p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Science Get Journal
Eka Cahya Muliawati
Institut Teknologi Adhi Tama Surabaya, Indonesia

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Green Synthesis of Silver Nanoparticles from Morning Glory Leaf Extract (Ipomoea tricolor) and its Antibacterial Activity Against Pathogenic Bacteria Eka Cahya Muliawati; Riri Oktaviani; Rahma Nurdi
Science Journal Get Press Vol 3 No 2 (2026): April, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i2.619

Abstract

Silver nanoparticles (AgNPs) have attracted considerable attention due to their exceptional physicochemical properties and broad-spectrum antibacterial activity. This study reports the first application of Ipomoea tricolor (morning glory) leaf extract distinguished by its uniquely high alkaloid (ergine, isoergine) and flavonoid (quercetin, rutin, kaempferol) content as a bifunctional bioreductant and capping agent for eco-friendly AgNP synthesis. Compared to commonly used plant sources, I. tricolor provides a rare combination of electron-rich phytochemicals that yield exceptionally small (18.4 ± 3.2 nm), highly stable (zeta potential: −32.4 mV, PDI: 0.214), and potently antibacterial nanoparticles without requiring additional stabilizers. Comprehensive characterization via UV-Vis (SPR at 425 nm), FTIR, XRD (FCC structure, 16.7 nm crystallite), TEM, and DLS confirmed nanoparticle formation and phytochemical capping. Antibacterial evaluation against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Streptococcus mutans demonstrated inhibition zones of 9.6–22.3 mm and MIC values of 6.25–25 µg/mL superior to AgNPs from most previously reported plant sources. These results establish I. tricolor-mediated AgNPs as promising sustainable candidates for biomedical applications, particularly in addressing antimicrobial resistance.
Thermoelectric Performance of Doped Polyaniline from Textile Dye Waste Eka Cahya Muliawati; Herma Syafika
Science Journal Get Press Vol 3 No 2 (2026): April, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i2.620

Abstract

This study investigates the thermoelectric performance of polyaniline (PANI) doped with textile dye waste, specifically methyl orange (MO) and congo red (CR), as sustainable alternative dopants. Polyaniline was synthesized via oxidative polymerization using ammonium persulfate as the oxidant at varying dopant concentrations (0.1–1.0 M), with three independent replicates per condition to ensure statistical validity. Characterization was performed using FTIR spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and four-probe electrical conductivity measurements. Thermoelectric performance was evaluated through the Seebeck coefficient (S), power factor (PF = S²σ), and figure of merit (ZT). Results show that PANI-CR 0.5 M yielded the highest Seebeck coefficient of 42.7 µV/K, electrical conductivity of 127.3 S/cm, and power factor of 2.31 × 10⁻⁴ W/m·K². The ZT value obtained reached 0.434 at the optimal temperature of 340 K, a significant improvement of 340% compared to undoped PANI, substantially superior to PANI-HCl (ZT = 0.040) and competitive with organic thermoelectric materials reported in recent literature (e.g., PANI-CSA: 1.83 × 10⁻⁴ W/m·K² at 300 K). Unlike conventional approaches using synthetic dopants, this waste-to-material strategy demonstrates that textile dye waste can be valorized as functional dopants, offering dual environmental benefits: reducing water pollution (0.01–1 mg/L threshold) while producing low-cost organic thermoelectric materials. These findings highlight the potential for scaling to industrial thermoelectric devices and battery thermal management systems. Future work will explore composite materials with carbon nanostructures and optimization through polymerization condition engineering.