Senior Lecturer, Co-coordinator Exploratory Nanotechnology
My research interests lie in the development of nanotechnology for applications in electronics and neuromorphic computing. I do materials-driven research with the aim understand and control the physics and processes involved in realizing new nanoelectronic device concepts.
I currently focus on developing resistive and ferroelectric memory and memristive devices based on HfO2 thin films, and their integration with III-V semiconductors. I am exploring the ability of these devices to function as synapses in artificial neuromorphic systems.
Previously, I pioneered antimonide-based nanowire synthesis during my PhD work, I have been strongly involved in InAs/GaSb-based tunnel field effect transistor (TFET) research both in Lund and at IBM, and at IBM I co-invented a novel method for CMOS-compatible III-V integration on Si, called Template-Assisted Selective Epitaxy (TASE).
- Memory technology for Machine Learning (EITP25)
The purpose of this course is to give an in depth understanding for the physics of common memory device technologies with focus on non-volatile memories. Furthermore, the course covers how these memory devices can be integrated to create neuromorphic hardware for applications in machine learning and artificial intelligence. Finally, the course gives an introduction to the architectures and algorithms that are used in machine learning, to give a basic understanding for the needs that memory devices and their connections need to fulfil.
- High-speed Devices (EITP01)
This course aims at providing fundamental knowledge of the physics which enables the very high frequency operation of modern transistors. Basic amplifier design for microwave frequencies is introduced. The course gives a modern description of transistors relevant for quantum well and FinFET devices, mainly based on ballistic transport.
Displaying of publications. Sorted by year, then title.
Available Master projects
Please email mattias [dot] borg [at] eit [dot] lth [dot] se (subject: Master%20thesis%20opportunity%3F) if you are interested in any of the projects below.
Modelling of currents in ferroelectric tunnel junctions
Ferroelectric tunnel junctions are important candidates for next-generation memories and artificial synapse devices. In this project numerical simulations for the current through the tunnel junction will be developed and matched to experimental data.
Crystallization by local heating
In highly integrated electronic systems, the limitations on thermal treatments are extremely strict, preventing the necessary anneals for synthesising ferroelectric hafnia. Here COMSOL will be used to simulate the viability of electrically induced crystallization by local heating in ferroelectric transistors.