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Articles 1081 - 1110 of 2359

Full-Text Articles in Engineering

Domain-Specific Use Cases For Knowledge-Enabled Social Media Analysis, Soon Jye Kho, Swati Padhee, Goonmeet Bajaj, Krishnaprasad Thirunarayan, Amit Sheth Sep 2018

Domain-Specific Use Cases For Knowledge-Enabled Social Media Analysis, Soon Jye Kho, Swati Padhee, Goonmeet Bajaj, Krishnaprasad Thirunarayan, Amit Sheth

Publications

No abstract provided.

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Tourism Review Sentiment Classification Using A Bidirectional Recurrent Neural Network With An Attention Mechanism And Topic-Enriched Word Vectors, Qin Li, Shaobo Li, Jie Hu, Sen Zhang, Jianjun Hu Sep 2018

Tourism Review Sentiment Classification Using A Bidirectional Recurrent Neural Network With An Attention Mechanism And Topic-Enriched Word Vectors, Qin Li, Shaobo Li, Jie Hu, Sen Zhang, Jianjun Hu

Faculty Publications

Sentiment analysis of online tourist reviews is playing an increasingly important role in tourism. Accurately capturing the attitudes of tourists regarding different aspects of the scenic sites or the overall polarity of their online reviews is key to tourism analysis and application. However, the performances of current document sentiment analysis methods are not satisfactory as they either neglect the topics of the document or do not consider that not all words contribute equally to the meaning of the text. In this work, we propose a bidirectional gated recurrent unit neural network model (BiGRULA) for sentiment analysis by combining a topic …

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End-To-End Convolutional Neural Network Model For Gear Fault Diagnosis Based On Sound Signals, Yong Yao, Honglei Wang, Shaobo Li, Zhongnhao Liu, Gui Gui, Yabo Dan, Jianjun Hu Sep 2018

End-To-End Convolutional Neural Network Model For Gear Fault Diagnosis Based On Sound Signals, Yong Yao, Honglei Wang, Shaobo Li, Zhongnhao Liu, Gui Gui, Yabo Dan, Jianjun Hu

Faculty Publications

Currently gear fault diagnosis is mainly based on vibration signals with a few studies on acoustic signal analysis. However, vibration signal acquisition is limited by its contact measuring while traditional acoustic-based gear fault diagnosis relies heavily on prior knowledge of signal processing techniques and diagnostic expertise. In this paper, a novel deep learning-based gear fault diagnosis method is proposed based on sound signal analysis. By establishing an end-to-end convolutional neural network (CNN), the time and frequency domain signals can be fed into the model as raw signals without feature engineering. Moreover, multi-channel information from different microphones can also be fused …

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Statistically Guided Synthesis Of Mov- Based Mixed Oxide Catalysts For Ethane Partial Oxidation, Juan D. Jimenez, Kathleen Mingle, Teeraya Bureerug, Cun Wen, Jochen Lauterbach Sep 2018

Statistically Guided Synthesis Of Mov- Based Mixed Oxide Catalysts For Ethane Partial Oxidation, Juan D. Jimenez, Kathleen Mingle, Teeraya Bureerug, Cun Wen, Jochen Lauterbach

Faculty Publications

The catalytic performance of Mo8V2Nb1-based mixed-oxide catalysts for ethane partial oxidation is highly sensitive to the doping of elements with redox and acid functionality. Specifically, control over product distributions to ethylene and acetic acid can be afforded via the specific pairing of redox elements (Pd, Ni, Ti) and acid elements (K, Cs, Te) and the levels at which these elements are doped. The redox element, acid element, redox/acid ratio, and dopant/host ratio were investigated using a three-level, four-factor factorial screening design to establish relationships between catalyst composition, structure, and product distribution for ethane partial oxidation. Results show that the balance …

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Statistically Guided Synthesis Of Mov-Based Mixed-Oxide Catalysts For Ethane Partial Oxidation, Juan D. Jimenez, Kathleen Mingle, Teeraya Bureerug, Cun Wen, Jochen A. Lauterbach Sep 2018

Statistically Guided Synthesis Of Mov-Based Mixed-Oxide Catalysts For Ethane Partial Oxidation, Juan D. Jimenez, Kathleen Mingle, Teeraya Bureerug, Cun Wen, Jochen A. Lauterbach

Faculty Publications

The catalytic performance of Mo8V2Nb1-based mixed-oxide catalysts for ethane partial oxidation is highly sensitive to the doping of elements with redox and acid functionality. Specifically, control over product distributions to ethylene and acetic acid can be afforded via the specific pairing of redox elements (Pd, Ni, Ti) and acid elements (K, Cs, Te) and the levels at which these elements are doped. The redox element, acid element, redox/acid ratio, and dopant/host ratio were investigated using a three-level, four-factor factorial screening design to establish relationships between catalyst composition, structure, and product distribution for ethane partial oxidation. Results show that the balance …

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Experimental Investigation Of Impact Localization In Composite Plate Using Newly Developed Imaging Method, Mohammad Faisal Haider, Asaad Migot, Md Yeasin Bhuiyan, Victor Giurgiutiu Aug 2018

Experimental Investigation Of Impact Localization In Composite Plate Using Newly Developed Imaging Method, Mohammad Faisal Haider, Asaad Migot, Md Yeasin Bhuiyan, Victor Giurgiutiu

Faculty Publications

This paper focuses on impact localization of composite structures, which possess more complexity in the guided wave propagation due to the anisotropic behavior of composite materials. In this work, a composite plate was manufactured by using a compression molding process with proper pressure and temperature cycle. Eight layers of woven composite prepreg were used to manufacture the composite plate. A structural health monitoring (SHM) technique was implemented with piezoelectric wafer active sensors (PWAS) to detect and localize the impact on the plate. There were two types of impact event that were considered in this paper (a) low energy impact event …

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Product Innovation Design Based On Deep Learning And Kansei Engineering, Huafeng Quan, Shaobo Li, Jianjun Hu Aug 2018

Product Innovation Design Based On Deep Learning And Kansei Engineering, Huafeng Quan, Shaobo Li, Jianjun Hu

Faculty Publications

Creative product design is becoming critical to the success of many enterprises. However, the conventional product innovation process is hindered by two major challenges: the difficulty to capture users’ preferences and the lack of intuitive approaches to visually inspire the designer, which is especially true in fashion design and form design of many other types of products. In this paper, we propose to combine Kansei engineering and the deep learning for product innovation (KENPI) framework, which can transfer color, pattern, etc. of a style image in real time to a product’s shape automatically. To capture user preferences, we combine Kansei …

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Multi-Pred: A Software Module For Predictive Modeling Of Coupled Multi-Physics Systems, Dan Gabriel Cacuci, Ruixian Fang, Madalina C. Badea Aug 2018

Multi-Pred: A Software Module For Predictive Modeling Of Coupled Multi-Physics Systems, Dan Gabriel Cacuci, Ruixian Fang, Madalina C. Badea

Faculty Publications

The software module MULTI-PRED implements the methodology for predictive modeling of coupled multi-physics systems (PM-CMPS) formulated by Cacuci [Ann. Nucl. Energy, Vol. 70, p, 266 (2014)]. This methodology fully takes into account the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PM-CMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the experimental and computational parameters and results of interest responses called for the multi-physics models …

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A Practical Incremental Learning Framework For Sparse Entity Extraction, Hussein Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, Amit Sheth Aug 2018

A Practical Incremental Learning Framework For Sparse Entity Extraction, Hussein Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, Amit Sheth

Publications

This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of sparse data and provide an online evaluation method as feedback. This incremental and interactive learning framework allows for rapid annotation and subsequent extraction of sparse data while maintaining high accuracy. We evaluate our framework on three publicly available datasets and show that it drastically reduces the cost of sparse entity …

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Machine Learning For Internet Of Things Data Analysis: A Survey, Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, Amit Sheth Aug 2018

Machine Learning For Internet Of Things Data Analysis: A Survey, Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, Amit Sheth

Publications

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the …

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An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu Jul 2018

An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu

Faculty Publications

Convolutional neural networks (CNNs) with log-mel audio representation and CNN-based end-to-end learning have both been used for environmental event sound recognition (ESC). However, log-mel features can be complemented by features learned from the raw audio waveform with an effective fusion method. In this paper, we first propose a novel stacked CNN model with multiple convolutional layers of decreasing filter sizes to improve the performance of CNN models with either log-mel feature input or raw waveform input. These two models are then combined using the Dempster–Shafer (DS) evidence theory to build the ensemble DS-CNN model for ESC. Our experiments over three …

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The Performance Of Syngas-Fueled Sofcs Predicted By A Reduced Order Model (Rom): Temperature And Fuel Composition Effects, Xinfang Jin, Anthony Ku, Atul Verma, Brandon Ohara, Kevin Huang, Surinder Singh Jul 2018

The Performance Of Syngas-Fueled Sofcs Predicted By A Reduced Order Model (Rom): Temperature And Fuel Composition Effects, Xinfang Jin, Anthony Ku, Atul Verma, Brandon Ohara, Kevin Huang, Surinder Singh

Faculty Publications

An electrochemical reduced order model (ROM) has been developed in this study to simulate the performance of syngas-fueled anode-supported SOFCs with coupled bulk chemical reactions and multi-species gas diffusion in the electrodes. Experimental V-I curves with syngas fuel were used to validate the model to ensure its high fidelity. The model was used to investigate the effects of fuel composition and temperature on the electrochemical performance of the cell, chemical reaction rate and concentration distributions of gaseous species across the anode. The results show that H2 electro-oxidation dominates the overall cell performance, and that CO contributes to the performance …

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Removal Of Total Dissolved Solids From Reverse Osmosis Concentrates From A Municipal Wastewater Reclamation Plant By Aerobic Granular Sludge, Do-Hyung Kim, Sangjin Park, Yeomin Yoon, Chang Min Park Jul 2018

Removal Of Total Dissolved Solids From Reverse Osmosis Concentrates From A Municipal Wastewater Reclamation Plant By Aerobic Granular Sludge, Do-Hyung Kim, Sangjin Park, Yeomin Yoon, Chang Min Park

Faculty Publications

Reverse osmosis (RO) has been widely utilized in water reclamation plants and produces a concentrated brine (or reject) stream as a by-product. RO concentrates (ROC) contain vast quantities of salts and dissolved organic matter, such as biomass and humic-like substances, which hinder biological wastewater treatment (such as biological nitrogen removal). In this study, we cultivated granular sludge in an aerobic sequencing batch reactor to treat municipal wastewater with an organic loading rate of 2.1–4.3 kgCOD/m3 day at room temperature (25 °C), and remove total dissolved solids (TDS) from ROC by biosorption, with aerobic granular sludge as a novel biosorbent. …

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Hydrogels For Cell Delivery, Esmaiel Jabbari Jul 2018

Hydrogels For Cell Delivery, Esmaiel Jabbari

Faculty Publications

No abstract provided.

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Inference Framework For Model Update And Development, Xiao Lin Jul 2018

Inference Framework For Model Update And Development, Xiao Lin

Theses and Dissertations

Computational models play an important role in scientific discovery and engineering design. However, developing computational models is challenging, since the process always follows a path contaminated with errors and uncertainties. The uncertainties and errors inherent in computational models are the result of many factors, including experimental uncertainties, model structure inadequacies, uncertainties in model parameters and initial conditions, as well as errors due to numerical discretizations. To realize the full potential in applications it is critical to systematically and economically reduce the uncertainties inherent in all computational models.

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Circadiomics: Circadian Omic Web Portal, Nicholas Ceglia, Yu Liu, Siwei Chen, Forest Agostinelli, Kristin Eckel-Mahan, Paolo Sassone-Corsi, Pierre Baldi Jun 2018

Circadiomics: Circadian Omic Web Portal, Nicholas Ceglia, Yu Liu, Siwei Chen, Forest Agostinelli, Kristin Eckel-Mahan, Paolo Sassone-Corsi, Pierre Baldi

Faculty Publications

Circadian rhythms play a fundamental role at all levels of biological organization. Understanding the mechanisms and implications of circadian oscillations continues to be the focus of intense research. However, there has been no comprehensive and integrated way for accessing and mining all circadian omic datasets. The latest release of CircadiOmics (http://circadiomics.ics.uci.edu) fills this gap for providing the most comprehensive web server for studying circadian data. The newly updated version contains high-throughput 227 omic datasets corresponding to over 74 million measurements sampled over 24 h cycles. Users can visualize and compare oscillatory trajectories across species, tissues and conditions. Periodicity statistics (e.g. …

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Multi-Task Learning Framework For Mining Crowd Intelligence Towards Clinical Treatment, Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth Jun 2018

Multi-Task Learning Framework For Mining Crowd Intelligence Towards Clinical Treatment, Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth

Publications

In recent past, social media has emerged as an active platform in the context of healthcare and medicine. In this paper, we present a study where medical user’s opinions on health-related issues are analyzed to capture the medical sentiment at a blog level. The medical sentiments can be studied in various facets such as medical condition, treatment, and medication that characterize the overall health status of the user. Considering these facets, we treat analysis of this information as a multi-task classification problem. In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the …

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Identifying Prevalent Mathematical Pathways To Engineering In South Carolina, Eliza Gallagher, Christy Brown, D. Andrew Brown, Kristin Kelly Frady, Patrick Bass, Michael A. Matthews, Thomas T. Peters, Robert J. Rabb, Ikhalfani Solan, Ronald W. Welch, Anand K. Gramopadhye Jun 2018

Identifying Prevalent Mathematical Pathways To Engineering In South Carolina, Eliza Gallagher, Christy Brown, D. Andrew Brown, Kristin Kelly Frady, Patrick Bass, Michael A. Matthews, Thomas T. Peters, Robert J. Rabb, Ikhalfani Solan, Ronald W. Welch, Anand K. Gramopadhye

Faculty Publications

National data indicate that initial mathematics course placement in college is a strong predictor of persistence to degree in engineering, with students placed in calculus persisting at nearly twice the rate of those placed below calculus. Within the state of South Carolina, approximately 95% of engineering-intending students who initially place below calculus are from in-state. In order to make systemic change, we are first analyzing system-wide data to identify prevalent educational pathways within the state, and the mathematical milestones along those pathways taken by students in engineering and engineering-related fields. This paper reports preliminary analysis of that data to understand …

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Synthesis-Structure-Activity Relationships In Co3o4 Catalyzed Co Oxidation, Kathleen Mingle, Jochen A. Lauterbach May 2018

Synthesis-Structure-Activity Relationships In Co3o4 Catalyzed Co Oxidation, Kathleen Mingle, Jochen A. Lauterbach

Faculty Publications

In this work, a statistical design and analysis platform was used to develop cobalt oxide based oxidation catalysts prepared via one pot metal salt reduction. An emphasis was placed upon understanding the effects of synthesis conditions, such as heating regimen and Co2+ concentration on the metal salt reduction mechanism, the resultant nanomaterial properties (i.e., size, crystal structure, and crystal faceting), and the catalytic activity in CO oxidation. This was accomplished by carrying out XRD, TEM, and FTIR studies on synthesis intermediates and products. Additionally, high-throughput experimentation was employed to study the performance of Co3O4 oxidation catalysts over a wide range …

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Pedestrian Injury Severity Analysis In Motor Vehicle Crashes In Ohio, Majbah Uddin, Fahim Ahmed May 2018

Pedestrian Injury Severity Analysis In Motor Vehicle Crashes In Ohio, Majbah Uddin, Fahim Ahmed

Faculty Publications

According to the National Highway Traffic Safety Administration, 116 pedestrians were killed in motor vehicle crashes in Ohio in 2015. However, no study to date has analyzed crashes in Ohio in order to explore the factors contributing to the pedestrian injury severity resulting from motor vehicle crashes. This study fills this gap by investigating the crashes involving pedestrians exclusively in Ohio. This study uses the crash data from the Highway Safety Information System, from 2009 to 2013. The explanatory factors include the pedestrian, driver, vehicle, crash, and roadway characteristics. Both fixed- and random-parameters ordered probit models of injury severity (where …

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Second-Order Sensitivity Analysis Of Uncollided Particle Contributions To Radiation Detector Responses, Dan Gabriel Cacuci, Jeffrey A. Favorite May 2018

Second-Order Sensitivity Analysis Of Uncollided Particle Contributions To Radiation Detector Responses, Dan Gabriel Cacuci, Jeffrey A. Favorite

Faculty Publications

This work presents an application of Cacuci's Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to the simplified Boltzmann equation that models the transport of uncollided particles through a medium to compute efficiently and exactly all of the first- and second-order derivatives (sensitivities) of a detector's response with respect to the system's isotopic number densities, microscopic cross sections, source emission rates, and detector response function. The off-the-shelf PARTISN multigroup discrete ordinates code is employed to solve the equations underlying the 2nd-ASAM. The accuracy of the results produced using PARTISN is verified by using the results of three test configurations: (1) a homogeneous …

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Uncertainty Evaluation In The Design Of Structural Health Monitoring Systems For Damage Detection, Christine Schubert Kabban, Richard Uber, Kevin Lin, Bin Li, Md Yeasin Bhuiyan, Victor Giurgiutiu Apr 2018

Uncertainty Evaluation In The Design Of Structural Health Monitoring Systems For Damage Detection, Christine Schubert Kabban, Richard Uber, Kevin Lin, Bin Li, Md Yeasin Bhuiyan, Victor Giurgiutiu

Faculty Publications

The validation of structural health monitoring (SHM) systems for aircraft is complicated by the extent and number of factors that the SHM system must demonstrate for robust performance. Therefore, a time- and cost-efficient method for examining all of the sensitive factors must be conducted. In this paper, we demonstrate the utility of using the simulation modeling environment to determine the SHM sensitive factors that must be considered for subsequent experiments, in order to enable the SHM validation. We demonstrate this concept by examining the effect of SHM system configuration and flaw characteristics on the response of a signal from a …

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Economic Analysis Of Reactive Distillation In The Production Of Tert-Amyl Methyl Ether (Tame), Clayton Brandenburg Apr 2018

Economic Analysis Of Reactive Distillation In The Production Of Tert-Amyl Methyl Ether (Tame), Clayton Brandenburg

Senior Theses

Aspen HYSYS was used to make two flowsheets, one with plug flow reactors and distillation columns and another with a reactive distillation column, to see which flowsheet was better at producing tert-amyl methyl ether (TAME) and which one was more economically feasible. The goal was to produce 15,000 metric tons of TAME per year by reacting a naptha stream with methanol. It was found that both flowsheets were capable of producing the desired amounts of TAME and with product purities around 100%. The conversions of the reactive distillation was 93.93%, significantly higher than the 72.48% and 76.98% in the base …

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Maximizing Whole Watershed Storage Through Optimized Reservoir Reoperation And Managed Aquifer Recharge, Erfan Goharian, Robert Gailey, Stephen Maples, Samuel Sandoval-Solis, Graham Fogg Apr 2018

Maximizing Whole Watershed Storage Through Optimized Reservoir Reoperation And Managed Aquifer Recharge, Erfan Goharian, Robert Gailey, Stephen Maples, Samuel Sandoval-Solis, Graham Fogg

Faculty Publications

No abstract provided.

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Development Of Rule-Based Recognition Systems For Continuous Monitorization Of Pulse Oximetry, Brian Delehanty Apr 2018

Development Of Rule-Based Recognition Systems For Continuous Monitorization Of Pulse Oximetry, Brian Delehanty

Senior Theses

Pulse Oximeters provide a convenient, non-invasive method to quickly gather information about a patient's pulse rate (PR) and arterial blood oxygen saturation (SpO2). Many pulse oximeters lack alert systems that notify caregivers if a patient's readings go outside the healthy range, and pulse oximeters that have these mechanisms are significantly more expensive. This project set out to write a program using LabVIEW that collects pulse oximeter data via Bluetooth and generates an alert when readings persist in the abnormal range for more than fifteen seconds. Due to privacy laws that allow pulse oximeter manufacturers to not disclose the …

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Osteon Mimetic Scaffolding, Janay Clytus Apr 2018

Osteon Mimetic Scaffolding, Janay Clytus

Senior Theses

The purpose of this research is to provide an alternative to naturally derived bone grafts. There is a gap in the supply of donors and the demand of bone tissue. Artificial scaffold creation can work as an implant and decrease the shortage of bone grafts and increase the range of injuries that can be repaired. Current research focuses on optimizing mechanical properties such as porosity, improving vascularization using cells, and generating osteoconductivity. For osteodifferentiation, mesenchymal stem cells (MSCs) can differentiate into mesodermal lineages such as chondrocytes, osteoblasts, adipocytes, and tenocytes by supplementing cultures with lineage-specific soluble factors (Marchetti). Co-culturing ECFCs …

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Increasing Drug Delivery Efficacy Of Drug-Coated Balloons, Alexander Galan, Eric Bidinger, Franco Godoy, Shrusti Patel Apr 2018

Increasing Drug Delivery Efficacy Of Drug-Coated Balloons, Alexander Galan, Eric Bidinger, Franco Godoy, Shrusti Patel

Senior Theses

Peripheral artery disease (PAD), the narrowing of peripheral arteries located in areas such as the arms and legs, is a common disease that affects 12% to 20% of people over 65. Numerous therapies have been developed to treat PAD, the most recent technology being drug-coated balloons. Drug-coated balloons release drugs, such as Paclitaxel (PTX), into the arterial wall during balloon angioplasty to locally treat PAD. Current levels of drug transfer from the balloon to the vascular endothelium are at a low 10%-18%. Our Biomedical Engineering Senior Design project aims to increase drug delivery of drug-coated balloons by manipulating the clinically-controllable …

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Optimization Of Microfluidic Chip Fabrication Via Femtosecond Laser Ablation, Kenneth Aycock Apr 2018

Optimization Of Microfluidic Chip Fabrication Via Femtosecond Laser Ablation, Kenneth Aycock

Senior Theses

Microfluidic devices have become staple tools in biomedical research and have a promising future as low cost, point-of-care (POC) diagnostic devices. Despite the advancements in microfluidic device technology, the manipulation and fabrication of these systems can be tedious and expensive. Repeatable techniques in which computer-aided designs are translated into microfluidic systems in a matter of minutes are highly desirable both for researchers and manufacturers. Laser ablation of tape substrates has shown promise in producing cost-effective, rapidly manipulable devices, but the work done thus far has utilized continuous wave lasers that perform suboptimally due to the relatively short wavelengths used and …

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Integration Of A Sensory Driven Model For Hand Grasp Function In 3d Printed Prostheses, Austin T. Hetherington Apr 2018

Integration Of A Sensory Driven Model For Hand Grasp Function In 3d Printed Prostheses, Austin T. Hetherington

Senior Theses

My Honors Thesis was completed through the Biomedical Engineering senior design project I worked on. Our project took a mechanically operated 3D printed prosthetic hand and automated the process by which it makes a grasp. The purpose of this project was to provide an affordable, automatic prosthetic hand to those either capable and incapable of wrist flexion. The current 3D printed prosthetic models require users to bend their wrist to initiate a simple grasp. However, our design took an alternative approach by using an EMG sensor placed on the ventral side of the forearm to record muscle activity, which, upon …

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Highly Efficient Electrochemical Reforming Of Ch4/Co2 In A Solid Oxide Electrolyser, Jinhai Lu, Changli Zhu, Changchang Pan, Wenlie Lin, John P. Lemmon, Fanglin Chen, Chunsen Li, Kui Xie Mar 2018

Highly Efficient Electrochemical Reforming Of Ch4/Co2 In A Solid Oxide Electrolyser, Jinhai Lu, Changli Zhu, Changchang Pan, Wenlie Lin, John P. Lemmon, Fanglin Chen, Chunsen Li, Kui Xie

Faculty Publications

Reforming CH4 into syngas using CO2 remains a fundamental challenge due to carbon deposition and nanocatalyst instability. We, for the first time, demonstrate highly efficient electrochemical reforming of CH4/CO2 to produce syngas in a solid oxide electrolyser with CO2 electrolysis in the cathode and CH4 oxidation in the anode. In situ exsolution of an anchored metal/oxide interface on perovskite electrode delivers remarkably enhanced coking resistance and catalyst stability. In situ Fourier transform infrared characterizations combined with first principle calculations disclose the interface activation of CO2 at a transition state between a CO …

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