jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Thomas Hansen | Tim P. Ofman | Joey G. C. Vlaming | Ivan A. Gagarinov | Jessey van Beek | Tessa A. Goté | Jacoba M. Tichem | Gijs Ruijgrok | Herman S. Overkleeft | Dmitri V. Filippov | Gijsbert A. van der Marel | Jeroen D. C. Codée
Source: Angewandte Chemie (article, 2020-08-28)
Field: Chemistry — Organic Chemistry

Reactivity–Stereoselectivity Mapping for the Assembly of <i>Mycobacterium marinum</i> Lipooligosaccharides Abstract The assembly of complex bacterial glycans presenting rare structural motifs and cis ‐glycosidic linkages is significantly obstructed by the lack of knowledge of the reactivity of the constituting building blocks and the stereoselectivity of the reactions in which they partake. We here report a strategy to map the reactivity of carbohydrate building blocks and apply it to understand the reactivity of the bacterial sugar, caryophyllose, a rare C12‐monosaccharide, containing a characteristic tetrasubstituted stereocenter. We mapped reactivity–stereoselectivity relationships for caryophyllose donor and acceptor glycosides by a systematic series of glycosylations in combination with the detection and characterization of different reactive intermediates using experimental and computational techniques. The insights garnered from these studies enabled the rational design of building blocks with the required properties to assemble mycobacterial lipooligosaccharide fragments of M. marinum . Reactivity (psychology) ; Stereoselectivity ; Stereocenter ; Glycosidic bond ; Chemistry ; Rational design ; Monosaccharide ; Mycobacterium marinum ; Glycan ; Stereochemistry ; Glycosylation ; Combinatorial chemistry ; Biology ; Organic chemistry ; Biochemistry ; Mycobacterium ; Enantioselective synthesis ; Bacteria ; Catalysis ; Genetics ; Enzyme ; Glycoprotein Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Enzyme Production and Characterization
Authors: Sun-Ting Tsai | Pratyush Tiwary
Source: Molecular Simulation (article, 2020-04-29)
Field: Chemistry — Spectroscopy

On the distance between A and B in molecular configuration space In this brief review, we discuss the question of calculating the distance between different molecular configurations. We focus on the theoretical basis of different existing methods for this problem, including ones which are more physics-driven and ones which are more data-driven. We explain the key ideas behind these methods, and conclude with what we see as the central challenges. We hope this review will be helpful to someone aiming to understand these methods, many of which are new and have not been compared and reviewed together. We also hope it will help develop new methods that address the challenges we identify and others. Focus (optics) ; Computer science ; Space (punctuation) ; Key (lock) ; Data science ; Management science ; Physics ; Engineering Molecular spectroscopy and chirality ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Gianluca Costagliola | Federico Bosia | Nicola M. Pugno
Source: New Journal of Physics (article, 2020-01-29)
Field: Materials Science — Polymers and Plastics

Random fuse model in the presence of self-healing Abstract Self-regeneration is a fundamental property of biological materials, leading to enhanced mechanical strength and toughness if subjected to stress and fatigue. Numerous efforts have been devoted to emulate this property and various self-healing materials have been designed with the aim of a practical adoption in construction and mechanical engineering. To achieve this, it is important to understand how damage evolution and fracture propagation are modified by self-healing and to evaluate how mechanical behaviour is affected before failure. In this paper, we implement for the first time a self-healing procedure in the random fuse model, whose characteristic scaling properties have been widely studied in the literature on damage evolution modelling. We identify some characteristic signatures of self-healing, showing that it can delay the failure of a material undergoing loading, but it also lead to a hard-to-predict, more catastrophic breakdown. Self-healing ; Fuse (electrical) ; Physics ; Toughness ; Self-healing material ; Property (philosophy) ; Scaling ; Composite material ; Materials science ; Medicine Polymer composites and self-healing ; Calcium Carbonate Crystallization and Inhibition ; Corrosion Behavior and Inhibition
Authors: Raju Kannadasan | Valsalal Prasad | Rajvikram Madurai Elavarasan | Umashankar Subramaniam | Dhafer Almakhles
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Development of High Gradient ZnO Arrester Material for High Voltage Applications The presence of stray capacitance in ZnO (Zinc Oxide) surge arresters causes hurdles in arrester operation and non-uniform voltage distribution along the arrester column, especially for High Voltage (HV) and Extra high voltage (EHV) applications. Since the magnitude of stray capacitance is directly proportional to the arrester height; the shortening of surge arresters is a preeminent method to enhance the arrester performance and voltage distribution. Particularly, this stray capacitive effect delays the arrester operation from in-action to action mode, especially against very fast surges. Moreover, the shortening of the arrester column improves the voltage distribution and hence the electric field varies between the stacks. Therefore, this research work focuses on the preparation of two new high gradient arrester materials doping with rare earth oxides. The microstructures of the newly developed materials are analyzed. It is found that there is a reduction of grain sizes and an increase of voltage gradients in the newly developed arrester materials. From this, the height requirement per unit is estimated and compared with the conventional ZnO arrester. Using these high gradient materials, the reduction of height and compactness of the arrester assembly may be achieved greatly. Thus, the developed ZnO surge arrester with high gradient materials enhances the arrester behavior with the attendant improvement of voltage distribution due to its reduced height and stray effect. Lightning arrester ; Surge arrester ; Materials science ; Voltage ; High voltage ; Capacitance ; Overvoltage ; Electrical engineering ; Varistor ; Parasitic capacitance ; Engineering ; Electrode ; Physics ZnO doping and properties ; Magnetic Field Sensors Techniques ; High voltage insulation and dielectric phenomena
Authors: Edward O. Pyzer‐Knapp | Graeme M. Day | Linjiang Chen | Andrew I. Cooper
Source: ChemRxiv (preprint, 2020-09-30)
Field: Materials Science — Materials Chemistry

Distributed Multi-Objective Bayesian Optimization for the Intelligent Navigation of Energy Structure Function Maps For Efficient Property Discovery Energy-structure-function (ESF) maps have emerged as a powerful tool for in silico materials design, coupling crystal structure prediction techniques with property simulations to assess the potential for new candidate materials to display desirable properties. Despite continuing increases to accessible computational power, however, the computational cost of acquiring an ESF map often remains too high to allow integration into true high-throughput virtual screening techniques. In this paper, we propose the next evolution of the ESF map, which uses parallel Bayesian optimization to selectively acquire energy and property data, generating the same levels of insight at a fraction of the computational cost by limiting the expensive property calculations to a small fraction of the predicted crystal structures associated with a molecule. We utilize this approach to obtain a two orders of magnitude speedup on a previous ESF study that focused on methane capture materials, saving over 500,000 CPUh from the original protocol. Through acceleration of the acquisition of ESF-type insight, we pave the way for the use of ESF maps in automated ultra-high throughput screening pipelines. This greatly reduce the opportunity risk associated with the choice of system to calculate. For example, it will allow researchers to use ESF maps in the search for physical properties where the computational costs are currently just intractable, or to investigate orders of magnitude more systems for a given computational cost.&lt;br&gt; Computer science ; Speedup ; Property (philosophy) ; Bayesian optimization ; Throughput ; Function (biology) ; Bayesian probability ; Pipeline (software) ; Distributed computing ; Data mining ; Machine learning ; Artificial intelligence ; Parallel computing Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Scientific Computing and Data Management
Authors: M. Razi | Akil Narayan | Robert M. Kirby | Dmitry Bedrov
Source: Computational Materials Science (article, 2020-01-14)
Field: Materials Science — Materials Chemistry

Force-field coefficient optimization of coarse-grained molecular dynamics models with a small computational budget Computer science ; Fidelity ; Computation ; Algorithm ; Field (mathematics) ; Computational complexity theory ; Force field (fiction) ; High fidelity ; Computational model ; Parameter space ; Set (abstract data type) ; Mathematical optimization ; Mathematics ; Artificial intelligence ; Physics ; Statistics Machine Learning in Materials Science ; Probabilistic and Robust Engineering Design ; Block Copolymer Self-Assembly
Authors: Jesse Maccione | Joseph Welch | Emily C. Heider
Source: Journal of Chemical Education (article, 2020-03-11)
Field: Chemistry — Physical and Theoretical Chemistry

Curve Fitting, Linear Algebra, and Solver in an Analytical Chemistry Course: A Facile and Safe Activity Suitable for the Classroom Setting Undergraduate analytical chemistry courses emphasize fundamental stoichiometric and physicochemical analytical techniques with statistical analysis and linear calibrations. Higher-level data analysis techniques may not be included in the college junior-level curriculum, but widely available software enables more complex analysis to be accessible. In this work, activities to train students in multicomponent spectral curve fitting (using Microsoft Excel’s Solver) and utilizing matrix algebra were incorporated within a large-enrollment undergraduate analytical chemistry lecture setting. When analyzing multiple compounds in solutions without separation pretreatment, both curve-fitting and classical matrix approaches are valuable techniques for students to understand and execute using commercially available software. When hands-on activities, multimedia screencasts, and in-class data collection and analysis were implemented, students were trained to employ these advanced analysis methods. The efficacy of the in-class practical activities was assessed with pre- and post-test instruments that quantified gains in learning outcomes. Inclusion of such activities will empower students with an expanded repertoire of these important analytical methods and their applications with a real world, portable, active-learning approach that can be completed in a lecture setting with nonhazardous samples. Computer science ; Solver ; Class (philosophy) ; Linear algebra ; Curriculum ; Software ; Microsoft excel ; Matrix (chemical analysis) ; Mathematics education ; Computational science ; Chemistry ; Mathematics ; Programming language ; Artificial intelligence ; Pedagogy Various Chemistry Research Topics ; Microfluidic and Capillary Electrophoresis Applications ; Analytical Chemistry and Chromatography
Authors: Gabriella N. Ruiz | Timothy C. Johnstone
Source: Journal of Chemical Education (article, 2020-05-12)
Field: Chemistry — Physical and Theoretical Chemistry

Computer-Aided Identification of Symmetry Relating Groups of Molecules Molecular symmetry plays an important role in many areas of chemistry, and students are generally taught to identify intramolecular symmetries at the undergraduate level. Intermolecular symmetry, the symmetry among groups of molecules, is of great importance in topics such as X-ray crystallography, but it receives substantially less attention. Even when familiar with such symmetries as translations, screw rotations, and glide reflections, students rarely obtain the same level of proficiency in identifying these symmetries via inspection as they do with the proper and improper rotations involved in point group symmetry. We describe a tool designed to scaffold the student’s ability to mentally manipulate molecules and identify the presence and nature of intermolecular symmetry. The tool consists of an algorithm that the student follows to generate centroids between atoms in putatively symmetry-related molecules. The easily recognized patterns formed by the centroids provide key information about the presence and nature of any intermolecular symmetry relating the molecules. The theoretical basis for the patterns formed by the centroids is provided along with worked examples, an example problem set, and a prescription for generating new exercises. Symmetry (geometry) ; Molecular symmetry ; Intermolecular force ; Centroid ; Molecule ; Group (periodic table) ; Intramolecular force ; Homogeneous space ; Theoretical physics ; Point group ; Symmetry group ; Set (abstract data type) ; Symmetry operation ; Chemistry ; Computer science ; Crystallography ; Chemical physics ; Physics ; Mathematics ; Geometry ; Artificial intelligence ; Quantum mechanics ; Stereochemistry Various Chemistry Research Topics ; Molecular spectroscopy and chirality ; History and advancements in chemistry
Authors: Issa I. Salame | Durica Nikolic
Source: Interdisciplinary Journal of Environmental and Science Education (article, 2020-12-22)
Field: Chemistry — Physical and Theoretical Chemistry

Examining Some of the Challenges Students Face in Learning about Solubility and the Dissolution Process Developing conceptual understanding of solubility and dissolution and the relationship to molecular structure, ionic salts’ charges, and enthalpy and entropy, play a significant role in the learning of chemistry. Dissolution and solubility are topics covered in general chemistry, quantitative analysis, biology, and organic chemistry. Alternative conceptions about some of the key chemistry principles can lead to students’ failure in understanding and accepting some of the future concepts. This study aims to examine some of the challenges and alternate conceptions that students face when learning about solubility and its relationship to Lewis structures and the driving force behind dissolution. A survey that consisted of ionic and molecular solubility related problems, short answers, and Likert-Type questions was given to 200 students in order to analyze their understanding of solubility, dissolution, alternate conceptions they possess, challenges they face in learning about the topics, and its relationship to Lewis dot structures and ionic charges. Our data indicates that students struggle with solving solubility and dissolution process related problems and rely on memorization to approach these problems. For ionic compounds, there seems to be a dependency on memorization and rote-learning of solubility rules instead of development of conceptual understanding of charges of ions and their relationship to entropy and enthalpy in the dissolution process. For molecular compounds, it should be noted that students lack mastery of determining molecular shape and its relationship to function but do emphasize the roles of Lewis structure and polarity in solubility. Finally, students do not attribute the combined effects of enthalpy and entropy as the driving forces behind dissolution and show very fragmented and naïve understanding of the concept. Dissolution ; Solubility ; Chemistry ; Enthalpy ; Memorization ; Ionic bonding ; Rote learning ; Thermodynamics ; Mathematics education ; Organic chemistry ; Psychology ; Ion ; Physics ; Teaching method ; Cooperative learning Various Chemistry Research Topics ; Science Education and Pedagogy ; Educational Strategies and Epistemologies
Authors: Sanghyun Yoo | Young Seok Kim | Kang Hyun Lee | Kuhwan Jeong | Junhwi Choi | Hoshik Lee | Young Sang Choi
Source: arXiv (Cornell University) (preprint, 2020-06-09)
Field: Materials Science — Materials Chemistry

Graph-Aware Transformer: Is Attention All Graphs Need? Graphs are the natural data structure to represent relational and structural information in many domains. To cover the broad range of graph-data applications including graph classification as well as graph generation, it is desirable to have a general and flexible model consisting of an encoder and a decoder that can handle graph data. Although the representative encoder-decoder model, Transformer, shows superior performance in various tasks especially of natural language processing, it is not immediately available for graphs due to their non-sequential characteristics. To tackle this incompatibility, we propose GRaph-Aware Transformer (GRAT), the first Transformer-based model which can encode and decode whole graphs in end-to-end fashion. GRAT is featured with a self-attention mechanism adaptive to the edge information and an auto-regressive decoding mechanism based on the two-path approach consisting of sub-graph encoding path and node-and-edge generation path for each decoding step. We empirically evaluated GRAT on multiple setups including encoder-based tasks such as molecule property predictions on QM9 datasets and encoder-decoder-based tasks such as molecule graph generation in the organic molecule synthesis domain. GRAT has shown very promising results including state-of-the-art performance on 4 regression tasks in QM9 benchmark. Computer science ; Decoding methods ; Theoretical computer science ; Transformer ; Encoder ; ENCODE ; Graph ; Algorithm Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: Tianyang Li | Chunsheng Yang | Zhiping Wei | Dong‐Sheng Pei | Guan Jiang
Source: OncoTargets and Therapy (review, 2020-05-01)
Field: Materials Science — Biomaterials

&lt;p&gt;Recent Advances of Magnetic Nanomaterials in the Field of Oncology&lt;/p&gt; Nanomagnetic devices, such as nano-field effect transistor biosensors and radio frequency magnetic induction therapies, came into being with the development of medical nanomaterials. The application of nanomagnetic materials in the treatment of cancers is rapidly becoming increasingly important because of its ability to target therapy and diagnose early. In this review, an untechnical overview of the fundamental of magnetism in nanomaterials and an illustration of how these materials are applied are presented. The applications of nano-field effect transistor biosensors for the detection of tumor biomarker nanomaterials in the therapy and diagnosis of cancers and nanomagnetic materials are summarized in this paper. A systemic summary of the use of nanomagnetic materials and nano-filed effect transistor biosensors for the treatment and diagnosis of tumors is also provided in the review. Nanomaterials ; Medicine ; Field (mathematics) ; Cancer research ; Oncology ; Internal medicine ; Medical physics ; Nanotechnology ; Materials science ; Mathematics Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: Hiroki Fujisawa | Meguya Ryu | Stefan Lundgaard | Denver P. Linklater | Elena Ivanova | Yoshiaki Nishijima | Saulius Juodkazis | Junko Morikawa
Source: Preprints.org (preprint, 2020-07-17)
Field: Materials Science — Biomaterials

Direct Measurement of Temperature Diffusivity of Nanocellulose Composite Films The thermal properties of novel nanomaterials play a significant role in determining the performance of the material in technological applications. Herein, direct measurement of the temperature diffusivity of cellulose nanocomposite films was carried out by the micro-contact method. Polymer films containing up to 2%wt. of nanocellulose were synthesised by a simple chemical process. Films of a high optical transmittance T &amp;asymp; 80 % (for a 200- &amp;mu; m-thick film), which were up to 44% crystalline, were characterised. Two different modalities of temperature diffusivity based on: 1) a resistance change and 2) micro-thermocouple detected modulation of a heat wave, were used for the polymer films with cross-sections of &amp;sim; 100 &amp;mu; m thickness. Twice different in-plane &amp;alpha; ‖ and out-of-plane &amp;alpha; &amp;perp; temperature diffusivities were directly determined with high fidelity: &amp;alpha; ‖ = 2 . 12 &amp;times; 10 &amp;minus; 7 m 2 /s and &amp;alpha; &amp;perp; = 1 . 13 &amp;times; 10 &amp;minus; 7 m 2 /s. An amorphous polyethylene terephthalate (PET) fiber was measured for comparison &amp;alpha; ‖ = 1 . 15 &amp;times; 10 &amp;minus; 7 m 2 /s. This work provides an example of a direct contact measurement of thermal properties of nanocellulose composite films. The thermal diffusivity, which is usually high in strongly interconnected networks and crystals, was investigated for the first time in this composite. Thermal diffusivity ; Nanocellulose ; Materials science ; Amorphous solid ; Composite number ; Nanocomposite ; Composite material ; Transmittance ; Analytical Chemistry (journal) ; Nanotechnology ; Cellulose ; Chemistry ; Crystallography ; Organic chemistry ; Thermodynamics ; Optoelectronics ; Physics Advanced Cellulose Research Studies ; Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging
Authors: Decai Gong | Xiaoning Zhang | Yuxuan Gong
Source: Journal of Conservation Science (article, 2020-02-28)
Field: Materials Science — Biomaterials

Insight Into the Crystallinity of Chinese Ancient Silk by Synchrotron Radiation-Based and Conventional X-ray Diffraction Methods This study investigates the crystallinity distribution of ancient silk. Owing to the inherent multi-hierarchical structure of silk protein and the complicated structural changes that occur due to various burial environments, it is challenging but worthwhile to study ancient silk ageing behavior, which is based on the fact that ageing begins with a single fiber and then spreads to a whole fabric. Crystallinity was one of the most effective indicators found to reveal the ageing status of silk. Therefore, a synchrotron radiation-based X-ray diffraction(SR-XRD) method was employed to study the crystallinity distribution of single fibers of ancient silk unearthed from seven archaeological sites in China from historical periods including the warring states, Han dynasty, Song dynasty, and Ming dynasty. In comparison, the conventional X-ray diffraction method, which uses large amounts of samples, was also performed to determine the integral crystallinity of ancient silk. Thermal stability experiments by thermogravimetry(TG) as well as morphology observations by scanning electron microscopy(SEM) and optical microscopy(OM) all confirmed the deterioration of ancient silk. Moreover, the ageing mechanism of ancient silk was proposed with the assistance of an artificial ageing study. The results confirmed the effectiveness of SR-XRD as an ageing indicator, revealing the crystallinity distribution. This research could provide motivation to determine the deterioration status of ancient silk, and would also aid in explaining the fragility of ancient silk due to ageing. Crystallinity ; SILK ; Synchrotron radiation ; Materials science ; Diffraction ; Composite material ; Optics ; Physics Silk-based biomaterials and applications ; Silkworms and Sericulture Research