This project uses a quantum simulation technique to reveal the true conducting properties of novel atomic precision advanced manufacturing materials. With Moore's law approaching the limit of scaling for the CMOS technology, it is crucial to provide the best computing power and resources to National Security missions. Atomic precision advanced manufacturing-based computing systems can become the key to the design, use, and security of modern weapon systems, critical infrastructure, and communications. We will utilize the state-of-the-art computational methodology to create a predictive simulator for p-type atomic precision advanced manufacturing systems, which may also find applications in counterfeit detection and anti-tamper.
We show, through the use of the Landauer-Büttiker (LB) formalism and a tight-binding (TB) model, that the transport gap of twinned graphene can be tuned through the application of a uniaxial strain in the direction normal to the twin band. Remarkably, we find that the transport gap Egap bears a square-root dependence on the control parameter ϵx – ϵc, where ϵx is the applied uniaxial strain and ϵc ~ 19% is a critical strain. We interpret this dependence as evidence of criticality underlying a continuous phase transition, with ϵx – ϵc playing the role of control parameter and the transport gap Egap playing the role of order parameter. For ϵx < ϵc, the transport gap is non-zero and the material is semiconductor, whereas for ϵx < ϵc the transport gap closes to zero and the material becomes conductor, which evinces a semiconductor-to-conductor phase transition. The computed critical exponent of 1/2 places the transition in the meanfield universality class, which enables far-reaching analogies with other systems in the same class.
Thin, high-density layers of dopants in semiconductors, known as δ-layer systems, have recently attracted attention as a platform for exploration of the future quantum and classical computing when patterned in plane with atomic precision. However, there are many aspects of the conductive properties of these systems that are still unknown. Here we present an open-system quantum transport treatment to investigate the local density of electron states and the conductive properties of the δ-layer systems. A successful application of this treatment to phosphorous δ-layer in silicon both explains the origin of recently-observed shallow sub-bands and reproduces the sheet resistance values measured by different experimental groups. Further analysis reveals two main quantum-mechanical effects: 1) the existence of spatially distinct layers of free electrons with different average energies; 2) significant dependence of sheet resistance on the δ-layer thickness for a fixed sheet charge density.
We present an efficient self-consistent implementation of the Non-Equilibrium Green Function formalism, based on the Contact Block Reduction method for fast numerical efficiency, and the predictor-corrector approach, together with the Anderson mixing scheme, for the self-consistent solution of the Poisson and Schrödinger equations. Then, we apply this quantum transport framework to investigate 2D horizontal Si:P δ-layer Tunnel Junctions. We find that the potential barrier height varies with the tunnel gap width and the applied bias and that the sign of a single charge impurity in the tunnel gap plays an important role in the electrical current.
The atomic precision advanced manufacturing (APAM) enabled vertical tunneling field effect transistor (TFET) presents a new opportunity in microelectronics thanks to the use of ultra-high doping and atomically abrupt doping profiles. We present modeling and assessment of the APAM TFET using TCAD Charon simulation. First, we show, through a combination of simulation and experiment, that we can achieve good control of the gated channel on top of a phosphorus layer made using APAM, an essential part of the APAM TFET. Then, we present simulation results of a preliminary APAM TFET that predict transistor-like current-voltage response despite low device performance caused by using large geometry dimensions. Future device simulations will be needed to optimize geometry and doping to guide device design for achieving superior device performance.
While it is likely practically a bad idea to shrink a transistor to the size of an atom, there is no arguing that it would be fantastic to have atomic-scale control over every aspect of a transistor – a kind of crystal ball to understand and evaluate new ideas. This project showed that it was possible to take a niche technique used to place dopants in silicon with atomic precision and apply it broadly to study opportunities and limitations in microelectronics. In addition, it laid the foundation to attaining atomic-scale control in semiconductor manufacturing more broadly.