jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kaitlin Tyler | Claes Fredriksson | Ansys Granta
Source: 2020 ASEE Virtual Annual Conference Content Access Proceedings (article, 2020-09-08)
Field: Materials Science — Materials Chemistry

Software Support for Materials-related Active Learning The world of education is ever expanding, and with it, our understanding of how people learn. By helping the students connect to their prior knowledge during the formal education in a structured course, the educators can help the students build a more complete comprehension of the topic. Active learning, as a broad term, serves to engage students in the course material in a variety of ways, thereby increasing the probability of connecting with prior knowledge and improving their overall subject understanding. Due to its nature, active learning is necessarily a broad field. There is no one size fits all; different approaches work for different students with different learning styles, subjects, teachers, classrooms, countries and cultural orientations. How can we incorporate active learning methods in teaching materials science and engineering to undergraduates across the globe? At Ansys Granta, we are interested in understanding how active learning methods are used across the world in materials science courses. For over 25 years, we have been supporting materials education globally through our software GRANTA EduPack. During that time, we have seen how teaching has evolved and the impact active learning techniques have had for materials education. In this paper, we will be sharing how materials teaching with active learning varies around the world and how GRANTA EduPack and its associated resources can support these efforts. We hope this insight gained over many years can aid those looking to adjust their materials courses to include more active learning techniques. Active learning (machine learning) ; Globe ; Computer science ; Comprehension ; Mathematics education ; Variety (cybernetics) ; Artificial intelligence ; Psychology Machine Learning in Materials Science ; Mechatronics Education and Applications ; Manufacturing Process and Optimization
Authors: Joseph H. Montoya | Kirsten T. Winther | Raul A. Flores | Thomas Bligaard | Jens S. Hummelshøj | Muratahan Aykol
Source: ChemRxiv (preprint, 2020-02-19)
Field: Materials Science — Materials Chemistry

Autonomous Intelligent Agents for Accelerated Materials Discovery We present an end-to-end computational system for autonomous materials discovery. The system aims for cost-effective optimization in large, high-dimensional search spaces of materials by adopting a sequential, agent-based approach to deciding which experiments to carry out. In choosing next experiments, agents can make use of past knowledge, surrogate models, logic, thermodynamic or other physical constructs, heuristic rules, and different exploration-exploitation strategies. We show a series of examples for (i) how the discovery campaigns for finding materials satisfying a relative stability objective can be simulated to design new agents, and (ii) how those agents can be deployed in real discovery campaigns to control experiments run externally, such as the cloud-based density functional theory simulations in this work. In a sample set of 16 campaigns covering a range of binary and ternary chemistries including metal oxides, phosphides, sulfides and alloys, this autonomous platform found 383 new stable or nearly stable materials with no intervention by the researchers. Computer science ; Heuristic ; Set (abstract data type) ; Binary number ; Autonomous agent ; Distributed computing ; Artificial intelligence ; Mathematics Machine Learning in Materials Science
Authors: Laura Stachow | Jared VanderZwaag | Kristen Limacher | Liza Abraham
Source: The Chemical Educator (article, 2020-02-01)
Field: Chemistry — Physical and Theoretical Chemistry

Transitioning from General Chemistry into Organic Chemistry A laboratory experiment was developed and implemented for second year undergraduate students as their first organic chemistry (OCHEM) laboratory experiment to facilitate a smoother transition from general chemistry (GCHEM) to OCHEM. The objective of the experiment was for students to execute a saponification reaction using coconut oil and understand the chemical principles behind that reaction. After performing the experiment, students formed into groups to discuss and answer inquiry-based questions provided by a supporting worksheet. Discussion groups were used to facilitate active participation and collaborative learning with the aim of building a connection between GCHEM and OCHEM concepts through the application of these principles in this laboratory experiment. Rather than employing the traditional, cook-book approach to laboratory experiments, this project allows students to critically review fundamental concepts through peer-led discussions, laying a strong foundation for the course materials, and strengthening understanding of fundamental chemistry concepts. Students have the opportunity to apply basic OCHEM concepts such as: structural representations, electronegativity, polarity, solubility, orbital overlap, sigma and pi bonding, functional groups as site of reactivity, electrophile and nucleophile, reaction mechanisms, resonance, and nucleophilic acyl substitution reaction as a means to explain the saponification reaction. The conversion of oils into soap is an ideal exercise to implement active learning through student engagement. By employing a simple saponification reaction and problem-solving discussions, students are better positioned to begin their studies in OCHEM. Saponification ; General chemistry ; Foundation (evidence) ; Green chemistry ; Nucleophilic substitution ; Ideal (ethics) Various Chemistry Research Topics ; Innovative Teaching Methods ; Science Education and Pedagogy
Authors: Gianluca Tirimbó | Onur Çaylak | Björn Baumeier
Source: arXiv (Cornell University) (preprint, 2020-12-03)
Field: Materials Science — Materials Chemistry

A Kernel-based Machine Learning Approach to Computing Quasiparticle Energies within Many-Body Green's Functions Theory We present a Kernel Ridge Regression (KRR) based supervised learning method combined with Genetic Algorithms (GAs) for the calculation of quasiparticle energies within Many-Body Green's Functions Theory. These energies representing electronic excitations of a material are solutions to a set of non-linear equations, containing the electron self-energy (SE) in the $GW$ approximation. Due to the frequency-dependence of this SE, standard approaches are computationally expensive and may yield non-physical solutions, in particular for larger systems. In our proposed model, we use KRR as a self-adaptive surrogate model which reduces the number of explicit calculations of the SE. Transforming the standard fixed-point problem of finding quasiparticle energies into a global optimization problem with a suitably defined fitness function, application of the GA yields uniquely the physically relevant solution. We demonstrate the applicability of our method for a set of molecules from the $GW$100 dataset, which are known to exhibit a particularly problematic structure of the SE. Results of the KRR-GA model agree within less than 0.01 eV with the reference standard implementation, while reducing the number of required SE evaluations roughly by a factor of ten. Quasiparticle ; GW approximation ; Kernel (algebra) ; Computer science ; Set (abstract data type) ; Physics ; Mathematics ; Applied mathematics ; Mathematical optimization ; Statistical physics ; Quantum mechanics ; Discrete mathematics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Computational Drug Discovery Methods
Authors: Meysam Hassanipour | Shinta Watanabe | Han Li | Kyosuke Hirayama | Hiroyuki Toda | Akihisa Takeuchi | Kentaro Uesugi
Source: MATEC Web of Conferences (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

A Surrogate Approach to Reveal Microstructural Mechanisms Controlling the 3D Short Crack Growth in a Ti-6Al-4V Alloy Microstructural features and short crack growth behavior were characterized and linked in a Ti-6Al-4V by employing X-ray micro-tomography combined with EBSD serial sectioning. Statistical analysis was used to rank the contributing features to the crack behavior. Afterwards, by creating surrogate models, the microstructural mechanism controlling the short crack behavior were revealed. Short crack preferably grows inside the predominant α phase above the average microstructural fraction. A high number of grains in contact with cracked α grains elongated in the loading direction may impose a constraint on the crack opening resulting in low crack growth rates. As the crack front becomes larger, the increase in the shear stress field away from the cracked grain leads to crack bifurcations, resulting in a decrease in crack driving forces with low crack growth rates. This leads to a preferable growth in α+β phase and along the interface above the average microstructural fractions. Materials science ; Crack closure ; Crack growth resistance curve ; Electron backscatter diffraction ; Shear (geology) ; Microstructure ; Composite material ; Alloy ; Fracture mechanics ; Metallurgy Titanium Alloys Microstructure and Properties ; High-Velocity Impact and Material Behavior ; Welding Techniques and Residual Stresses
Authors: E. Macerata | M. Negrin | F. Concia | Eros Mossini | Gabriele Magugliani | Susanna Sancassani | Mira Mariani
Source: Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (article, 2020-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Learning nuclear chemistry and radiochemistry through a massive open online course A MOOC on Nuclear and RadioChemistry (NRC) has been developed within the EU-H2020 MEET-CINCH project, in order to attract more students towards the discipline and increase people awareness. The course is divided into five “weeks” highlighting the importance of radiochemistry and nuclear chemistry for environment, health, industry, nuclear energy and society. Each week consists of different modules covering all possible applications of NRC within the week topic. The module follows a pedagogical framework designed ad hoc, that gradually introduces the topic to students, giving them different examples and applications to understand the theoretical concepts and to acquire a technical terminology. Feedback obtained by the pilot edition showed very good results: despite the short duration of the course, 25% of the 203 users successfully completed the course achieving the Certificate of Accomplishment. The answers collected in the inital survey and the final customer satisfaction questionnaire showed that users belonged to the selected target group and greatly appreciated the presence of practical examples and the different lesson formats adopted. The MOOC objective of attracting new students towards NRC appears to be on a good track, however this can only be confirmed by monitoring the next MOOC editions. Course (navigation) ; Online course ; Massive open online course ; Radiochemistry ; Chemistry ; Mathematics education ; Engineering ; Psychology Various Chemistry Research Topics
Authors: Mark A. Buntine | Karen Burke da Silva | Scott H. Kable | Kieran F. Lim | Simon M. Pyke | Justin R. Read | Manjula D. Sharma | Alexandra Yeung
Source: International Journal of Innovation in Science and Mathematics Education (article, 2020-12-31)
Field: Chemistry — Physical and Theoretical Chemistry

Perceptions and Misconceptions about the Undergraduate Laboratory from Chemistry, Physics and Biology Academics The undergraduate laboratory occupies a large fraction of science students’ time. Over 3000 students were asked to rate their laboratory learning experience using 12 metrics. 362 academics were asked to predict which of these 12 aspects of the student experience would correlate with the overall laboratory learning experience. Responses from academics in biology, chemistry and physics departments, and from the USA and Australia, are statistically the same. However, the correlation between these staff predictions and student results is poor. The student results are consistent with extant educational research, but it appears that these findings are not reaching those who are responsible for developing undergraduate laboratory courses. There is a great need for educational research to be made more accessible for academics who are trained in scientific, but not in educational research. Extant taxon ; Undergraduate research ; Mathematics education ; Perception ; Undergraduate education ; Medical education ; Chemistry ; Psychology ; Biology ; Medicine ; Evolutionary biology Various Chemistry Research Topics ; Innovative Teaching Methods ; Science Education and Pedagogy
Authors: Didi MA
Source: Academic Journal of Engineering Studies (article, 2020-09-15)
Field: Chemistry — Analytical Chemistry

Cloud Point Extraction of Toxic Red Bemacid Dye by Ionic Liquids and Nonionic Surfactant System and Factorial Design The present study investigates the effects of additives on the cloud point temperature of Triton X-100 as a non-ionic surfactant in aqueous solutions (% of Triton X-100,% of salts (NaCl, Na2S2O3, Na2SO4, KI, KBr, KNO3), and concentrations of synthesized ionic liquids (Thiocyanate trioctylmethyl ammonium (LI1), Hydrogenophosphatetrioctylmethyl ammonium (LI2)). The parametric study based on the experimental design methodology by means of 24 factorial design, allows us to predict the effect of the main parameters pH (4.0-8.0), percent mass of Triton X-100 (2-10%), Na2SO4 (8-10%) and Red Bemacid dye concentration (10-100ppm) with 100ppm of synthetic ionic liquids on the extraction efficiency of the dye.The extraction using the CPE process (Cloud Point Extraction) of Red Bemacid showed to be efficient, reaching values of more than 100% dye recovery in optimum conditions using these two ionic liquids Pulmonary surfactant ; Cloud point ; Extraction (chemistry) ; Factorial experiment ; Chromatography ; Nonionic surfactant ; Chemistry ; Mathematics ; Statistics ; Biochemistry Dye analysis and toxicity ; Bee Products Chemical Analysis ; melanin and skin pigmentation
Authors: Poliana G. Abrantes | João Batista Moura de Resende Filho | A. Simões
Source: Revista Virtual de Química (article, 2020-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Contradictions and Misconceptions in High School Chemistry Textbooks About the Concept and Classification of Salts The didactic book is an important knowledge-guiding instrument used in teaching-learning processes. Usually, it is the only educational media used in the classroom by teachers at several levels of education. However, many books present conceptual errors that can lead to confusion and hinder the teaching-learning process. Thus, the present paper brings an investigation of the salt concept present in High School textbooks of Chemistry, in order to identify and discuss possible misconceptions. A bibliographical research was used as a method for collecting data, using a qualitative approach, in which the concepts found in the High School textbooks were compared with those present in Undergraduation and Graduation Chemistry books, IUPAC Gold Book and scientific articles. Results show several conceptual misconceptions, poor definitions and ideas that do not conform to scientific language: use of erroneous synonyms, classification of salts as chemical function, use of the term "hydroxyl" as equal to "hydroxide", among others. Mathematics education ; Chemistry ; Environmental chemistry ; Psychology Various Chemistry Research Topics
Authors: Christoph Tietz | Tobias Fritz | Katharina Holzweber | Michael Legenstein | B. Sepioł | Michael Leitner
Source: Physical Review Research (article, 2020-10-27)
Field: Materials Science — Materials Chemistry

Diffusive dynamics in an amorphous superionic conductor The fast diffusion of alkali ions and resulting high ionic conductivity is a defining feature of alkali borate glasses. Here we report impedance spectroscopy and atomic-scale x-ray photon correlation spectroscopy measurements on rubidium borate systems (Rb 2 O) x (B 2 O 3 ) 100-x with particular focus on x = 30 mol %. We find that the coherently scattered intensity does not show temporal fluctuations on timescales corresponding to ionic diffusion. We conclude that the spatial configuration of alkali sites as stepping stones for ionic diffusion evolves on the same timescales as the borate backbone, and that the defect density is low, i.e., at a given instant, nearly all alkali sites are singly occupied. Alkali metal ; Ion ; Amorphous solid ; Ionic bonding ; Diffusion ; Chemistry ; Ionic conductivity ; Physics ; Chemical physics ; Crystallography ; Physical chemistry ; Thermodynamics ; Quantum mechanics Material Dynamics and Properties ; Glass properties and applications ; Theoretical and Computational Physics
Authors: Julia Winter | Sarah E. Wegwerth | Gianna J. Manchester | Michael T. Wentzel | Michael Evans | James E. Kabrhel | Lawrence J. Yee
Source: ChemRxiv (preprint, 2020-03-05)
Field: Chemistry — Physical and Theoretical Chemistry

The Mechanisms App: Electron-Pushing Formalism as a Software System &lt;p&gt;The arrows depicting electron movement and the bond-making and breaking events are the maps that guide student instruction in organic chemistry curricula. For students, the pathways represented by electron pushing formalism (EPF) can be tough to navigate. For instructors, providing formative feedback to students to support their learning of the EPF arrow system is difficult to provide in a timely manner. The Mechanisms app (“Mechanisms”) was developed as a method for students to explore the electron movement of organic chemistry through a touch screen interface of a smart phone or tablet and do so within a game-like experience. In this paper the pedagogical content of the Mechanisms app (“Mechanisms”) is described along with studies of students’ use of the app to understand whether the open-ended experience to construct understanding of EPF is valuable as a formative assessment method. Presented in this paper are the results of Mechanisms use by analysis of a multi-institution anonymous student survey, with a usability study of organic chemistry students, and with three case studies detailing the use of the app in college classrooms. &lt;/p&gt; Formative assessment ; Usability ; Curriculum ; Computer science ; Chemistry ; Construct (python library) ; Human–computer interaction ; Formalism (music) ; Mathematics education ; Multimedia ; World Wide Web ; Psychology ; Pedagogy ; Art ; Visual arts Various Chemistry Research Topics ; Innovative Teaching Methods ; Innovative Teaching and Learning Methods
Authors: Alexander Ganago
Source:  (article, 2020-09-03)
Field: Chemistry — Physical and Theoretical Chemistry

Lab Lecture Experiments As A Principle Of Teaching Instructors who teach theory traditionally provide their students with several ways to ensure that they have attained the required new knowledge or skill before being tested on it. Students can ask questions during lectures and office hours, practice exercises in the textbook and do the assigned homework, etc. Thus the tradition creates several steps of reassurance for the student that the material has been learned before grade points are given or deducted for the results of this learning demonstrated on the exam. Surprisingly, this tradition is often defied in laboratory teaching. For example, it is not unusual to find a laboratory assignment, in which the beginning students who were just shown an oscilloscope are required to make measurements using this new instrument, with a possibility of losing the points for getting wrong results. The learning suffers when students are unsure whether they are doing the right thing and whether their data make sense. Lack of reassurance leads to unnecessary stress, shifts focus from learning to fear of losing points, and makes laboratory activities less effective than they should be. Computer science ; Mathematics education ; Mathematics Various Chemistry Research Topics ; Experimental Learning in Engineering ; Innovative Teaching Methods
Authors: R. W. Seymour | Sjoerd van der Post | Arshag D. Mooradian | Jason M. Held
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-11-25)
Field: Chemistry — Spectroscopy

ProteoSushi: a software tool to biologically annotate and quantify modification-specific, peptide-centric proteomics datasets Abstract Large-scale proteomic profiling of protein post-translational modifications has provided important insights into the regulation of cell signaling and disease. These modification-specific proteomics workflows nearly universally enrich modified peptides prior to mass spectrometry analysis, but protein-centric proteomic software tools have many limitations evaluating and interpreting these peptide-centric datasets. We therefore developed ProteoSushi, a software tool tailored to the analysis of each modified site in peptide-centric proteomic datasets that is compatible with any post-translational modification or chemical label. ProteoSushi uses a unique approach to assign identified peptides to shared proteins and genes, minimizing redundancy by prioritizing shared assignments based on UniProt annotation score and optional user-supplied protein/gene lists. ProteoSushi simplifies quantitation by summing or averaging intensities, merging overlapping peptide charge states, missed cleavages, peptide spectral matches, and variable modifications into a single value for each modified site. ProteoSushi annotates each PTM site with the most up-to-date biological information available from UniProt, such as functional roles or known modifications, the protein domain in which the site resides, the protein’s subcellular location and function and more. ProteoSushi has a graphical user interface for ease of use. ProteoSushi’s flexibility and combination of features streamlines peptide-centric data processing and knowledge mining of large modification-specific proteomics datasets. UniProt ; Proteomics ; Computer science ; Computational biology ; Workflow ; Software ; Profiling (computer programming) ; Peptide ; Bioinformatics ; Data mining ; Biology ; Gene ; Database ; Biochemistry Advanced Proteomics Techniques and Applications ; Peptidase Inhibition and Analysis ; Machine Learning in Bioinformatics
Authors: Om Prakash
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-03-06)
Field: Chemistry — Spectroscopy

Algorithm for theoretical mapping of bio-strings for co-expression: bridging genotype to phenotype ABSTRACT Identification of possibility of co-expression or co-performance directly from set of bio-strings as protein sequences represents an important problem of bridging between genotype to phenotype. This algorithm presents above bridging. Algorithm was implemented with proteins known from human hormone signaling system. Co-expression of proteins was cross-validated through human gene COXPRESdb v7 database. Possibility of protein-protein interaction (PPI) was also cross checked through STRING database. Results were found to be effectively fascinating. Considering the indications from results, this algorithm can be adopted for theoretical identification of co-expression or co-performance of bio-strings. Bridging (networking) ; Phenotype ; Identification (biology) ; Genotype ; Computational biology ; Expression (computer science) ; Gene ; Computer science ; String (physics) ; Biology ; Genetics ; Mathematics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Biotin and Related Studies