2-2-3 物性値主成分を用いるメタンドライリフオーミング用触媒への添加物探索(2-2 天然ガス科学,Session 2 天然ガス・メタンハイグレート等)

概要

論文の詳細を見る
Cobalt catalyst supported on strontium carbonate (Co/SrCO_3) showed high activity for dry reforming of methane at 1 MPa, 750℃, SV = 100,000 mL/h/g, feed composition = CH_4/CO_2/N_2 = 45/45/10. In the first step of the optimization, new additives to the catalyst had been screened by using a Radial Basis Function Network (RBFN). Catalytic activities of 10 mol% Co + 1 mol% X/SrCO_3 (X = B, K, Sc, Mn, Zn, Nb, Ag, Nd, Re, or Tl) and 16 physicochemical properties of these 10 elements were used for the regression model, and the effect of each additive among 53 elements was predicted by the model by RBFN. In the present study principal component analysis was conducted to make input dataset for a new regression model. In addition to RBFN, Support Vector Machine (SVM) and Gaussian Process Regression was used. New additives were suggested by the new regression models.
2012-07-30