Abstract

Quantum spin Hall effect (QSHE) a fascinating topological phenomenon that could happen when electrons are confined in two-dimension (2D). It plays an important role in understanding fundamental topological physics principle in materials, as well as in engineering low-power electronic and quantum computation device applications.

In this project, we will attempt to realize QSHE in heterostructures formed by atomically thin 2D materials. We will employ electron transport measurements at cryogenic temperatures and search for the quantized conductance as evidence of QSHE. We will get theory support from Dr. Joaquín Fernández-Rossier at the International Iberian Nanotechnology Laboratory (INL), Portugal, to design experiments and understand the data obtained. In addition, the experimental group of Sascha Sadewasser will contribute with the growth of as a substrate materials using molecular beam epitax. We will arrange exchanges of staff and students to facilitate realizing the goal of this project.

Beginning with this seed project, we expect to establish a long-term collaboration to generate impacts in higher-education, fundamental physic research, and industrial application in MIT and in Portugal.

MIT PI
Long Ju, Assistant Professor, Department of Physics

PT PIs
Joaquín Fernández-Rossier, International Iberian Nanotechnology Laboratory, group leader of Theory of Quantum Nanostructures and tenured staff researcher, Portugal
Sascha Sadewasser, International Iberian Nanotechnology Laboratory, Leader of the Laboratory for Nanostructured Solar Cells

Abstract

We aim to develop neuromorphic computing systems by exploiting the stochastic nature of nanoscale spintronic devices. Currently neural networks have achieved remarkable success in various application areas. However, existing silicon-based hardware exhibits inefficiency at processing compute-intensive models compared to the human brain. Bio-inspired computing models based on stochastic activations and learning rules provide new opportunities for developing efficient neuromorphic systems with complex cognitive capabilities. In this proposal, we will leverage the intrinsic stochasticity from the compact and energy-efficient spintronic devices for realizing stochastic neuro-mimetic components, and realize algorithms and architecture to achieve balanced performance among accuracy, robustness, synaptic memory requirements, and energy efficiency. Particularly, we will develop stochastic spin-orbit torque magnetic tunnel junctions for both neurons and synapses. Compared to state of the art, the proposed devices and circuits will minimize the influence of noises and device variations, leading to a scalable solution for robust and efficient implementation of stochastic neural networks.

MIT PI
Luqiao Liu, Associate Professor, Department of Electrical Engineering and Computer Science

PT PI
Susana Cardoso de Freitas, INESC-MN and Instituto Superior Tecnico, Principal Investigator and Full Professor

Abstract

Sepsis is a leading cause of death from infection, driven by a dysregulated immune response. There is a need for technology to monitor sepsis progression and guide treatment. Neutrophils are abundant and easily accessible immune cells, and their functional state holds promise as a real-time biomarker for sepsis and other diseases of the immune system. Here we propose to integrate a microfluidic electronic cellular analysis chip developed at MIT called isodielectric separation with a nanoelectronic graphene field-effect transistor chip sensor developed at INL that is capable of detecting reactive oxygen species, a key neutrophil effector function. This combined platform will provide high-resolution, multidimensional profiling of neutrophil function from a drop of blood. We will develop an integrated chip-based platform and validate the system using chemically activated human neutrophils. This work will enable more precise immune monitoring in sepsis and other immune-related conditions, advancing clinical applications and providing substantial commercial potential.

MIT PI
Joel Voldman, Professor, Department of Electrical Engineering and Computer Science

PT PI
Pedro Alpuim, Research Group Leader, International Iberian Nanotechnology Laboratory
Jérôme Borme, Research Scientist PI, International Iberian Nanotechnology Laboratory