Sina Jamalzadegan

Sina Jamalzadegan
North Carolina State University | NCSU · Department of Chemical and Biomolecular Engineering

Ph.D.

About

10
Publications
4,823
Reads
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90
Citations
Introduction
Biosensors | Machine Learning | Chemical Engineering | Biotechnology | Human Diseases | Plant Diseases |
Education
August 2019 - May 2021
University of Houston
Field of study
  • Chemical Engineering

Publications

Publications (10)
Preprint
Full-text available
Volatile organic compounds (VOCs) are common constituents of fruits, vegetables, and crops, and are closely associated with their quality attributes, such as firmness, sugar level, ripeness, translucency, and pungency levels. While VOCs are vital for assessing vegetable quality, traditional detection methods, such as Gas Chromatography-Mass Spectro...
Article
Full-text available
This paper describes laser exposure to tune the infrared (IR) emissivity of a film of eutectic gallium indium (EGaIn) particles. EGaIn – a liquid metal at room temperature – forms a native oxide that keeps particles of the metal from spontaneously percolating. Photothermal energy from a CO2 laser percolates the particles into a conductive network....
Preprint
Full-text available
Liquid metals (LM) are emerging plasmonic nanomaterials with transformable surface plasmon resonances (SPR) due to their liquid-like deformability. This study delves into the plasmonic properties of LM nanoparticles, with a focus on EGaIn (eutectic gallium-indium)-based materials. Leveraging Finite-Difference Time-Domain (FDTD) simulations, we expl...
Article
Full-text available
Biosensors are analytical tools for monitoring various parameters related to living organisms, such as humans and plants. Liquid metals (LMs) have emerged as a promising new material for biosensing applications in recent years. LMs have attractive physical and chemical properties such as deformability, high thermal and electrical conductivity, low...
Conference Paper
Full-text available
Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting volatile organic compounds (VOCs), temperature, and...
Article
Full-text available
Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting volatile organic compounds (VOCs), temperature, and...
Article
Full-text available
This study proposed a novel and cost-effective approach to enhance and optimize the exo-polygalacturonase from P. indica, a root endophytic fungus. In the current investigation, the impact of ammonium sulfate, sugar beet pulp (SBP), and glucose as variables on induction of exo-polygalacturonase from P. indica was optimized using the central composi...
Article
Full-text available
Monitoring and measurement of carbon dioxide (CO2) is critical for many fields. The gold standard CO2 sensor, the Severinghaus electrode, has remained unchanged for decades. In recent years, many other CO2 sensor formats, such as detection based upon pH-sensitive dyes, have been demonstrated, opening the door for relatively simple optical detection...
Preprint
Full-text available
This study proposed a novel and cost-effective approach to enhance and optimize the polygalacturonase from P. indica. In current investigation, the impact of ammonium sulfate, sugar beet pulp (SBP) and glucose as variables on induction of polygalacturonase from P. indica was optimized using the central composite design (CCD) of response surface met...
Preprint
Full-text available
This study proposed a novel and cost-effective approach to enhance and optimize the polygalacturonase from P. indica. In current investigation, the impact of ammonium sulfate, sugar beet pulp (SBP) and glucose as variables on induction of polygalacturonase from P. indica was optimized using the central composite design (CCD) of response surface met...

Questions

Question (1)
Question
Generative AI (GenAI) is a branch of artificial intelligence that uses models to create new data such as text, images, or videos based on patterns learned from training data. It generates outputs in response to prompts by understanding the underlying structures of the input data.
Let's discuss the potential applications and benefits of Generative AI in biotechnology and explore how it can address current challenges in the field.

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