jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Valentina Di Francesco | Martina Di Francesco | Paolo Decuzzi | Roberto Palomba | Miguel Ferreira
Source: Pharmaceutics (article, 2021-03-04)
Field: Materials Science — Biomaterials

Synthesis of Two Methotrexate Prodrugs for Optimizing Drug Loading into Liposomes Methotrexate (MTX), a compound originally used as an anticancer drug, has also found applications in a broad variety of autoimmune disorders thanks to its anti-inflammation and immunomodulatory functions. The broad application of MTX is anyway limited by its poor solubility in biological fluids, its poor bioavailability and its toxicity. In addition, encapsulating its original form in nanoformulation is very arduous due to its considerable hydrophobicity. In this work, two strategies to efficiently encapsulate MTX into liposomal particles are proposed to overcome the limitations mentioned above and to improve MTX bioavailability. MTX solubility was increased by conjugating the molecule to two different compounds: DSPE and PEG. These two compounds commonly enrich liposome formulations, and their encapsulation efficiency is very high. By using these two prodrugs (DSPE-MTX and PEG-MTX), we were able to generate liposomes comprising one or both of them and characterized their physiochemical features and their toxicity in primary macrophages. These formulations represent an initial step to the development of targeted liposomes or particles, which can be tailored for the specific application MTX is used for (cancer, autoimmune disease or others). Prodrug ; Bioavailability ; Liposome ; Methotrexate ; Chemistry ; Drug ; Pharmacology ; PEG ratio ; Toxicity ; Combinatorial chemistry ; Medicine ; Biochemistry ; Organic chemistry ; Immunology Nanoparticle-Based Drug Delivery ; Monoclonal and Polyclonal Antibodies Research ; Advanced Drug Delivery Systems
Authors: Pengfei Wang | Qianqian Hu | Bocheng Lv | Yu Liu | Jun Yin | Jia‐Lin Sun
Source: Materials Advances (article, 2021-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Oxidized eutectic gallium–indium (EGaIn) nanoparticles for broadband light response in a graphene-based photodetector Oxidized EGaIn nanoparticles on suspended graphene achieve photodetection with improvement in responsivity by three orders of magnitude from ultraviolet to near infrared light. Responsivity ; Materials science ; Photodetection ; Graphene ; Photodetector ; Optoelectronics ; Eutectic system ; Indium ; Ultraviolet ; Gallium ; Nanoparticle ; Nanotechnology ; Alloy ; Composite material ; Metallurgy Ga2O3 and related materials ; Graphene research and applications ; GaN-based semiconductor devices and materials
Authors: Cristine Santos de Oliveira | Richard Kohns | Felix Meyerhöfer | Simon Carstens | Dirk Enke | Ralf B. Wehrspohn | Juliana Martins de Souza e Silva
Source: Materials Chemistry Frontiers (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Multi-technique structural characterization of glass foams with complex pore structures obtained through phase separation Typical pore characterization techniques combined with computed tomography provided a complete description of the multimodal porous architecture of novel glass foams synthesised <italic>via</italic> foaming process followed by phase-separation and selective leaching. Materials science ; Characterization (materials science) ; Porosity ; Leaching (pedology) ; Phase (matter) ; Porous glass ; Chemical engineering ; Porous medium ; Composite material ; Nanotechnology ; Chemistry ; Organic chemistry ; Geology Pickering emulsions and particle stabilization ; Catalysis and Oxidation Reactions ; Aerogels and thermal insulation
Authors: David Lacroix | Mykola Isaiev | Gilles Pernot
Source: Physical review. B./Physical review. B (article, 2021-10-19)
Field: Materials Science — Materials Chemistry

Thermal transport in semiconductors studied by Monte Carlo simulations combined with the Green-Kubo formalism In this paper, we demonstrate that it is possible to combine two computational approaches, usually used in very different contexts, namely, the Green-Kubo formalism and statistical approaches, to solve the Boltzmann transport equation to calculate the thermal conductivity of semiconductors. In this framework, first the phonon transport is solved by the Monte Carlo method according to the Debye-Callaway or Holland formalisms, then the flux autocorrelation is calculated. This new approach has been implemented to calculate the properties of Si, Ge, GaN, and C (diamond) in an extended temperature range, from 50 to 600 K. The simulation results are compared with those given by experimentation, with very good agreement. Monte Carlo method ; Kubo formula ; Statistical physics ; Formalism (music) ; Phonon ; Rotation formalisms in three dimensions ; Boltzmann equation ; Physics ; Thermal conductivity ; Boltzmann constant ; Autocorrelation ; Transport phenomena ; Condensed matter physics ; Quantum mechanics ; Mathematics ; Conductivity Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Thermal Radiation and Cooling Technologies
Authors: Viki Kumar Prasad | Zhipeng Pei | Simon Edelmann | Alberto Otero‐de‐la‐Roza | Gino A. DiLabio
Source:  (preprint, 2021-07-14)
Field: Materials Science — Materials Chemistry

BH9, a New Comprehensive Benchmark Dataset for Barrier Heights and Reaction Energies: Assessment of Density Functional Approximations and Basis Set Incompleteness Potentials The calculation of accurate reaction energies and barrier heights is essential in computational studies of reaction mechanisms and thermochemistry. In order to assess methods regarding their ability to predict these two properties, high-quality benchmark sets are required that comprise a reasonably large and diverse set of organic reactions. Due to the time-consuming nature of both locating transition states and computing accurate reference energies for reactions involving large molecules, previous benchmark sets have been limited in scope, the number of reactions considered, and the size of the reactant and product molecules. Recent advances in coupled-cluster theory, in particular local correlation methods like DLPNO-CCSD(T), now allow the calculation of reaction energies and barrier heights for relatively large systems. In this work, we present a comprehensive, and diverse benchmark set of barrier heights and reaction energies based on DLPNO-CCSD(T)/CBS, called BH9. BH9 comprises 449 chemical reactions belonging to nine types common in organic chemistry and biochemistry. We examine the accuracy of DLPNO-CCSD(T) vis-a-vis canonical CCSD(T) for a subset of BH9 and conclude that, although there is a penalty in using the DLPNO approximation, the reference data are accurate enough to serve as benchmark for density-functional theory (DFT) methods. We then present two applications of the BH9 set. First, we examine the performance of several density functional approximations commonly used in thermochemical and mechanistic studies. Second, we assess our basis set incompleteness potentials regarding their ability to mitigate basis set incompleteness error. The number of data points, the diversity of the reactions considered, and the relatively large size of the reactant molecules make BH9 the most comprehensive thermochemical benchmark set to date, and a useful tool for the development and assessment of computational methods. Benchmark (surveying) ; Coupled cluster ; Basis set ; Set (abstract data type) ; Density functional theory ; Thermochemistry ; Statistical physics ; Basis (linear algebra) ; Computer science ; Computational chemistry ; Chemistry ; Molecule ; Mathematics ; Physics ; Physical chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Chemical Physics Studies
Authors: Yan Duan | Joana T. Coutinho | Lorena E. Rosaleny | Salvador Cardona | José J. Baldoví | Alejandro Gaita‐Ariño
Source: Research Square (preprint, 2021-06-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Data mining, dashboards and statistics: a powerful framework for the chemical design of molecular nanomagnets Abstract Three decades of intensive research in molecular nanomagnets have brought the magnetic memory in molecules from liquid helium to liquid nitrogen temperature. The enhancement of this operational temperature relies on a wise choice of the magnetic ion and the coordination environment. However, serendipity, oversimplified theories and chemical intuition have played the main role. In order to establish a powerful framework for statistically driven chemical design, we collected chemical and physical data for lanthanide-based nanomagnets to create a catalogue of over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis to it. We found that the effective energy barrier derived from the Arrhenius equation displays an excellent correlation with the magnetic memory, and that among all chemical families studied, only terbium bis-phthalocyaninato sandwiches and dysprosium metallocenes consistently present magnetic memory up to high temperature, but that there are some promising strategies for improvement. Nanomagnet ; Data science ; Computer science ; Nanotechnology ; Computational biology ; Biology ; Materials science ; Physics Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Metal-Organic Frameworks: Synthesis and Applications
Authors: R. Raghavendra Rao | S. Pradeep | Nasim Hasan | B. S. Shivashankara | Mohamed Abdelghany Elkotb | C. Ahamed Saleel | Asif Afzal | B. Saleh
Source: Advances in Materials Science and Engineering (article, 2021-01-01)
Field: Materials Science — Polymers and Plastics

Comparative Study of the Mechanical and Water Absorption Behaviour of Basalt Fiber Reinforced Polymer Matrix Composites with Different Epoxies as Matrix for Biomedical Applications In comparison to conventional materials, polymer matrix composite materials have witnessed a surge in applicability due to their higher specific strength‐to‐weight ratio, abundant availability, and ease of shaping. Due to technological, economic, environmental, and societal challenges, bio‐based fibers began to emerge quickly for use in industrial components. Due to its unique chemistry‐related characteristics, basalt fiber holds a prominent position among the many bio‐based fibers. So, it could be thought of used as a replacement for some components used in the biomedical equipments. In the present investigation, plain‐woven basalt fiber at a constant percentage of 55% is added as reinforcement to three different epoxy resin‐hardener combinations such as Lapox L12‐Lapox K6, Araldite LY1564‐Aradur 22962, and Araldite LY556‐Aradur HY951 as matrix, and comparative studies are carried out. Fabrication is carried out by hand lay‐up technique. Test specimens are prepared as per the respective ASTM standards by subjecting the laminate to water jet machining. Mechanical characterization such as tensile, flexural, and density tests is conducted for the test specimen using BISS‐50 kN Universal Testing Machine (UTM). Water absorption tests are also conducted for 24 and 48 hours duration. From the results obtained, it is concluded that the highest tensile, flexural strengths are obtained for laminate L 3 which used LY556 epoxy and HY951 hardener combination as matrix. Also, less rate of water absorption is seen for L 3 laminate for both 24 and 48 hrs which makes it suitable for biomedical applications. Materials science ; Araldite ; Composite material ; Absorption of water ; Epoxy ; Flexural strength ; Ultimate tensile strength ; Polymer ; Matrix (chemical analysis) ; Universal testing machine ; Fiber ; Izod impact strength test Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research ; Innovations in Concrete and Construction Materials
Authors: Lihua Shao | Ru Ji | Shuyi Du | Hongqing Song
Source: Geofluids (article, 2021-12-09)
Field: Chemistry — Analytical Chemistry

Prediction of Fluid Viscosity in Multiphase Reservoir Oil System by Machine Learning It is important to realize rapid and accurate prediction of fluid viscosity in a multiphase reservoir oil system for improving oil production in petroleum engineering. This study proposed three viscosity prediction models based on machine learning approaches. The prediction accuracy comparison results show that the random forest (RF) model performs accurately in predicting the viscosity of each phase of the reservoir, with the lowest error percentage and highest <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:msup> <a:mrow> <a:mi>R</a:mi> </a:mrow> <a:mrow> <a:mn>2</a:mn> </a:mrow> </a:msup> </a:math> values. And the RF model is tremendously fast in a computing time of 0.53 s. In addition, sensitivity analysis indicates that for a multiphase reservoir system, the viscosity of each phase of the reservoir is determined by different factors. Among them, the viscosity of oil is vital for oil production, which is mainly affected by the molar ratio of gas to oil (MR-GO). Viscosity ; Petroleum engineering ; Oil viscosity ; Oil production ; Phase (matter) ; Petroleum reservoir ; Petroleum ; Enhanced oil recovery ; Sensitivity (control systems) ; Geology ; Materials science ; Environmental science ; Computer science ; Thermodynamics ; Chemistry ; Engineering ; Physics ; Organic chemistry Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Spectroscopy and Chemometric Analyses
Authors: Amirhossein Mahtabani | Minna Niittymäki | Rafał Anyszka | Ilkka Rytöluoto | Xiaozhen He | Eetta Saarimäki | Kari Lahti | Mika Paajanen | Wilma K. Dierkes | Anke Blume
Source: IEEE Access (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Deposition of Ureido and Methacrylate Functionalities Onto Silica Nanoparticles and its Effect on the Properties of Polypropylene-Based Nanodielectrics Surface modification of nanoparticles is often utilized to tailor the interfacial properties in dielectric nanocomposites. Introducing different functional groups to the nanoparticles’ surface may induce localized states (traps) that can enhance the dielectric performance of the material depending on their density and energy levels. Furthermore, surface modification of the filler can affect the dispersion quality and crystallization of the nanocomposites which can ultimately alter the dielectric response of the material. In this study, functionalization of silica nanoparticles is demonstrated using 3-(trimethoxysilyl)propyl methacrylate (TMPM) and 1-[3-(trimethoxysilyl)propyl]urea (TMPU) as modifying agents. The effect of such modifications on the crystallization behavior, dispersion quality of the nanoparticles, as well as charge trapping and transport under a medium DC field is studied in nanocomposites based on polypropylene (PP)/ethylene-octene-copolymer (EOC) blends at 1% and 5% of filler concentrations. The results show that both ureido and methacrylate functional groups introduce localized states, but with different energy levels. Nitrogen containing ureido groups in TMPU tend to introduce deeper traps to the filler-polymer interfaces, compared to the methacrylate silane modification. Comparing the two types of surface functionalization, the ureido-functionalized silica resulted in a suppression of space charge formation at the interfaces under a medium DC electric field, despite the relatively larger mean cluster size of nanoparticles. Polypropylene ; Methacrylate ; Nanoparticle ; Deposition (geology) ; Chemical engineering ; Materials science ; Polymer chemistry ; Composite material ; Polymer ; Nanotechnology ; Copolymer ; Geology High voltage insulation and dielectric phenomena ; Dielectric materials and actuators ; Polymer Nanocomposite Synthesis and Irradiation
Authors: Junfeng Hou | Shipeng Wang | Yingqiu Jiang | Jin Yong-ming | Youming Yu
Source: Journal of Advanced Concrete Technology (article, 2021-09-22)
Field: Materials Science — Polymers and Plastics

Probing the Effects of Density on Combustion Performance of Cement-bonded Particleboard Produced from Wood Processing Residues The purpose of this study was to provide insights into deeper understanding of the combustion performance of cement-bonded particleboards. Cement-bonded particleboard produced from Chinese fir processing residues is fabricated and its combustion performance is further evaluated by cone calorimeter analysis. Obtained results revealed that combustion performance of cement-bonded particleboard positively depends on the density of which, and higher density imparts corresponding particleboards reduction in heat release rate, total heat release, and mass loss rate, along with elevated time to ignition. With the density of particleboard increasing from 0.7 to 1.0 g/cm3, peak and average heat release rate, total heat release and average mass loss rate of specimens were decreased by 55.9, 73.4, 77.8 and 60.3%, respectively. Furthermore, time to ignition of particleboard increased by more than 20 times as the density increasing. Residual mass of specimens was also remarkably elevated along with higher yields of CO and CO2 as the density of particleboard increasing. We believe that proposed investigation is beneficial for the value-added utilization of wood processing residues and further developing products fabricated by wood processing residues. Materials science ; Combustion ; Cone calorimeter ; Ignition system ; Composite material ; Heat of combustion ; Cement ; Calorimeter (particle physics) ; Waste management ; Pulp and paper industry ; Chemistry ; Char ; Organic chemistry Natural Fiber Reinforced Composites ; Fire dynamics and safety research ; Lignin and Wood Chemistry
Authors: Lorena-de Arriba-Rodríguez | Francisco Ortega Fernández | Joaquín Villanueva Balsera | Vicente Rodríguez Montequín
Source: Complexity (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Corrosion Predictive Model in Hot‐Dip Galvanized Steel Buried in Soil Corrosion is one of the main concerns in the field of structural engineering due to its effect on steel buried in soil. Currently, there is no clearly established method that allows its calculation with precision and ensures the durability of this type of structures. Qualitative methods are commonly used rather than quantitative methods. The objective of this research is the development of a multivariate quantitative predictive model for estimating the loss of thickness that will occur in buried hot‐dip galvanized steel as a function of time. The technique used in the modelling is the Adaptive Regression of Multivariate Splines (MARS). The main drawback of this kind of studies is the lack of data since it is not possible to have a priori the corrosive behaviour that the buried material will have as a function of time. To solve this issue, a solid and reliable database was built from the analysis and treatment of the existing literature and with the results obtained from a predictive model to estimate the thickness loss of ungalvanized steel. The input variables of the model are 5 characteristics of the soil, the useful life of the structure, and the loss of corroded ungalvanized steel in the soil. This last data is the output variable of another previous predictive model to estimate the loss of thickness of bare steel in a soil. The objective variable of the model is the loss of thickness that hot‐dip galvanized steel will experience buried in the ground and expressed in g/m 2 . To evaluate the performance and applicability of the proposed model, the statistical metrics RMSE, R 2 , MAE, and RAE and the graphs of standardized residuals were used. The results indicated that the model offers a very high prediction performance. Specifically, the mean square error was 290.6 g/m 2 (range of the objective variable is from 51.787 g/m 2 to 5950.5 g/m 2 ), R 2 was 0.96, and from a relative error of 0.14, the success of the estimate was 100%. Therefore, the use of the proposed predictive model optimizes the relationship between the amount of hot‐dip galvanized steel and the useful life of the buried metal structure. Galvanization ; Durability ; Corrosion ; Multivariate statistics ; Multivariate adaptive regression splines ; Structural engineering ; Environmental science ; Regression analysis ; Computer science ; Engineering ; Materials science ; Metallurgy ; Bayesian multivariate linear regression ; Composite material ; Machine learning Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Structural Integrity and Reliability Analysis
Authors: Fatima Omeis | Mondher Besbes | Christophe Sauvan | H. Benisty
Source: Optics and Photonics Journal (article, 2021-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Highly Angular Tolerant Transmission Filters for Narrow-Band Image Sensors A dielectric transmittance filter composed of subwavelength grating sandwiched between two few-layers distributed Bragg reflectors (DBRs) is proposed with the aim of being compatible with CMOS technology and to be tunable by lithographic means of the grating pattern without the need of thickness changes, in the broad spirit of metamaterials. The DBR mirrors form a Fabry-Perot (FP) cavity whose resonant frequency can be tuned by changing the effective refractive index of the cavity, here, by tailoring the in-plane filling factor of the grating. The structure has been studied and designed by performing numerical simulations using Fourier Modal Method (FMM). This filter proves to have high broad angular tolerance up to ±30˚. This feature is crucial for evaluating the spectral performance of narrow-band filters especially the so-called Ambient light sensors (ALS). By analyzing the transmittance spectral distributions in the band diagram, it is found that the angular tolerance is due to coupling between the FP and the guided mode inside the cavity in analogy to resonances occurring within multimode periodic waveguides in a different context. Optics ; Grating ; Materials science ; Metamaterial ; Transmittance ; Fiber Bragg grating ; Stopband ; Optoelectronics ; Optical filter ; Guided-mode resonance ; Filter (signal processing) ; Refractive index ; Diffraction grating ; Resonator ; Physics ; Computer science Optical Coatings and Gratings ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Yan Li | Bo‐Wei Huang | Guoxing Lin | Jincan Chen | E. Brück
Source: International Journal of Refrigeration (article, 2021-12-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Investigation on the regenerative Brayton refrigeration cycle performances using novel Mn-Fe-P-Si composite material with thermal hysteresis as the working medium Brayton cycle ; Magnetic refrigeration ; Materials science ; Composite number ; Refrigeration ; Hysteresis ; Thermodynamics ; Thermal ; Work (physics) ; Composite material ; Magnetization ; Magnetic field ; Condensed matter physics ; Physics Magnetic and transport properties of perovskites and related materials ; Shape Memory Alloy Transformations ; Thermal Expansion and Ionic Conductivity