The Center for Innovation, Commercialization & Entrepreneurship (CICE) promotes innovation across the university through the CICE Innovation Grants. The program supports applied research in emerging technologies such as AI, Deep Learning, Nanotech, Biotech, Blockchain, Drones, 3DP, and others to:
CICE Innovation Grants support the ÃÛÌÒÊÓƵ University Strategic Plan to leverage core strengths and elevate educational programs and scholarship. The program supports efforts to: (1) enhance productivity in industry relevant research, scholarship, and creative activity; and (2) develop programs in high profile niche research areas, including specialized and
Many of these projects are inter-disciplinary in nature, with faculty and students from multiple disciplines working together to learn “outside the textbook”. Hands-on Technology Commercialization training workshops are provided to students and faculty on the essentials of commercialization – IP, market needs, requirements analysis, MPV, product development, and other aspects of commercialization that are often not covered in regular college courses but are deeply valued in technology companies.
Funds are raised by the CICE through donors who have a passion for innovation and commercialization, and who want ÃÛÌÒÊÓƵ University to impact the region and the national stage. To date, the CICE Innovation awards have resulted in at least 16 published papers, several patent applications, and multiple novel teaching techniques brought into the classroom.
The 2021 CICE Innovation Grant recipients include the Colleges of Engineering, Arts & Science, and Fine Arts & Communication. In total, 12 students will be supported in emerging technologies such as Artificial Intelligence, Nanotech, Biotech, Blockchain development, drones, novel diagnostic approaches, and space exploration and recovery with the European Space Agency. If you are interested in learning more about these projects, please contact tmane@lamar.edu.
Department: Chemical Engineering PI: Dr. James Henry
Diabetes is the 7th leading cause of death in the US as of 2018, affecting an estimated 34.2 million Americans with another 90 million indicated as prediabetic (27.6% of the population). With the high levels of obesity expected to continue for decades, diabetes will continue to be a major public health problem for the foreseeable future. To ensure minimal economic and societal impact, affective monitoring and treatment of diabetics is necessary. Unfortunately, a significant barrier to achieving effective monitoring in diabetics is patient resistance to effective glucose monitoring. The biggest complaint is the pain involved in drawing blood for testing and the complication in getting good readings consistently. As such, we will work on perform a proof-of-concept analysis for a long-term stable fluorescence-based subcutaneous implant that would be readable through tissue.
Department: Environmental & Chemical Engineering PI: Dr. Thinesh Selvaratnam, Dr. Clayton Jeffryes
Increasing population and rapid urbanization have been made huge impacts on the waste management industry over the past few decades. There is an ever-growing demand to develop scalable, sustainable treatment technologies to replace the current wastewater treatment industry's outdated energy-intensive technologies. Landfill leachate management is one of those industries currently looking for on-site treatment techniques with a primary focus on energy and nutrient recovery and recycling. Municipal landfill leachate is laden with organic carbon, nutrients, and complex organic/inorganic species needed treatment before releasing into the environment. The most common treatment option for leachate is co-treating them with Publicly owned treatment works in off-site locations, which are often viewed as unsustainable due to extensive cost and ever-changing regulatory and permitting issues. This specific study will leverage the results from our current baseline studies and develop a pilot-scale algal-based bioremediation system to treat the leachate on-site. Also, this study will evaluate the potential scalability of this system and perform an economic analysis to demonstrate the system’s feasibility in large-scale on-site applications. Successful implementation of the proposed system will reduce the leachate treatment costs and provide an avenue for supplemental revenue from the produced biomass and recovered nutrients.
Department: Industrial Engineering PI: Dr. Yueqing Li, Dr. Xinyu Liu
Pipelines are considered as one of the most practical transportation means for crude oil. Therefore, the safe operation of pipeline is extremely important. Pipeline failures such as blockage and leakage may result in environmental pollution, economic losses, and even serious threats to human safety and property. Consequently, monitoring pipelines is an important task. Detection of exact fault quantity and its location is necessary for smooth operation of factories and industries and environmental safety. It is essential to develop a timely and reliable method to detect and locate pipeline leakage. This project aims to develop a drone-based crude oil leak detection method in pipeline systems. A drone technology-based image processing algorithm will be developed and tested in a self-developed pipeline system in different scenarios based on the real environment. A complete strategy will be proposed for the application in local industries. The research shall give insights of using drone technology to improve the performance of crude oil leak detection and maintain the crude oil pipeline systems.
Department: Computer Science & Civil Engineering PI: Dr. Bo Sun, Dr. Jing Zhang, Dr. Qin Qian
The goal of this project is to design and implement a framework based on a Wireless Sensor Network (WSN), which hydrologists, water resource scientists, and water resource engineers could utilize to collect in situ real-time water quality measurements, including Temperature, Dissolved Oxygen, Water Depth, Flow Rate and pH Value. Neches River Watershed upstream of I-10 will be instrumented with sensor probes connected to wireless sensor networks (WSNs) to provide real-time water-quality information. A deep learning-based neural network will be utilized to train the collected data and create the model.
Department: Electrical Engineering PI: Dr. Reza Barzagaranbaboli
Monitoring and maintenance of complex and tiny components in electro-thermal system are problematic, especially when they are in extreme and outreach environment such as on outreach pipes and inaccessible chemical and power substations. There is a necessary need for a method to detect incipient fault of these components to avoid massive failure and accordingly outage and extremely expensive and time-consuming maintenance. The nonintrusive condition monitoring using the artificial intelligence system empowered with required sensors is proposed in this project. We will build state-of-the-art heat and electromagnetic sensors embedded in the drone that will transfer the necessary data from components under monitoring to the supervisory system. The proposed system detects electrical failures and leakage in pumps which leads to enhancing the reliability and resiliency of the systems in energy sector.
Department:Chemical Engineering PI: Dr. Clayton Jeffryes
Water-in-oil and oil-in-water emulsions are stable blends of water and oil frequently formed by the high shear mixing of process water and product petroleum during operations such as extraction, pumping or desalting. Breaking emulsions into their separate water and oil phases is costly, but necessary. Water must be removed from the oil phase prior to transport or refining and oil must be removed from the water phase for wastewater treatment or recycle. This demulsification process is typically achieved using thermal energy plus costly chemical demulsifiers. However, the PI’s lab has made significant progress toward developing a chemical-free, microwave demulsification process with economic promise. The current project will develop a 3D printed, combined microwave gas-flotation demulsification device to exploit both phenomena for a more efficient separation. This process is completely new and validation of the prototype could be of high commercial value.
Department: Chemical Engineering PI: Dr. Qiang Xu
The shutdown operation of a distillation column is one of the critical abnormal operations for a chemical/petrochemical plant. Currently, planned shutdown operations for distillation columns are all manually operated, which may result in significant differences among different operators or even costly human errors and uncertainties. Meanwhile, the column shutdown operation also involves big concerns of operating safety, on-spec product recovery, energy consumption, and emission generations. Thus, tremendous potential opportunities are existing in current chemical/petrochemical plants on the optimization of shutdown operations of distillation columns. In this project, a systematic methodology on dynamic simulation and optimization for automatic shutdown operation of a distillation column will be developed and examined, which is to accomplish the quick and automated shutdown operation with considerations of both operating safety and energy/material savings. The shutdown operation of the most important distillation column in olefin plants, the C2 splitter, will be employed as case studies, where different shutdown control strategies will be modeled, programmed, and automated via rigorous dynamic simulations for quantitative analysis. This study will lay out a promising foundation for the future optimization and automation of important operating units during abnormal operations in chemical/petrochemical plants.
Department: Industrial Engineering PI: Dr. Robert Bradley
The shutdown operation of a distillation column is one of the critical abnormal operations for a chemical/petrochemical plant. Currently, planned shutdown operations for distillation columns are all manually operated, which may result in significant differences among different operators or even costly human errors and uncertainties. Meanwhile, the column shutdown operation also involves big concerns of operating safety, on-spec product recovery, energy consumption, and emission generations. Thus, tremendous potential opportunities are existing in current chemical/petrochemical plants on the optimization of shutdown operations of distillation columns. In this project, a systematic methodology on dynamic simulation and optimization for automatic shutdown operation of a distillation column will be developed and examined, which is to accomplish the quick and automated shutdown operation with considerations of both operating safety and energy/material savings. The shutdown operation of the most important distillation column in olefin plants, the C2 splitter, will be employed as case studies, where different shutdown control strategies will be modeled, programmed, and automated via rigorous dynamic simulations for quantitative analysis. This study will lay out a promising foundation for the future optimization and automation of important operating units during abnormal operations in chemical/petrochemical plants.
Department: Speech and Hearing Sciences PI: Dr. Lilian Felipe
Virtual reality is an innovative form of technology that produces a computer-generated experience similar to the real world. Vestibular Galvanic Stimulation is equipment that is traditionally stimulating/altering balance through the vestibular system. The combined use of these instruments allows a unique form of therapy to target all necessary points for a successful balance system. The goal is to develop a protocol for balance training for space agencies to utilize for subjects placed in extreme conditions to prevent Space Motion Sickness (SMS) and guarantee space exploration fewer risks. SMS symptoms are similar to those in other motion sicknesses & include nausea, fatigue, etc., which can affect operational performance of astronauts. Before this can be applied to astronauts, trials with the guide must be implemented in a control group. This will be investigated on three different groups, then data analysis will be executed, and results will then be proposed to space agencies. The protocol will allow them to save millions of dollars during space missions and improve astronauts’ overall quality of life.
The 2019 CICE Innovation Grant were awarded to 9 riveting projects, with more emphasis on interdisciplinary collaborations leading to possible commercialization. The selected projects use innovative technology from drones to virtual reality to solve problems that we face as a society. If you are interested in learning more about these projects, please contact tmane@lamar.edu.
Department: Physics & Earth Science
PI: Dr. Phil Cole & Dr. Jim Jordan
Presently no reliable technology exists to remotely determine the real-time leak rate of hydrocarbons from pipelines. The objective of the overall project is to determine the sensitivity of a well-calibrated infrared imaging system to ten species of hydrocarbons with respect to five parameters: wind speed, mass fraction, mass flow rate, distance, and contrasting temperature. In continuation of last year ,this project expands the calibration methods and develops a method of quantifying the mass flow rate of hydrocarbons with optical gas imaging. This project is in collaboration with Infared Cameras Inc.
Department: Nursing & Computer Science
PI: Dr. LeAnn Chisholm & Dr. Xingya Liu
Currently, there are no accessible systems in the Southeast area for aggregating data from multiple devices in rural patients and communicating the data in a meaningful way to their rural healthcare providers. This collaborative project will develop a system to aggregate health data in a meaningful way in rural areas.
Department: Computer Science & Industrial Engineering
PI: Dr. Jing Zhang & Dr. Seokyon Hwang & Dr. Berna Tokgoz
The utility poles of the electric power distribution network carrying power from local substations to customers are extremely vulnerable to frequent and large-scale damages caused by severe weather conditions, such as wind gusts, storms, and hurricanes. Overgrown vegetation near transmission lines also cause electricity arc and pose another major threat to the power distribution network. The goal of this project is to develop an automated, low-cost, portable, and reliable system for monitoring the health condition of electrical utility poles and managing vegetation near power transmission lines.
Department: Chemical Engineering & Environmental Engineering
PI: Dr. Clayton Jeffryes & Dr. Liv Haselbach
The antimicrobial wipe (disinfectant wipes, sponges, etc.) market is rapidly growing and an expanding share of this commercial activity uses materials infused with silver or Copper nanoparticles (AgNPs/CuNPs), which have antimicrobial properties. AgNPs are simple to synthesize and are easily prepared into stable solutions amenable for application to, or infusion into, textiles and paper-tissues. This project will make and test a cheaper and more efficient Copper Nanoparticle infused antibacterial wipes according to industry standards and determine the most cost-effective dosage to each sellable unit.
Department: Chemical Engineering & Biology
PI: Dr. James Henry & Dr. Maryam Vasefi
Alzheimer’s disease (AD) is the seventh leading cause of death in the United Sates, affecting 5.5 million Americans with the number expected to double by 2050 due to the expected continued increase in average life expectancy and US population. The current treatment (behavioral and symptom management) does not address the need to treat the underlying condition, the formation and deposition of A-beta oligomers. Since A-beta formation is a fact of existence, it becomes necessary to identify dietary and nutraceutical solutions that can be lifelong preventive measures. This project will look to utilize cutting-edge technologies and well-established techniques to evaluate readily available food-based options (polyphenols) to identify viable targets for such long-term preventative measures.
Department: Physics
PI: Dr. Rafael De La Madrid
The primary goal of this research is to advance mist eliminator design by acquiring adhesion data that has proven to be elusive due to the limitations of existing methods. The project will utilize state-of-the-art acoustic and force-sensor technologies to measure the force necessary to remove liquid droplets from monofilament used in mist eliminators. This project will also measure the work of adhesion of the monofilament-liquid system.
Department: Industrial Engineering
PI: Dr. Yueqing Li & Dr. Xinyu Liu
The research aims to develop a collaborative UAV (drone) system to enhance the security in refineries in unconstrained environment, such as rain, snow, fog, night, etc. An image processing algorithm will be proposed. The system will be evaluated in real time in a medium-sized enterprise (50-249 employees). A complete strategy will be proposed for the application of the collaborative UAV system in local industries and communities.
Department: Mechanical Engineering
PI: Dr. Ping He & Dr. Chun-Wei Yao
The goal of this research is to reveal the general control conditions of micro-pattern, which separates the Cassie-Baxter and Wenzel states. When a liquid droplet interacts with a micro-patterned substrate (which can be a nature product, e.g., a lotus leaf, or an engineered surface), there exists two main wetting states: the Cassie-Baxter (CB) state and the Wenzel (WZ) state. In the CB state, the droplet sits on top of the micro-patterns, while in the WZ state, the droplet sinks into the micro-patterned valleys. valleys. Both states can yield hydrophobic conditions if the material itself is hydrophobic; however, because CB has a limited liquid-solid contact area much less than WZ, it reduces the liquid, solid friction, corrosion and fouling tendencies much better than WZ.
Department: Speech and Hearing Sciences
PI: Dr. Lilian Felipe
The goal of this project is to develop a Virtual Reality model with fully-immersive stimulation that could establish a rehabilitation protocol for balance disorders starting with subjects inserted in extreme conditions (e.g. the space). By studying the phenomenon of microgravity and radiation with the physiology of the human body will allow to create