Prediction of influence of stepwise increment of initial acetic acid concentration in charging medium on acetification rate of semi-continuous process by artificial neural network

Based on industrial vinegar production, ethanol concentration in charging medium is normally considered as a strong variable influencing the acetification for a given initial acetic acid concentration. Moreover, high initial acetic acid concentration is considered when higher than 100 g L⁻¹ of acetic acid as finished product is obtained. This study assessed the effect of a stepwise increment of initial acetic acid concentration in fermentation medium of 45, 55, and 65 g L⁻¹ after charging at constant ethanol concentration of 35 g L⁻¹ on acetification rate (ETA) by high acid-tolerant strain of Acetobacter aceti WK. Average ETA was 8.144 + 0.09 g L⁻¹ d⁻¹ at 45 g L⁻¹ and 8.655 + 0.09 g L⁻¹ d⁻¹ at 55 g L⁻¹, and significant decreased to 6.819 + 0.23 g L⁻¹ d⁻¹ at 65 g L⁻¹. An artificial neural network (ANN) model was applied to predict the ETA in semi-continuous acetification under the conditions of the study. The optimized ANN structure was revealed to contain two hidden layers and seven neurons per layer. The experimental acetification correlated to the predicted data with R² of training and testing data set of 0.858 and validation data set of 0.831, respectively. Results indicated that the inputs as acetic acid and ethanol concentrations successfully predicted the ETA of semi-continuous acetification process.     

Xanthan Production by Mutant Strain of Xanthomonas campestris TISTR 840 in Raw Cassava Starch Medium

Raw cassava starch was used as carbon source in growing Xanthomonas campestris TISTR 840 for xanthan production due to its cheap price and mass production in Thailand. However, xanthan production with raw cassava starch yielded low content (4.31 g/l). A low level of amylase was detected in the XOL medium of X. campestris when raw cassava starch was used. Treatment of X. campestris TISTR 840 with ethyl methansulfonate resulted in the isolation of Xc-M, a strain that showed highest amylase overproduction. When cultured in bioreactor with a medium containing raw cassava starch, the growth of Xc-M cells was significantly higher than that of the wild type. The mutant produced 3.46- and 1.39-fold increased amylase activity and xanthan yield, respectively. Xc-M is useful for xanthan production in media containing raw starch as a carbon source.     

3D Printed High‐Performance Lithium Metal Microbatteries Enabled by Nanocellulose

Batteries constructed via 3D printing techniques have inherent advantages including opportunities for miniaturization, autonomous shaping, and controllable structural prototyping. However, 3D‐printed lithium metal batteries (LMBs) have not yet been reported due to the difficulties of printing lithium (Li) metal. Here, for the first time, high‐performance LMBs are fabricated through a 3D printing technique using cellulose nanofiber (CNF), which is one of the most earth‐abundant biopolymers. The unique shear thinning properties of CNF gel enables the printing of a LiFePO₄ electrode and stable scaffold for Li. The printability of the CNF gel is also investigated theoretically. Moreover, the porous structure of the CNF scaffold also helps to improve ion accessibility and decreases the local current density of Li anode. Thus, dendrite formation due to uneven Li plating/stripping is suppressed. A multiscale computational approach integrating first‐principle density function theory and a phase‐field model is performed and reveals that the porous structures have more uniform Li deposition. Consequently, a full cell built with a 3D‐printed Li anode and a LiFePO₄ cathode exhibits a high capacity of 80 mA h g^?1 at a charge/discharge rate of 10 C with capacity retention of 85% even after 3000 cycles.