DrChristoforos Panteli
Visiting Researcher
Department of Electrical and Electronic Engineering - Faculty of Engineering
Orcid identifier0000-0002-6554-7192 (opens in a new tab)
- Visiting ResearcherDepartment of Electrical and Electronic Engineering - Faculty of Engineering
- Electrical Engineering, South Kensington Campus, United Kingdom
RESEARCH
Research Accomplishments
Fabrication process
Polymer-Assisted Graphene Transfer
I developed a universal Polymer-Assisted Graphene Transfer (PAGT) process for monolayer and multilayer sheets on any substrate including silicon, silicon dioxide, and Complementary Metal Oxide Semiconductor (CMOS) chips.
Environmentally Friendly Quasi-Ambient Temperature bonding process
I am leading the hardware development of an environmentally friendly and room-temperature process to bond and package electronic devices and systems. This project is in collaboration with Universities of Manchester and Loughborough and industrial partners in the UK including Indium Corporation©, TT Electronics©, Dynex Semiconductor© and more. In this work I am using lasers to process the nonmaterial Nanofoil® and characterise the bonded system performance. This work has produced one journal paper so far.
GAS SENSORs
Suspended graphene gas sensor
I pioneered the suspend graphene gas sensor that uses both top and bottom surfaces for sensing. Using the PAGT process, I suspended graphene over centimetres of area on silicon nanowire arrays fabricated by metal-assisted chemical etching (MACE). This device offers faster signal response, and more than double signal response compared to supported graphene gas sensors. With electronics the smart sensor included automatic zeroing, curve fitting and temperature control for higher efficiency. This device finds application in ammonia and acetone gas detection in breath that are correlated to kidney failure and diabetes, respectively. This work has delivered one journal publication and three conference proceedings.
RAPID GAS-PHASE DETECTION OF BACTERIAL CULTURES
Using commercial gas sensors, custom electronics and mathematical algorithms, we are able to detect the infection in bacterial cultures under 6 hours which is much faster than the current diagnosis protocol that needs 24-72 hours. This result arises from the speed of released gases and the efficient algorithms that analyse the measured signal in real-time. The applications for this method are mainly in the medical field for Urinary Tract Infections (UTI) diagnosis and more.
CMOS
CMOS ISFET pH sensing system plasma-etching
I pioneered a material selective plasma-etch process for post-processing of CMOS Ion-Sensitive Field-Effect Transistors (ISFETs) sensor system on chip. Using this process, I improved the time stability of the CMOS ISFET sensors while identifying the physical location of trapped charge within the device. This process can be used to optimise the sensing membrane and signal readout of any biochemical sensor integrated in CMOS. This work was in collaboration with Dr P. Georgiou in the Centre of Bio-Inspired Technology (CBIT) and has produced two journal publications and two conference proceedings.
Graphene on CMOS ISFET pH sensing systems
I pioneered the world’s first graphene on CMOS ISFET chip using the developed PAGT process. Taking advantage of graphene’s ultra thin, very high mechanical robustness and adsorption site capacity, the ISFET sensors showed 50% reduction in drift while maintaining pH sensitivity. Further development of this work is being carried out and graphene can be the key to stop the drift of ISFET sensors due to exposure to electrolyte solutions. This work has produced one journal publication and one conference proceeding. Graphene-coated CMOS ISFETs are still an active research where graphene is used to boost the selectivity of the sensors for various applications.
Research Interests
My dream is to contribute and make an impact in science and improve the healthcare technology through research. My current research focus is on the design, fabrication, and implementation of microelectronic sensing systems for breath monitoring and detection of diseases. More specifically, my research is guided by the following principal areas:
Microelectronics and Sensors
Analogue microelectronics are very underestimated technology thus, digital computation has taken over. However, analogue design is making a come back in the artificial intelligence revolution. In a data driven world were there is increase in dement for processing power, low energy, and security, analogue in-memory compute, neuromorphic design, and current mode systems may be the key to tackle these challenges. The analogue signal processing has the advantages of speed, low power and local computation. Using the above circuit design methodologies, I aim to design CMOS chips to process signals from gas, pH and motion sensors locally and efficiently.
Breath
The increase in population leads to increase in healthcare demand and thus new approaches for rapid diagnosis and monitoring are needed. Breath is a multi-parameter function of the human body. It is also the only subconscious function that can be controlled by will. The study of breath consists of exhaled gases, condensate and the motion of the thorax. There can be studied using different types of sensors. For example, Parkinson's disease is detectable via thorax motion patterns years before the clinical symptoms appear. Another example is diabetes that can be monitored via exhaled alcohol and other volatile organic compounds. Cancer is also detectable via exhaled gases and the list goes on.
However, we don't know the correlation between the phases of breath and which is the most appropriate for different diseases. Thus, pattern recognition is essential for early detection and monitoring of diseases. Artificial intelligence for pattern recognition is very fashionable and applies directly to this case. However, neural networks in analogue hardware benefit from the speed and power efficiency of analogue computation and maintain local processing for data privacy. Therefore, analogue microelectronics and sensors combined with AI in hardware can be proven to be very beneficial in the case of multi-parameter breath diagnostics.
Fabrication process
Polymer-Assisted Graphene Transfer
I developed a universal Polymer-Assisted Graphene Transfer (PAGT) process for monolayer and multilayer sheets on any substrate including silicon, silicon dioxide, and Complementary Metal Oxide Semiconductor (CMOS) chips.
Environmentally Friendly Quasi-Ambient Temperature bonding process
I am leading the hardware development of an environmentally friendly and room-temperature process to bond and package electronic devices and systems. This project is in collaboration with Universities of Manchester and Loughborough and industrial partners in the UK including Indium Corporation©, TT Electronics©, Dynex Semiconductor© and more. In this work I am using lasers to process the nonmaterial Nanofoil® and characterise the bonded system performance. This work has produced one journal paper so far.
GAS SENSORs
Suspended graphene gas sensor
I pioneered the suspend graphene gas sensor that uses both top and bottom surfaces for sensing. Using the PAGT process, I suspended graphene over centimetres of area on silicon nanowire arrays fabricated by metal-assisted chemical etching (MACE). This device offers faster signal response, and more than double signal response compared to supported graphene gas sensors. With electronics the smart sensor included automatic zeroing, curve fitting and temperature control for higher efficiency. This device finds application in ammonia and acetone gas detection in breath that are correlated to kidney failure and diabetes, respectively. This work has delivered one journal publication and three conference proceedings.
RAPID GAS-PHASE DETECTION OF BACTERIAL CULTURES
Using commercial gas sensors, custom electronics and mathematical algorithms, we are able to detect the infection in bacterial cultures under 6 hours which is much faster than the current diagnosis protocol that needs 24-72 hours. This result arises from the speed of released gases and the efficient algorithms that analyse the measured signal in real-time. The applications for this method are mainly in the medical field for Urinary Tract Infections (UTI) diagnosis and more.
CMOS
CMOS ISFET pH sensing system plasma-etching
I pioneered a material selective plasma-etch process for post-processing of CMOS Ion-Sensitive Field-Effect Transistors (ISFETs) sensor system on chip. Using this process, I improved the time stability of the CMOS ISFET sensors while identifying the physical location of trapped charge within the device. This process can be used to optimise the sensing membrane and signal readout of any biochemical sensor integrated in CMOS. This work was in collaboration with Dr P. Georgiou in the Centre of Bio-Inspired Technology (CBIT) and has produced two journal publications and two conference proceedings.
Graphene on CMOS ISFET pH sensing systems
I pioneered the world’s first graphene on CMOS ISFET chip using the developed PAGT process. Taking advantage of graphene’s ultra thin, very high mechanical robustness and adsorption site capacity, the ISFET sensors showed 50% reduction in drift while maintaining pH sensitivity. Further development of this work is being carried out and graphene can be the key to stop the drift of ISFET sensors due to exposure to electrolyte solutions. This work has produced one journal publication and one conference proceeding. Graphene-coated CMOS ISFETs are still an active research where graphene is used to boost the selectivity of the sensors for various applications.
Research Interests
My dream is to contribute and make an impact in science and improve the healthcare technology through research. My current research focus is on the design, fabrication, and implementation of microelectronic sensing systems for breath monitoring and detection of diseases. More specifically, my research is guided by the following principal areas:
Microelectronics and Sensors
Analogue microelectronics are very underestimated technology thus, digital computation has taken over. However, analogue design is making a come back in the artificial intelligence revolution. In a data driven world were there is increase in dement for processing power, low energy, and security, analogue in-memory compute, neuromorphic design, and current mode systems may be the key to tackle these challenges. The analogue signal processing has the advantages of speed, low power and local computation. Using the above circuit design methodologies, I aim to design CMOS chips to process signals from gas, pH and motion sensors locally and efficiently.
Breath
The increase in population leads to increase in healthcare demand and thus new approaches for rapid diagnosis and monitoring are needed. Breath is a multi-parameter function of the human body. It is also the only subconscious function that can be controlled by will. The study of breath consists of exhaled gases, condensate and the motion of the thorax. There can be studied using different types of sensors. For example, Parkinson's disease is detectable via thorax motion patterns years before the clinical symptoms appear. Another example is diabetes that can be monitored via exhaled alcohol and other volatile organic compounds. Cancer is also detectable via exhaled gases and the list goes on.
However, we don't know the correlation between the phases of breath and which is the most appropriate for different diseases. Thus, pattern recognition is essential for early detection and monitoring of diseases. Artificial intelligence for pattern recognition is very fashionable and applies directly to this case. However, neural networks in analogue hardware benefit from the speed and power efficiency of analogue computation and maintain local processing for data privacy. Therefore, analogue microelectronics and sensors combined with AI in hardware can be proven to be very beneficial in the case of multi-parameter breath diagnostics.