Prof. Mathieu Luisier Computational Nanolectronics · Prof. Mathieu Luisier Computational Nanolectronics Mission Technology computer aided design (TCAD) can be of great help to accelerate

Prof. Mathieu Luisier | Integrated Systems Laboratory | www.iis.ee.ethz.ch

Prof. Mathieu Luisier Computational Nanolectronics

MissionTechnology computer aided design (TCAD) can be of great help to accelerate the emergence of new materials, structures, and devices for applications in energy, electronics, or health science, provided that simulation tools captur- ing the proper physics are available. Nowadays, the active regions of the most advanced transistors, solar cells, light- emitting diodes (LEDs), sensors, antennas, or batteries do not exceed a couple of nanometers. They are composed of a countable number of atoms, and strong quantum me- chanical effects influence their characteristics. Continuous methods based on classical physics fail at explaining the phenomena occurring in nano-devices and cannot predict the behavior of not-yet-fabricated components. Hence, fu-ture progresses in nanotechnology require the development of state-of-the-art modeling tools.

Quantum mechanical approaches are widely used in computational chemistry and physics to study the electronic, optical, structural, and thermal properties of materials. As engineers, we are also interested in the currents that flow through the resulting devices when they are driven out- of-equilibrium by voltages, temperature gradients, or electro- magnetic fields. The Computational Nanoelectronics Group (CNG) is therefore developing a general-purpose quantum transport environment that (i) combines the material perspective of physicist with the device consideration of en- gineers, (ii) relies on first-principles concepts, (iii) includes electron, phonon, photon, and ion transport as well as the interactions between them, (iv) covers a wide range of applications, (v) leverages the most powerful supercomput- ers to reduce the calculation time, and (vi) serves as a reference to parameterize simpler and computationally more efficient models.

Currently, the CNG is using its TCAD tool to analyze the performance of ultimate transistors at the end of Moore’s scaling law, to optimize the light emission of quantum dot LEDs, and to design efficient Lithium ion batteries with improved storage capabilities.

Curriculum VitaeProf. Mathieu LuisierProfessor of Computational Nanoelectronics

Degrees / Higher Education2007: PhD from ETH Zurich with a thesis entitled “Quantum Transport beyond the Effective Mass Approximation” 2003: Dipl.-Ing. in Electrical Engineering, ETH Zurich

Professional Career2011-present: SNSF Assistant Professor, ETH Zurich. Research field: computational nanoelectronics

2008-2011: Research Assistant Professor, Network for Computational Nanotechnology, Purdue University, USA. Research area: development and application of atomistic quantum transport models for post-Si-CMOS devices

2007: Postdoc, Integrated Systems Laboratory, ETH Zurich. Research topic: simulation of gate leakage currents in ultra-scaled nano-transistors

2003-2007: Research Assistant, Integrated Systems Laboratory, ETH Zurich. Research area: theoretical and numerical investigation of quantum transport techniques

Honors and Awards2013: European Research Council (ERC) Starting Grant for the project “Enhanced Modeling and Optimization of Batteries Incorporating Lithium-ion Elements (E-MOBILE)”

2011: Honorable Mention at the ACM Gordon Bell Prize in High Performance Computing for the paper entitled “Atomistic nanoelectronic device engineering with sustained performances up to 1.44 PFlop / s”

2007: ETH Medal for the PhD Thesis “Quantum Transport beyond the Effective Mass Approximation”

2003: ETH Medal for the Diploma Work “Simulation of Semiconductor Lasers”

Professor Mathieu Luisier

Prof. Mathieu Luisier | Integrated Systems Laboratory | www.iis.ee.ethz.chProf. Mathieu Luisier | Integrated Systems Laboratory | www.iis.ee.ethz.ch

The research activities in the Computational Nanoelectronics Group articulate themselves around three principle axes:

Multi-scale Modeling of Nano-devices

To enable new electrical, optical, or thermal functionalities, nanostructures must be embedded into larger environments, e.g. metallic contacts, Bragg reflectors, heaters / coolers, in-tegrated circuits, that extend over several micrometers. While it is mandatory to treat the active regions of nano-devices at an atomistic quantum mechanical (QM) level, such ac-curacy is not necessary for the surrounding layers. In fact, the heavy computational burden associated with QM simu-lations limits the investigation of microstructures to (semi-) classical approaches.

As part of a SNSF and EU project, the CNG is developing a multi-scale scheme to accurately model transport phe-nomena in different types of nanostructures (transistors, light-emitting devices, molecular switches, thermoelectric generators, memory units). 1 Postdoc and 4 PhD students are assigned to this research activity. The key idea is summarized in Figure 1. So far, the main focus has been set on the central part, the extension of an existing quantum transport simula-tor called OMEN that can handle electrons, phonons, and the dissipative interactions between them. The next step consists in adding photon transport and integrating it with the electron and phonon populations.

Regarding the multi-scale coupling, the OMEN nano- TCAD tool will be able on one side to take ab-initio (from first-principles) data as input parameters, for example atomic structures, Hamiltonian matrices, deformation potentials, or vibrational frequencies and use them to perform ballistic and dissipative quantum transport calculations. On the other side, a window approach will be developed to insert a quantum mechanical region inside a classical one. This requires the establishment of proper boundary conditions at the interface between the two domains.

Figure 1: Schematic of a multi-scale simulation approach for nanostructures. It ranges from first-principles theories up to classical drift-diffusion methods, going through quantum transport (QT) techniques. The CNG focuses on the QT part and its upwards and downwards coupling.

Performance Analysis of Ultimate Transistors After more than 40 years of aggressive scaling according to Moore’s law, the size of the transistors has been reduced to the nanometer scale. Strong quantum mechanical effects such as energy quantization, confinement, tunneling, and wave-particle duality have started to appear and to affect the behavior of nano-transistors. The recent replacement of planar Si MOSFETs by 3-D FinFETs is expected to minimize the negative impact of leakage currents, heat generation, and performance degradation caused by size scaling for a couple of technology nodes. However, advanced transistor designs and materials will be needed in the near future to overcome the limitations imposed by quantum mechanics. It is not clear yet how next-generation binary switches will look like, but the quest for the best-suited candidate has already started.

The OMEN quantum transport simulator was originally devel-oped to address this question and predict the performance of ultimate transistors at the end of the semiconductor road map. The CNG is active in two EU and two SNSF projects to

Research Activities and Achievements

Figure 2: (Top) Spectral distribution of the electron current flowing through a nanowire transistor in the presence of electron-phonon scattering. Red indicated high current concentrations, green no current. The blue line refers to the conduction band edge of the transistor. By emitting phonons (green stars), electrons (blue dots) loose energy while flowing from source to drain. (Bottom) Atomically- resolved lattice temperature in the same nano- wire transistor as above. Local self-heating effects close to the drain contact can be observed.

Figure 3: Schematic view of a Lithium-ion battery cell whose anode is made of graphite and cathode of LiCoO2. During the charge and discharge cycles, Li ions move from the cathode to the anode and vice-versa through a separator region.

numerically determine the best material-structure-device combination that will offer the highest ON-current, lowest OFF-current, shortest delay, and minimum power consump-tion at given dimensions, especially gate length. The choice has been made to concentrate on (i) ultra-scaled nanowire transistors (Si, Ge, III-V), (ii) III-V MOSFETs, (iii) band-to-band tunneling field-effect transistors (TFETs), and (iv) two-dimen-sional semiconductors such as graphene and metal-dichal-cogenide (MoS2, WSe2, SnSe2, etc.). Four PhD students are involved in this search for the future optimal transistor.

The originality of the simulation approach pursued here comes from the fact that the OMEN simulator does not only provide ballistic electron currents, as most other TCAD tools, but it can also deliver thermal properties and coupled electro-ther-mal effects in a full-band and atomistic basis, as shown in Figure 2 for a Si nanowire transistor. There, the increase of the lattice temperature due to electron-phonon scattering is clearly visible. Being able to capture such a behavior is es-sential to understand and minimize heat generation at the nanoscale.

Simulation of Lithium-ion BatteriesThis is a new research activity that started in October 2013. It involves 1 Postdoc and one PhD student, but 2 additional PhD students will join in 2014. The objective is to develop a multi-scale simulator for Lithium-ion batteries (LIBs), as depicted in Figure 3, that will leverage the scheme described in Figure 1. It is not necessary to recall how energy is import ant in our modern society: to better control the always-growing energy demand coming from industry, transport, and housing, it is a goal of utmost importance to develop new storage facilities that can help utilize the available energy when and where needed. Lithium-ion batteries are very promising candidates to fulfill this task, and TCAD is an efficient way to design them.

The simulation tool proposed here will combine the mate-rial and device properties of LIBs. On the material side, the emphasis will be set on nanostructured electrodes and their study with ab-initio methods, both at the ion and electron lev-el. This is probably the first time that quantum transport tech-niques will be applied to battery investigations. On the device side, an open-source, versatile, multi-dimensional, and mas-sively parallel simulation environment will be implemented that goes beyond standard models, uses the data obtained from material simulations as input parameters, is validated with experimental data, and is connected to an optimizer, for example a genetic algorithm optimizer, to automatically de-termine the best battery configuration.

This project is expected to significantly impact the design of future LIBs and contribute to the emergence of batteries with higher energy and power density to be used in all-electrical vehicles.