Search

Prediction of sugar yields during hydrolysis of lignocellulosic biomass using artificial neural network modeling

메타 데이터

바이오화학분류
    • 바이오플라스틱
      1. 기타
    • 바이오정밀화학
      1. 기타
    • 화장품용 기능성소재
      1. 기타
    • 의료용 화학소재
      1. 식품첨가제
논문

Prediction of sugar yields during hydrolysis of lignocellulosic biomass using artificial neural network modeling

학술지

Bioresource technology : biomass, bioenergy, biowastes, conversion technologies, biotransformations, production technologies

저자명

Vani, S.; Sukumaran, R.K.; Savithri, S.

초록

The present investigation was carried out to study application of ANN as a tool for predicting sugar yields of pretreated biomass during hydrolysis process at various time intervals. Since it is known that biomass loading and particle size influences the rheology and mass transfer during hydrolysis process, these two parameters were chosen for investigating the efficiency of hydrolysis. Alkali pretreated rice straw was used as the model feedstock in this study and biomass loadings were varied from 10% to 18%. Substrate particle sizes used were <0.5mm, 0.5-1mm, >1mm and mixed size. Effectiveness of hydrolysis was strongly influenced by biomass loadings, whereas particle size did not have any significant impact on sugar yield. Higher biomass loadings resulted in higher sugar concentration in the hydrolysates. Optimum hydrolysis conditions predicted were 10FPU/g cellulase, 5IU/g BGL, 7500U/g xylanase, 18% biomass loading and mixed particle size with reaction time between 12-28h.

발행연도

2015

발행기관

Elsevier Applied Science

ISSN

0960-8524

188

페이지

pp.128-135

주제어

Particle size; Biomass loading; Biofuel; Artificial neural network modeling; Biomass hydrolysis

0건의 논문이 있습니다.

0건의 특허가 있습니다.

0건의 무역이 있습니다.

1건의 후보군 물질이 있습니다.

1 2023-12-11

논문; 2015-07-01

Export

About

Search

Trend