jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Maryam Azizi‐Lalabadi | Leila Rafiei | Bahark Divband | Ali Ehsani
Source: Food Science & Nutrition (article, 2020-10-19)
Field: Materials Science — Biomaterials

Active packaging for Salmon stored at refrigerator with Polypropylene nanocomposites containing 4A zeolite, ZnO nanoparticles, and green tea extract In this study, three types of Polypropylene-based (PP) films (two active nanocomposites and one control film) containing zinc oxide nanoparticles (ZnO NPs), 4A zeolite (4A Z), and green tea extract (GTE) were studied as modern active packaging's that can adjust the release of antimicrobial agents. The influence of PP nanocomposite with 3% (w/w) ZnO NPs/4A Z/GTE (treatment 1) and 6% (w/w) ZnO NPs/4A Z/GTE (treatment 2) on controlling microbial growth and preserving the sensory and chemical qualities of Salmon over nine days of storage at 4 ± 1°C was evaluated. The disk diffusion test revealed inhibition zones in the range of 10.98 ± 0.03 to 13.42 ± 0.01 m for treatments 1 and 2, respectively; the nanocomposite film with 6% ZnO NPs/4A Z/GTE had the highest antimicrobial effect against Gram-negative bacteria (<i>p</i> < .05). Chemical analysis revealed that the initial peroxide value of Salmon was 0.68 ± 0.0 mEq/kg, which increased by day 9 to 12.3 ± 0.03 mEq/kg in the control sample, but rising only to 9.9 ± 0.01 and 7.3 ± 0.02 mEq/kg in treatments 1 and 2, respectively (<i>p</i> < .05). The shelf life of Salmon given treatment 2 increased significantly to nine days relative to the control. Accordingly, these nanocomposite films are promising as new active packaging for preventing microbial growth and preserving the quality of salmon. Nanocomposite ; Polypropylene ; Active packaging ; Green tea extract ; Bacterial growth ; Nuclear chemistry ; Shelf life ; Antimicrobial ; Materials science ; Nanoparticle ; Chemistry ; Food science ; Chemical engineering ; Nanotechnology ; Food packaging ; Bacteria ; Composite material ; Organic chemistry ; Green tea ; Biology Nanocomposite Films for Food Packaging ; Nanoparticles: synthesis and applications ; Antimicrobial agents and applications
Authors: Lukas Steinmetz | Christoph Geers | Sandor Balog | Mathias Bonmarin | Laura Rodríguez‐Lorenzo | Patricia Taladriz‐Blanco | Barbara Rothen‐Rutishauser | Alke Petri‐Fink
Source: Nanoscale Advances (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

A comparative study of silver nanoparticle dissolution under physiological conditions Upon dissolution of silver nanoparticles, silver ions are released into the environment, which are known to induce adverse effects. However, since dissolution studies are predominantly performed in water and/or at room temperature, the effects of biological media and physiologically relevant temperature on the dissolution rate are not considered. Here, we investigate silver nanoparticle dissolution trends based on their plasmonic properties under biologically relevant conditions, <i>i.e.</i> in biological media at 37 °C over a period of 24 h. The studied nanoparticles, surface-functionalized with polyvinylpyrrolidone, beta-cyclodextrin/polyvinylpyrrolidone, and starch/polyvinylpyrrolidone, were analysed by UV-Vis spectroscopy, lock-in thermography and depolarized dynamic light scattering to evaluate the influence of these coatings on silver nanoparticle dissolution. Transmission electron microscopy was employed to visualize the reduction of the nanoparticle core diameters. Consequently, the advantages and limitations of these analytical techniques are discussed. To assess the effects of temperature on the degree of dissolution, the results of experiments performed at biological temperature were compared to those obtained at room temperature. Dissolution is often enhanced at elevated temperatures, but has to be determined individually for every specific condition. Furthermore, we evaluated potential nanoparticle aggregation. Our results highlight that additional surface coatings do not necessarily hinder the dissolution or aggregation of silver nanoparticles. Dissolution ; Polyvinylpyrrolidone ; Silver nanoparticle ; Nanoparticle ; Materials science ; Chemical engineering ; Dynamic light scattering ; Nanotechnology ; Transmission electron microscopy ; Polymer chemistry Nanoparticles: synthesis and applications ; Air Quality and Health Impacts ; Laser-Ablation Synthesis of Nanoparticles
Authors: Bernd Bauerhenne | Vladimir Lipp | Tobias Zier | Eeuwe S. Zijlstra | Martı́n E. Garcia
Source: Physical Review Letters (article, 2020-02-25)
Field: Materials Science — Materials Chemistry

Self-Learning Method for Construction of Analytical Interatomic Potentials to Describe Laser-Excited Materials Large-scale simulations using interatomic potentials provide deep insight into the processes occurring in solids subject to external perturbations. The atomistic description of laser-induced ultrafast nonthermal phenomena, however, constitutes a particularly difficult case and has so far not been possible on experimentally accessible length scales and timescales because of two main reasons: (i) ab initio simulations are restricted to a very small number of atoms and ultrashort times and (ii) simulations relying on electronic temperature- (T_{e}) dependent interatomic potentials do not reach the necessary ab initio accuracy. Here we develop a self-learning method for constructing T_{e}-dependent interatomic potentials which permit ultralarge-scale atomistic simulations of systems suddenly brought to extreme nonthermal states with density-functional theory (DFT) accuracy. The method always finds the global minimum in the parameter space. We derive a highly accurate analytical T_{e}-dependent interatomic potential Φ(T_{e}) for silicon that yields a remarkably good description of laser-excited and -unexcited Si bulk and Si films. Using Φ(T_{e}) we simulate the laser excitation of Si nanoparticles and find strong damping of their breathing modes due to nonthermal melting. Interatomic potential ; Excited state ; Ab initio ; Excitation ; Physics ; Laser ; Length scale ; Atomic physics ; Materials science ; Molecular dynamics ; Molecular physics ; Quantum mechanics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Advanced Electron Microscopy Techniques and Applications
Authors: Suha Dadou | Zoé Senta-Loys | Ammar Almajaan | Shu Li | David S. Jones | Anne Marie Healy | Yiwei Tian | Gavin P. Andrews
Source: International Journal of Pharmaceutics (article, 2020-04-28)
Field: Materials Science — Materials Chemistry

The development and validation of a quality by design based process analytical tool for the inline quantification of Ramipril during hot-melt extrusion Quality by Design ; Critical quality attributes ; Process analytical technology ; Calibration ; Design of experiments ; Computer science ; Process validation ; Process engineering ; Extrusion ; Pharmaceutical manufacturing ; Process (computing) ; Materials science ; Mathematics ; Chemistry ; Work in process ; Particle size ; Engineering ; Verification and validation ; Statistics Crystallization and Solubility Studies ; Protein purification and stability ; Drug Solubulity and Delivery Systems
Authors: Olivier Spitz | Jiagui Wu | Andreas Herdt | G. Maisons | Mathieu Carras | Wolfgang Elsäßer | Chee-Wei Wong | Frédéric Grillot
Source: Advanced Photonics (article, 2020-10-21)
Field: Chemistry — Spectroscopy

Extreme events in quantum cascade lasers We demonstrate experimentally that mid-infrared quantum cascade lasers (QCLs) operating under external optical feedback exhibit extreme pulses. These events can be triggered by adding small amplitude periodic modulation, with the highest success rate for the case of a pulse-up excitation. These findings broaden the potential applications for QCLs, which have already been proven to be a semiconductor laser of interest for spectroscopic applications and countermeasure systems. The ability to trigger extreme events paves the way for optical neuron-like systems where information propagates as a result of high intensity bursts. Cascade ; Laser ; Quantum ; Modulation (music) ; Physics ; Pulse (music) ; Optoelectronics ; Countermeasure ; Amplitude ; Semiconductor laser theory ; Excitation ; Quantum well ; Optics ; Materials science ; Quantum mechanics ; Acoustics ; Engineering Spectroscopy and Laser Applications ; Nonlinear Dynamics and Pattern Formation ; Neural Networks and Reservoir Computing
Authors: Jasmin Reiner | Kristin Protte | Jörg Hinrichs
Source: ChemEngineering (article, 2020-07-19)
Field: Chemistry — Analytical Chemistry

Investigation of the Applicability of Raman Spectroscopy as Online Process Control during Consumer Milk Production Online detection of product defects using fast spectroscopic measurements is beneficial for producers in the dairy industry since it allows readjustment of product characteristics or redirection of product streams during production. Raman spectroscopy has great potential for such application due to the fast and simple measurement. Its suitability as online sensor for process control was investigated at typical control points in consumer milk production being raw milk storage, standardization, and heat treatment. Additionally, the appropriateness of Raman spectroscopy to act as indicator for product application parameters was investigated using the example of barista foam. To assess the suitability of a pure online system, the merit of Raman spectra was evaluated by a principal component analysis (PCA). Thereby, proteolytic spoilage due to the presence of extracellular enzymes of Pseudomonas sp. was detected and samples based on the applied heat treatment (extended shelf life (ESL) and ultra-high temperature (UHT)) could be separated. A correlation of the content of free fatty acids and foam stability with spectra of the respective milk samples was found, allowing a prediction of the technofunctional quality criterion “Barista” suitability of a UHT milk. The results underlined the suitability of Raman spectroscopy for the detection of deviations from a defined product standard of consumer milk. Raman spectroscopy ; Principal component analysis ; Raw milk ; Food science ; Food spoilage ; Process engineering ; Raw material ; Materials science ; Chemistry ; Analytical Chemistry (journal) ; Computer science ; Chromatography ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Listeria monocytogenes in Food Safety
Authors: Florina-Dorina Covaciu | Camelia Berghian-Groșan | Ioana Feher | Dana Alina Măgdaş
Source: Applied Sciences (article, 2020-11-24)
Field: Chemistry — Analytical Chemistry

Edible Oils Differentiation Based on the Determination of Fatty Acids Profile and Raman Spectroscopy—A Case Study This study proposes a comparison between two analytical techniques for edible oil classification, namely gas-chromatography equipped with a flame ionization detector (GC-FID), which is an acknowledged technique for fatty acid analysis, and Raman spectroscopy, as a real time noninvasive technique. Due to the complexity of the investigated matrix, we used both methods in connection with chemometrics processing for a quick and valuable evaluation of oils. In addition to this, the possible adulteration of investigated oil varieties (sesame, hemp, walnut, linseed, sea buckthorn) with sunflower oil was also tested. In order to extract the meaningful information from the experimental data set, a supervised chemometric technique, namely linear discriminant analysis (LDA), was applied. Moreover, for possible adulteration detection, an artificial neural network (ANN) was also employed. Based on the results provided by ANN, it was possible to detect the mixture between sea buckthorn and sunflower oil. Chemometrics ; Linear discriminant analysis ; Sunflower oil ; Chromatography ; Chemistry ; Vegetable oil ; Pattern recognition (psychology) ; Artificial intelligence ; Mathematics ; Food science ; Computer science Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies
Authors: Laura‐Jayne A. Ellis | Iseult Lynch
Source: Environmental Science Nano (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Mechanistic insights into toxicity pathways induced by nanomaterials in <i>Daphnia magna</i> from analysis of the composition of the acquired protein corona Secreted corona composition of Ag and TiO<sub>2</sub> NMs, evaluated after 7 days of continuous exposure to daphnids, provides important insights into the biological pathways perturbed by the NMs. Daphnia magna ; Toxicity ; Nanotoxicology ; Composition (language) ; Nanomaterials ; Chemistry ; Environmental chemistry ; Biophysics ; Biology ; Nanotechnology ; Materials science ; Organic chemistry Nanoparticles: synthesis and applications ; Electrochemical Analysis and Applications ; Environmental Toxicology and Ecotoxicology
Authors: Joseph M. Chemmarappally | Henry Pegram | Neranga Abeywickrama | Enzo Fornari | Alan J. Hargreaves | Luigi A. De Girolamo | Robert S. Stevens
Source: Scientific Reports (article, 2020-02-17)
Field: Materials Science — Biomaterials

A co-culture nanofibre scaffold model of neural cell degeneration in relevance to Parkinson’s disease Current therapeutic strategies for Parkinson's disease (PD) aim to delay progression or replace damaged neurons by restoring the original neuronal structures. The poor regenerative capacity of neural tissue highlights the need for the development of cellular environments to model the pathogenesis of PD. In the current work, we have characterised the growth, survival and response to PD mimetics of human SH-SY5Y neuroblastoma and U-87MG glioblastoma cell lines cultured on polyacrylonitrile (PAN) and Jeffamine® doped polyacrylonitrile (PJ) nano-scaffolds. Differentiation induced by a range of agents was evaluated by immunoassays of neural protein biomarkers. PAN and PJ nanofibre scaffolds provided suitable three-dimensional (3D) environment to support the growth, differentiation and network formation of dopaminergic neuron- and astrocyte-like cell populations, respectively. The scaffolds selectively supported the survival and differentiation of both cell populations with prolonged neuronal survival when exposed to PD mimetics in the presence of astrocytes in a co-culture model. Such 3D nanoscaffold-based assays could aid our understanding of the molecular basis of PD mimetic-induced Parkinsonism and the discovery of neuroprotective agents. Dopaminergic ; Neuroscience ; Neuroblastoma ; Cellular model ; Polyacrylonitrile ; Neural cell ; Neural stem cell ; Parkinson's disease ; Cellular differentiation ; Cell culture ; Scaffold ; Neuroprotection ; Astrocyte ; Neuron ; Chemistry ; Biology ; Medicine ; Cell ; Cell biology ; Disease ; Dopamine ; Stem cell ; Pathology ; Central nervous system ; Biomedical engineering ; Biochemistry ; Gene Electrospun Nanofibers in Biomedical Applications ; Nerve injury and regeneration ; Graphene and Nanomaterials Applications
Authors: Ryuichi Kato | Masahiko Hiraki | Yusuke Yamada | Mikio Tanabe | Toshiya Senda
Source: Acta Crystallographica Section F Structural Biology Communications (article, 2020-12-18)
Field: Materials Science — Materials Chemistry

A fully automated crystallization apparatus for small protein quantities In 2003, a fully automated protein crystallization and monitoring system (PXS) was developed to support the structural genomics projects that were initiated in the early 2000s. In PXS, crystallization plates were automatically set up using the vapor-diffusion method, transferred to incubators and automatically observed according to a pre-set schedule. The captured images of each crystallization drop could be monitored through the internet using a web browser. While the screening throughput of PXS was very high, the demands of users have gradually changed over the ensuing years. To study difficult proteins, it has become important to screen crystallization conditions using small amounts of proteins. Moreover, membrane proteins have become one of the main targets for X-ray crystallography. Therefore, to meet the evolving demands of users, PXS was upgraded to PXS2. In PXS2, the minimum volume of the dispenser is reduced to 0.1 µl to minimize the amount of sample, and the resolution of the captured images is increased to five million pixels in order to observe small crystallization drops in detail. In addition to the 20°C incubators, a 4°C incubator was installed in PXS2 because crystallization results may vary with temperature. To support membrane-protein crystallization, PXS2 includes a procedure for the bicelle method. In addition, the system supports a lipidic cubic phase (LCP) method that uses a film sandwich plate and that was specifically designed for PXS2. These improvements expand the applicability of PXS2, reducing the bottleneck of X-ray protein crystallography. Crystallization ; Bottleneck ; Protein crystallization ; Computer science ; Materials science ; Chemical engineering ; Engineering ; Embedded system Enzyme Structure and Function ; Protein Structure and Dynamics ; Metabolomics and Mass Spectrometry Studies
Authors: Dejian Dai | Tao Jiang | Wei Lu | Xuan Shen | Rui Xiu | Jingwei Zhang
Source: Sensors (article, 2020-09-25)
Field: Chemistry — Analytical Chemistry

Nondestructive Detection for Egg Freshness Based on Hyperspectral Scattering Image Combined with Ensemble Learning Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy, and explain its mechanism. A variety of weak classifiers classify eggs based on the spectra after preprocessing and feature wavelength extraction to obtain three classifiers with the highest accuracy. The three classifiers are used as metamodels of stacking ensemble learning to improve the highest accuracy from 96.25% to 100%. Moreover, the highest accuracy of scattering, reflection, transmission, and mixed hyperspectral of eggs are 100.00%, 88.75%, 95.00%, and 96.25%, respectively, indicating that the scattering hyperspectral for egg freshness detection is better than that of the others. In addition, the accuracy is inversely proportional to the angle of incidence, i.e., the smaller the incident angle, the camera collects a larger proportion of scattering light, which contains more biochemical parameters of an egg than that of reflection and transmission. These results are very important for improving the accuracy of non-destructive testing and for selecting the incident angle of a light source, and they have potential applications for online non-destructive testing. Hyperspectral imaging ; Preprocessor ; Scattering ; Artificial intelligence ; Ensemble learning ; Reflection (computer programming) ; Transmission (telecommunications) ; Computer science ; Optics ; Feature (linguistics) ; Light scattering ; Nondestructive testing ; Feature extraction ; Pattern recognition (psychology) ; Materials science ; Physics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Jari Järvi | Patrick Rinke | Milica Todorović
Source: Beilstein Journal of Nanotechnology (article, 2020-10-19)
Field: Materials Science — Materials Chemistry

Detecting stable adsorbates of (1<i>S</i>)-camphor on Cu(111) with Bayesian optimization Identifying the atomic structure of organic-inorganic interfaces is challenging with current research tools. Interpreting the structure of complex molecular adsorbates from microscopy images can be difficult, and using atomistic simulations to find the most stable structures is limited to partial exploration of the potential energy surface due to the high-dimensional phase space. In this study, we present the recently developed Bayesian Optimization Structure Search (BOSS) method as an efficient solution for identifying the structure of non-planar adsorbates. We apply BOSS with density-functional theory simulations to detect the stable adsorbate structures of (1<i>S</i>)-camphor on the Cu(111) surface. We identify the optimal structure among eight unique types of stable adsorbates, in which camphor chemisorbs via oxygen (global minimum) or physisorbs via hydrocarbons to the Cu(111) surface. This study demonstrates that new cross-disciplinary tools, such as BOSS, facilitate the description of complex surface structures and their properties, and ultimately allow us to tune the functionality of advanced materials. Boss ; Camphor ; Surface (topology) ; Materials science ; Molecular dynamics ; Planar ; Potential energy surface ; Chemical physics ; Density functional theory ; Gas phase ; Nanotechnology ; Computer science ; Computational chemistry ; Chemistry ; Molecule ; Physical chemistry ; Mathematics ; Geometry Machine Learning in Materials Science ; Surface Chemistry and Catalysis ; Surface and Thin Film Phenomena
Authors: Aday J. Molina‐Mendoza | Matthias Paur | Thomas Mueller
Source: Advanced Optical Materials (article, 2020-04-13)
Field: Materials Science — Materials Chemistry

Nonvolatile Programmable WSe<sub>2</sub> Photodetector Abstract Optoelectronic devices with nonvolatile memory are an important component in a wide variety of applications ranging from optoelectronic random‐access‐memories, with the advantage of using optical stimuli as an added parameter, to complex artificial neuromorphic networks that pretend to mimic the working schemes of the human brain. In the past few years, 2D materials have been proposed as attractive candidates to build such optoelectronic devices with memory due to their excellent optoelectronic properties and high sensitivity to external electric fields. Here, a WSe 2 monolayer p–n junction working as a nonvolatile programmable photodetector is reported, that, enabled by a split‐gate configuration with embedded charge‐trapping layers, is capable of retaining custom responsivity values over time, prior configuration by the user. Once configured, this photodetector can operate without external applied bias voltage as a self‐driven photodetector, as well as without external back‐gate voltage thanks to the charge stored in the floating gates. Furthermore, the device shows a remarkable performance, with open‐circuit voltage around 1 V at approximately 270 W m −2 white light, fill factor higher than 30%, and fast response times. This programmable photodetector sets a new concept as a building block in more complex image‐sensing systems. Photodetector ; Optoelectronics ; Responsivity ; Materials science ; Neuromorphic engineering ; Non-volatile memory ; Voltage ; Computer science ; Electrical engineering ; Artificial intelligence 2D Materials and Applications ; Perovskite Materials and Applications ; Advanced Memory and Neural Computing