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Research of Scientia Naturalis
Published by Yayasan Adra Karima Hubbi
ISSN : 30479932     EISSN : 30479940     DOI : 10.70177/scientia
Core Subject : Science, Agriculture,
Agriculture, Biological Sciences & Forestry Chemistry Physics
Research of Scientia Naturalis is an international forum for the publication of peer-reviewed integrative review articles, special thematic issues, reflections or comments on previous research or new research directions, interviews, replications, and intervention articles - all pertaining to the research fields of Mathematics and Natural Sciences. All publications provide breadth of coverage appropriate to a wide readership in Mathematics and Natural Sciences research depth to inform specialists in that area. We feel that the rapidly growing Research of Scientia Naturalis community is looking for a journal with this profile that we can achieve together. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 4 (2025)" : 5 Documents clear
Ferroelectric Thin Films for Neuromorphic Computing: Synthesis, Characterization, and Device Integration Huda, Nurul; Zaki, Amin; Chai, Nong; Shofiah, Siti
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2385

Abstract

The limitations of conventional von Neumann computing architectures in handling complex, data-intensive tasks have spurred significant interest in brain-inspired neuromorphic computing. A critical challenge in this field is the development of hardware that can efficiently emulate the synaptic plasticity of biological neurons. This study focuses on the synthesis, characterization, and integration of ferroelectric thin films, specifically hafnium zirconium oxide (HZO), as a promising material platform for creating artificial synaptic devices. The primary objective was to fabricate high-quality HZO thin films and demonstrate their capacity to mimic key synaptic functions. HZO films were synthesized using pulsed laser deposition, followed by comprehensive characterization of their structural, ferroelectric, and electrical properties using XRD, PFM, and I-V measurements. The optimized films were then integrated into two-terminal memristive device structures. The resulting devices successfully exhibited essential synaptic behaviors, including potentiation, depression, and spike-timing-dependent plasticity (STDP), with low energy consumption per synaptic event. The gradual and controllable modulation of ferroelectric domain switching was identified as the core mechanism enabling this analog-like resistance modulation.  
Al-Augmented Spectroscopy for Early Detection of Cervical Cancer Biomarkers Zani, Benny Novico; Rith, Vicheka; Dara, Ravi
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2387

Abstract

Cervical cancer remains a leading cause of mortality among women worldwide, primarily due to challenges in early and accurate detection. Conventional screening methods like Pap smears are subject to human error and have moderate sensitivity. This study aimed to develop and validate a novel, non-invasive diagnostic platform combining Raman spectroscopy with artificial intelligence (AI) for the rapid and highly accurate detection of early-stage cervical cancer biomarkers. The objective was to create a system that could overcome the limitations of current screening techniques. We collected cervical cell samples from clinically diagnosed healthy, pre-cancerous (CIN I-III), and cancerous patients. Raman spectroscopy was used to acquire high-resolution biochemical fingerprints from these samples. A custom-developed convolutional neural network (CNN) was then trained on the spectral data to learn and identify subtle biomarker-associated patterns indicative of neoplastic transformation. The AI-augmented system achieved a diagnostic accuracy of 96.5%, with a sensitivity of 98% and a specificity of 95% in differentiating high-grade lesions and cancerous samples from healthy ones. The model successfully identified key spectral shifts related to nucleic acid and protein conformational changes, correlating them with disease progression.
Comparative Analysis of Smart Catalysts for CO? Reduction: From Molecular Design to Lab-Scale Performance Nampira, Ardi Azhar; Mendes, Clara; Costa, Tiago
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2388

Abstract

The electrochemical reduction of carbon dioxide (CO?) is a critical strategy for mitigating climate change and producing value-added chemicals, yet the development of highly selective catalysts remains a primary challenge. This study aimed to conduct a rigorous comparative analysis of three distinct classes of "smart" catalysts—a molecular cobalt complex, a metal-organic framework (MOF), and a single-atom copper catalyst (Cu-SAC)—to elucidate the relationship between molecular design and lab-scale performance. The catalysts were synthesized, characterized via XRD and XAS, and evaluated for electrocatalytic CO? reduction in a flow cell reactor. The results showed that the Cu-SAC exhibited superior performance, achieving a Faradaic efficiency for ethylene (C?H?) exceeding 70% at a low cell voltage, significantly outperforming the MOF and molecular catalysts, which primarily produced CO and formate. This high selectivity was directly correlated with the optimized coordination environment of the isolated Cu sites. This comparative analysis confirms that rational design at the atomic level is a highly effective strategy for steering reaction pathways towards valuable multi-carbon products, providing a crucial benchmark for future catalyst development.  
Quantum Dot-Embedded Polymer Films for Flexible Photonic Devices: Fabrication and Characterization Nampira, Ardi Azhar; Zahir, Roya; Khan, Omar; Shofiah, Siti
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2389

Abstract

materials for photonic devices that can conform to non-planar surfaces. Quantum dots (QDs) are ideal candidates due to their size-tunable emission and high quantum yields, but their integration into durable, flexible platforms remains a key challenge. This study aimed to develop and characterize highly luminescent and mechanically flexible quantum dot-embedded polymer films as a robust platform for next-generation photonic applications. We fabricated composite films by embedding cadmium selenide/zinc sulfide (CdSe/ZnS) core-shell QDs into a polydimethylsiloxane (PDMS) polymer matrix via solution casting. The structural, optical, and mechanical properties were systematically investigated using transmission electron microscopy (TEM), UV-Vis absorption, photoluminescence (PL) spectroscopy, and cyclic bending tests. The results showed that TEM analysis confirmed a uniform dispersion of QDs within the PDMS matrix without aggregation. The composite films exhibited intense, stable photoluminescence, retaining the characteristic sharp emission of the colloidal QDs. Crucially, the films demonstrated exceptional mechanical flexibility, maintaining over 95% of their initial PL intensity after 1,000 bending cycles to a 5 mm radius. The optical properties remained stable under various strain conditions, proving the effective protection afforded by the polymer matrix. This work successfully demonstrates a scalable method for producing high-quality, flexible photonic materials.  
Computational and Experimental Insights into Hydrogen Storage in Metal-Organic Frameworks (MOFs) Nampira, Ardi Azhar; Lee, Ava; Tan, Marcus
Research of Scientia Naturalis Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i4.2390

Abstract

The transition to a hydrogen economy is critically dependent on the development of safe and efficient onboard hydrogen storage materials. Metal-Organic Frameworks (MOFs) have emerged as highly promising candidates due to their exceptionally high surface areas and tunable pore environments. This study aimed to combine computational modeling with experimental validation to elucidate the key structural factors governing hydrogen storage capacity in MOFs. A dual approach was employed, using Grand Canonical Monte Carlo (GCMC) simulations to predict hydrogen uptake in a series of MOFs with varying pore sizes and metal centers, followed by experimental synthesis and gas sorption analysis to validate the computational findings. The results revealed a strong correlation between the simulated and experimental data, confirming that both high surface area and optimal pore size (~10-15 Å) are crucial for maximizing physisorption. The GCMC simulations accurately predicted that MOFs with open metal sites exhibit enhanced hydrogen binding energies. This research concludes that a combined computational and experimental approach provides powerful predictive insights, confirming that tailoring pore geometry and introducing strong adsorption sites are key strategies for the rational design of next-generation MOFs for high-density hydrogen storage.    

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