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The earth abundant and environmentally friendly element iron (Fe) forms various functional materials of metallic iron, iron oxides, iron carbides, natural iron ore, and iron-based metallic-organic frameworks. The Fe-based materials have been intensively studied as oxygen carriers, catalysts, adsorbents, and additives in bioenergy production. This review was to provide a fundamental understanding of the syntheses and characteristics of various Fe-based materials for further enhancing their functionalities and facilitating their applications in various bioenergy conversion processes. The syntheses, characteristics, and applications of various iron-based materials for bioenergy conversion published in peer-reviewed articles were first reviewed. The challenges and perspectives of the wide applications of those functional materials in bioenergy conversion were then discussed. The functionalities, stability, and reactivity of Fe-based materials depend on their structures and redox phases. Furthermore, the phase and composition of iron compounds change in a process. More research is needed to analyze the complex phase and composition changes during their applications, and study the type of iron precursors, synthesizing conditions, and the use of promoters and supports to improve their performance in bioenergy conversion. More studies are also needed to develop multifunctional Fe-based materials to be used for multi-duties in a biorefinery and develop green processes to biologically, economically, and sustainably produce those functional materials at a large scale.

 

High surface area graphitic mesoporous carbons (M‐mGMC; M=Ni, Fe, Co or Ni‐Fe) were synthesizedviacatalytic graphitization using a hard template based synthesis method. In house prepared SBA‐15 silica material was impregnated with metal precursors to obtain M/SBA‐15, template for M‐mGMC synthesis. These materials were studied using different material characterization techniques, such as nitrogen adsorption desorption (BET), X‐ray diffraction (XRD) analysis, Raman spectroscopy, X‐ray photoelectron spectroscopy (XPS), Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Specific surface area ranging from 1,227.9 m²g⁻¹to 1,320.7 m²g⁻¹was observed for four M‐mGMCs. Raman spectroscopy, XPS and wide angle XRD suggested presence of graphitic structure in these materials along with disorders. Electrocatalytic performance of these materials along with conventional carbon black (Vulcan XC‐72) were evaluated in a single‐stack proton exchange membrane fuel cell (PEMFC). Pt/NiFe‐mGMC exhibited enhanced electrocatalytic activity compared to Pt/Ni‐mGMC, Pt/Fe‐mGMC and Pt/Co‐mGMC electrocatalysts. However, Pt/NiFe‐mGMC lacked adequate proton transport in membrane electrode assembly (MEA) compared to Pt/Vulcan XC‐72. This exploratory study showed that NiFe‐mGMC may find application as electrocatalyst support material in PEMFC.

 

Abstract Chemical Looping Combustion (CLC) is a technology that efficiently combines power generation and CO 2 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. 

Anaerobic digestion (AD), microalgae cultivation, and microbial fuel cells (MFCs) are the major biological processes to convert organic solid wastes and wastewater in the agricultural industry into biofuels, biopower, various biochemical and fertilizer products, and meanwhile, recycle water. Various nanomaterials including nano zero valent irons (nZVIs), metal oxide nanoparticles (NPs), carbon-based and multicompound nanomaterials have been studied to improve the economics and environmental sustainability of those biological processes by increasing their conversion efficiency and the quality of products, and minimizing the negative impacts of hazardous materials in the wastes. This review article presented the structures, functionalities and applications of various nanomaterials that have been studied to improve the performance of AD, microalgae cultivation, and MFCs for recycling and valorizing agricultural solid wastes and wastewater. The review also discussed the methods that have been studied to improve the performance of those nanomaterials for their applications in those biological processes. 

The National Agricultural Statistics Service, the statistical arm of the US Department of Agriculture, and the Multi-Resolution Land Characteristics Consortium, a group of the US federal agencies, collect and publish several land-use and land-cover data sets. The aim of this study is to analyze the consistency of forestland estimates based on two widely used, publicly available products: the National Land-Cover Database (NLCD) and Cropland Data Layer (CDL). Both remote-sensing-based products provide raster-formatted land-cover categorization at a spatial resolution of 30 m. Although the processing of the yearly published CDL non-agricultural land-cover data is based on less frequently updated NLCD, the consistency of large-area forestland mapping between these two datasets has not been assessed. To assess the similarities and the differences between CDL- and NLCD-based forestland mappings for the state of North Carolina, we overlay the two data products for the years 2011 and 2016 in ArcMap 10.5.1 and analyze the location and attributes of the matched and mismatched forestland. We find that the mismatch is relatively smaller for the areas of the state where forests occupy larger shares of the total land, and that the relative mismatch is smaller in 2011 when compared to 2016. We also find that a large portion of the forestland mismatch is attributable to the dynamics of re-growth of periodically harvested and otherwise disturbed forests. Our results underscore the need for a holistic approach to data preparation, data attribution, and data accuracy when performing high-scale map-based analyses using each of these products.