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The algae-derived bio-binder (ADBB) from hydrothermal liquefaction has been reported to be an effective and sustainable new alternative to petroleum-based curing agents for epoxy resin. However, there is still room for the epoxy/ADBB system to attain the comprehensive mechanical performance of conventional epoxy-based nanocomposites, typically reinforced with surface-functionalized nanofillers (e.g., glass nanoparticles (GNPs)) by petroleum-based silane coupling agents. Herein, we explored the use of ADBB as an innovative surface-modifying agent to functionalize GNPs and evaluated the potential of ADBB surface-functionalized GNPs (ADBB-GNPs) as a reinforcing agent in the epoxy/ADBB matrix nanocomposite by comparing them to pristine GNPs and (3-aminopropyl) triethoxysilane (APTES) (a popular silane coupling agent) surface-modified GNPs (APTES-GNPs). The surface functionalization of GNPs with ADBB was carried out and characterized by scanning electron microscopy (SEM), dynamic light scattering (DLS), and Fourier-transform infrared spectroscopy (FTIR). Material performance including tensile, flexural, and Izod impact properties and thermal properties of the resulting epoxy/ADBB nanocomposites were investigated by corresponding ASTM mechanical test standards and thermogravimetric analysis (TGA). Our results revealed that the ADBB is a sustainable and effective surface-modifying agent that can functionalize GNPs. The obtained ADBB-GNPs significantly improved the mechanical performance of the epoxy/ADBB system at ultra-low loading (0.5 wt.%) by up to 42% and the maximum decomposition rate temperature increased from 419 °C to 422 °C, both of which outperformed APTES-GNPs. This research sheds light on developing sustainable surface-modifying agents for nanofillers to create high-performance sustainable polymer composite materials. 

We report a transformative epoxy system with a microalgae-derived bio-binder from hydrothermal liquefaction processing (HTL). The obtained bio-binder not only served as a curing agent for conventional epoxy resin (e.g., EPON 862), but also acted as a modifying agent to enhance the thermal and mechanical properties of the conventional epoxy resin. This game-changing epoxy/bio-binder system outperformed the conventional epoxy/hardener system in thermal stability and mechanical properties. Compared to the commercial EPON 862/EPIKURE W epoxy product, our epoxy/bio-binder system (35 wt.% bio-binder addition with respect to the epoxy) increased the temperature of 60% weight loss from 394 °C to 428 °C and the temperature of maximum decomposition rate from 382 °C to 413 °C, while the tensile, flexural, and impact performance of the cured epoxy improved in all cases by up to 64%. Our research could significantly impact the USD 38.2 billion global market of the epoxy-related industry by not only providing better thermal and mechanical performance of epoxy-based composite materials, but also simultaneously reducing the carbon footprint from the epoxy industry and relieving waste epoxy pollution. 

Algae is a promising sustainable feedstock for the generation of bio-crude oil, which is a sustainable alternative to fossil fuels, through the thermochemical process of hydrothermal liquefaction (HTL). However, this process also generates carbon particles (algae-derived carbon, ADC) as a significant byproduct. Herein, we report a brand-new and value-added use of ADC particles as a reinforcing agent for epoxy matrix composites (EMCs). ADC particles were synthesized through HTL processing of Chlorella vulgaris (a green microalgae) and characterized for morphology, average size, specific surface area, porosity, and functional groups. The ADC particles were subsequently integrated into a representative epoxy resin (EPON 862) as a reinforcing filler at loading levels of 0.25%, 0.5%, 1%, and 2% by weight. The tensile, flexural, and Izod impact properties, as well as the thermal stability, of the resulting EMCs were evaluated. It is revealed that the ADC particles are a sustainable and effective reinforcing agent for EMCs at ultra-low loading. Specifically, the ADC-reinforced EMC with 1 wt.% ADC showed improvements of ~24%, ~30%, ~31%, and ~57% in tensile strength, Young’s modulus, elongation at break, and work of fracture (WOF), respectively, and improvements of ~10%, ~37%, ~24%, and ~39% in flexural strength, flexural modulus, flexural elongation at break, and flexural WOF, respectively, as well as an improvement of ~54% in Izod impact strength, compared to those corresponding properties of neat epoxy. In the meantime, the thermal decomposition temperatures at 60% and 80% weight loss of the abovementioned ADC-reinforced EMC increased from 410 °C to 415 °C and from 448 °C to 515 °C in comparison with those of neat epoxy. This study highlighted the potential of sustainable ADC particles as a reinforcing agent in the field of polymer matrix composite materials, which represented a novel and sustainable approach that would mitigate greenhouse gas remission and reduce reliance on nonrenewable reinforcing fillers in the polymer composite industry. 

Abstract 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. 

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. 

Statistical network models have been used to study the competition among different products and how product attributes influence customer decisions. However, in existing research using network-based approaches, product competition has been viewed as binary (i.e., whether a relationship exists or not), while in reality, the competition strength may vary among products. In this paper, we model the strength of the product competition by employing a statistical network model, with an emphasis on how product attributes affect which products are considered together and which products are ultimately purchased by customers. We first demonstrate how customers’ considerations and choices can be aggregated as weighted networks. Then, we propose a weighted network modeling approach by extending the valued exponential random graph model to investigate the effects of product features and network structures on product competition relations. The approach that consists of model construction, interpretation, and validation is presented in a step-by-step procedure. Our findings suggest that the weighted network model outperforms commonly used binary network baselines in predicting product competition as well as market share. Also, traditionally when using binary network models to study product competitions and depending on the cutoff values chosen to binarize a network, the resulting estimated customer preferences can be inconsistent. Such inconsistency in interpreting customer preferences is a downside of binary network models but can be well addressed by the proposed weighted network model. Lastly, this paper is the first attempt to study customers’ purchase preferences (i.e., aggregated choice decisions) and car competition (i.e., customers’ co-consideration decisions) together using weighted directed networks.