EML webinar overview: Elastic Strain Engineering for unprecedented properties

Elastic Strain Engineering (ESE) utilizes all six components of the strain tensor to guide the interactions of material structures with electrons, phonons, etc. and control energy, mass and information flows. The success of Strained Silicon technology today harbingers what deep ESE (> 5% elastic strain in a large enough space-time volume) may accomplish for civilization, with likely breakthroughs in electronics, photonics, superconductivity, quantum information processing, etc. In this webinar I give examples of exploiting the strain and strain-gradient design space of nanostructured materials. Inhomogeneous elastic strain patterns lead to dynamically tunable artificial atoms and pseudoheterostructures to regulate quasiparticle energetics and motion. Strain also governs crystal defect charging levels, carrier effective mass, direct-to-indirect bandgap and band topology transitions, etc. which can be efficiently sampled by quantum mechanical calculations and represented by machine learning models such as neural network (NN) representations. Technology computer-aided design (TCAD) finite-element simulations with first-principles machine-learned (FPML) constitutive relations coupled to topology optimization (TO) tools are being developed to guide the design of freely suspended, micro-electromechanical system (MEMS) devices in fin-field-effect transistor (FinFET) like geometries. Productions of kilogram-scale nanowire composites and metallic glasses under large tensile elastic strain have also been demonstrated for energy technology applications, that can lead to better superconductors, catalysts and magnets. By controlling the strain patterns, one opens up a much larger parameter space - on par with chemical alloying - for optimizing the functional properties of materials, thus fulfilling Feynman's vision There's Plenty of Room at the Bottom . EML webinar speakers, videos, and overviews can be found at https://imechanica.org/node/24098. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Elastic Strain Engineering (ESE) utilizes all six components of the strain tensor to guide the interactions of material structures with electrons, phonons, etc. and control energy, mass and information flows. Deep ESE (> 5% elastic strain in a large enough space-time volume) has the potential to make breakthroughs in electronics, photonics, superconductivity, quantum information processing, etc. by exploiting the strain and strain-gradient design space of nanostructured materials. This field also opens up opportunities for developing machine learning models and simulation tools to optimize the functional properties of materials. The production of nanowire composites and metallic glasses under large tensile elastic strain has shown promise for energy technology applications.