Maria Eduarda Alves

Maria Eduarda Alves


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 October 2025 in Sustainability
Verified
Journal Article
Open access
PDF file
LBLaysa Silva Barboza
Laysa Silva Barboza
PPPedro Afonso de moraes Paes
Pedro Afonso de moraes Paes
MAMaria Eduarda Alves
Maria Eduarda Alves
MCMarceli Do Nascimento Da Conceicao
Marceli Do Nascimento Da Conceicao
NSNancy Camilly Marques de Sena
Nancy Camilly Marques de Sena
DBDaniele Cruz Bastos
Daniele Cruz Bastos
Thermoplastic starch (TPS) is a biodegradable polymer from renewable sources, but its limited mechanical and thermal properties restrict wider industrial use compared to petroleum-based plastics. In this study, TPS-based biocomposites were developed and optimized by incorporating agricultural and mineral Residues: coffee husks (CH), potassium feldspar (PF), and Bahia Beige marble (BB) as reinforcements. Mechanical, thermal, and morphological characterizations were carried out, and a simplex–lattice mixture design was applied to optimize the formulations. The 70/20/5/5 (TPS/CH/PF/BB, wt.%) composition achieved the highest tensile strength (2.0 MPa) and elastic modulus (70.2 MPa), while the 90/0/5/5 formulation showed superior impact resistance. FTIR and SEM analyses confirmed effective filler dispersion and strong matrix–filler interactions. Scheffé polynomial models (R2 > 87%) accurately predicted performance, highlighting the reliability of the statistical approach. From a sustainability perspective, this work demonstrates that upcycling coffee husks and mineral residues into TPS-based biocomposites contributes to waste reduction, landfill diversion, and the development of cost-effective biodegradable materials. The proposed systems offer potential for eco-friendly packaging and agricultural applications, reducing dependence on fossil-based plastics and mitigating the environmental footprint of polymer industries. Statistical optimization further enhances efficiency by minimizing experimental waste. Moreover, this research supports circular economy strategies and provides scalable, sustainable solutions for waste valorization.