Engineering Commons^™

Charge Storage In Wo³ Polymorphs And Their Application As Supercapacitor Electrode Material, Vaibhav Lokhande, Abhishek Lokhande, Gon Namkoong, Jin Hyeok Kim, Taeksoo Ji

Electrical & Computer Engineering Faculty Publications

Tungsten oxide is a versatile material with different applications. It has many polymorphs with varying performance in energy storage application. We report simple and facile way to synthesize four phases of tungsten oxide from same precursor materials only by changing the pH and temperature values. Monoclinic, hexagonal, orthorhombic and tetragonal phase obtained, were analyzed and tested for supercapacitor application. The electrochemical analysis of four phases indicates that the hexagonal phase is best-suited electrode material for supercapacitor. The hexagonal phase exhibits higher specific capacitance (377.5 Fg^-1 at 2 mVs^-1), higher surface capacitive contribution (75%), better stability and rate …

Carbon Multicharged Ion Generation From Laser-Spark Ion Source, Md. Mahmudur Rahman, Oguzhan Balki, Hani E. Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

Multicharged carbon ions are generated by using a laser-assisted spark-discharge ion source. A Q-switched Nd:YAG laser pulse (1064 nm, 7 ns, ≤ 4.5 × 10⁹ W/cm²) focused onto the surface of a glassy carbon target results in its ablation. The spark-discharge (∼1.2 J energy, ∼1 µs duration) is initiated along the direction of the plume propagation between the target surface and a grounded mesh that is parallel to the target surface. Ions emitted from the laser-spark plasma are detected by their time-of-flight using a Faraday cup. The ion energy-to-charge ratio is analyzed by a three-mesh retarding field …

A Review: Thermal Stability Of Methylammonium Lead Halide Based Perovskite Solar Cells, Tanzila Tasnim Ava, Abdullah Al Mamun, Sylvain Marsillac, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Perovskite solar cells have achieved photo-conversion efficiencies greater than 20%, making them a promising candidate as an emerging solar cell technology. While perovskite solar cells are expected to eventually compete with existing silicon-based solar cells on the market, their long-term stability has become a major bottleneck. In particular, perovskite films are found to be very sensitive to external factors such as air, UV light, light soaking, thermal stress and others. Among these stressors, light, oxygen and moisture-induced degradation can be slowed by integrating barrier or interface layers within the device architecture. However, the most representative perovskite absorber material, CH_{3 …}

The Effect Of Tube Geometry On The Chiral Plasma, S. Jin, D. Zou, X. Lu, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

A chiral plasma plume has recently been reported inside a circular quartz tube without the use of an external magnetic field. It is believed that the quartz tube plays an important role in the formation of the chiral plasma plume. In this paper, to better understand how this interesting structure is generated, the effect of the tube geometry on the chiral plasma is investigated. First, the effect of the thickness of the tube wall on the chiral plasma is investigated. It is interesting to find that a too thin or too thick tube wall is not favorable for generating the …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …