jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Vignesh Rajamanickam | Christoph Herwig | Oliver Spadiut
Source:  (article, 2019-01-01)
Field: Chemistry — Spectroscopy

A Generic Workflow for Bioprocess Analytical Data: Screening Alignment Techniques and Analyzing their Effects on Multivariate Modeling UV chromatographic data in combination with multivariate data analysis (MVDA) has been extensively used for bioprocess monitoring. However, they are usually attributed to shifts along the retention time and require preprocessing. Misaligned UV chromatographic data result in inconsistent MVDA models. Numerous preprocessing techniques are available, each varying in the number of meta-parameters to optimize, complexity and computational time. Therefore, we aimed at developing a generic workflow to screen for preprocessing techniques. We chose four datasets with increasing complexity containing UV chromatographic data from reverse-phase and size exclusion chromatography HPLC. We aligned all four datasets using three preprocessing techniques, namely icoshift, PAFFT and RAFFT algorithms. We chose several statistical tools to validate the performance of the preprocessing techniques and to screen for meta-parameters. We validated the performance of the preprocessing techniques in terms of data preservation, complexity and computational time, and identified the optimal ranges of meta-parameters for each dataset. Finally, we established principal component analysis (PCA) models to evaluate the chosen alignment technique. Summarizing, in this study a generic workflow has been developed to validate alignment of chromatographic data using statistical tools. Preprocessor ; Workflow ; Computer science ; Multivariate statistics ; Data pre-processing ; Principal component analysis ; Bioprocess ; Data mining ; Machine learning ; Artificial intelligence ; Engineering ; Database Analytical Chemistry and Chromatography ; Spectroscopy and Chemometric Analyses ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Zhiyong Luo | Chujian Liao | Chuanbing Cai | Zhi-Yong LIU | Minjuan Li | Yu-Ming LU
Source: Journal of Inorganic Materials (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Argon Ion Etching on Property of YBa2Cu3O7-x Thin Films Prepared by TFA-MOD Process TFA Materials science ; Mod ; Argon ; Etching (microfabrication) ; Process (computing) ; Ion ; Thin film ; Chemical engineering ; Composite material ; Nanotechnology ; Organic chemistry ; Layer (electronics) ; Chemistry ; Computer science ZnO doping and properties ; Advanced ceramic materials synthesis ; Copper Interconnects and Reliability
Authors: Mogomotsi J. Molefe | Isaac N. Simate
Source: Energy and Environment Research (article, 2019-05-30)
Field: Materials Science — Materials Chemistry

Potential of Combustion of Poultry Litter for Space Heating in Poultry Production Confined poultry production, which is expected to double by 2050, produces a lot of litter. For successful and sustainable poultry production, litter management is prompted and should be prioritized. Poultry litter can serve as an energy feedstock for space heating and electricity generation. Currently, heating systems in use depend on electricity, charcoal or diesel which are very expensive leading to high energy costs in poultry production. The purpose of this study was therefore to investigate the potential of combustion of poultry litter for space heating in poultry production. A brazier with 32 holes, of a diameter of 1cm, on its sides comprising of dimensions; Diameter=8 cm and Height=65 cm was used to burn 1kg of Poultry Litter Briquettes. The briquettes were made with a mincer which had a nozzle of dimensions, Length=11 cm and Diameter= 25 mm producing briquettes of a diameter of 25 mm and a length of 10 cm. The briquettes were made from poultry litter of chickens at the ages of 4, 5 and 6 weeks, and were either sun or solar dried. They were then directly combusted in the brazier and heat distribution was measured at distances of 30 cm, 60 cm and 90 cm from the brazier. Charcoal was used as a control. The maximum average temperatures recorded on the surface of the brazier for week 4, 5, 6 were 471oC, 491oC, 493oC respectively; whereas for charcoal was 555oC. However, the poultry litter briquettes were not able to sustain high temperatures for long compared to charcoal. Complete combustion took an average of 120 minutes while charcoal took an average of 180 minutes. Poultry litter ; Briquette ; Litter ; Charcoal ; Poultry farming ; Environmental science ; Combustion ; Raw material ; Broiler ; Electricity ; Pulp and paper industry ; Animal science ; Waste management ; Materials science ; Nutrient ; Biology ; Chemistry ; Agronomy ; Ecology ; Coal ; Metallurgy Advanced Thermoelectric Materials and Devices ; Agriculture Sustainability and Environmental Impact
Authors: Halil İbrahim Çelık | Elif GÜLTEKİN | Aydın Başkar | Büşra Öztürk | Halil İbrahim Demirel
Source: Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi (article, 2019-11-29)
Field: Materials Science — Polymers and Plastics

DESIGN OF AN IMAGE PROCESSING SYSTEM FOR FABRIC DRAPE MEASUREMENT Fabric drapeability is an important parameter that affects the apparelcomfort and appearance of the fabric. Fabric drape measurement is based oncalculating the shadow area of the hanged fabric created due to its weight.This measurement is performed manually and therefore a subjective assessment ismade. Today, with the developments in image acquisition technology and imageprocessing methods, many measurements and evaluations can be made objectivelyand accurately by adapting vision systems. In this study, an example prototypesystem with which fabric drape can be measured by image processing techniquesis presented. The designed system consists of machine vision hardware, equipmentand image processing software. The system was tested on 12 different types ofwoven and knitted fabrics. The fabric samples were selected randomly. Drapemeasurements were performed with developed image processing software. The samesamples were also applied bending length and Cusick drapeability tests to confirmthe results obtained by image processing (IP) method and the relationshipbetween the three measurements was determined by regression analysis. As aresult, 0.92 and 0.84 R2 values were obtained between IP method andbending length and Cusick drapeablility results respectively. Art ; Mathematics ; Humanities Textile materials and evaluations
Authors: Yu‐Sheng Kuo
Source: eScholarship (California Digital Library) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Lattice dynamics of substitutional alloys through a combined vibrational and compositional expansion A general method incorporating both vibrational and configurational degrees of freedom is proposed by expanding energy into vibrational clusters. Our approach captures vibrational properties in substitutional alloys with arbitrary atomic configurations which can serve as an accurate surrogate model for first-principles calculations. Compressive sensing is applied to robustly and accurately select the important configuration dependent force constants and determine their value by learning from first principles calculations in one shot. Unlike virtual crystal approximation which tends to overestimate lattice thermal conductivity at high concentration range. Great agreements with experimental results across all composition for PbTe-Se demonstrates our VCE method is an accurate approach to generate high fidelity potential energy surface across a wide range of alloy materials. Lattice (music) ; Statistical physics ; Materials science ; Physics ; Condensed matter physics Machine Learning in Materials Science ; Advanced Thermoelectric Materials and Devices ; Advanced Semiconductor Detectors and Materials
Authors: Megha Satyanarayana
Source: C&EN Global Enterprise (article, 2019-01-28)
Field: Chemistry — Physical and Theoretical Chemistry

Rebuilding undergrad chemistry by making it more like high school Ask Nicholas Heelan about his first pass at intro-level college chemistry or about his professor, and he’ll tell you, “It was really bad. He would just talk and talk, and there wasn’t much interaction.” Fast-forward one year, after giving Michigan State University’s version of the class a try, and he’s emphatic: it was so. much. better. “It was interactive. We could talk to the people sitting next to us. It’s not like learning facts. It’s more like common sense, or reasoning,” the 20-year-old says, knee-deep in his second semester of general chemistry and thinking he’ll major in biochemistry. This is music to Melanie Cooper’s ears. Her chemistry education program at MSU is one of many that subscribe to active learning, a mode of teaching that emphasizes student participation over lecture alone. But Cooper, a chemist herself, and her team wanted to go deeper. Active learning, she says, focuses too much Chemistry ; Mathematics education ; Nanotechnology ; Engineering physics ; Psychology ; Materials science ; Engineering Various Chemistry Research Topics
Authors: Olli-Pekka Koistinen | Vilhjálmur Ásgeirsson | Aki Vehtari | Hannes Jónsson
Source: ChemRxiv (preprint, 2019-10-21)
Field: Materials Science — Materials Chemistry

Minimum Mode Saddle Point Searches Using Gaussian Process Regression with Inverse-Distance Covariance Function The minimum mode following method can be used to find saddle points on an energy surface by following a direction guided by the lowest curvature mode. Such calculations are often started close to a minimum on the energy surface to find out which transitions can occur from an initial state of the system, but it is also common to start from the vicinity of a first order saddle point making use of an initial guess based on intuition or more approximate calculations. In systems where accurate evaluations of the energy and its gradient are computationally intensive, it is important to exploit the information of the previous evaluations to enhance the performance. Here, we show that the number of evaluations required for convergence to the saddle point can be significantly reduced by making use of an approximate energy surface obtained by a Gaussian process model based on inverse inter-atomic distances, evaluating accurate energy and gradient at the saddle point of the approximate surface and then correcting the model based on the new information. The performance of the method is tested with start points chosen randomly in the vicinity of saddle points for dissociative adsorption of an H2 molecule on the Cu(110) Surface and three gas phase chemical reactions.&lt;br&gt; Saddle point ; Inverse ; Covariance ; Saddle ; Gaussian curvature ; Curvature ; Mathematics ; Physics ; Mathematical analysis ; Mathematical optimization ; Geometry ; Statistics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Gaussian Processes and Bayesian Inference
Authors: Robert Bücker | Pascal Hogan-Lamarre | P. Mehrabi | Eike C. Schulz | Lindsey A. Bultema | Y. Gevorkov | W. Brehm | Oleksandr Yefanov | Dominik Oberthür | Günther Kassier | R. J. Dwayne Miller
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-06-26)
Field: Materials Science — Materials Chemistry

Serial protein crystallography in an electron microscope Abstract Serial X-ray crystallography at free-electron lasers allows to solve biomolecular structures from sub-micron-sized crystals. However, beam time at these facilities is scarce, and involved sample delivery techniques are required. On the other hand, rotation electron diffraction (MicroED) has shown great potential as an alternative means for protein nano-crystallography. Here, we present a method for serial electron diffraction of protein nanocrystals combining the benefits of both approaches. In a scanning transmission electron microscope, crystals randomly dispersed on a sample grid are automatically mapped, and a diffraction pattern at fixed orientation is recorded from each at a high acquisition rate. Dose fractionation ensures minimal radiation damage effects. We demonstrate the method by solving the structure of granulovirus occlusion bodies and lysozyme to resolutions of 1.55 Å and 1.80 Å, respectively. Our method promises to provide rapid structure determination for many classes of materials with minimal sample consumption, using readily available instrumentation. Diffraction ; Transmission electron microscopy ; Electron diffraction ; Electron microscope ; Protein crystallization ; Electron backscatter diffraction ; Materials science ; Sample (material) ; Scanning electron microscope ; Crystallography ; Sample preparation ; Electron crystallography ; Optics ; Nanotechnology ; Chemistry ; Physics ; Chromatography ; Crystallization Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Advanced X-ray Imaging Techniques
Authors: R. Preuss | R. Arredondo | U. von Toussaint
Source:  (article, 2019-12-18)
Field: Chemistry — Spectroscopy

Bayesian Determination of Parameters for Plasma-Wall Interactions Within a Bayesian framework we propose a non-intrusive reduced-order spectral approach (polynomial chaos expansion) to assess the uncertainty of ion-solid interaction simulations. The method not only reduces the number of function evaluations but provides simultaneously a quantitative measure for which combinations of inputs have the most important impact on the result. It is applied to the ion-solid simulation program SDTrimSP with several uncertain and Gaussian distributed input parameters, i.e., angle &alpha; , projectile energy E 0 and surface binding energy E s b . In combination with recently acquired experimental data the otherwise hardly accessible model parameter E s b can now be estimated. Projectile ; Polynomial chaos ; Bayesian probability ; Gaussian process ; Gaussian ; Function (biology) ; Measure (data warehouse) ; Energy (signal processing) ; Computer science ; Polynomial ; Algorithm ; Statistical physics ; Applied mathematics ; Physics ; Monte Carlo method ; Mathematics ; Artificial intelligence ; Statistics ; Data mining ; Mathematical analysis Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; Energetic Materials and Combustion
Authors: Andrew Young | William Aylward | Paul Murray | Graeme West | S.D.J. McArthur
Source: Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (article, 2019-02-12)
Field: Materials Science — Materials Chemistry

Automatic anomaly detection in fuel grab load trace data using a knowledge-based system vs. multiple deep autoencoders Of the seven Advanced Gas-cooled Reactor nuclear power stations in the UK, the majority are approaching their planned closure date. As the graphite core of these type of reactors cannot be repaired or replaced, this is one of the main life-limiting factors. The refuelling of a nuclear power station is an ongoing process and refuelling of the reactor occurs typically every 6 to 8 weeks. During this process, data relating to the weight of the fuel assembly is recorded: this data is called fuel grab load trace data and the major contributing factor to this are the frictional forces, with a magnitude related to the channel bore diameter. Through an understanding of this data, it is possible to manually interpret whether there are any defects in the individual brick layers that make up the graphite core but doing so requires significant expertise, experience and understanding. In this paper, we present a knowledge-based system to automatically detect defects in individual brick layers in the fuel grab load trace data. This is accomplished using a set of rules defined by specialist engineers. Secondly, by splitting up the trace into overlapping regions, the use of multiple deep autoencoders is explored to produce a generative model for a normal response. Using this model, it is possible to detect responses that do not generalise and identify anomalies such as defects in the individual brick layers. Finally, the two approaches are compared, and conclusions are drawn about the applications of these techniques into industry. TRACE (psycholinguistics) ; Process (computing) ; Computer science ; Core (optical fiber) ; Nuclear reactor core ; Limiting ; Nuclear power ; Set (abstract data type) ; Data set ; Data mining ; Artificial intelligence ; Engineering ; Mechanical engineering ; Nuclear engineering Graphite, nuclear technology, radiation studies ; Nuclear reactor physics and engineering ; Nuclear and radioactivity studies
Authors: Kentaro Takada | Ken-ichi SAITOH | Tomohiro Sato | Masanori TAKUMA | Yoshimasa TAKAHASHI
Source: Soft Nanoscience Letters (article, 2019-01-01)
Field: Materials Science — Biomaterials

Molecular Dynamics Study on Transmission Mechanism of Torsional Deformation in Cellulose Nanofibers with Hierarchical Structure Cellulose nanofiber (CNF) is a fibrous and nano-sized substance produced by decomposition of bulk-type cellulose which is a main component of plants. It has high strength comparable to steel, and it shows low environmental load during a cycle of production and disposal. Besides it has many excellent properties and functions such as high rigidity, light-weight, flexibility and shape memory effect, so it is expected as a next-generation new material. Usually it is composed of many cellulose micro fibrils (CMFs) in which molecular chains of cellulose are aggregated in a crystal structure, the knowledge of mechanical properties for each CMF unit is important. Since actual fibrils are complicatedly intertwined, it is also crucial to elucidate the transmission mechanism of force and deformation not only in one fibril but also in between fibrils. How the dynamic and hierarchical structure composed of CMFs responds to bending or torsion is an interesting issue. However, little is known on torsional characteristics (shear modulus, torsional rigidity, etc.) concerning CMF. In general, in a wire-like structure, it is difficult to enhance torsional rigidity and strength, compared with tensile ones. Therefore, in this study, we try to build a hierarchical model of CNF by multiplying CMF fibers and to conduct molecular dynamics simulation for torsional deformation, by using hybrid model between all-atom and united-atoms model. First, shear modulus was estimated for one CMF fibril and it showed a value close to the experimental values. Also, we assume a state in which two CMFs are ideally arranged in parallel, and create a hierarchical structure. We evaluate the dependence on the temperature for the bond strength and toughness in the hierarchical structures. Furthermore, we mentioned the transmission mechanism between components of a hierarchical structure. Materials science ; Torsion (gastropod) ; Fibril ; Cellulose ; Shear modulus ; Composite material ; Molecular dynamics ; Structural rigidity ; Rigidity (electromagnetism) ; Nanofiber ; Flexural rigidity ; Ultimate tensile strength ; Modulus ; Crystal structure ; Crystallography ; Structural engineering ; Chemistry ; Computational chemistry Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Electrospun Nanofibers in Biomedical Applications
Authors: Gabriel Raicu | Alexandra Raicu
Source: Materials science forum (article, 2019-06-01)
Field: Materials Science — Materials Chemistry

Composite Materials Cyberspace Constraints Industry 4.0 era, as a whole, when economical entities not need to worry only about the classical business issues like natural disasters, asymmetrical competition, loss of key employees, among others, will be faced with increasingly sophisticated cyber threats targeting critical infrastructure as well as the smart devices that we use to control them virtually. Modern technology is prone to vulnerabilities that can be exploiting to get into targeted networks. Any connected system or industrial robot can easily be scanned for vulnerabilities that can be exploited and lead to the production of defective goods. As a paradox of this society, the future of Polymeric and Composites Materials and of related infrastructure will be based on high degree of automation – despite all associated cyber risks. Moreover, the blue efficiency paradigm will be based on increased role of IT and AI tools that will push the cyber risks even further. The paper will address the cyberspace constraints and corresponding solutions applied to Polymeric and Composites Materials paradigm. Cyberspace ; Automation ; Computer security ; Risk analysis (engineering) ; Lead (geology) ; Robot ; Competition (biology) ; Computer science ; The Internet ; Business ; Engineering ; Mechanical engineering ; Artificial intelligence Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Big Data and Digital Economy
Authors: Vladimir Batrakov -Csc | Leonid Shabalin -Csc | Mikhail Kiauka | Oleg N. Bezzametnov | V. I. Khaliulin | В. В. Батраков | L. P. Shabalin | Sakamoto Hiraku | Furuya Hiroshi | Satou Yasutaka | Okuizumi Nobukatsu | H Mansourinejad | M Sharavi | K Daneshjoo | Roh Jin-Ho | Bae Jae-Sung | Mallikarachchi Ch | S Pellegrino | K Kwok | J Block | M Straubel | M Wiedemann | L Datashvili | H Baier | L Rocha-Schmidt | A Endruweit | A Long | S Lane | T Murphey | M Zatman | H Mallikarachchi | Y Hongling | Z Chunhua | Z | M Sakovsky | J Yee | M Yinji | F Daining | F Dewalque | J Collette | O Brls | L Hua | L Brown | J Footdale | Y Liu | H Du | L Liu | J Leng | Hiraku Sakamoto | Furuya | & Hiroshi | Satou | & Yasutaka | Okuizumi | & Nobukatsu | Takai | & Moto | M Natori | D Piovesan | M Zaccariotto | C Bettanini | M Pertile | S Debei | Huina& Mao | Pier Ganga | Michele &ghiozzi | Ivchenko | & Nickolay | Gunnar Tibert | Jin-Ho & Roh | Jae-Sung Bae | Loredana Santo | Quadrini | Antonio Fabrizio & Accettura | Walter Villadei | Chinthaka Mallikarachchi | Sergio Pellegrino
Source: PNRPU Mechanics Bulletin (article, 2019-01-01)
Field: Materials Science — General Materials Science

THE RESEARCH OF THE MECHANICAL BEHAVIOR OF ELASTICALLY TRANSFORMABLE COMPOSITE STRUCTURES - . . Composite number ; Materials science ; Structural engineering ; Composite material ; Engineering Material Properties and Applications ; Structural mechanics and materials