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◆ Bioresource technology2026-09-09

Energy-based prediction of biological feedstock densification from laboratory to industrial pelleting.

Wanfeng Sun, Yu Wang, Bo Cui, Chi Xu, Xiaofei Dong, Wang Xi, Jian Yang, Liang Li

原始摘要(英文原文)· Original abstract
Pelleting converts loose biological powders into stable particulate products, improving storage, transport, and energy-efficient utilization. However, reliable control of industrial ring-die pelleting remains limited by the lack of a predictive link between laboratory-scale compression and the coupled powder flow, die-wall friction, moisture-dependent bonding, and energy consumption that occur during production. This study developed an energy-based single-hole open compression (SHOC) framework for biological feedstocks by combining SHOC tests, ring-die pelleting tests, rapid viscosity analysis, and differential scanning calorimetry gelatinization analysis of corn, wheat, and soybean flour systems. Rebound-corrected validation supported the pressure-valve hypothesis, with the corrected compression curve matching the validation test below 3 kN (R2 = 0.995). Die length, die diameter, and effective area ratio controlled compression pressure, pellet density, and specific energy consumption (SEC), whereas inlet angle became negligible after an accumulation zone formed. Moisture and batch mass produced independent produced nonlinear responses. At 20 wt% moisture, SEC reached 16.92 kWh·t-1, and density produced per unit SEC increased by 47.20 % relative to 10 wt% moisture. Thermal analysis indicated that complete bulk gelatinization was unlikely, although locally retained frictional heat could activate starch-rich contact zones and improve bonding. Industrial validation gave pellet-property deviations of 1.20-3.25 % and an SEC difference of 11.32 %, demonstrating that the SHOC-derived pressure and energy relationships were retained at production scale. The framework links material transformation with process energy allocation and establishes a transferable basis for energy-efficient biological feedstock pelleting.
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Energy-based prediction of biological feedstock densification from laboratory to industrial pelleting. — 科研速览 Science Skim