PMC

Flow chart of vinegar manufacturing using peeled and unpeeled bellflower roots. (A) Processing of bellflower vinegar (BV). (B) Raw material of bellflower. (C) Acidogenic ability of Acetobacter pasteurianus A11-2 as a starter culture. (D) Fermented vessels (traditional ceramic and fermenter) used for vinegar fermentation.

Testing of clay raw material. Profiles of locations 1, 2 and 3 of ceramic raw material sampling (1–3); thin section microphotographs of ceramic raw materials (a-f); a–sample Sur35, depth approx. 0.6 m, clay rich in fine grains, iron oxide and hydroxides and fine mica flakes, PPL; b–sample Sur36, depth approx. 0.8 m, smaller content of silt fraction, orange color of clay matrix, PPL; c–sample37, depth approx. 0.6 m, high content of silt fraction and fine opaque minerals, PPL; d–sample Sur38, depth approx. 1.1 mm, smaller content of silt fraction, very fine grained clay, PPL; e–sample Sur39, depth approx. 0,6 m, medium sorted, fragments of sedimentary rocks occur, PPL; f–sample Sur40, depth approx. 0.8 m, clay with the smallest content of silt fraction, fragments of sedimentary rocks occur.

The flow chart for predicting the mechanical property. The model has investigated the non-linear relationship among the raw material’s content composition, component, and the fracture complexities of the composite ceramic and flexural strength. The proposed ANN model predicted the mechanical characteristics of the alumina matrix ceramic tool. The neural network model was trained using a toolbox available in MATLAB (MATrix LABoratoryMA software). The two and three-phase composite ceramic tools of the mechanical properties like Al₂O₃–(W, Ti)C and Al₂O₃–TiC–ZrO₂ were predicted to verify their proposed model.

X-ray diffraction (XRD) patterns of raw material and mixture powder calcined at different temperature from 600 to 900 °C after ball milling for 8 h.