jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shuang Han | Steen Lysgaard | Tejs Vegge | Heine Anton Hansen
Source: ChemRxiv (preprint, 2022-07-10)
Field: Materials Science — Materials Chemistry

Rapid and accurate mapping of reaction condition-dependent alloy phase diagrams via Bayesian evolutionary multitasking Many global optimization tasks have partially or completely shared search spaces. This is particularly common in computational heterogeneous catalysis, where catalysts are optimized to their lowest-energy configurations under various idealized chemical conditions to construct phase diagrams. If each task represents the global optimization under a unique reaction condition, all tasks essentially shares the same configurational search space as well as the same black-box function that takes as input the configuration and returns the relaxed energy obtained by an expensive electronic structure calculation. Bayesian optimization represents an efficient paradigm for solving a single global optimization task of an expensive black-box function. Evolutionary multitasking is a newly emerging paradigm for solving multiple global optimization tasks simultaneously. Here we present a Bayesian evolutionary multitasking (BEM) framework combining the best of the two paradigms. As a case study, we aim to derive the phase diagram of Pt-doped Ni nanoparticles covering a wide variety of steam methane reforming conditions. By integrating knowledge such as graph theory and lattice symmetry, the BEM framework as a whole can significantly accelerate the mapping of phase diagrams for very complex heterogeneous systems. The efficient calculation of surface free energies of low index facets in the reactive catalyst environment provides insight into catalyst deactivation through coking and sulfur poisoning. Human multitasking ; Computer science ; Bayesian optimization ; Optimization problem ; Theoretical computer science ; Algorithm ; Artificial intelligence Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Hydrodesulfurization Studies
Authors: Biaojie Yan | Zhiyi Wang | Tao Fa | Liang Cheng | Pengcheng Zhang
Source: Ceramics International (article, 2022-05-06)
Field: Materials Science — Materials Chemistry

Bi-objective optimization of thermal conductivity and thermal stress of UO2–Mo–Nb composite through Gaussian process regression and NSGA-II method Materials science ; Thermal conductivity ; Composite number ; Thermal expansion ; Matrix (chemical analysis) ; Stress (linguistics) ; Composite material ; Range (aeronautics) Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear Engineering Thermal-Hydraulics
Authors: Michael F. Ofori | Cynthia Amaning Danquah | Paul Poku Sampene Ossei | Gilbrene Rahamani | Isaac Newton Nugbemado | Peace Doe | Theophilus Kwesi Ninkyi
Source: Journal of Applied Pharmaceutical Science (article, 2022-05-05)
Field: Chemistry — Organic Chemistry

Antitubercular activities of Crinum asiaticum bulb extract using aeroso-linduced Mycobacterium smegmatis in mice model Tuberculosis (TB) is one of the highly infectious diseases affecting one-third of the world's population. The emergence of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis has affected TB management. The death toll from MDR-and XDR-TB is estimated to be more than a million people each year which is alarming; therefore, there is a need to discover novel compounds which could be developed to tackle resistant TB. The extracts from the bulbs of the plant Crinum asiaticum are used ethnomedicinally to treat upper respiratory tract infections and skin infections and for wound healing activities. The work seeks to investigate the antitubercular activities of chloroformic C. asiaticum bulb extracts (CCAE) in aerosol-induced TB in a mice model using Mycobacterium smegmatis strains. From the results obtained, the histology of the infected lungs managed with 500 and 1,000 mg/kg doses of CCAE showed improved lung alveolar space, lung parenchyma, and bronchial functions. CCAE reduced significantly (p 0.05) the colony-forming unit/ml count of M. smegmatis on the lungs. In the assessment of tumor necrosis factor-alpha and interleukin-6 levels expressed, CCAE showed a significant (p 0.05) reduction in their levels. There were dose-dependent increases in red blood cells and hemoglobin, while there was a decrease in white blood cells count in the hematological analysis of CCAE treated groups compared with the negative control group. Overall, C. asiaticum bulb extract showed a promising antitubercular effect, which makes it a potential lead in the discovery and development of anti-TB agents that could help resolve issues of resistance in the management of TB. Mycobacterium smegmatis ; Bulb ; Traditional medicine ; Biology ; Microbiology ; Botany ; Mycobacterium tuberculosis ; Medicine ; Tuberculosis Chemical synthesis and alkaloids ; Alkaloids: synthesis and pharmacology ; Plant-based Medicinal Research
Authors: Christopher A. Nix | Isadore Nottolini | Jonathan D. Caranto | Yulia V. Gerasimova | Dmitry M. Kolpashchikov | Erin K. H. Saitta
Source: International Journal of Higher Education (article, 2022-06-07)
Field: Chemistry — Physical and Theoretical Chemistry

Championing the Involvement of Practitioners in the Biochemistry Educational Research Process: A Phenomenological View of the Early Stages of Collaborative Action Research The disparity between post-secondary STEM instruction and the practices suggested in education and cognitive research is not a novel issue. Despite evidence-based practices being available to practitioners, traditional lecture-based instruction continues to dominate higher STEM education. In this study, we discussed practitioner involvement in biochemistry education research as a potential means to address the gap between research and practice. We used phenomenology as a lens through which to view faculty experiences of participating in a team-based curricular redesign. We administered a concept inventory to examine undergraduate students’ understanding of key concepts and to identify misconceptions. We captured faculty perspectives and reflections on student data through semi-structured interviews, finding that faculty dissatisfaction with traditional practices were rooted in experiences from early on in their teaching careers. Their students demonstrated a lack of conceptual understanding, similar to findings of other studies in undergraduate biochemistry, and key misconceptions the student population held were identified. When examining students’ conceptual understanding data, the faculty gained new insights into where students struggle in the course that they would not have gained without participation in this project. This reinforced their desire to implement curricular change. These findings add to the available data on students’ conceptual understanding in biochemistry and suggest that shared assessments like concept inventories can unify instructors as they engage in team-based curricular reform. Phenomenology (philosophy) ; Psychology ; Action research ; Conceptual framework ; Process (computing) ; Pedagogy ; Medical education ; Conceptual change ; Engineering ethics ; Sociology ; Medicine ; Engineering ; Social science ; Computer science ; Epistemology Various Chemistry Research Topics ; Science Education and Pedagogy ; Innovative Teaching and Learning Methods
Authors: Kelechi O. Uleanya | Caroline E. H. Dessent | Sam Furfari | Leonie C. Jones | Kgato P. Selwe | Amelia B. Milner
Source: ChemRxiv (preprint, 2022-10-25)
Field: Chemistry — Physical and Theoretical Chemistry

A Resource to Support Decolonization of the Undergraduate Chemistry Curriculum In our taught chemistry curricula, the majority of individuals who are used to illustrate historical aspects of chemistry topics are white western chemists. Decolonizing the undergraduate chemistry curricula is increasingly recognized as an important step towards developing a more inclusive higher-education environment for students from minoritized ethnic backgrounds. Here, we provide the first openly accessible resource that can be used to decolonize an undergraduate chemistry course. In particular, the resource provides examples of both individual scientists and groups that can be used to illustrate chemistry teaching, and hence provide role model examples of scientists from different cultures. The resource presented provides a significant body of examples for chemistry lecturers to use as they begin working towards decolonizing their curricula. Curriculum ; Resource (disambiguation) ; Chemistry ; Chemistry education ; Engineering ethics ; Ethnic group ; Decolonization ; Mathematics education ; Pedagogy ; Sociology ; Engineering ; Political science ; Computer science ; Psychology ; Anthropology Various Chemistry Research Topics ; Innovative Teaching Methods
Authors: Roselle Urbano | Herbert De Jesus | Ponciano Dimla
Source: International Journal of Education Teaching and Social Sciences (article, 2022-06-03)
Field: Chemistry — Physical and Theoretical Chemistry

Measuring Students' Learning and Attitude as Exposed to Microscale Laboratory Experiments in Inorganic Chemistry Microscale chemistry is an approach to conducting chemistry experiments which can help overcome increased concerns about environmental pollution problems as well as rising laboratory costs. It is accomplished by using miniature labware and significantly reduced amounts of chemicals. The main goal of this study was to explore whether the use of microscale chemistry experiments can increase student’s understanding of chemistry concepts and improve attitude towards chemistry practical work. Quasi-experimental design without control group was used to determine from purposively selected class of 40 freshman students of Bachelor of Secondary Education (BSE). The students worked in groups on eight microscale chemistry experiments in a period of 8 weeks. Pre and post-test were administered before and after the treatment. Results revealed that microscale approach significantly improved student chemistry academic performance. Students’ perception of microscale is positive. Findings showed that the microscale approach can increase understanding of chemistry concepts. Keywords: learning, students’ attitude, microscale laboratory Microscale chemistry ; Chemistry ; Mathematics education ; Psychology Various Chemistry Research Topics ; Mobile Learning in Education ; Problem and Project Based Learning
Authors: E. A. Saveleva | Valentina Svitelman
Source: Radioactive waste (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Uncertainty management in the context of long-term safety assessment Uncertainty management is a key element of a confidence-building process in the context of the numerical safety assessment of radioactive waste disposal facilities. This paper presents an overview of the approaches for uncertainty treatment at different stages of a safety assessment with a focus on the characterization and reduction of uncertainties of a particular numerical model. Context (archaeology) ; Risk analysis (engineering) ; Safety case ; Key (lock) ; Term (time) ; Risk assessment ; Process (computing) ; Uncertainty analysis ; Computer science ; Engineering ; Environmental science ; Business ; Simulation ; Geology ; Computer security Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies ; Probabilistic and Robust Engineering Design
Authors: Pranav Shetty | Arunkumar Chitteth Rajan | Christopher Kuenneth | Sonkakshi Gupta | Lakshmi Prerana Panchumarti | Lauren Holm | Chao Zhang | Rampi Ramprasad
Source: arXiv (Cornell University) (preprint, 2022-09-27)
Field: Materials Science — Materials Chemistry

A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language Processing The ever-increasing number of materials science articles makes it hard to infer chemistry-structure-property relations from published literature. We used natural language processing (NLP) methods to automatically extract material property data from the abstracts of polymer literature. As a component of our pipeline, we trained MaterialsBERT, a language model, using 2.4 million materials science abstracts, which outperforms other baseline models in three out of five named entity recognition datasets when used as the encoder for text. Using this pipeline, we obtained ~300,000 material property records from ~130,000 abstracts in 60 hours. The extracted data was analyzed for a diverse range of applications such as fuel cells, supercapacitors, and polymer solar cells to recover non-trivial insights. The data extracted through our pipeline is made available through a web platform at https://polymerscholar.org which can be used to locate material property data recorded in abstracts conveniently. This work demonstrates the feasibility of an automatic pipeline that starts from published literature and ends with a complete set of extracted material property information. Pipeline (software) ; Property (philosophy) ; Computer science ; Natural language processing ; Information retrieval ; Set (abstract data type) ; Data set ; Artificial intelligence ; Data extraction ; Programming language ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Satanu Ghosh | Kun Lü
Source: Aslib Journal of Information Management (article, 2022-08-26)
Field: Materials Science — Materials Chemistry

Band gap information extraction from materials science literature – a pilot study Purpose The purpose of this paper is to present a preliminary work on extracting band gap information of materials from academic papers. With increasing demand for renewable energy, band gap information will help material scientists design and implement novel photovoltaic (PV) cells. Design/methodology/approach The authors collected 1.44 million titles and abstracts of scholarly articles related to materials science, and then filtered the collection to 11,939 articles that potentially contain relevant information about materials and their band gap values. ChemDataExtractor was extended to extract information about PV materials and their band gap information. Evaluation was performed on randomly sampled information records of 415 papers. Findings The findings of this study show that the current system is able to correctly extract information for 51.32% articles, with partially correct extraction for 36.62% articles and incorrect for 12.04%. The authors have also identified the errors belonging to three main categories pertaining to chemical entity identification, band gap information and interdependency resolution. Future work will focus on addressing these errors to improve the performance of the system. Originality/value The authors did not find any literature to date on band gap information extraction from academic text using automated methods. This work is unique and original. Band gap information is of importance to materials scientists in applications such as solar cells, light emitting diodes and laser diodes. Computer science ; Information extraction ; Identification (biology) ; Information gap ; Information retrieval ; Gap analysis (conservation) ; Photovoltaic system ; Originality ; Work (physics) ; Information science ; Data science ; Library science ; Engineering ; Sociology ; Electrical engineering ; Mechanical engineering Machine Learning in Materials Science ; scientometrics and bibliometrics research
Authors: Fan Bai | Alan Ritter | Peter B. Madrid | Dayne Freitag | John Niekrasz
Source: arXiv (Cornell University) (preprint, 2022-08-15)
Field: Materials Science — Materials Chemistry

SynKB: Semantic Search for Synthetic Procedures In this paper we present SynKB, an open-source, automatically extracted knowledge base of chemical synthesis protocols. Similar to proprietary chemistry databases such as Reaxsys, SynKB allows chemists to retrieve structured knowledge about synthetic procedures. By taking advantage of recent advances in natural language processing for procedural texts, SynKB supports more flexible queries about reaction conditions, and thus has the potential to help chemists search the literature for conditions used in relevant reactions as they design new synthetic routes. Using customized Transformer models to automatically extract information from 6 million synthesis procedures described in U.S. and EU patents, we show that for many queries, SynKB has higher recall than Reaxsys, while maintaining high precision. We plan to make SynKB available as an open-source tool; in contrast, proprietary chemistry databases require costly subscriptions. Computer science ; Transformer ; Plan (archaeology) ; Information retrieval ; Engineering Machine Learning in Materials Science ; Advanced Text Analysis Techniques ; Semantic Web and Ontologies
Authors: Jerome D. Roscioli | Michael Desanker | Kshitish A. Patankar | Adam L. Grzesiak | Xiaoyun Chen
Source: Applied Spectroscopy (article, 2022-06-17)
Field: Chemistry — Analytical Chemistry

Simultaneous High-Throughput Monitoring of Urethane Reactions Using Near-Infrared Hyperspectral Imaging High-throughput (HTP) research is becoming more widely utilized due to its advantages in rapid screening of large parameter space. When HTP is used for reaction screening, often only the end products are analyzed by off-line techniques, leaving behind valuable process information. Information-rich spectroscopy tools have remained under-utilized in HTP workflows. In this study, near-infrared (NIR) hyperspectral imaging (HSI) is demonstrated to be a versatile and accurate tool that can simultaneously monitor multiple reactions, opening up future opportunities to maximize information extraction from such HTP reaction screening experiments. Model urethane reactions are used here to demonstrate the concept, and the general approach can be widely applied to any reactions involving NIR-active functional groups. The fast speed and accurate chemical information made possible by NIR HSI are expected be another important addition to the toolkit of HTP research. Hyperspectral imaging ; Throughput ; Chemical imaging ; Computer science ; Workflow ; Near-infrared spectroscopy ; Process engineering ; Infrared ; Process (computing) ; Nanotechnology ; Biological system ; Biochemical engineering ; Chemistry ; Materials science ; Artificial intelligence ; Optics ; Physics ; Database ; Telecommunications ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Birk Fritsch | Tobias Zech | Mark Bruns | Andreas Körner | Saba Khadivianazar | Mingjian Wu | Neda Zargar Talebi | Sannakaisa Virtanen | Tobias Unruh | Michael P. M. Jank | Erdmann Spiecker | Andreas Hutzler
Source: ChemRxiv (preprint, 2022-04-08)
Field: Materials Science — Surfaces, Coatings and Films

Radiolysis-Driven Evolution of Gold Nanostructures – Model Verification by Scale Bridging in situ Liquid-Phase Transmission Electron Microscopy and X-ray Diffraction Formation and degradation of gold nanostructures in tetrachloroauric acid (HAuCl4) is comprehensively investigated via in situ liquid-phase transmission electron microscopy (LP-TEM). By introducing a novel technique to simulate arbitrary kinetic models for radiochemistry, we provide a holistic understanding of reaction mechanisms in irradiated HAuCl4 solutions, allowing for quantitative prediction and tailoring of redox processes in LP-TEM experiments. It is demonstrated that no experimentally relevant threshold for gold reduction during LP-TEM exists and that radiation-induced metal-ion reduction is relevant even for experiments utilizing X-rays such as X-ray diffraction (XRD). Furthermore, we unveil that oxidative etching of gold nanoparticles depends on both, precursor concentration, and dose rate. This dependency is harnessed to probe the electron beam-induced shift in the Gibbs free energy landscape by analyzing the critical radius of gold nanoparticles. Transmission electron microscopy ; Nanostructure ; Materials science ; Colloidal gold ; Diffraction ; Radiolysis ; Synchrotron ; Chemical physics ; Electron diffraction ; Phase (matter) ; Nanoparticle ; Nanotechnology ; Chemistry ; Aqueous solution ; Physical chemistry ; Optics ; Physics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; nanoparticles nucleation surface interactions
Authors: John K. Marshall | Peter Bowden | Jean Claude Schmit | Fay Betsou
Source:  (preprint, 2022-10-04)
Field: Chemistry — Spectroscopy

Creation of a federated database of blood proteins: a powerful new tool for finding and characterizing biomarkers in serum Protein biomarkers offer major benefits for diagnosis and monitoring of disease processes. Recent advances in protein mass spectrometry make it feasible to use this very sensitive technology to detect and quantify proteins in blood. To explore the potential of blood biomarkers, we conducted a thorough review to evaluate the reliability of data in the literature and to determine the spectrum of proteins reported to exist in blood with a goal of creating a Federated Database of Blood Proteins (FDBP). A unique feature of our approach is the use of a SQL database for all of the peptide data; the power of the SQL database combined with standard informatic algorithms such as BLASTand the statistical analysis system (SAS) allowed the rapid annotation and analysis of the database without the need to create special programs to manage the data. Our mathematical analysis and review shows that in addition to the usual secreted proteins found in blood, there are many reports of intracellular proteins and good agreement on transcription factors, DNA remodelling factors in addition to cellular receptors and their signal transduction enzymes. Overall, we have catalogued about 12,130 proteins identified by at least one unique peptide, and of these 3858 have 3 or more peptide correlations. The FDBP with annotations should facilitate testing blood for specific disease biomarkers. Computer science ; Database ; SQL ; Computational biology ; Proteomics ; Bioinformatics ; Biology ; Gene Advanced Proteomics Techniques and Applications ; Data Mining Algorithms and Applications ; Machine Learning in Bioinformatics
Authors: Ye Yuan | Max Van Belkum | Alana O’Brien | Alain Garcia | Karla Troncoso | Ahmed S. Elshikha | Lei Zhou | Sihong Song
Source: Biomolecules (article, 2022-09-22)
Field: Materials Science — Biomaterials

Human Alpha 1 Antitrypsin Suppresses NF-κB Activity and Extends Lifespan in Adult Drosophila Human alpha 1 antitrypsin (hAAT) is a multifunctional protein that has been shown to have anti-inflammatory and cellular protective properties. While previous studies demonstrated the antiaging potential of hAAT, the mechanism(s) underlying the antiaging effect remain elusive. In this study, we performed a detailed analysis of transcriptomic data that indicated that NF-κB-targeted genes and NF-κB-regulated pathways were selectively inhibited by hAAT treatment. We further showed that the first detectable impact of hAAT treatment was the inhibition of the nuclear activity of NF-κB. Subsequently, hAAT treatment suppressed the mRNA levels of NF-κB-targeted genes, as well as <i>NF-κB</i> itself (<i>P65</i> and <i>P50</i>), in human senescent cells. Using <i>Drosophila</i> models, we further examined the impact of hAAT on locomotor activity and endurance. Finally, using an adult-specific promotor, we demonstrated that overexpression of hAAT in the late stage of life significantly extended the lifespan of transgenic flies. These results extend the current understanding of the anti-inflammatory function of hAAT. Transcriptome ; Transgene ; Alpha (finance) ; Biology ; Gene ; Drosophila melanogaster ; Genetically modified mouse ; Cell biology ; Gene expression ; Genetics ; Medicine Silk-based biomaterials and applications ; Invertebrate Immune Response Mechanisms ; Insect Resistance and Genetics