jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Martin Amezcua | Léa El Khoury | David L. Mobley
Source: ChemRxiv (preprint, 2020-11-16)
Field: Materials Science — Materials Chemistry

SAMPL7 Host-Guest Challenge Overview: Assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges have thus frequently included a component focusing on host-guest binding, which removes some of these challenges while still focusing on molecular recognition. Here, we report on the results of the SAMPL7 blind prediction challenge for host-guest affinity prediction. In this study, we focused on three different host-guest categories -- a familiar deep cavity cavitand series which has been featured in several prior challenges (where we examine binding of a series of guests to two hosts), a new series of cyclodextrin derivatives which are monofunctionalized around the rim to add amino acid-like functionality (where we examine binding of two guests to a series of hosts), and binding of a series of guests to a new acyclic TrimerTrip host which is related to previous cucurbituril hosts. Many predictions used methods based on molecular simulations, and overall success was mixed, though several methods stood out. As in SAMPL6, we find that one strategy for achieving reasonable accuracy here was to make empirical corrections to binding predictions based on previous data for host categories which have been studied well before, though this can be of limited value when new systems are included. Additionally, we found that alchemical free energy methods using the AMOEBA polarizable force field had considerable success for the two host categories in which they participated. The new TrimerTrip system was also found to introduce some sampling problems, because multiple conformations may be relevant to binding and interconvert only slowly. Overall, results in this challenge tentatively suggest that further investigation of polarizable force fields for these challenges may be warranted. Computer science ; Host (biology) ; Protonation ; Binding affinities ; Binding energy ; Cavitand ; Computational chemistry ; Series (stratigraphy) ; Machine learning ; Artificial intelligence ; Chemistry ; Molecule ; Physics ; Biology ; Supramolecular chemistry Machine Learning in Materials Science ; Chemical Synthesis and Analysis ; Protein Structure and Dynamics
Authors: Camila B. Paz | Rinaldo dos Santos Araújo | Lais F. Oton | Alcinéia C. Oliveira | J.M. Soares | Susana N. Medeiros | Enrique Rodrı́guez-Castellón | Elena Rodríguez‐Aguado
Source: Materials (article, 2020-03-02)
Field: Chemistry — Organic Chemistry

Acid Red 66 Dye Removal from Aqueous Solution by Fe/C-based Composites: Adsorption, Kinetics and Thermodynamic Studies The presence of synthetic dyes in water causes serious environmental issues owing to the low water quality, toxicity to environment and human carcinogenic effects. Adsorption has emerged as simple and environmental benign processes for wastewater treatment. This work reports the use of porous Fe-based composites as adsorbents for Acid Red 66 dye removal in an aqueous solution. The porous FeC and Fe/FeC solids were prepared by hydrothermal methods using iron sulfates and sucrose as precursors. The physicochemical properties of the solids were evaluated through X-ray diffraction (XRD), Scanning electron microscopy coupled with Energy dispersive spectroscopy (SEM-EDS), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared s (FTIR), Raman and Mössbauer spectroscopies, nitrogen adsorption-desorption isotherms, Electron Paramagnetic Resonance (EPR) and magnetic saturation techniques. Results indicated that the Fe species holds magnetic properties and formed well dispersed Fe<sub>3</sub>O<sub>4</sub> nanoparticles on a carbon layer in FeC nanocomposite. Adding iron to the previous solid resulted in the formation of γ-Fe<sub>2</sub>O<sub>3</sub> coating on the FeC type structure as in Fe/FeC composite. The highest dye adsorption capacity was 15.5 mg·g<sup>-1</sup> for FeC nanocomposite at 25 °C with the isotherms fitting well with the Langmuir model. The removal efficiency of 98.4% was obtained with a pristine Fe sample under similar experimental conditions. Aqueous solution ; Adsorption ; Kinetics ; Chemistry ; Materials science ; Composite material ; Nuclear chemistry ; Chemical engineering ; Organic chemistry Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Environmental remediation with nanomaterials
Authors: Anh D. Phan | Katsunori Wakabayashi
Source: Pharmaceutics (article, 2020-02-19)
Field: Materials Science — Materials Chemistry

Theory of Structural and Secondary Relaxation in Amorphous Drugs under Compression Compression effects on alpha and beta relaxation process of amorphous drugs are theoretically investigated by developing the elastically collective nonlinear Langevin equation theory. We describe the structural relaxation as a coupling between local and nonlocal activated process. Meanwhile, the secondary beta process is mainly governed by the nearest-neighbor interactions of a molecule. This assumption implies the beta relaxation acts as a precursor of the alpha relaxation. When external pressure is applied, a small displacement of a molecule is additionally exerted by a pressure-induced mechanical work in the dynamic free energy, which quantifies interactions between a molecule with its nearest neighbors. The local dynamics has more restriction and it induces stronger effects of collective motions on single-molecule dynamics. Thus, the alpha and beta relaxation times are significantly slowed down with increasing compression. We apply this approach to determine the temperature and pressure dependence of the alpha and beta relaxation time for curcumin, glibenclamide, and indomethacin, and compare numerical results with prior experimental studies. Both qualitative and quantitative agreement between theoretical calculations and experiments validate our assumptions and reveal their limitations. Our approach would pave the way for the development of the drug formulation process. Relaxation (psychology) ; Amorphous solid ; BETA (programming language) ; Statistical physics ; Langevin equation ; Chemistry ; Molecule ; Compression (physics) ; Molecular dynamics ; Nonlinear system ; Computational chemistry ; Materials science ; Chemical physics ; Physics ; Thermodynamics ; Crystallography ; Computer science ; Quantum mechanics Material Dynamics and Properties ; Rheology and Fluid Dynamics Studies ; Polymer crystallization and properties
Authors: Ryo Murakami | Hiromi Tanaka | Hiroshi Shinotsuka | Kenji Nagata | Hayaru Shouno | Hideki Yoshikawa
Source: Journal of Electron Spectroscopy and Related Phenomena (article, 2020-10-03)
Field: Materials Science — Surfaces, Coatings and Films

Development of multiple core-level XPS spectra decomposition method based on the Bayesian information criterion Spectral line ; X-ray photoelectron spectroscopy ; Computer science ; Reference data ; Core (optical fiber) ; Bayesian information criterion ; Bayesian probability ; Computational physics ; Algorithm ; Biological system ; Analytical Chemistry (journal) ; Mathematics ; Data mining ; Chemistry ; Artificial intelligence ; Physics ; Nuclear magnetic resonance ; Telecommunications Electron and X-Ray Spectroscopy Techniques ; Nuclear Physics and Applications ; Machine Learning in Materials Science
Authors: Luna Shrestha | Boris Kulig | Roberto Moscetti | Riccardo Massantini | Elke Pawelzik | Oliver Hensel | Barbara Sturm
Source: Journal of Spectroscopy (article, 2020-06-29)
Field: Chemistry — Analytical Chemistry

Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices The assessment of the quality of fresh-cut apple slices is important for processing, storage, market value, and consumption. Determination of polyphenol oxidase activity (PPO) in apples is critical for controlling the quality of the final product (i.e., dried apples and juices). Hyperspectral imaging (HSI) is a nondestructive, noncontact, and rapid food quality assessment technique. It has the potential to detect physical and chemical quality attributes of foods such as PPO of apple. The aim of this study was to investigate the suitability of HSI in the visible and near-infrared (VIS-NIR) range for indirect assessment of PPO activity of fresh-cut apple slices. Apple slices of two cultivars (cv. Golden Delicious and Elstar) were used to build a robust detection algorithm, which is independent of cultivars and applied treatments. Partial least squares (PLS) regression using the 7-fold cross-validation method and method comparison analysis (Bland–Altman plot, Passing–Bablok regression, and Deming regression) were performed. The 95% confidence interval (CI) bands for the Bland–Altman analysis between the methods were −4.19 and 13.11, and the mean difference was 3.7 e −12 . The Passing–Bablok regression had a slope of 0.8 and an intercept of 7.6. The slope of the Deming regression was 0.8 within the CI bands of 0.56 and 1.10. These results show acceptable performance and no significant deviation from linearity. Hence, the results demonstrated the feasibility of HSI as an indirect alternative to the standard chemical analysis of PPO enzyme activity. Partial least squares regression ; Hyperspectral imaging ; Polyphenol oxidase ; Linear regression ; Mathematics ; Coefficient of determination ; Food science ; Cultivar ; Chemistry ; Horticulture ; Statistics ; Artificial intelligence ; Computer science ; Biology Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Meat and Animal Product Quality
Authors: Wei Ju | Changhua Lu | Chun Liu | Weiwei Jiang | Yujun Zhang | Feng Hong
Source: Journal of Spectroscopy (article, 2020-01-22)
Field: Chemistry — Analytical Chemistry

Rapid Identification of Atmospheric Gaseous Pollutants Using Fourier-Transform Infrared Spectroscopy Combined with Independent Component Analysis Fourier-transform infrared (FTIR) spectroscopy is a rapid and nondestructive technology for monitoring atmospheric quality. The identification of each component from the FTIR spectra is a prerequisite for the accurate quantitative analysis of gaseous pollutants. Due to the overlap of different gas absorption peaks and the interference of water vapor in the actual measurement, the existing identification methods of gas spectra have drawbacks of low identification rate and the inability to carry out real-time online analysis in atmospheric quality monitoring. In this work, independent component analysis (ICA) is applied to the spectral separation of heavily overlapped spectra of gaseous pollutants. The proposed method is validated by the analysis of mixture spectra obtained in laboratory and actual atmospheric spectra collected from stationary source. The average time consumption of separation process is less than 0.2 seconds, and the identification rate of experimental gases is up to 100%, as shown by the results of peak searching and the analysis of the correction coefficient between the separated spectra and the standard spectra database. The identification results of actual atmospheric spectra demonstrated that the proposed method can effectively identify the gaseous pollutants whose concentration changes in the measured spectra, and it is a promising qualitative spectral analysis tool that can shorten the identification time, as well as increase the identification rate. Therefore, this method can be a useful alternative to traditional qualitative identification methods for real-time online atmospheric pollutant detection. Spectral line ; Fourier transform infrared spectroscopy ; Interference (communication) ; Infrared spectroscopy ; Analytical Chemistry (journal) ; Spectroscopy ; Infrared ; Fourier transform ; Pollutant ; Chemistry ; Environmental chemistry ; Optics ; Computer science ; Mathematics ; Physics ; Telecommunications Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Hongxiang Zong | Heather Wiebe | Graeme J. Ackland
Source: Nature Communications (article, 2020-10-06)
Field: Chemistry — Physical and Theoretical Chemistry

Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential The hydrogen phase diagram has several unusual features which are well reproduced by density functional calculations. Unfortunately, these calculations do not provide good physical insights into why those features occur. Here, we present a fast interatomic potential, which reproduces the molecular hydrogen phases: orientationally disordered Phase I; broken-symmetry Phase II and reentrant melt curve. The H<sub>2</sub> vibrational frequency drops at high pressure because of increased coupling between neighbouring molecules, not bond weakening. Liquid H<sub>2</sub> is denser than coexisting close-packed solid at high pressure because the favored molecular orientation switches from quadrupole-energy-minimizing to steric-repulsion-minimizing. The latter allows molecules to get closer together, without the atoms getting closer, but cannot be achieved within in a close-packed layer due to frustration. A similar effect causes negative thermal expansion. At high pressure, rotation is hindered in Phase I, such that it cannot be regarded as a molecular rotor phase. Phase diagram ; Molecular dynamics ; Phase (matter) ; Molecule ; High pressure ; Solid hydrogen ; Coupling (piping) ; Hydrogen ; Hydrogen bond Crystallography and molecular interactions ; High-pressure geophysics and materials ; Thermal Expansion and Ionic Conductivity
Authors: Taekyung Lee
Source: Applied Sciences (article, 2020-11-07)
Field: Materials Science — Materials Chemistry

Variation in Mechanical Properties of Ti-13Nb-13Zr Depending on Annealing Temperature Ti-13Nb-13Zr alloy is an orthopedic implant material possessing good mechanical properties, corrosion resistance, and biocompatibility. An international standard suggests a heat treatment known as “capability aging” for this alloy. This study provides extensive data of mechanical properties under a wide temperature condition built around the capability-aging process. Specifically, it investigates the effect of annealing temperature (573–973 K) on mechanical properties (i.e., yield strength, tensile strength, hardness, Young’s modulus, and mechanical compatibility) of Ti-13Nb-13Zr alloys. Although these mechanical properties showed similar trends with respect to the annealing temperature, Young’s modulus exhibited the highest value at 873 K in contrast to those of the other properties shown at 773 K. Such a disparity was discussed in light of static spheroidization and phase decomposition based on microstructural characteristics of the annealed Ti-13Nb-13Zr alloys. Materials science ; Annealing (glass) ; Ultimate tensile strength ; Alloy ; Modulus ; Composite material ; Biocompatibility ; Microstructure ; Metallurgy Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Nuclear Materials and Properties
Authors: Suganya Govindarajan | Jorge Alfredo Ardila‐Rey | Kannan Krithivasan | S. Jayalalitha | Nikhith Sannidhi | M. Balasubramanian
Source: IEEE Access (article, 2020-12-24)
Field: Materials Science — Materials Chemistry

Development of Hypergraph Based Improved Random Forest Algorithm for Partial Discharge Pattern Classification Precise partial discharge (PD) detection is a key factor in anticipating insulation failures. The continuous efforts of researchers have led to the design of a variety of algorithms focusing on PD pattern classification. However, the trade-off between features taken up for classification and the detection rate continues to pose considerable challenges in terms of feature selection from acquired data, increased computing time, and so on. In this article, a Hypergraph (HG) based improved Random Forest (RF) algorithm by employing the Recursive Feature Elimination (RFE) algorithm (HG-RF-RFE), has been developed for PD source classification. HG representation of data is considered for obtaining statistical features, which turn out to be a subset of a set of all hyper edges called Hyper statistical features (Helly, Non-Helly, and Isolated hyper edges). HG-RF-RFE takes hyper statistical features and hyper edges as features for classification. The algorithm’s efficiency is tested against noise-free PD data obtained from SASTRA High Voltage Laboratory, and large-sized noisy PD data obtained from High-Voltage Research and Test Laboratory at Universidad Técnica Federico Santa Maria (LIDAT). The robustness of the proposed algorithm is tested with both time and phase domain PD features using the Mathews Correlation Coefficient (MCC), harmonic mean-based feature Score (F1 Score) as evaluation metrics, and by k-fold validation technique. The proposed HG-RF-RFE achieved 98.8% accuracy with minimal features and significantly reduces computation time without compromising accuracy. It is worth mentioning that the HG-RF-RFE technique is superior to many state of the art algorithms in terms of feature elimination and classification accuracy. Hypergraph ; Random forest ; Computer science ; Algorithm ; Pattern recognition (psychology) ; Artificial intelligence ; Mathematics ; Combinatorics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Geophysical Methods and Applications
Authors: Najmeh Ketabchi | Rassoul Dinarvand | Mahdi Adabi | Mahdi Gholami | Saman Firoozi | Bentolhoda Amanzadi | Reza Faridi‐Majidi | J Boateng | K Matthews | H Stevens | G Eccleston | K Nuutila | J Grolman | L Yang | M Broomhead | S Lipsitz | A Onderdonk | D Mooney | E Eriksson | W Jung | H Winter | H Soroff | D Sasvary | M Dadras | J Wagner | C Wallner | A Sogorski | M Sacher | K Harati | M Lehnhardt | B Behr | E Salmern-Gonzlez | E Garca-Vilario | M Prez-Del-Caz | A Snchez-Garca | A Valverde-Navarro | O Cope | J Langohr | F Moore | R Webster | Z Janekovic | P Ranjbarvan | M Soleimani | A Samadi Kuchaksaraei | J Ai | R Faridi Majidi | J Verdi | J Plichta | C Holmes | R Gamelli | K Radek | Q Husain | C zcan | O Ergn | A elik | N rdk | G zok | Hoa Bach | T Pham | T Dinh | T Takagi | H | D Lewis | B Luh | R Kazem | A Habeeb | M Boland | M Hardman | A Mostafaie | A Bidmeshkipour | Z Shirvani | K Mansouri | M Chalabi | R Yarani | H Mohammadi-Motlagh | M Bakhtiari | F Shirvani | A Mostafaei | Z Shirvani Farsani | S Sugiyama | K Ohtsuki | K Sato | M Kawabata | K Morimoto | S Kunii | K Hamano | B Tonomura | T Sill | H Von Recum | L Mehraz | M Nouri | H Namazi | Y Singh
Source: Biointerface Research in Applied Chemistry (article, 2020-10-25)
Field: Materials Science — Biomaterials

Study of Third-Degree Burn Wounds Debridement and Treatment by Actinidin Enzyme Immobilized on Electrospun Chitosan/PEO Nanofibers in Rats In this study, the actinidin enzyme that was extracted from kiwi fruit was immobilized on a scaffold based on electrospun chitosan nanofibers, and its ability to treat burn wounds was investigated. Afterward, cytotoxicity of the nanofibrous patch and nanofibers with actinidin enzyme was evaluated by MTT test separately on skin fibroblast cells (AGO1522), and their efficacy was investigated on rat model’s full-thickness burn wounds. As a result, SEM showed the diameters of the fibers that were in a range of 100-200 nm depending on the electrospinning condition. MTT results confirmed the cell viability is exposing the enzyme and nanofibers. Then evaluating wound closure percentage in animal samples was analyzed by statistical tests. Considering P&lt;0/05, a significant difference in the rate of wound closure between the groups was observed. Histopathological assays also showed the accelerating effect of the nanofibrous patch with an enzyme in epithelisation, angiogenesis, collagen deposition, and its effective role in scar formation prevention. In this study, actinidin also showed perfect compatibility with cells, and chitosan could prevent wounds infection. So using this bandage could eliminate the scars and reduce the treatment time. Nanofiber ; Chitosan ; Chemistry ; Electrospinning ; MTT assay ; Wound healing ; Sponge ; Biomedical engineering ; Surgery ; Materials science ; Cell ; Biochemistry ; Medicine ; Nanotechnology ; Organic chemistry Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments
Authors: Saman Moniri | Hrishikesh Bale | Tobias Volkenandt | Yeqing Wang | Jianrong Gao | Tianxiang Lu | Kai Sun | Robert O. Ritchie | Ashwin J. Shahani
Source: Small (article, 2020-01-23)
Field: Materials Science — Materials Chemistry

Multi‐Step Crystallization of Self‐Organized Spiral Eutectics A method for the solidification of metallic alloys involving spiral self-organization is presented as a new strategy for producing large-area chiral patterns with emergent structural and optical properties, with attention to the underlying mechanism and dynamics. This study reports the discovery of a new growth mode for metastable, two-phase spiral patterns from a liquid metal. Crystallization proceeds via a non-classical, two-step pathway consisting of the initial formation of a polytetrahedral seed crystal, followed by ordering of two solid phases that nucleate heterogeneously on the seed and grow in a strongly coupled fashion. Crystallographic defects within the seed provide a template for spiral self-organization. These observations demonstrate the ubiquity of defect-mediated growth in multi-phase materials and establish a pathway toward bottom-up synthesis of chiral materials with an inter-phase spacing comparable to the wavelength of infrared light. Given that liquids often possess polytetrahedral short-range order, our results are applicable to many systems undergoing multi-step crystallization. Crystallization ; Materials science ; Eutectic system ; Spiral (railway) ; Nanotechnology ; Self-assembly ; Crystallography ; Chemical engineering ; Composite material ; Chemistry ; Engineering ; Microstructure ; Mechanical engineering Crystallization and Solubility Studies ; Calcium Carbonate Crystallization and Inhibition ; Machine Learning in Materials Science