Abolghasem Shahbazi

With global population growth accelerating and food demand rising, the need for efficient farmland surveying to maximize crop yields through precision agriculture has never been more critical. Unmanned Aerial Vehicles (UAVs) have emerged as capable tools due to their advanced sensor capabilities, high mobility, and ability to collect data with minimal risk to both farmers and crops. While single UAV platforms offer significant potential, their effectiveness remains limited by factors such as restricted battery life, limited flight duration, and high operational costs, among other aspects. This article addresses these limitations by introducing a sensing- and constraint-aware, cooperative coverage framework designed for agricultural surveying using a heterogeneous team of UAVs. Our approach accounts for both the physical constraints of UAVs and the user-defined data collection needs, while minimizing the total mission time and energy consumption. The framework begins by defining the Region of Interest (ROI) as a convex polygon, which is then decomposed into subregions based on the relative sensing and flight capabilities of each UAV. Each partition is assigned to a specific UAV based on its relative capability, and coverage paths are generated using an efficient back-and-forth sweeping strategy. A novel receding horizon Mixed Integer Linear Programming (MILP) technique is then applied to produce collision-free trajectories tailored to each UAV’s constraints. We validated the framework within the CoppeliaSim physics-based simulator, where results demonstrate the effective trajectory coordination and full ROI coverage, confirming the system’s adaptability and performance under realistic conditions. The derived solutions will provide an opportunity for farmers to regularly and efficiently survey agricultural fields to maximize crop yields.

With the worldwide awareness of sustainability, biomass-derived carbon electrode materials for supercapacitors have attracted growing attention. In this research, for the first time, we explored the feasibility of making use of the carbon byproduct from hydrothermal liquefaction (HTL) of microalgae, termed herein as algae-derived carbon (ADC), to prepare sustainable carbon electrode materials for high-performance supercapacitor development. Specifically, we investigated carbon activation with a variety of activating reagents as well as N- and Fe-doping of the obtained ADC with the intention to enhance its electrochemical performance. We characterized the structure of the activated and doped ADCs using scanning electron microscope (SEM), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and BET surface area and pore analysis, and correlated the ADCs’ structure with their electrochemical performance as evaluated using cyclic voltammetry (CV), galvanostatic charge/discharge (GCD), impedance, and cycle stability through an assembled symmetric two-electrode cell with 1 M H₂SO₄ as electrolyte. It was found that the ADC that is activated using KOH (KOH-ADC) showed the best electrochemical performance, and its specific capacitance was 14.1-fold larger with respect to that of the raw ADC and reached 234.5 F/g in the GCD test at a current density of 0.5 A/g. The KOH-ADC also demonstrated excellent capacitance retention (97% after 10,000 cycles at a high current density of 10 A/g) for stable long-term operations. This research pointed out a promising direction to develop sustainable electrode materials for supercapacitors from the carbon byproduct produced after HTL processing of algae.

A supercapacitor is an electrical energy storage system with high power output. With worldwide awareness of sustainable development, developing cost-effective, environmentally friendly, and high-performance supercapacitors is an important research direction. The use of sustainable components like wood biochar in the electrode materials for supercapacitor uses holds great promise for sustainable supercapacitor development. In this study, we demonstrated a facile and powerful approach to prepare meso-microporous carbon electrode materials for sustainable and high-performance supercapacitor development by electrospinning polyacrylonitrile (PAN) with F-treated biochar and subsequent aerogel construction followed by stabilization, carbonization, and carbon activation. The resultant carbon nanofibrous aerogel electrode material (ENFA-FBa) exhibited exceptional specific capacitance, attributing to enormously increased micropore and mesopore volumes, much more activated sites to charge storage, and significantly greater electrochemical interaction with electrolyte. This electrode material achieved a specific capacitance of 407 F/g at current density of 0.5 A/g in 1 M H₂SO₄ electrolyte, which outperformed the state-of-the-art specific capacitance of biochar-containing electrospun carbon nanofibrous aerogel electrode materials (<300 F/g). A symmetric two-electrode cell with ENFA-FBa as electrode material showed an energy density of 11.2 Wh/kg at 125 W/kg power density. Even after 10,000 cycles of charging-discharging at current density of 10 A/g, the device maintained a consistent coulombic efficiency of 53.5% and an outstanding capacitance retention of 91%. Our research pointed out a promising direction to develop sustainable electrode materials for future high-performance supercapacitors.

In recent years, carbon nanofibers from electrospinning (ECNFs) have been extensively studied as promising electrode material for supercapacitors. In order to further improve the electrochemical performance of ECNFs, porous or hollow ECNF structures have been investigated. However, the state-of-the-art ECNF research for supercapacitors reported only one type of carbon nanofibrous structure, i.e. porous, hollow (hollow nanofibers with a solid wall), or hollow porous (hollow nanofibers with a porous wall), at a time; the electrochemical data from these reports are not directly comparable due to different electrospinning conditions and various instruments for electrochemical measurements. In this chapter, a side-by-side comparison of the electrochemical performance of four types of ECNF supercapacitor electrode materials including solid, porous, hollow, and hollow porous, respectively, has been studied. The findings herein provide an in-depth understanding of the relationship between 1D carbon nanofibrous structures from electrospinning and their corresponding electrochemical performance as electrode materials for future high-performance supercapacitor applications.

A sequential modular hydrodynamic model integrated with detailed reaction kinetics (SMHM-RK) was developed and validated to predict tar and syngas components produced by the steam gasification of biomass in a fluidized bed gasifier. The simulations showed that the prediction accuracy is sensitive to both models for hydrodynamics and reaction kinetics. The simulations showed that the tar composition predicted by the SMHM-RK was more close to the measured values than those predicted by the well-mixed hydrodynamic model integrated with the same reaction kinetics (WMHM-RK). The predictions showed that the total tar decreased, but the polycyclic aromatic tar compounds increased with the increase in gasification temperature. There was an optimum steam-to-biomass ratio (SBR) for minimizing tar formation. The simulations found that the contents of total tar and heavy tar compounds decreased by increasing the SBR from 0.3 to 0.9, and then increased by further increasing the SBR. The injection of a small amount of oxygen in steam gasification cannot reduce tar formation. The injection of oxygen in steam gasification changed the reaction pathways of naphthalene to produce more naphthalene in the syngas. The de-volatilization rate affects pyrolytic volatile compositions and subsequent tar formation. Therefore, biomass devolatilization and homogeneous gas reactions should be solved simultaneously to accurately predict the syngas and tar composition.

Chemical Looping Combustion (CLC) is a technology that efficiently combines power generation and CO₂ capture. In CLC, the fuel is oxidized by a metal oxide called an oxygen carrier (OC). CLC uses two reactors: a fuel reactor and an air reactor. The fuel reactor oxidizes the fuel and reduces the OC. The air reactor oxidizes the OC using air and then the OC is cycled back to the fuel reactor. It is typical for both the fuel and the air reactors to be fluidized beds (FBs). In this research, an Aspen Plus model was developed to simulate a CLC system. Aspen Plus has recently included a built-in FB unit operation module. To our knowledge, no literature has been reported using this FB module for simulating fluidized bed combustion or gasification. This FB unit process was investigated in Aspen Plus and a kinetic based model was used and compared the simulation results to experimental data and the commonly used Gibbs equilibrium model. The FB unit and the kinetic model well fit the experimental data for syngas and methane combustion within 2% of the molar composition of syngas combustion and within 4% for the methane combustion. An advantage of this model over other kinetic models in literature is that the core shrinking model kinetic rate equations have been converted into a power law form. This allows Aspen Plus to use a calculator instead of an external Fortran compiler. This greatly simplifies the modeling process. The reaction rate equations are given for all reactions. A sensitivity analysis of the reaction kinetics was conducted. All data, code, and simulation files are given.