157nm resist material design for improvement of its transparency by using highly precise theoretical calculation

2003 ◽  
Author(s):  
T. Yamazaki ◽  
T. Itani
Keyword(s):  
Theoretical Calculation ◽  
Material Design

Analysis of electro- and thermophysical processes occurring during electrocontact baking of flour products.

2020 ◽  
Vol 29 (11) ◽  
pp. 50-55
Author(s):  
V.I. Maklyukov ◽  
◽  
E.O. Gerasimova ◽  
N. V. Labutina ◽  
E.N. Rogozkin ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Theoretical Calculation ◽  
Heat Balance ◽  
Electric Contact ◽  
Wheat Dough ◽  
Baking Process ◽  
Free Moisture ◽  
Contact Heating ◽  
The Heat Balance

The article considers the results of research conducted during electric contact heating of rye-wheat dough pieces. It is established that the electrical conductivity of the crumb dough does not depend on the total humidity of the material, but mainly on the amount of free moisture. Using the current and temperature graphs, you can imagine how free moisture changes during the baking process and the influence of the thermophysical and colloidal process on the change in the value of free moisture. Experimentally determined the amount of heat that is spent on baking 1 kg of bread. The accuracy of the theoretical calculation of this parameter in the heat balance of the baking chamber is confirmed.

ORGANIC (1).pdf

2017 ◽  
Author(s):  
Benjamin Sanchez-Lengeling ◽  
Carlos Outeiral ◽  
Gabriel L. Guimaraes ◽  
Alan Aspuru-Guzik
Keyword(s):  
Machine Learning ◽  
Learning Community ◽  
Chemical Species ◽  
Material Design ◽  
Organic Photovoltaic ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Photovoltaic Material

Molecular discovery seeks to generate chemical species tailored to very specific needs. In this paper, we present ORGANIC, a framework based on Objective-Reinforced Generative Adversarial Networks (ORGAN), capable of producing a distribution over molecular space that matches with a certain set of desirable metrics. This methodology combines two successful techniques from the machine learning community: a Generative Adversarial Network (GAN), to create non-repetitive sensible molecular species, and Reinforcement Learning (RL), to bias this generative distribution towards certain attributes. We explore several applications, from optimization of random physicochemical properties to candidates for drug discovery and organic photovoltaic material design.

New Insights into the Nature of the Band Gap of CuGeO3 Nanoparticles: Synthesis, Electronic Structure, and Optical and Photocatalytic Properties

2019 ◽  
Author(s):  
Victor Y. Suzuki ◽  
Luís Henrique Cardozo Amorin ◽  
Natália H. de Paula ◽  
Anderson R. Albuquerque ◽  
Julio Ricardo Sambrano ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Band Gap ◽  
Material Design ◽  
Photocatalytic Properties ◽  
Critical Parameters ◽  
Synthetic Approach ◽  
Microwave Assisted ◽  
Theoretical Approaches ◽  
Nanoparticles Synthesis ◽  
First Time

<p>We report, for the first time, new insights into the nature of the band gap of <a>CuGeO<sub>3</sub> </a>(CGO) nanocrystals synthesized from a microwave-assisted hydrothermal method in the presence of citrate. To the best of our knowledge, this synthetic approach has the shortest reaction time and it works at the lowest temperatures reported in the literature for the preparation of these materials. The influence of the surfactant on the structural, electronic, optical, and photocatalytic properties of CGO nanocrystals is discussed by a combination of experimental and theoretical approaches, and that results elucidates the nature of the band gap of synthetized CGO nanocrystals. We believe that this particular strategy is one of the most critical parameters for the development of innovative applications and that result could shed some light on the emerging material design with entirely new properties.</p> <p><b> </b></p>

Pengembangan Bahan Ajar Mata Pelajaran Sosiologi Siswa Madrasah Aliyah

2017 ◽  
Vol 2 (1) ◽  
pp. 51
Author(s):  
Wagimin Wagimin
Keyword(s):  
High School ◽  
Small Group ◽  
Field Test ◽  
Instructional Material ◽  
Material Design ◽  
Teaching Sociology ◽  
One To One ◽  
Teaching Learning ◽  
Developing Method ◽  
Test Result

Abstract Penelitian ini bertujuan untuk mengembangkan perangkat materi pembelajaran untuk pengajaran sosiologi guna memotivasi siswa. Penelitian ini menggunakan metode penelitian dan pengembangan guna menformulasi produk dan mengukur efektifitasnya melalui validasi dan pengujian ahli di bidangnya. Ada tiga tipe test yang digunakan yaitu, one to one, small group, dan field test yang menunjukkan bahwa desain materi tersebut efektif. Setelah melalui revisi, desain meteri pembelajaran Sosiologi dianggap bermanfaat dan dapat digunakan dalam proses belajar mengajar Kata Kunci: Perangkat pembelajaran, mata pelajaran Sosiologi, siswa Madrasah Aliyah Abstract [Tittle: The Development of Sosiology Instructional Material for The Students fo Islamic Senior High School] . The research aims at developing a set of instructional material for teaching Sociology in order to motivate the students. The researcher employed a research and developing method to formulate a product and to measure its effectiveness through validation and trial-out by the experts of content-material and material-design. There were three types of trial to test the design; one to one, small group, and field test. Based on the test result, it was found that students in average can achieve 84% of overall score which indicate that the designed material is effective. After being revised several times in each stage, the design of instructional material for Sociology subject is considered as beneficial and able to be used in the teaching learning process

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

scholarly journals Characteristics Analysis and Modelling of a Pneumatic Underwater Launching System

2018 ◽  
Vol 232 ◽  
pp. 02005
Author(s):  
Bin Li ◽  
Song Guo ◽  
Wei Li ◽  
Deman Zhang ◽  
Nei Wang
Keyword(s):  
Theoretical Calculation ◽  
Calculation Formula ◽  
Numerical Work ◽  
Characteristics Analysis ◽  
Hydrodynamic Noise

Comprehensive characteristics of a pneumatic underwater launching system were analyzed and the simulation was carried out by simulink. The components of the pneumatic underwater launching system were introduced, and the theoretical calculation formula for the system was derived. A rated pressure of 3.5MPa and 5MPa was offered in the numerical work. Analyses in different piston height show good behaviors: Proper increase of piston-initial accumulator pressure is beneficial to reduce hydrodynamic noise, choose the appropriate pressure of accumulator. The hydrodynamic noise of the system can be significantly reduced by optimizing the structure of the double-acting cylinder, increasing the height of the piston and improving the structure of the piston.

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