A nano-manufacturing facility requires high levels of precision due to the strong quantum effects for devices at a 2 to 4 nanometer footprint. We develop a feedback process control to realize a 3-D scaffolding approach. Our technology uses master equation models that are based on a quantized Hamiltonian that is tracked by the Hamiltonian of a modified ink-jet based printer to deploy the circuit design. We develop a quantum hybrid controller for manufacturing processes at the mesoscopic and quantum levels that includes interdependent multi-stage processes (e.g., quantum lithography, molecular epitaxial deposition, vertical dots, quantum wells, quantum wires, etc.). The quantum hybrid controller is able to transform a desired circuit (expressed in logic and continuous rules) into manufacturing processes that will realize the nano-circuit and achieve performance criteria (such as maximize yield, maximize signal-to-noise ratio, minimize energy consumption, minimize dissipation, etc.). The proposed system will include a language for the rules that describe the specifications of the circuit, an interface with the manufacturing processes to monitor and prescribe the sequencing, and a design dashboard. The quantum hybrid controller works with Hamiltonian operators to represent the system to achieve overall manufacturing synchronization and control, including tunneling control. The quantum hybrid controller will enable automation of nano-manufacturing of nano-circuits. This will facilitate manufacturing of IoT systems. The optimal control system implements the process control for manufacturing IoT systems represented by the switching functions. This manufacturing process control is based on a quantum representation of the switching functions. These switching functions are implemented by quantum reversible circuits with a basic programmable unit. The difference between one quantum computational element and another is the program which is described by its realization functions. The central approach in a quantum hybrid control is to express the switching functions of the design with a Hamiltonian representation. The switching functions and associated rules describing the desired behavior of the circuit will include: rules for physical principles, such as conservation of mass; rules that capture the tunneling effect and cross-talk; and soft rules for quantifying behavior and performance criteria. We construct the Hamiltonian from the switching functions and the rules using a Cooperative Distributed Inferencer (CDI). Our quantum controller tracking system will allow us to manufacture semi-conductor circuits with low footprint, taking into account quantum effects. It can be realized in a single step as opposed to sequencing step systems used for classical VLSI systems.
Journal: TechConnect Briefs
Volume: 4, Informatics, Electronics and Microsystems: TechConnect Briefs 2018
Published: May 13, 2018
Pages: 67 - 69
Industry sector: Sensors, MEMS, Electronics
Topicss: Advanced Manufacturing, Nanoelectronics