Study of a Self-Powered Lactate and Glucose Biosensor Platform

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 202x-202x. Tutor/Director: xxxxLactate and Glucose detection and monitoring have shown to have a significant impact on patients’ wellbeing, for allowing the prognosis of worsening patient conditions in hospital settings and assisting on early diagnosis and detection of diabetes mellitus complications. Biological Fuel Cell (BFC) technology allows the transformation from chemical to electrical energy and has recently emerged as a key lithium-ion battery competitor for its sustainability, miniaturization power, and high energy density. Their characteristics make them an interesting alternative to power electronic devices, and their possible application in the development of medical measurement platforms. Point of Care (POC) Biosensor devices powered with BFC present a compelling perspective to medical monitoring and individualized proactive healthcare since these types of devices allow near-patient settings and encourage a more personalized medicine approach to improve quality of life in developed countries. The two main objectives of this project are to develop a biosensing platform architecture for Glucose and Lactate Fuel Cells and the use of a commercially available DC-DC converter to apply said BFC to power the instrumentation and obtain a self-powered application. The proposed dual-layered platform attempts to provide a viable biosensor structure, based on the sensing of current proportional to sample concentration, a later amplification, and an event detection circuit to be used as a comparator. This study and proposal, if developed into reality, would comply with the “ASSURED” criteria for POC tests, which states they must be Affordable, Sensitive, Specific, User-friendly, Robust and rapid, Equipment-free, and Deliverable to those who need them

Study of systems powered by triboelectric generators for bioengineering applications

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Director: Pere Lluís Miribel Català. Co-director: Manel Puig i Vida

Multi-Fidelity Bayesian Optimization for Efficient Materials Design

Materials design is a process of identifying compositions and structures to achieve desirable properties. Usually, costly experiments or simulations are required to evaluate the objective function for a design solution. Therefore, one of the major challenges is how to reduce the cost associated with sampling and evaluating the objective. Bayesian optimization is a new global optimization method which can increase the sampling efficiency with the guidance of the surrogate of the objective. In this work, a new acquisition function, called consequential improvement, is proposed for simultaneous selection of the solution and fidelity level of sampling. With the new acquisition function, the subsequent iteration is considered for potential selections at low-fidelity levels, because evaluations at the highest fidelity level are usually required to provide reliable objective values. To reduce the number of samples required to train the surrogate for molecular design, a new recursive hierarchical similarity metric is proposed. The new similarity metric quantifies the differences between molecules at multiple levels of hierarchy simultaneously based on the connections between multiscale descriptions of the structures. The new methodologies are demonstrated with simulation-based design of materials and structures based on fully atomistic and coarse-grained molecular dynamics simulations, and finite-element analysis. The new similarity metric is demonstrated in the design of tactile sensors and biodegradable oligomers. The multi-fidelity Bayesian optimization method is also illustrated with the multiscale design of a piezoelectric transducer by concurrently optimizing the atomic composition of the aluminum titanium nitride ceramic and the device’s porous microstructure at the micrometer scale.Ph.D

Recent Progress in Self-Powered Skin Sensors

Self-powered skin sensors have attracted significant attention in recent years due to their great potential in medical care, robotics, prosthetics, and sports. More importantly, self-powered skin sensors do not need any energy-supply components like batteries, which allows them to work sustainably and saves them the trouble of replacement of batteries. The self-powered skin sensors are mainly based on energy harvesters, with the device itself generating electrical signals when triggered by the detected stimulus or analyte, such as body motion, touch/pressure, acoustic sound, and chemicals in sweat. Herein, the recent research achievements of self-powered skin sensors are comprehensively and systematically reviewed. According to the different monitoring signals, the self-powered skin sensors are summarized and discussed with a focus on the working mechanism, device structure, and the sensing principle. Based on the recent progress, the key challenges that exist and the opportunities that lie ahead are also discussed