jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yuval Elbaz | David Furman | Maytal Caspary Toroker
Source: Advanced Functional Materials (article, 2019-07-23)
Field: Materials Science — Materials Chemistry

Modeling Diffusion in Functional Materials: From Density Functional Theory to Artificial Intelligence Abstract Diffusion describes the stochastic motion of particles and is often a key factor in determining the functionality of materials. Modeling diffusion of atoms can be very challenging for heterogeneous systems with high energy barriers. In this report, popular computational methodologies are covered to study diffusion mechanisms that are widely used in the community and both their strengths and weaknesses are presented. In static approaches, such as electronic structure theory, diffusion mechanisms are usually analyzed within the nudged elastic band (NEB) framework on the ground electronic surface usually obtained from a density functional theory (DFT) calculation. Another common approach to study diffusion mechanisms is based on molecular dynamics (MD) where the equations of motion are solved for every time step for all the atoms in the system. Unfortunately, both the static and dynamic approaches have inherent limitations that restrict the classes of diffusive systems that can be efficiently treated. Such limitations could be remedied by exploiting recent advances in artificial intelligence and machine learning techniques. Here, the most promising approaches in this emerging field for modeling diffusion are reported. It is believed that these knowledge‐intensive methods have a bright future ahead for the study of diffusion mechanisms in advanced functional materials. Density functional theory ; Diffusion ; Computer science ; Statistical physics ; Field (mathematics) ; Materials science ; Artificial intelligence ; Nanotechnology ; Computational chemistry ; Physics ; Thermodynamics ; Mathematics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Thermal properties of materials
Authors: Anel Beganović | Luzia Maria Hawthorne | Katrin Bach | Christian W. Huck
Source: Foods (review, 2019-02-01)
Field: Chemistry — Analytical Chemistry

Critical Review on the Utilization of Handheld and Portable Raman Spectrometry in Meat Science Traditional methods for the determination of meat quality-relevant parameters are rather time-consuming and destructive, whereas spectroscopic methods offer fast and non-invasive measurements. This review critically deals with the application of handheld and portable Raman devices in the meat sector. Some published articles on this topic tend to convey the impression of unrestricted applicability of mentioned devices in this field of research. Furthermore, results are often subjected to over-optimistic interpretations without being underpinned by adequate test set validation. On the other hand, deviations in reference methods for meat quality assessment and the inhomogeneity of the meat matrix pose a challange to Raman spectroscopy and multivariate models. Nonetheless, handheld and portable Raman devices show considerable potential for some applications in the meat sector. Mobile device ; Raman spectroscopy ; Computer science ; Quality (philosophy) ; Physics ; World Wide Web Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Identification and Quantification in Food
Authors: Antonio Lama‐Muñoz | María del Mar Contreras | Francisco Espínola | Manuel Moya | Inmaculada Romero | Eulógio Castro
Source: Energies (article, 2019-06-28)
Field: Chemistry — Organic Chemistry

Optimization of Oleuropein and Luteolin-7-O-Glucoside Extraction from Olive Leaves by Ultrasound-Assisted Technology The olive orchard cultivation in Mediterranean countries results in huge amounts of lignocellulosic biomass residues. One of the main residues are olive leaves. Olive leaves contain high concentrations of bioactive antioxidant compounds like oleuropein and luteolin-7-glucoside. The production of biactive compounds from olive leaves requires treatments capable of breaking the lignocellulosic structure. Current research focuses on use of inexpensive, quick, and not harmful to the environment treatments, searching a more simplified large-scale operation approach. Recently, advances in applied chemistry have led to possible new emerging industrial techniques like ultrasound-assisted extraction (UAE). This technology is a promising candidate as a green treatment solution for olive leaves utilization in a biorefinery. However, this application goes through prior optimization of technique and operating conditions. The goal of this study was to optimize the extraction of oleuropein and luteolin-7-glucoside from olive leaves through an investigation of the influence of key factors of ultrasound-assisted extraction using an experimental central composite design, in comparison with conventional Soxhlet extraction. The highest extraction efficiency and antioxidant capacity were obtained under optimal increment of temperature and amplitude conditions (40 °C and 30%, respectively). Values for oleuropein, luteolin-7-glucoside were 69.91 g/kg and 1.82 g/kg, respectively. Oleuropein ; Olive leaf ; Extraction (chemistry) ; Luteolin ; Chemistry ; Olea ; Lignocellulosic biomass ; Biorefinery ; Biomass (ecology) ; Pulp and paper industry ; Central composite design ; Food science ; Response surface methodology ; Chromatography ; Botany ; Antioxidant ; Biology ; Agronomy ; Olive oil ; Flavonoid ; Biochemistry ; Organic chemistry ; Raw material ; Engineering Edible Oils Quality and Analysis ; Essential Oils and Antimicrobial Activity ; Spectroscopy and Chemometric Analyses
Authors: Yun Jin | Yiyi Fan | Xiuxia Meng | Weimin Zhang | Bo Meng | Naitao Yang | Shaomin Liu
Source: Processes (article, 2019-10-15)
Field: Materials Science — Materials Chemistry

Theoretical and Experimental Insights into the Mechanism for Gas Separation through Nanochannels in 2D Laminar MXene Membranes Clarifying the mechanism for the gas transportation in the emerging 2D materials-based membranes plays an important role on the design and performance optimization. In this work, the corresponding studies were conducted experimentally and theoretically. To this end, we measured the gas permeances of hydrogen and nitrogen from their mixture through the supported MXene lamellar membrane. Knudsen diffusion and molecular sieving through straight and tortuous nanochannels were proposed to elucidate the gas transport mechanism. The average pore diameter of 5.05 Å in straight nanochannels was calculated by linear regression in the Knudsen diffusion model. The activation energy for H2 transport in molecular sieving model was calculated to be 20.54 kJ mol−1. From the model, we can predict that the gas permeance of hydrogen (with smaller kinetic diameter) is contributed from both Knudsen diffusion and molecular sieving mechanism, but the permeance of larger molecular gases like nitrogen is sourced from Knudsen diffusion. The effects of the critical conditions such as temperature, the diffusion pore diameter of structural defects, and the thickness of the prepared MXene lamellar membrane on hydrogen and nitrogen permeance were also investigated to understand the hydrogen permeation difference from Knudsen diffusion and molecular sieving. At room temperature, the total hydrogen permeance was contributed 18% by Knudsen diffusion and 82% by molecular sieving. The modeling results indicate that molecular sieving plays a dominant role in controlling gas selectivity. Permeance ; Knudsen diffusion ; Knudsen number ; Diffusion ; Hydrogen ; Membrane ; Lamellar structure ; Permeation ; Molecular diffusion ; Chemistry ; Thermodynamics ; Molecular dynamics ; Materials science ; Chemical physics ; Chemical engineering ; Computational chemistry ; Organic chemistry ; Crystallography MXene and MAX Phase Materials ; Graphene research and applications ; Energy Harvesting in Wireless Networks
Authors: Iwona Bernacka‐Wojcik | Miriam Huerta | Klas Tybrandt | Michal Karády | Mohammad Yusuf Mulla | David J. Poxson | Erik O. Gabrielsson | Karin Ljung | Daniel T. Simon | Magnus Berggren | Eleni Stavrinidou
Source: Small (article, 2019-09-12)
Field: Materials Science — Polymers and Plastics

Implantable Organic Electronic Ion Pump Enables ABA Hormone Delivery for Control of Stomata in an Intact Tobacco Plant Electronic control of biological processes with bioelectronic devices holds promise for sophisticated regulation of physiology, for gaining fundamental understanding of biological systems, providing new therapeutic solutions, and digitally mediating adaptations of organisms to external factors. The organic electronic ion pump (OEIP) provides a unique means for electronically-controlled, flow-free delivery of ions, and biomolecules at cellular scale. Here, a miniaturized OEIP device based on glass capillary fibers (c-OEIP) is implanted in a biological organism. The capillary form factor at the sub-100 µm scale of the device enables it to be implanted in soft tissue, while its hyperbranched polyelectrolyte channel and addressing protocol allows efficient delivery of a large aromatic molecule. In the first example of an implantable bioelectronic device in plants, the c-OEIP readily penetrates the leaf of an intact tobacco plant with no significant wound response (evaluated up to 24 h) and effectively delivers the hormone abscisic acid (ABA) into the leaf apoplast. OEIP-mediated delivery of ABA, the phytohormone that regulates plant's tolerance to stress, induces closure of stomata, the microscopic pores in leaf's epidermis that play a vital role in photosynthesis and transpiration. Efficient and localized ABA delivery reveals previously unreported kinetics of ABA-induced signal propagation. Abscisic acid ; Biomolecule ; Apoplast ; Nanotechnology ; Biophysics ; Chemistry ; Materials science ; Biology ; Biochemistry Conducting polymers and applications ; Analytical Chemistry and Sensors ; Organic Electronics and Photovoltaics
Authors: Congying Jiang | Yuchen Gu | Wanbing Guan | Jiahong Zheng | Meng Ni | Zheng Zhong
Source: International Journal of Hydrogen Energy (article, 2019-11-12)
Field: Materials Science — Materials Chemistry

3D thermo-electro-chemo-mechanical coupled modeling of solid oxide fuel cell with double-sided cathodes Materials science ; Cathode ; Solid oxide fuel cell ; Electrolyte ; Stress (linguistics) ; Thermal ; Oxide ; Thermal expansion ; Current (fluid) ; Voltage ; Heat transfer ; Current density ; Temperature gradient ; Electrochemistry ; Convection ; Composite material ; Thermodynamics ; Electrode ; Chemistry ; Electrical engineering ; Metallurgy Advancements in Solid Oxide Fuel Cells ; Catalysis and Oxidation Reactions ; Chemical Looping and Thermochemical Processes
Authors: Ke Jiang | Ling Zhang | Tifeng Xia | Yu Yang | Bin Li | Yuanjing Cui | Guodong Qian
Source: Science China Materials (article, 2019-04-28)
Field: Chemistry — Inorganic Chemistry

A water-stable fcu-MOF material with exposed amino groups for the multi-functional separation of small molecules Adsorption ; Materials science ; Molecule ; Methane ; Selectivity ; Chemical engineering ; Metal-organic framework ; Carbon fibers ; Carbon dioxide ; Porosity ; Functional group ; Selective adsorption ; Organic chemistry ; Chemistry ; Catalysis ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Artem Osypenko | Émilie Moulin | Odile Gavat | Gad Fuks | Mounir Maaloum | Mark A. J. Koenis | Wybren Jan Buma | Nicolas Giuseppone
Source: Chemistry - A European Journal (article, 2019-07-18)
Field: Materials Science — Biomaterials

Temperature Control of Sequential Nucleation–Growth Mechanisms in Hierarchical Supramolecular Polymers Upon cooling in solution, chiral triarylamine tris-amide unimers produce organogels by stacking into helical supramolecular polymers, which subsequently bundle into larger fibers. Interestingly, circular dichroism, vibrational circular dichroism, and AFM imaging of the chiral self-assemblies revealed that monocolumnar P-helical fibrils formed upon fast cooling, whereas bundled M-superhelical fibers formed upon slow cooling. The mechanistic study of this structural bifurcation reveals the presence of a strong memory effect, reminiscent of a complex stepwise combination of primary and secondary nucleation-growth processes. These results highlight the instrumental role of sequential self-assembly processes to control supramolecular architectures of multiple hierarchical order. Supramolecular chemistry ; Nucleation ; Circular dichroism ; Stacking ; Supramolecular polymers ; Polymer ; Crystallography ; Materials science ; Chemistry ; Crystal structure ; Organic chemistry ; Composite material Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Synthesis and Properties of Aromatic Compounds
Authors: Yuqing Meng | Le Sun | Jun Gao | Wenzhou Tan | Chusheng Chen | Jianxin Yi | H.J.M. Bouwmeester | Zhihu Sun | Kyle S. Brinkman
Source: ACS Applied Materials & Interfaces (article, 2019-03-04)
Field: Materials Science — Materials Chemistry

Insights into the CO<sub>2</sub> Stability-Performance Trade-Off of Antimony-Doped SrFeO<sub>3−δ</sub> Perovskite Cathode for Solid Oxide Fuel Cells One major challenge for the further development of solid oxide fuel cells is obtaining high-performance cathode materials with sufficient stability against reactions with CO<sub>2</sub> present in the ambient atmosphere. However, the enhanced stability is often achieved by using material systems exhibiting decreased performance metrics. The phenomena underlying the performance and stability trade-off has not been well understood. This paper uses antimony-doped SrFeO<sub>3-δ</sub> as a model material to shed light on the relationship between the structure, stability, and performance of perovskite-structured oxides which are commonly used as cathode materials. X-ray absorption revealed that partial substitution of Fe by Sb leads to a series of changes in the local environment of the iron atom, such as a decrease in the iron oxidation state and increase in the oxygen coordination number. Theoretical calculations show that the structural changes are associated with an increase in both the oxygen vacancy formation energy and metal-oxygen bond energy. The area-specific resistance (ASR) of the perovskite oxide increases with Sb doping, indicating a deterioration of the oxygen reduction activity. Exposure of the materials to CO<sub>2</sub> leads to depressed oxygen desorption and an increased ASR, which becomes less pronounced at higher Sb doping levels. Origin of the stability-performance trade-off is discussed based on the structural parameters. Materials science ; Perovskite (structure) ; Oxide ; Doping ; Cathode ; Oxygen ; Antimony ; Chemical engineering ; Inorganic chemistry ; Metallurgy ; Physical chemistry ; Optoelectronics ; Chemistry Advancements in Solid Oxide Fuel Cells ; Magnetic and transport properties of perovskites and related materials ; Electronic and Structural Properties of Oxides
Authors: G. G. Guzmán-Verri | Richard Brierley | P. B. Littlewood
Source: Nature (article, 2019-12-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Cooperative elastic fluctuations provide tuning of the metal–insulator transition Condensed matter physics ; Ionic radius ; Phase transition ; Metal–insulator transition ; Superconductivity ; Materials science ; Lattice (music) ; Physics ; Chemical physics ; Metal ; Ion ; Quantum mechanics Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics ; Electronic and Structural Properties of Oxides
Authors: Dasom Kim | Jangsun Hwang | Yonghyun Choi | Yejin Kwon | Jaehee Jang | Semi Yoon | Jonghoon Choi
Source: Cancers (article, 2019-10-27)
Field: Materials Science — Biomaterials

Effective Delivery of Anti-Cancer Drug Molecules with Shape Transforming Liquid Metal Particles Liquid metals are being studied intensively because of their potential as a drug delivery system. Eutectic gallium-indium (EGaIn) alloy liquid metals have a low melting point, low toxicity, and excellent tissue permeability. These properties may enable them to be vascular embolic agents that can be deformed by light or heat. In this study, we developed EGaIn particles that can deliver anticancer drugs to tumor cells in vitro and change their shapes in response to external stimuli. These particles were prepared by sonicating a solution containing EGaIn and amphiphilic lipids. The liquid metal (LM)/amphiphilic lipid (DSPC, 1,2-distearoyl-sn-glycero-3-phosphocholin) particles formed a vehicle for doxorubicin, an anticancer drug, which was released (up to 50%) when the shape of the particles was deformed by light or heat treatment. LM/DSPC particles are non-toxic and LM/DSPC/doxorubicin particles have anticancer effects (resulting in a cell viability of less than 50%). LM/DSPC/doxorubicin particles were also able to mimic blood vessel embolisms by modifying their shape using precisely controlled light and heat in engineered microchannels. The purpose of this study was to examine the potential of EGaIn materials to treat tumor tissues that cannot be removed by surgery. Drug delivery ; Cancer ; Drug ; Cancer research ; Medicine ; Nanotechnology ; Materials science ; Chemistry ; Pharmacology ; Internal medicine Nanoparticle-Based Drug Delivery ; Gold and Silver Nanoparticles Synthesis and Applications ; Nanoplatforms for cancer theranostics
Authors: May Ali Alsaffar | Bamidele Victor Ayodele | Siti Indati Mustapa
Source: Journal of Cleaner Production (article, 2019-11-06)
Field: Materials Science — Materials Chemistry

Scavenging carbon deposition on alumina supported cobalt catalyst during renewable hydrogen-rich syngas production by methane dry reforming using artificial intelligence modeling technique Syngas ; Methane ; Carbon dioxide reforming ; Catalysis ; Carbon fibers ; Hydrogen production ; Greenhouse gas ; Hydrogen ; Cobalt ; Carbon dioxide ; Chemical engineering ; Materials science ; Environmental science ; Chemistry ; Inorganic chemistry ; Engineering ; Geology ; Composite material ; Organic chemistry ; Composite number Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Oxidation Reactions
Authors: Heather J. Kulik
Source: Wiley Interdisciplinary Reviews Computational Molecular Science (article, 2019-08-02)
Field: Materials Science — Materials Chemistry

Making machine learning a useful tool in the accelerated discovery of transition metal complexes Abstract As machine learning (ML) has matured, it has opened a new frontier in theoretical and computational chemistry by offering the promise of simultaneous paradigm shifts in accuracy and efficiency. Nowhere is this advance more needed, but also more challenging to achieve, than in the discovery of open‐shell transition metal complexes. Here, localized d or f electrons exhibit variable bonding that is challenging to capture even with the most computationally demanding methods. Thus, despite great promise, clear obstacles remain in constructing ML models that can supplement or even replace explicit electronic structure calculations. In this article, I outline the recent advances in building ML models in transition metal chemistry, including the ability to approach sub‐kcal/mol accuracy on a range of properties with tailored representations, to discover and enumerate complexes in large chemical spaces, and to reveal opportunities for design through analysis of feature importance. I discuss unique considerations that have been essential to enabling ML in open‐shell transition metal chemistry, including (a) the relationship of data set size/diversity, model complexity, and representation choice, (b) the importance of quantitative assessments of both theory and model domain of applicability, and (c) the need to enable autonomous generation of reliable, large data sets both for ML model training and in active learning or discovery contexts. Finally, I summarize the next steps toward making ML a mainstream tool in the accelerated discovery of transition metal complexes. This article is categorized under: Electronic Structure Theory &gt; Density Functional Theory Software &gt; Molecular Modeling Computer and Information Science &gt; Chemoinformatics Computer science ; Representation (politics) ; Density functional theory ; Chemical space ; Set (abstract data type) ; Drug discovery ; Machine learning ; Artificial intelligence ; Chemistry ; Theoretical computer science ; Computational chemistry ; Programming language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Anita Halder | Aishwaryo Ghosh | Tanusri Saha‐Dasgupta
Source: Physical Review Materials (article, 2019-08-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Machine-learning-assisted prediction of magnetic double perovskites Magnetism is an important property of materials that plays a key role in many different applications. In the present paper, we use a combination of computational tools: a machine-learning technique for screening of stable candidates, an evolutionary algorithm for crystal structure determination, and first-principles calculations for characterization of electronic and magnetic properties to make predictions on magnetic double perovskites, which are yet to be synthesized. Out of 412 scanned candidates of ${A}_{2}{BB}^{\ensuremath{'}}{O}_{6}$ composition with $3d$ and $4d$ or $5d$ transition metals at B and ${B}^{\ensuremath{'}}$ sites, we found 33 compounds to form stable double-perovskite structures, 25 of which were further considered for characterization of their structure and properties. Our exercise predicted 21 double perovskites of varying magnetic and electronic properties, ranging from ferromagnetic half metals to ferri- and antiferromagnetic insulators to ferromagnetic metals and a rare example of antiferromagnetic metals. Our computational study is expected to help in discovering new magnetic double perovskites. Antiferromagnetism ; Ferromagnetism ; Magnetism ; Materials science ; Characterization (materials science) ; Condensed matter physics ; Transition metal ; Perovskite (structure) ; Electronic structure ; Crystal structure ; Crystallography ; Nanotechnology ; Chemistry ; Physics ; Catalysis Magnetic and transport properties of perovskites and related materials ; Multiferroics and related materials ; Advanced Condensed Matter Physics
Authors: Nan Nan | Jingxin Wang
Source: Advances in Materials Science and Engineering (article, 2019-07-21)
Field: Materials Science — Materials Chemistry

FIB-SEM Three-Dimensional Tomography for Characterization of Carbon-Based Materials A review on the recent advances of the three-dimensional (3D) characterization of carbon-based materials was conducted by focused ion beam-scanning electron microscope (FIB-SEM) tomography. Current studies and further potential applications of the FIB-SEM 3D tomography technique for carbon-based materials were discussed. The goal of this paper is to highlight the advances of FIB-SEM 3D reconstruction to reveal the high and accurate resolution of internal structures of carbon-based materials and provide suggestions for the adoption and improvement of the FIB-SEM tomography system for a broad carbon-based research to achieve the best examination performances and enhance the development of innovative carbon-based materials. Materials science ; Characterization (materials science) ; Focused ion beam ; Scanning electron microscope ; Carbon fibers ; Tomography ; Nanotechnology ; Resolution (logic) ; Ion ; Optics ; Composite material ; Computer science ; Composite number ; Artificial intelligence Diamond and Carbon-based Materials Research ; Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications