University of Brawijaya

The valorization of abundant agricultural residues, such as edamame peel waste, into high-value nanomaterials represents a critical opportunity for the circular bioeconomy. While conventional NCC extraction relies on environmentally hazardous mineral acids, this study investigates a sustainable, phase-controlled pathway using a heterogeneous zirconium phosphate solid acid catalyst. By systematically varying the orthophosphoric acid precursor concentration (0.1-0.6 M), the catalyst's structural phase was actively tailored, culminating in a highly crystalline and thermally stable alpha-ZrP phase at 0.6 M. This specific structural transition in the catalyst proved highly effective for cellulose hydrolysis, increasing the product's crystallinity index from 44.44% to 59.93%, alongside the confirmed removal of amorphous lignin and hemicellulose domains. Crucially, this catalytic system enabled precise morphological control over the extracted NCC: lower concentrations of ZrP yielded elongated nanofibers (12.72 nm diameter), whereas the robust crystalline alpha-ZrP phase directed the synthesis toward short, rod-like nanocrystals (22.53 nm diameter, 105.19 nm length). Furthermore, the resulting NCC demonstrated superior thermal resistance, characterized by a substantial char residue (53.82% compared to 23.47% for the original cellulose). Ultimately, this work establishes a highly tunable and eco-friendly approach to producing specialized NCC, advancing sustainable bioprocessing using dynamic solid acid catalysts.

Nanocellulose has emerged as a versatile, bio-based, and eco-friendly material due to its high transparency, excellent mechanical properties, and biodegradability, positioning it as a promising alternative for sustainable packaging. In this study, we present a mild, acid-free extraction method to obtain high-crystallinity nanocellulose from underutilized Walikukun fiber (WF) using sequential alkali treatment, bleaching, and mechanical sonication. Fourier-transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) confirm the effective removal of lignin and hemicellulose, resulting in a crystallinity index of up to 91.61% and the formation of densely packed cellulose fibrils. Thermogravimetric analysis reveals enhanced thermal stability, partly attributed to oxidation and structural modifications induced by sonication. Overall, WF-derived nanocellulose demonstrates potential as a sustainable alternative to petroleum-based polymers, offering improved barrier properties, thermal stability, and optical clarity for eco-friendly packaging. This work highlights the environmental benefits of using renewable natural fibers, thereby contributing to circular economy objectives and reducing dependence on nonrenewable resources.

Defect engineering is widely applied to improve the photocatalytic performance of metal–organic frameworks (MOFs), but its role is often interpreted from a structural perspective rather than an electronic one. This review examines defect formation in MOFs from a coordination chemistry standpoint, focusing on how variations in metal–ligand environments influence electronic structure and charge-transfer behavior. The interplay between metal nodes, organic linkers, and defect types is analyzed to clarify their impact on orbital alignment and electronic coupling. Charge-transfer pathways, including ligand-to-metal (LMCT), metal-to-ligand (MLCT), metal-to-metal (MMCT), and ligand-to-ligand (LLCT) processes, are discussed in relation to defect-induced structural distortions. Synthetic strategies such as modulated synthesis, mixed-linker approaches, ligand functionalization, and post-synthetic modification are evaluated based on their ability to generate and regulate defects. Defect density influences photocatalytic behavior in a non-linear manner, reflecting the balance between improved charge separation and reduced electronic connectivity. Current limitations in correlating defect structures with electronic properties are addressed, highlighting the need for improved control and characterization. This review outlines a framework that connects coordination environment, electronic structure, and charge-transfer processes in defect-engineered MOFs.

Seaweeds, also known as macroalgae, are marine photosynthetic organisms that play an important role in aquatic ecosystems and hold great promise as raw materials for biodegradable packaging. This review investigates the biodegradability and toxicity of seaweed-based packaging materials, as well as their potential to lessen the environmental effect of traditional petroleum-derived plastics. Seaweed-based biopolymers are gaining popularity due to their renewability, biocompatibility, and biodegradability, making them interesting options for sustainable packaging applications. The review emphasizes important safety factors, notably seaweeds’ tendency to absorb heavy metals, pesticides, and other environmental toxins from nearby waterways. Effective monitoring, purification, and detoxification of seaweed biomass are thus required to assure the safe use of seaweed-derived materials in packaging applications. In addition to its environmental benefits, seaweed-based packaging materials help to minimize greenhouse gas emissions, decrease reliance on fossil fuels, and reduce plastic waste accumulation in terrestrial and marine habitats. Overall, this review emphasizes the promise of seaweed-based packaging as an environmentally friendly option that also provides economic opportunities for coastal communities by creating jobs and diversifying resources. The findings highlight the necessity of incorporating biodegradability testing, toxicity testing, and sustainable cultivation procedures to promote the development and widespread use of seaweed-based packaging materials.

Globally, wind is one of the fastest growing renewable energy sources, requiring innovative computational methods across the spectrum of wind energy engineering tasks to boost wind energy production. Recent advancements in generative artificial intelligence (AI) models have led to the integration of the models into wind energy engineering to develop solutions. Previous surveys primarily focused on the general applications of AI in wind energy. The objectives of this survey are to: (i) review modified generative AI models in wind energy engineering tasks, (ii) develop taxonomy linking model variants to tasks, (iii) develop performance evaluation metrics taxonomy, (iv) analyze the core concepts and limitations of the modified generative AI models, (v) examine data sources, (vi) present real-world case studies, (vii) identify emerging trends and challenges. This is the first comprehensive survey exclusively for modified generative AI models across different aspects of wind energy engineering. The survey examines the modifications of generative AI models for wind energy applications, explaining the core idea behind each modification, its suitability for specific task and the limitations identified in the corresponding model. New taxonomies were introduce to support synthesis and analysis. The survey extends beyond theoretical discussion by highlighting real-world case studies where generative AI models have been deployed in real-world commercial wind farms. Additionally, emerging open challenges are identified and future research directions are proposed from new perspectives. This survey provide a fundamental reference for early career researchers, a guide to industry practitioners and a benchmark for innovations for expert researchers.