화학공학소재연구정보센터
검색결과 : 88건
No. Article
1 Experimental methods in chemical engineering: Transmission electron microscopy-TEM
Braidy N, Bechu A, Terra JCD, Patience GS
Canadian Journal of Chemical Engineering, 98(3), 2020
2 Variation in the mineral composition of wine produced using different winemaking techniques
Shimizu H, Akamatsu F, Kamada A, Koyama K, Iwashita K, Goto-Yamamoto N
Journal of Bioscience and Bioengineering, 130(2), 166, 2020
3 Challenges in sample preparation for measuring nanoparticles size by scanning electron microscopy from suspensions, powder form and complex media
Ghomrasni NB, Chivas-Joly C, Devoille L, Hochepied JF, Feltin N
Powder Technology, 359, 226, 2020
4 Next-generation virtual metrology for semiconductor manufacturing: A feature-based framework
Suthar K, Shah D, Wang J, He QP
Computers & Chemical Engineering, 127, 140, 2019
5 A series of microscope objective lenses combined with an interferometer for individual nanoparticles detection
Ibrahim DGA
Current Applied Physics, 19(7), 822, 2019
6 Characteristics of a plasma information variable in phenomenology-based, statistically-tuned virtual metrology to predict silicon dioxide etching depth
Jang YC, Roh HJ, Park S, Jeong S, Ryu S, Kwon JW, Kim NK, Kim GH
Current Applied Physics, 19(10), 1068, 2019
7 Ultrasonic parameter measurement as a means of assessing the quality of biodiesel production
Baesso RM, Costa-Felix RPB, Miloro P, Zeqiri B
Fuel, 241, 155, 2019
8 Measurement challenges for hydrogen vehicles
Murugan A, de Huu M, Bacquart T, van Wijk J, Arrhenius K, te Ronde I, Hemfrey D
International Journal of Hydrogen Energy, 44(35), 19326, 2019
9 DeepVM: A Deep Learning-based approach with automatic feature extraction for 2D input data Virtual Metrology
Maggipinto M, Beghi A, McLoone S, Susto GA
Journal of Process Control, 84, 24, 2019
10 DeepVM: A Deep Learning-based approach with automatic feature extraction for 2D input data Virtual Metrology
Maggipinto M, Beghi A, McLoone S, Susto GA
Journal of Process Control, 84, 24, 2019