Abstract:
One of the most fundamental properties of semiconductors is their ability to support electric currents in the presence of electric and magnetic fields. These properties are described by transport coefficients such as drift and Hall electron and hole mobilities. During the past decade, there has been considerable progress in calculations of these coefficients at the level of individual atoms, by leveraging quantum mechanics and the Boltzmann transport equation. The reliability, accuracy, and reproducibility of these calculations keep improving at a fast pace, and we are now at a point where state-of-the-art methods and high-performance computing software carry (nearly) predictive power, meaning that we can compute the carrier mobility of a new semiconductor before this material even exists. In this discussion, I will review the formalism underlying the ab initio Boltzmann transport equation, and outline the key approximations and the computational challenges of this approach. I will describe the Boltzmann transport solver of the software package EPW that we develop, and review some of its history and the ups and downs of scientific software development. To illustrate the methodology, I will mention recent work on the design of high-performance two-dimensional materials for next-generation nanoscale electronics. If time permits, I will cover a few additional aspects of materials discovery and design at the atomic scale.
Bio:
Feliciano Giustino is Professor of Physics at the University of Texas, Austin, and holds the W. A. "Tex" Moncrief, Jr. Chair in Quantum Materials Engineering. He earned his Ph.D. in Physics at the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and held a post-doctoral appointment at the University of California, Berkeley. Prior to joining the University of Texas, he spent over a decade at the University of Oxford as Professor of Materials Science, and one year at Cornell University as the Mary Shepard B. Upson Visiting Professor in Engineering. He is the recipient of a Leverhulme Research Leadership Award, a Moncrief Grand Challenge Award, a Fellow of the American Physical Society, and a Clarivate Analytics Highly Cited Researcher. He serves on the Executive Editorial Board of JPhys Materials and is an Associate Editor of Journal of Computational Electronics. He specializes in electronic structure theory, high-performance computing, and the quantum design of advanced materials at the atomic scale. He is author of 180 scientific publications and one book on density-functional theory published by Oxford University Press. He initiated the open-source software project EPW, which is regularly used by research groups around the world.
Summary:
Focus: Microelectronics
Computation is critical for society and our needs for it are growing
E.g. training LLMs is extremely expensive:
Training GPT-3 costs 500 Tons of CO2
Training GPT-4: 20k tons of CO2
Need new ideas/techniques for providing more compute capability at a lower cost
Scaling trend of microelectronics is at 2nm feature size
Current semiconductor path is stalling
Need new ideas: integrated photonics, neuromorphic, quantum, or new semiconductor materials (focus of this talk)
Researching new 2D semiconductor transistors
Traditional Planar MOSFET: flow of current between two endpoints controlled by a metal gate that can be enabled or disabled by applying a small voltage (design common 1971 - 2010)
Evolution of MOSFET
Transistor size shrinking over time
The smaller feature size required the design to evolve in 3D to provide a larger connection between the key components even as they get smaller
FinFET -> GAAFET/RibbonFET
Current depends on electron mobility (want it to be high, to drive transistor at high speed with moderate power use and heat)
Mobility drops very low as transistor shrinks
Expected to shrink to 0 at 1nm
Cause: surface area to volume ratio drops for very small transistors
At surface between materials electrons need to overcome the disorder across material boundaries
Motivates transition to 2D materials (multiple materials aligned at atomic level to have a consistent boundary with no disorder across boundaries)
Challenge: Consistent production of transistors to avoid defects in their manufactured shape
Goal: find materials with high mobility that can be used in next-generation transistors
Electron mobility
Electron travels through lattice of a material
Scatters through it randomly
Electric field pushes electron in one direction; still moves randomly but with a bias in a given direction
Induces a motion velocity on the electron’s noisy path
Modeling mobility
Quantum mechanical models are too expensive
Using a Boltzmann transport equation model
Models number of electronics in a given state within the quantum state space
Start with collisionless flow and adjust for scattering
Because electrons are quantum they can only be in a certain set of states within a given solid
Most electrons are in a very narrow range of the possible state space
Model focused on capturing the phase space occupied by electronics and how they move across it
Hardest: scattering of electronics between different states
Scales as O(#atoms4)
Using Density Functional Theory to approximate the potential function that models the interactions among the electrons without explicitly modeling individual electrons
High-throughput screening of high-mobility 2D materials
Materials Cloud: repository of materials calculations
Different resolution levels of models (more runs for cheaper, less accurate models)
Was able to show that the Monolayer WS2 material has high potential as a ultra-high mobility 2D semiconductor
Driving experimental work to develop manufacture techniques to reach this potential
Software
Materials Cloud: https://www.materialscloud.org/home
EPW: Electron-phonon physics from first principles: https://epw-code.org
QuantumEspresso: electronic-structure calculations and materials modeling: https://www.quantum-espresso.org
MATCSSI: Materials Cyberinfrastructure for Sustained Scientific Innovation: https://matcssi.tacc.utexas.edu