Novel Solid Base Catalysts for the Production of Biodiesel from Lipids

The primary commercial biodiesel production processes use homogeneous base catalysts which cause separation and wastewater discharge problems. Solid base catalysts can overcome these drawbacks. However, a solid base catalyst with high activity and stability for biodiesel production still remains a challenge. This dissertation is dedicated to developing novel solid base catalysts and applying them to an environmentally beneficial reactive distillation process for transesterification of vegetable oils with methanol into biodiesel. Novel solid base catalysts included commercial nanopowder calcium oxides, synthesized Al2O3-, SiO2- and zeolite Y-supported base catalysts. For the first time, nanopowder calcium oxides were utilized in biodiesel production at elevated temperatures in this dissertation. Nanopowder CaOs possess a relatively large BET surface area associated with nano-sized particles. The larger surface area of nanopowder CaOs provides more accessible active sites leading to a much higher catalytic activity than laboratory-grade CaO. NanoScale-CaO exhibited a higher activity than nano-CaO due to its larger surface area. Recycling experiments showed that nanopowder CaOs could be used without a significant yield drop for 10 cycles. The loss of BET surface area caused by aggregation of nano-sized particles could be the main reason for the slight yield drop. The reaction microkinetics study was performed guided by experimental data obtained. A reaction mechanism based on Langmuir-Hinshelwood model has been proposed. A mathematical kinetics model was developed and the limiting-step was determined based on this proposed mechanism. The effective reaction constants, effective activation energies and pre-exponential factors have been calculated. Thiele modulus showed that internal mass transfer did not limit the overall reaction rate due to nanosized catalyst particles. Novel mesoporous Al2O3-, SiO2-supported solid base catalysts containing Ca, K as active elements were synthesized by a single-step sol-gel method. The synthesized catalysts possess a large BET surface area in the range of 180-400m2/g and a mesoporous pore size in the range of 60-120Å. The basic sites density can be adjusted to targeted values by changing the Metal/Al or Si molar ratio. Nanosized metal particles were evenly and highly dispersed over pores of supports which resulted in a very high catalytic activity. A 100% yield was obtained in 30min when 1wt% K/Al-0.6 or Ca/Al-4.0 catalyst was used. Ca-loaded catalysts exhibited a higher stability than K-loaded catalysts. The amount of Ca leaching was reduced significantly with the Ca/Al or Si molar ratio. Al2O3-, SiO2- and zeolite Y-supported solid base catalysts were also synthesized by the incipient-wetness impregnation method. The BET surface area of synthesized catalysts was less than that of parent supports because some K2O or CaO particles clogged the pores in parent supports. Though synthesized catalysts present high activity, they lack enough stability in recycling experiments. K leaching was believed to be the main reason for catalyst deactivation. An intensified reactive distillation (RD) system for biodiesel production using both homogeneous and heterogeneous catalysts was developed. It is demonstrated that RD system intensified the transesterification reaction efficiently. A shorter reaction time and a less amount of methanol were needed compared to the conventional batch reactor. The process simulation of the RD system was performed using ASPEN Plus 11.1 software based on the reaction microkinetics data obtained in Chapter 3. A significant enhancement of efficiency was obtained in the RD system catalyzed by the highly active heterogeneous solid base catalyst. Ca leaching was estimated to be reduced due to a much shorter residence time

Realization of Analog Wavelet Filter using Hybrid Genetic Algorithm for On-line Epileptic Event Detection

© 2020 The Author(s). This open access work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.As the evolution of traditional electroencephalogram (EEG) monitoring unit for epilepsy diagnosis, wearable ambulatory EEG (WAEEG) system transmits EEG data wirelessly, and can be made miniaturized, discrete and social acceptable. To prolong the battery lifetime, analog wavelet filter is used for epileptic event detection in WAEEG system to achieve on-line data reduction. For mapping continuous wavelet transform to analog filter implementation with low-power consumption and high approximation accuracy, this paper proposes a novel approximation method to construct the wavelet base in analog domain, in which the approximation process in frequency domain is considered as an optimization problem by building a mathematical model with only one term in the numerator. The hybrid genetic algorithm consisting of genetic algorithm and quasi-Newton method is employed to find the globally optimum solution, taking required stability into account. Experiment results show that the proposed method can give a stable analog wavelet base with simple structure and higher approximation accuracy compared with existing method, leading to a better spike detection accuracy. The fourth-order Marr wavelet filter is designed as an example using Gm-C filter structure based on LC ladder simulation, whose power consumption is only 33.4 pW at 2.1Hz. Simulation results show that the design method can be used to facilitate low power and small volume implementation of on-line epileptic event detector.Peer reviewe

DTER: Schedule Optimal RF Energy Request and Harvest for Internet of Things

We propose a new energy harvesting strategy that uses a dedicated energy source (ES) to optimally replenish energy for radio frequency (RF) energy harvesting powered Internet of Things. Specifically, we develop a two-step dual tunnel energy requesting (DTER) strategy that minimizes the energy consumption on both the energy harvesting device and the ES. Besides the causality and capacity constraints that are investigated in the existing approaches, DTER also takes into account the overhead issue and the nonlinear charge characteristics of an energy storage component to make the proposed strategy practical. Both offline and online scenarios are considered in the second step of DTER. To solve the nonlinear optimization problem of the offline scenario, we convert the design of offline optimal energy requesting problem into a classic shortest path problem and thus a global optimal solution can be obtained through dynamic programming (DP) algorithms. The online suboptimal transmission strategy is developed as well. Simulation study verifies that the online strategy can achieve almost the same energy efficiency as the global optimal solution in the long term

Design of Gm-C wavelet filter for on-line epileptic EEG detection

Copyright © 2019 The Institute of Electronics, Information and Communication EngineersAnalog filter implementation of continuous wavelet transform is considered as a promising technique for on-line spike detection applied in wearable electroencephalogram system. This Letter proposes a novel method to construct analog wavelet base for analog wavelet filter design, in which the mathematical approximation model in frequency domain is built as an optimization problem and the genetic algorithm is used to find the global optimum resolution. Also, the Gm-C filter structure based on LC ladder simulation is employed to synthesize the obtained analog wavelet base. The Marr wavelet filter is designed as an example using SMIC 1V 0.35μm CMOS technology. Simulation results show that the proposed method can give a stable analog wavelet filter with higher approximation accuracy and excellent circuit performance, which is well suited for the design of low-frequency low-power spike detector.Peer reviewe