Modern electronics rely on conducting materials that exhibit metallic properties. A typical modern-day computer represents information in these materials using a binary number system of discrete bits, represented as either 0 and 1. A quantum computer uses a sequence of quantum bits, or qubits. It’s this leap that is envisioned to make quantum computers so incredibly powerful.
In addition to its charge, an electron also has a so-called spin, which generates a magnetic field. The spin can be used as a qubit. The electron spin states therefore need to be robust against decoherence – a quantum mechanism which results in the loss of information. The electron spin lifetimes (i.e. the time before the spin information decoheres) are affected by lattice vibrations in a material and neighbouring magnetic interactions.
Archer is using a unique carbon nanomaterial for the development of its qubit devices. These devices rely on the spin of electrons for logic operations. So it is critical to develop accurate models simulating the electronic properties of Archer’s qubit material for the successful development of the 12CQ chip.
This synthetic carbon nanomaterial is categorised as a ‘carbon nano-onion’ due to the resemblance of the materials’ nanostructure with a multitude of concentric shells.
Archer worked with researchers at EPFL to model and simulate the unique carbon nano-onion structure on an atomic level. The collaboration involved access to one of Europe’s most powerful supercomputing clusters, the Piz Daint, to perform some of the calculations.
We employed a fast, approximate quantum mechanical simulation methodology that allowed us to consider tens of thousands of atoms in various carbon nanomaterial structures, with a focus on disorder and defects that contribute to electron delocalisation. Different material models were developed to explore the effects of a wide variety of structural parameters with increasing degree of disorder and complexity.
During the discovery process, we first defined the initial atom structure of the carbon nano-onions, and using Density Functional Theory, we calculated the electronic properties of this initial model. DFT is a quantum-mechanical computational method used to model the electronic structure of atoms, molecules, and materials. It relies on the concept that the behaviour of electrons in a system can be described by a mathematical function called the electron density. This density function can be used to calculate various electronic properties of the system, such as its energy and charge distribution. It is this charge distribution, i.e. how far within the material the electrons are effectively spread out, that determines whether a material is metallic or an insulator.
The carbon nano-onion structures represented and calculated using DFT contained a few thousand atoms. These early calculations gave the first theoretical evidence for the metallic nature experimentally observed in the carbon nano-onions.
With the initial DFT models, we advanced to using molecular dynamics simulations that included successive details gathered during experimentation. A more representative structure of the carbon nano-onions containing details of the ‘edges’ of constituent graphene flakes that make up the material was derived. This required the deployment of an advanced Density Functional Tight Binding (DFTB) computational methods and model. DFTB allowed an order of magnitude increase in the number of atoms that could be used in the calculations, resulting in the most realistic computational models of the carbon nano-onions to date.
The full research paper by Archer and EPFL has been published in this month’s issue of Carbon: https://doi.org/10.1016/j.carbon.2023.03.056
Kristiāns Čerņevičs, Martin Fuechsle, Matthew Broome, Mohammad Choucair, Oleg V. Yazyev. Origin of metallic-like behavior in disordered carbon nano-onions. Carbon, Volume 208, Pages 303-310, (2023).
Designed by Aaron Knight.