jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Toyin Omojola | A.C. van Veen
Source: ChemRxiv (preprint, 2021-03-09)
Field: Chemistry — Inorganic Chemistry

Mechanistic Insights into the Conversion of Dimethyl Ether over ZSM-5 Catalysts: A Combined Temperature Programmed Surface Reaction and Microkinetic Modelling Study Rates of adsorption, desorption, and surface reaction of dimethyl ether (DME) to olefins over fresh and working ZSM-5 catalysts of different Si/Al ratios (36 and 135) have been decoupled using a combination of temperature programmed surface reaction experiments and microkinetic modelling. Transient reactor performance was simulated by solving coupled 1D non-linear partial differential equations accounting for elementary steps occurring during the induction period based on the methoxymethyl mechanism on the zeolite catalyst, and axial dispersion and convection in the reactor. Propylene is the major olefin formed and scaling relations between activation energies of DME desorption and barriers of formation of methoxymethyl and methyl propenyl ether are observed. Six ensembles of sites are observed with a maximum of three adsorption/desorption sites and three adsorption/desorption/reaction sites. Barriers are generally higher over working catalysts than fresh catalysts. Activation energies of propylene formation of ca. 200 kJ mol-1 are obtained corroborating direct mechanistic proposals. Dimethyl ether ; Catalysis ; Desorption ; Chemistry ; ZSM-5 ; Thermal desorption spectroscopy ; Adsorption ; Zeolite ; Reaction mechanism ; Dispersion (optics) ; Reaction rate ; Chemical engineering ; Physical chemistry ; Organic chemistry Zeolite Catalysis and Synthesis ; Catalytic Processes in Materials Science ; Catalysis and Hydrodesulfurization Studies
Authors: Anna N. Morozovska | Eugene А. Eliseev | Arpan Biswas | Nicholas V. Morozovsky | Sergei V. Kalinin
Source: Physical Review Applied (preprint, 2021-10-27)
Field: Materials Science — Materials Chemistry

Effect of Surface Ionic Screening on Polarization Reversal and Phase Diagrams in Thin Antiferroelectric Films for Information and Energy Storage Emergent behaviors in antiferroelectric thin films due to a coupling between surface electrochemistry and intrinsic polar instabilities are explored within the framework of the modified 2-4-6 Landau-Ginzburg-Devonshire (LGD) thermodynamic approach. By using phenomenological parameters of the LGD potential for a bulk antiferroelectric and a Stephenson-Highland (SH) approach, we study the role of surface ions with a charge density proportional to the relative partial oxygen pressure on the dipole states and their reversal mechanisms in antiferroelectric thin films. The combined LGDSH approach allows the boundaries of antiferroelectric, ferroelectriclike antiferroionic, and electretlike paraelectric states as a function of temperature, oxygen pressure, surface-ion formation energy and concentration, and film thickness to be delineated. This approach also allows the characterization of the polar and antipolar orderings dependence on the voltage applied to the antiferroelectric film, as well as the analysis of their static and dynamic hysteresis loops. The applications of the antiferroelectric films covered with a surface-ion layer for energy and information storage are explored and discussed. Antiferroelectricity ; Materials science ; Thin film ; Ferroelectricity ; Dipole ; Condensed matter physics ; Ion ; Polarization (electrochemistry) ; Hysteresis ; Dielectric ; Ionic bonding ; Phase (matter) ; Phase diagram ; Surface energy ; Chemical physics ; Nanotechnology ; Chemistry ; Optoelectronics ; Composite material ; Physics ; Physical chemistry Solid-state spectroscopy and crystallography ; Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials
Authors: Tommi Välikangas | Tomi Suomi | Courtney E. Chandler | Alison Scott | Bao Tran | Robert K. Ernst | David R. Goodlett | Laura L. Elo
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-04-19)
Field: Chemistry — Spectroscopy

Enhanced longitudinal differential expression detection in proteomics with robust reproducibility optimization regression Abstract Quantitative proteomics has matured into an established tool and longitudinal proteomic experiments have begun to emerge. However, no effective, simple-to-use differential expression method for longitudinal proteomics data has been released. Typically, such data is noisy, contains missing values, has only few time points and biological replicates. To address this need, we provide a comprehensive evaluation of several existing differential expression methods for high-throughput longitudinal omics data and introduce a new method, Robust longitudinal Differential Expression (RolDE). The methods were evaluated using nearly 2000 semi-simulated spike-in proteomic datasets and a large experimental dataset. The RolDE method performed overall best; it was most tolerant to missing values, displayed good reproducibility and was the top method in ranking the results in a biologically meaningful way. Furthermore, contrary to many approaches, the open source RolDE does not require prior knowledge concerning the types of differences searched, but can easily be applied even by non-experienced users. Ranking (information retrieval) ; Computer science ; Proteomics ; Reproducibility ; Differential (mechanical device) ; Expression (computer science) ; Data mining ; Missing data ; Protein expression ; Regression ; Artificial intelligence ; Machine learning ; Statistics ; Biology ; Mathematics ; Engineering Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Gene expression and cancer classification
Authors: Tanishq Gupta | Mohd Zaki | N. M. Anoop Krishnan | Mausam Mausam
Source: arXiv (Cornell University) (preprint, 2021-09-30)
Field: Materials Science — Materials Chemistry

MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extraction An overwhelmingly large amount of knowledge in the materials domain is generated and stored as text published in peer-reviewed scientific literature. Recent developments in natural language processing, such as bidirectional encoder representations from transformers (BERT) models, provide promising tools to extract information from these texts. However, direct application of these models in the materials domain may yield suboptimal results as the models themselves may not be trained on notations and jargon that are specific to the domain. Here, we present a materials-aware language model, namely, MatSciBERT, which is trained on a large corpus of scientific literature published in the materials domain. We further evaluate the performance of MatSciBERT on three downstream tasks, namely, abstract classification, named entity recognition, and relation extraction, on different materials datasets. We show that MatSciBERT outperforms SciBERT, a language model trained on science corpus, on all the tasks. Further, we discuss some of the applications of MatSciBERT in the materials domain for extracting information, which can, in turn, contribute to materials discovery or optimization. Finally, to make the work accessible to the larger materials community, we make the pretrained and finetuned weights and the models of MatSciBERT freely accessible. Computer science ; Natural language processing ; Domain (mathematical analysis) ; Information extraction ; Relationship extraction ; Jargon ; Language model ; Artificial intelligence ; Transformer ; Natural language ; Named-entity recognition ; Information retrieval ; Task (project management) ; Linguistics Machine Learning in Materials Science ; Corrosion Behavior and Inhibition
Authors: John K. Marshall | Peter Bowden | Jean Claude Schmit | Fay Betsou
Source:  (preprint, 2021-05-24)
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 ; Bioinformatics ; Proteomics ; Biology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Data Mining Algorithms and Applications ; Machine Learning in Bioinformatics
Authors: Yash S. Raval | Anna Samstag | Cedric Taylor | Guohui Huang | O. Thompson Mefford | Tzuen‐Rong Tzeng
Source: Nanomaterials (article, 2021-09-22)
Field: Materials Science — Biomaterials

Assessing the Biocompatibility of Multi-Anchored Glycoconjugate Functionalized Iron Oxide Nanoparticles in a Normal Human Colon Cell Line CCD-18Co We have previously demonstrated that iron oxide nanoparticles with dopamine-anchored heterobifunctional polyethylene oxide (PEO) polymer, namely PEO-IONPs, and bio-functionalized with sialic-acid specific glycoconjugate moiety (Neu5Ac(α2-3)Gal(β1-4)-Glcβ-sp), namely GM3-IONPs, can be effectively used as antibacterial agents against target <i>Escherichia coli</i>. In this study, we evaluated the biocompatibility of PEO-IONPs and GM3-IONPs in a normal human colon cell line CCD-18Co via measuring cell proliferation, membrane integrity, and intracellular adenosine triphosphate (ATP), glutathione GSH, dihydrorhodamine (DHR) 123, and caspase 3/7 levels. PEO-IONPs caused a significant decrease in cell viability at concentrations above 100 μg/mL whereas GM3-IONPs did not cause a significant decrease in cell viability even at the highest dose of 500 μg/mL. The ATP synthase activity of CCD-18Co was significantly diminished in the presence of PEO-IONPs but not GM3-IONPs. PEO-IONPs also compromised the membrane integrity of CCD-18Co. In contrast, cells exposed to GM3-IONPs showed significantly different cell morphology, but with no apparent membrane damage. The interaction of PEO-IONPs or GM3-IONPs with CCD-18Co resulted in a substantial decrease in the intracellular GSH levels in a time- and concentration-dependent manner. Conversely, levels of DHR-123 increased with IONP concentrations. Levels of caspase 3/7 proteins were found to be significantly elevated in cells exposed to PEO-IONPs. Based on the results, we assume GM3-IONPs to be biocompatible with CCD-18Co and could be further evaluated for selective killing of pathogens in vivo. Chemistry ; Biochemistry ; Viability assay ; Intracellular ; Iron oxide nanoparticles ; Biocompatibility ; Glutathione ; Biophysics ; Cell ; Biology Nanoparticle-Based Drug Delivery ; Drug Transport and Resistance Mechanisms ; Antibiotic Resistance in Bacteria
Authors: Afaf Jghamou | Salma Lahbabi | Fouad Riane
Source:  (article, 2021-03-07)
Field: Materials Science — Materials Chemistry

Automated decisional process for material and equipment selection: Application to the selection of material for water pipes In this paper, we are interested in the material selection process as one of the essential steps in the design of products or projects. This task is very complex due to the multitude and heterogeneity of criteria involved and the specificities of each project. The selection process can be very time consuming, especially if it is a repetitive operation. This type of process also requires the use of all the knowledge already available to guarantee the reliability of the decisions. This article proposes a methodology for selecting equipment and material based on an automated model that integrates Multiple-Criteria Decision Analysis (MCDA) methods and knowledge management principles. This model is particularly relevant in situations where the selection process is repetitive but should be reviewed according to the specific conditions of each case. Using this model will allow decision-makers to save time and benefit from the knowledge created during selection processes. A practical application to water pipe material selection is proposed to illustrate practical contribution of the model. It is also applicable to other cases where the selection process is repetitive and depends each time on specific conditions. Selection (genetic algorithm) ; Process (computing) ; Computer science ; Task (project management) ; Material selection ; Multiple-criteria decision analysis ; Reliability (semiconductor) ; Systems engineering ; Risk analysis (engineering) ; Management science ; Machine learning ; Operations research ; Engineering Material Selection and Properties ; Offshore Engineering and Technologies
Authors: M.A. Hadi | Stavros‐Richard G. Christopoulos | A. Chroneos | S. H. Naqib | A.K.M.A. Islam
Source: Research Square (preprint, 2021-09-08)
Field: Materials Science — Materials Chemistry

DFT insights into the electronic structure, mechanical behaviour, lattice dynamics and defect processes in the first Sc-based MAX phase Sc2SnC Abstract The ceramic and metallic properties of the MAX phases make them attractive for numerous technological applications. The very recent experimental synthesis of the first scandium (Sc) based MAX phase Sc 2 SnC is an important addition to the MAX phase family as it further expands the diversity of physical characteristics of this family. Here we employ density functional theory (DFT) calculations to investigate the structural, electronic, mechanical, lattice dynamical properties of Sc 2 SnC including defect processes to compare with those of existing M 2 SnC phases. The calculated structural properties are in good agreement with the experimental values. The new phase Sc 2 SnC is structurally, mechanically and dynamically stable. Sc 2 SnC is metallic with a mixture of covalent and ionic character. The covalency of Sc 2 SnC including M 2 SnC is mostly controlled by the effective valence. Sc 2 SnC in M 2 SnC family ranks second in the scale of deformability, softness and machinability. The elastic anisotropy level in Sc 2 SnC is moderate compared to the other M 2 SnC phases. Like other members of the M 2 SnC family, Sc 2 SnC has the potential to be etched into 2D MXenes and has the potential to be a thermal barrier coating (TBC) material. The hardness and melting point of Sc 2 SnC, including M 2 SnC, follows the trend of bulk modulus. MAX phases ; MXenes ; Chemistry ; Ionic bonding ; Melting point ; Ceramic ; Thermodynamics ; Materials science ; Nanotechnology ; Ion ; Physics MXene and MAX Phase Materials ; Aluminum Alloys Composites Properties ; Advanced ceramic materials synthesis
Authors: P.A. Fuaad | Agne Swerin | Fredrik Lundell | Martti Toivakka
Source: Journal of Coatings Technology and Research (article, 2021-09-10)
Field: Materials Science — Biomaterials

Simulation of slot-coating of nanocellulosic material subject to a wall-stress dependent slip-velocity at die-walls Abstract Bio-based nanocellulosic materials are non-toxic, renewable, exhibit excellent barrier properties, and are suitable candidates for sustainable food packaging applications. Sizing and designing coating parameters for slot-coating process using nanocellulose suspensions is challenging due to complex shear-thinning rheology and the presence of a water-rich boundary layer, effecting significant apparent slip at the wall. Previous studies have shown that the flow inside the coating bead can be complex, with occasional stagnation regions and a rheological model incorporating yield stress which should be considered while analyzing slot coating of nanocellulosic flows. This work extends earlier investigations by including the effects of the particle depleted water-rich boundary layer. The suspension is modeled as a Casson fluid with a shear-thinning viscosity, and the particle depletion at the wall is represented by an infinitely thin layer modeled as a local shear-dependent nonlinear slip law. The resulting two-phase flow equations are solved using a Finite Volume Method (FVM) coupled with the Volume of Fluid (VoF) method for tracking the free surface interface. It is observed that slip alters the flow’s dynamics in the coating bead, and the effect of slip cannot be ignored, especially at high shear rates. For thin films, the presence of slip enhances the flow, leading to more material coated on the substrate. In contrast, for thicker coatings, apparent slip leads to an augmentation in stagnant, non-yielded regions, potentially generating uneven surfaces. Materials science ; Coating ; Composite material ; Shear stress ; Slip (aerodynamics) ; Rheology ; Volume of fluid method ; Boundary layer ; Mechanics ; Flow (mathematics) ; Thermodynamics Advanced Cellulose Research Studies ; Rheology and Fluid Dynamics Studies ; Material Properties and Processing
Authors: Theresa Hwang | Robert A. Grant | Meucci W Ilunga | Venkatesh Sivaraman | Amy E. Keating
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-03-22)
Field: Chemistry — Spectroscopy

Native proline-rich motifs exploit sequence context to target actin-remodeling Ena/VASP proteins Abstract The human proteome is replete with short linear motifs (SLiMs) of 4-6 residues that are critical for protein-protein interactions, yet the importance of the sequence surrounding such motifs is underexplored. We devised a proteomic screen to systematically examine the influence of SLiM sequence context on protein-protein interactions. Focusing on the EVH1 domain of ENAH, an actin regulator that is upregulated in invasive cancers, we screened 36-residue proteome-derived peptides for binding. We discovered a pocket on the ENAH EVH1 domain that diverged from its orthologs to recognize extended SLiMs, and we found that proteins with two EVH1-binding SLiMs can wrap around a single domain. We also found that the ciliary protein PCARE uses an extended 23-residue region to obtain higher affinity than any known ENAH EVH1-binding motif. Our screen provides a way to uncover the effects of broader proteomic context on motif-mediated interactions, revealing diverse mechanisms of contextual control over EVH1 interactions and establishing that SLiMs can’t be fully understood outside of their native context. Proteome ; Sequence motif ; Biology ; Computational biology ; Human proteome project ; Context (archaeology) ; Actin ; Consensus sequence ; Cell biology ; Peptide sequence ; Bioinformatics ; Proteomics ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Cellular transport and secretion ; Ubiquitin and proteasome pathways
Authors: Lorenza Suber | L. Pilloni | Kshitij Khanna | Giuliana Righi | Ludovica Primitivo | Martina De Angelis | Daniela Caschera
Source: Journal of Nanoscience and Nanotechnology (article, 2021-03-03)
Field: Materials Science — Materials Chemistry

Fine-Tuning Synthesis of Fluorescent Silver Thiolate Nanoclusters Noble metal thiolate nanoclusters are a new class of nanomaterials with molecular-like properties such as high dispersibility and fluorescence in the visible and infrared spectral region, properties highly requested in biomedicine for imaging, sensing and drug delivery applications. We report on three new silver phenylethane thiolate nanoclusters, differing for slight modifications of the preparation, i.e., the reaction solvent and the thiolate quantity, producing changes in the nanocluster composition as well as in the fluorescence behavior. All samples, excited in the range 250–500 nm, emit around 400 and 700 nm differing in the emission maxima and behavior. The silver thiolate nanoclusters have been characterized by way of C, H, S elemental analyses and Thermal Gravimetric Analysis (TGA) to determine the nanocluster composition, Scanning Transmission Electron Microscopy (STEM) to investigate the nanocluster morphology and UV-Vis and fluorescence spectroscopy to study their optical properties. Nanoclusters ; Materials science ; Fluorescence ; Nanotechnology ; Photochemistry ; Chemical engineering ; Optoelectronics ; Optics Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Rajul Ranjan Choudhury | R. Chitra | Swayam Kesari | Rekha Rao | Е. В. Селезнева | А. П. Дудка | И. П. Макарова
Source: Molecular Physics (article, 2021-11-15)
Field: Chemistry — Physical and Theoretical Chemistry

Fine tuning of hydrogen bond strength in crystals: a case study of O–H–O hydrogen bond in ammonium substituted potassium dihydrogen phosphate Hydrogen bonds are one of the most enigmatic intermolecular interactions where the strength of interaction depends very intimately on the local environment of the bonded atoms. One can change the entire nature of the interactions by changing its local environment. Many of the enzymatic reactions work by this above-mentioned mechanism. Hence, it is important to understand how changes in the local environment can modify hydrogen bonds. In line with this, complete structural and vibrational investigations on ammonium ion substituted potassium dihydrogen phosphate mixed crystals K0.988(NH4)0.012H2PO4 and (K0.956(NH4)0.044H2PO4) are performed. The behaviour of O–H–O hydrogen bond in these crystals is very sensitive to changes in the local environment. A small change in the concentration of K+ ion has an observable effect on hydrogen bond geometry and hence on the double-well potential energy contour for these bonds. The dynamics of H atom depends on the potential barrier height. It changes gradually with decreasing temperature from predominantly inter-well to completely intra-well dynamics with an intermediate precursor region, where inter-well and intra-well dynamics are important. Hydrogen bond ; Ammonium dihydrogen phosphate ; Chemistry ; Ion ; Hydrogen ; Ammonium ; Potassium ; Crystallography ; Intermolecular force ; Phosphate ; Bond strength ; Chemical physics ; Molecule ; Inorganic chemistry ; Organic chemistry ; Adhesive Crystallography and molecular interactions ; Enzyme Structure and Function ; Crystallization and Solubility Studies
Authors: Chao Dong | Daosheng Liu | Lei Zhang | Xiang‐Ping Hu
Source: Tetrahedron Letters (article, 2021-01-07)
Field: Chemistry — Inorganic Chemistry

Rh-catalyzed asymmetric hydrogenation of α-aryl-β-alkylvinyl esters with chiral ferrocenylphosphine-phosphoramidite ligand Phosphoramidite ; Chemistry ; Catalysis ; Ligand (biochemistry) ; Enantioselective synthesis ; Aryl ; Asymmetric hydrogenation ; Organic chemistry ; Chiral ligand ; Combinatorial chemistry ; Medicinal chemistry ; Receptor ; Oligonucleotide Asymmetric Hydrogenation and Catalysis ; Surface Chemistry and Catalysis ; Catalytic C–H Functionalization Methods
Authors: Catherine A. Kelly | Mike Jenkins | Shona Marsh
Source: Materials Today Communications (article, 2021-09-14)
Field: Materials Science — Biomaterials

Rheological analysis of heat labile poly(3-hydroxybutyrate-co-3-hydroxyvalerate):poly(ethylene glycol) blends Materials science ; Miscibility ; Ethylene glycol ; PEG ratio ; Chemical engineering ; Embrittlement ; Polymer ; Rheology ; Degradation (telecommunications) ; Thermal stability ; Crystallization ; Polymer blend ; Copolymer ; Polymer chemistry ; Composite material biodegradable polymer synthesis and properties ; Polymer crystallization and properties ; Natural Fiber Reinforced Composites