Computer science ; Power (physics) ; Engineering ; Electrochemistry ; Metallurgy ; Supercapacitor Advanced ceramic materials synthesis ; Advancements in Solid Oxide Fuel Cells ; Advanced Battery Materials and Technologies
Authors: Agustín Blázquez-Martín | Ester Verde‐Sesto | Angel J. Moreno | Arantxa Arbe | Juan Colmenero | José A. Pomposo
Source: Polymers (review, 2021-01-18)
Field: Chemistry — Organic Chemistry

Advances in the Multi-Orthogonal Folding of Single Polymer Chains into Single-Chain Nanoparticles The folding of certain proteins (e.g., enzymes) into perfectly defined 3D conformations via multi-orthogonal interactions is critical to their function. Concerning synthetic polymers chains, the "folding" of individual polymer chains at high dilution via intra-chain interactions leads to so-called single-chain nanoparticles (SCNPs). This review article describes the advances carried out in recent years in the folding of single polymer chains into discrete SCNPs via multi-orthogonal interactions using different reactive chemical species where intra-chain bonding only occurs between groups of the same species. First, we summarize results from computer simulations of multi-orthogonally folded SCNPs. Next, we comprehensively review multi-orthogonally folded SCNPs synthesized via either non-covalent bonds or covalent interactions. Finally, we conclude by summarizing recent research about multi-orthogonally folded SCNPs prepared through both reversible (dynamic) and permanent bonds. Single chain ; Folding (DSP implementation) ; Covalent bond ; Polymer ; Nanoparticle ; Chain (unit) ; Protein folding ; Materials science ; Nanotechnology ; Chemistry ; Chemical physics ; Physics ; Organic chemistry Advanced Polymer Synthesis and Characterization ; biodegradable polymer synthesis and properties ; Polymer Surface Interaction Studies
Authors: Francisco José Alguacil | Félix A. López
Source: Preprints.org (preprint, 2021-05-25)
Field: Chemistry — Analytical Chemistry

Organic Dyes Versus Adsorption Processing Even in the first quarter of XXI century, the presence of organic dyes in wastewaters is a normal occurrence in a series of countries, and being these compounds toxics, their removal from these waters is of a necessity. Among the separation technologies, adsorption processing appeared as one of the most widely used to reach this goal. The present work reviewed the most recent approaches (first half of 2021 year) about the use of a variety of adsorbents on the removal of, also, a variety of organic dyes of different nature. Adsorption ; Quarter (Canadian coin) ; Variety (cybernetics) ; Environmental chemistry ; Environmental science ; Chemistry ; Waste management ; Organic chemistry ; Computer science ; Engineering ; Geography ; Artificial intelligence ; Archaeology Dye analysis and toxicity ; Synthesis of Tetrazole Derivatives ; Water Quality Monitoring and Analysis
Authors: Shiyang He | Yang Yang | Zhili Li | Jiye Zhang | Chenyang Wang | Wenqing Zhang | Jun Luo
Source: Science China Materials (article, 2021-02-04)
Field: Materials Science — Materials Chemistry

A general strategy for high-throughput experimental screening of promising bulk thermoelectric materials Materials science ; Thermoelectric effect ; Characterization (materials science) ; Thermoelectric materials ; Throughput ; Nanotechnology ; Thermal conductivity ; Composite material ; Computer science ; Thermodynamics Machine Learning in Materials Science ; Advanced Thermoelectric Materials and Devices ; Thermal properties of materials
Authors: Liliana Roşu | Cristian–Dragos Varganici | Dan Roşu | Ștefan Oprea
Source: Polymers (article, 2021-01-07)
Field: Materials Science — Polymers and Plastics

Effect of Thermal Aging on the Physico-Chemical and Optical Properties of Poly(ester urethane) Elastomers Designed for Passive Damping (Pads) of the Railway The aim of this study consists of monitoring the effect of thermal aging on the physico-chemical and optical properties of poly(ester urethane) elastomers designed as damping materials for railways. The materials were obtained by polyaddition in two stages in melt, resulting in regular structures. The structural modifications during the thermal aging of the samples were monitored using FTIR, color changes, TGA in non-isothermal and isothermal conditions, DSC and physico-mechanical measurements. The structural regularity of the rigid and flexible segments maintained the good mechanical properties of the structures up to 200 h of thermal aging at the elevated temperatures of 40 °C, 70 °C, 100 °C and 130 °C. It was observed that at 40 °C and low exposure times, changes occur mainly to the carbonyl groups of the soft segments. At higher temperatures and longer exposure times urethane groups were affected. Extended thermal aging led to significant changes in thermo-mechanical and optical properties. Elastomer ; Materials science ; Isothermal process ; Composite material ; Thermal ; Fourier transform infrared spectroscopy ; Chemical engineering ; Thermodynamics Polymer Nanocomposites and Properties ; Polymer composites and self-healing ; Tribology and Wear Analysis
Authors: Martyna Moskal | Wiktor Beker | Sara Szymkuć | Bartosz A. Grzybowski
Source: Angewandte Chemie (article, 2021-04-20)
Field: Materials Science — Materials Chemistry

Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions This work describes a method to vectorize and Machine-Learn, ML, non-covalent interactions responsible for scaffold-directed reactions important in synthetic chemistry. Models trained on this representation predict correct face of approach in ca. 90 % of Michael additions or Diels-Alder cycloadditions. These accuracies are significantly higher than those based on traditional ML descriptors, energetic calculations, or intuition of experienced synthetic chemists. Our results also emphasize the importance of ML models being provided with relevant mechanistic knowledge; without such knowledge, these models cannot easily "transfer-learn" and extrapolate to previously unseen reaction mechanisms. Intuition ; Scaffold ; Computer science ; Covalent bond ; Machine learning ; Artificial intelligence ; Chemistry ; Selectivity ; Combinatorial chemistry ; Cognitive science ; Organic chemistry ; Programming language ; Psychology ; Catalysis Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Fatima Ghassan Alabtah | E. Mahdi | Marwan Khraisheh
Source: Materials (article, 2021-10-29)
Field: Materials Science — Materials Chemistry

External Corrosion Behavior of Steel/GFRP Composite Pipes in Harsh Conditions In this study, we report on the corrosion behavior of hybrid steel/glass fiber-reinforced polymer (GFRP) composite pipes under harsh corrosive conditions for prolonged durations. Specimens were immersed in highly concentrated solutions of hydrochloric acid, sodium chloride, and sulfuric acid for durations up to one year. Detailed qualitative analysis using scanning electron microscopy (SEM), X-ray diffraction analysis (XRD), and energy-dispersive X-ray spectroscopy (EDX) is presented. It is shown that the hybrid pipes have excellent corrosion resistance with a corrosion rate of less than 1% of the corrosion rate for conventional steel pipes. That low corrosion rate can be attributed to the formation of pores in the GFRP layer due to increased absorption and saturation moisture in the material with increased soaking time. This can be reduced or even prevented through a more controlled process for fabricating the protective layers. These promising results call for more utilization of GFRP protective layers in novel design concepts to control corrosion. Corrosion ; Materials science ; Fibre-reinforced plastic ; Scanning electron microscope ; Composite material ; Sulfuric acid ; Composite number ; Glass fiber ; Hydrochloric acid ; Chloride ; Metallurgy Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Javier Espinoza-Vergara | Paulo Molina | Mariana Walter | Miguel Gulppi | Nelson Vejar | Francisco Melo | Marcela Urzúa | Hugo Muñoz | José H. Zagal | Xiaorong Zhou | Manuel Azócar | Maritza Páez
Source: Frontiers in Bioengineering and Biotechnology (article, 2021-12-06)
Field: Chemistry — Electrochemistry

Effect of pH on the Electrochemical Behavior of Hydrogen Peroxide in the Presence of Pseudomonas aeruginosa The influence of pH on the electrochemical behavior of hydrogen peroxide in the presence of <i>Pseudomonas aeruginosa</i> was investigated using electrochemical techniques. Cyclic and square wave voltammetry were used to monitor the enzymatic activity. A modified cobalt phthalocyanine (CoPc) carbon electrode (OPG), a known catalyst for reducing O<sub>2</sub> to H<sub>2</sub>O<sub>2</sub>, was used to detect species resulting from the enzyme activity. The electrolyte was a sterilized aqueous medium containing Mueller-Hinton (MH) broth. The open-circuit potential (OCP) of the <i>Pseudomonas aeruginosa</i> culture in MH decreased rapidly with time, reaching a stable state after 4 h. Peculiarities in the E / I response were observed in voltammograms conducted in less than 4 h of exposure to the culture medium. Such particular E/I responses are due to the catalase's enzymatic action related to the conversion of hydrogen peroxide to oxygen, confirming the authors' previous findings related to the behavior of other catalase-positive microorganisms. The enzymatic activity exhibits maximum activity at pH 7.5, assessed by the potential at which oxygen is reduced to hydrogen peroxide. At higher or lower pHs, the oxygen reduction reaction (ORR) occurs at higher overpotentials, i.e., at more negative potentials. In addition, and to assess the influence of bacterial adhesion on the electrochemical behavior, measurements of the bacterial-substrate metal interaction were performed at different pH using atomic force microscopy. Hydrogen peroxide ; Chemistry ; Catalase ; Inorganic chemistry ; Cyclic voltammetry ; Electrochemistry ; Catalysis ; Nuclear chemistry ; Enzyme ; Electrode ; Biochemistry Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Conducting polymers and applications
Authors: Nakul Rampal | Abdulmalik Ajenifuja | Andi Tao | Christopher Balzer | Matthew Cummings | Arwyn Evans | Rocío Bueno-Pérez | David J. Law | Leslie W. Bolton | Camille Petit | Flor R. Siperstein | Martin P. Attfield | Megan Jobson | Peyman Z. Moghadam | David Fairen‐Jiménez
Source: Chemical Science (article, 2021-01-01)
Field: Chemistry — Inorganic Chemistry

The development of a comprehensive toolbox based on multi-level, high-throughput screening of MOFs for CO/N<sub>2</sub>separations The separation of CO/N<sub>2</sub> mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal-organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process - <i>i.e.</i> an optimal material requires fulfillment of several criteria simultaneously - makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications. Toolbox ; Visualization ; Process (computing) ; Computer science ; Adsorption ; Throughput ; Development (topology) ; Process development ; Nanotechnology ; Process engineering ; Materials science ; Chemistry ; Data mining ; Engineering ; Mathematics ; Physical chemistry Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science ; Gas Sensing Nanomaterials and Sensors
Authors: Jonathan M. Polfus | Thijs Peters | Rune Bredesen | Ole Martin Løvvik
Source: Physical Chemistry Chemical Physics (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Vacancy diffusion in palladium hydrides The self-diffusion coefficients of palladium in PdHx (x = 0, 0.25, 0.5, 0.75, 1) were studied using density functional theory to obtain the required thermodynamic and kinetic parameters. The enthalpy of migration decreased from 0.95 eV for Pd to 0.78 eV for PdH. The enthalpy of vacancy formation exhibited a substantial decrease from about 1.1 eV in Pd to 0.4 eV in PdH, which was ascribed to successive filling of antibonding states weakening the Pd-Pd bonds. Concurrently, the Arrhenius pre-exponential was significantly reduced from 4.75 × 10-3 cm2 s-1 for Pd to 5.67 × 10-9 cm2 s-1 for PdH due to softening of the vibrational modes that determine the entropy of vacancy formation and initial/transition state frequencies. A linear correlation between the logarithm of the pre-exponential and the activation energy was interpreted as enthalpy-entropy compensation (Meyer-Neldel rule). The Pd self-diffusion coefficients in the hydrides were within 1 order of magnitude of that in pure palladium above 200 °C for hydrogen pressures up to at least 107 Pa. Palladium ; Vacancy defect ; Diffusion ; Materials science ; Chemistry ; Crystallography ; Thermodynamics ; Organic chemistry ; Catalysis ; Physics Hydrogen Storage and Materials ; Nuclear Materials and Properties ; Advanced Chemical Physics Studies
Authors: Mahsa Mirzaei | Irini Furxhi | Finbarr Murphy | Martin Mullins
Source: Coatings (article, 2021-12-13)
Field: Materials Science — Materials Chemistry

A Supervised Machine-Learning Prediction of Textile’s Antimicrobial Capacity Coated with Nanomaterials Textile materials, due to their large surface area and moisture retention capacity, allow the growth of microorganisms, causing undesired effects on the textile and on the end-users. The textile industry employs nanomaterials (NMs)/composites and nanofibers to enhance textile features such as water/dirt-repellent, conductivity, antistatic properties, and enhanced antimicrobial properties. As a result, textiles with antimicrobial properties are an area of interest to both manufacturers and researchers. In this study, we present novel regression models that predict the antimicrobial activity of nano-textiles after several washes. Data were compiled following a literature review, and variables related to the final product, such as the experimental conditions of nano-coating (finishing technologies) and the type of fabric, the physicochemical (p-chem) properties of NMs, and exposure variables, were extracted manually. The random forest model successfully predicted the antimicrobial activity with encouraging results of up to 70% coefficient of determination. Attribute importance analysis revealed that the type of NM, shape, and method of application are the primary features affecting the antimicrobial capacity prediction. This tool helps scientists to predict the antimicrobial activity of nano-textiles based on p-chem properties and experimental conditions. In addition, the tool can be a helpful part of a wider framework, such as the prediction of products functionality embedded into a safe by design paradigm, where products’ toxicity is minimized, and functionality is maximized. Antimicrobial ; Textile ; Textile industry ; Biochemical engineering ; Materials science ; Computer science ; Process engineering ; Composite material ; Engineering ; Chemistry Nanoparticles: synthesis and applications ; Microplastics and Plastic Pollution ; Dyeing and Modifying Textile Fibers
Authors: Zhong Wu | Jingyun Chen | Qifeng Li | Da‐Hai Xia | Yida Deng | Yiwen Zhang | Zhenbo Qin
Source: Materials (article, 2021-04-16)
Field: Materials Science — Materials Chemistry

Preparation and Thermal Conductivity of Epoxy Resin/Graphene-Fe3O4 Composites By modifying the bonding of graphene (GR) and Fe<sub>3</sub>O<sub>4</sub>, a stable structure of GR-Fe<sub>3</sub>O<sub>4</sub>, namely magnetic GR, was obtained. Under the induction of a magnetic field, it can be orientated in an epoxy resin (EP) matrix, thus preparing EP/GR-Fe<sub>3</sub>O<sub>4</sub> composites. The effects of the content of GR and the degree of orientation on the thermal conductivity of the composites were investigated, and the most suitable Fe<sub>3</sub>O<sub>4</sub> load on GR was obtained. When the mass ratio of GR and Fe<sub>3</sub>O<sub>4</sub> was 2:1, the thermal conductivity could be increased by 54.8% compared with that of pure EP. Meanwhile, EP/GR-Fe<sub>3</sub>O<sub>4</sub> composites had a better thermal stability, dynamic thermomechanical properties, and excellent electrical insulation properties, which can meet the requirements of electronic packaging materials. Materials science ; Composite material ; Epoxy ; Thermal conductivity ; Thermal stability ; Graphene ; Composite number ; Thermal ; Chemical engineering High voltage insulation and dielectric phenomena ; Thermal properties of materials ; Graphene research and applications