We present thermoelectrically coupled nanoantennas (TECNAs) with log-spiral antennas for mid- and long-wave infrared (MWIR and LWIR) detection. The nanoantenna resonantly absorbs the incident infrared (IR) radiation and, due to its shape, provides selectivity for circular polarization. We used HFSS simulations to design TECNAs with both left- and right-handed antennas and show the effect of each design parameter of the spiral on the response of the devices. The fabricated devices were characterized at$10.6~\mu $m wavelength, and the measurement results show that the response is about five times larger when the polarization handedness of the incident IR radiation matches the antenna.

The field of design and design automation of micro-/nano-circuits and systems has played a pivotal role in advancing information technologies that are an inseparable part of all our lives. Without the fundamental principles and tools created in this field, modern-day electronic systems that form the foundations of today's information age would not be a reality. Though the field has achieved tremendous success in the past few decades, it is now facing some unprecedented challenges, stemming from foundational technologies all the way to new applications. Business-as-usual approaches are plateauing. New, fundamental research and innovation are needed to sustain the demanded growth. This paper aims to summarize the key challenges and future research directions in the field of micro/nano circuits and systems design and design automation.

As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of “let physics do the computing” can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.

This paper will give a review of recent work on using networks of coupled oscillators for analog information processing. We will discuss the rationale of using coupled oscillators, and how they can be used to perform computational tasks, such as associative computing primitives, or how they can serve as hardware accelerators in vision processing pipelines. Further, we will study two specific physical implementations for such oscillator, namely relaxation oscillators based on metal-insulator phase transitions and magnetic spin-torque oscillators. We will also discuss the potential of such coupled-oscillator networks to solve computationally-hard optimization problems or even NP-hard problems.

In this paper, we demonstrate an optically inspired massively parallel non-Boolean operator which can emulate 3D wave dynamics on a 2D FPGA-based architecture. The algorithm is based on the Paraxial Helmholtz Equation: which describes the beam propagation through different media with different refractive indices. To solve this wave propagation equation numerically the FPGA-accelerated hardware have to operate with spatial varying templates. The FPGA-based implementation is very well parallelizable, consequently it is also be amenable to mega-core architectures.

Nanomagnet Logic (NML) accomplishes computation through magnetic dipole-dipole interactions. It has the potential for low-power dissipation, radiation hardness and non-volatility. NML circuits have been designed to process and move information via nearest neighbor, device-to-device coupling. However, the resultant layouts often fail to function correctly. This paper reveals an important cause of such failures showing that a robust NML layout must take into account not only nearest neighbor, but also the next nearest neighbor couplings. A new design method is then introduced to address this issue that leverages the minimum-energy states of an NML circuit to guide the layout process. Case studies show that the new method is efficient and effective in arriving at correct NML layouts.

We discuss the opportunities of performing associative processing based on the phase locking of coupled oscillators. The use of coupled oscillators, rather than Boolean logic, provides for implementations using emerging nano-technology such as magnetic spin torque oscillators and resonant body transistor oscillators, which each have the potential of lower energy operations and higher density scaling than traditional CMOS solutions.

Field-coupled nanomagnets can offer significant energy savings at iso-performance versus CMOS equivalents. Magnetic logic could be integrated with CMOS, operate in environments that CMOS cannot, and retain state without power. Clocking requirements lead to inherently pipelined circuits, and high throughput further improves application-level performance. However, bit conflicts -- that will occur in defect free, pipelined ensembles -- can make non-volatile logic volatile. Assuming a field-based clock, we present hardware designs to improve steady state non-volatility, and explain how design enhancements could increase clock energy. We then suggest materials-related design levers that could simultaneously deliver non-volatility and low clock energy.

Sooner or later, fundamental limitations destine complementary metal-oxide-semiconductor (CMOS) scaling to a conclusion. A number of unique switches have been proposed as replacements, many of which do not even use electron charge as the state variable. Instead, these nanoscale structures pass tokens in the spin, excitonic, photonic, magnetic, quantum, or even heat domains. Emergent physical behaviors and idiosyncrasies of these novel switches can complement the execution of specific algorithms or workloads by enabling quite unique architectures. Ultimately, exploiting these unusual responses will extend throughput in high-performance computing. Alternative tokens also require new transport mechanisms to replace the conventional chip wire interconnect schemes of charge-based computing. New intrinsic limits to scaling in post-CMOS technologies are likely to be bounded ultimately by thermodynamic entropy and Shannon noise.

Magnetic phenomena are commonly used for data-storage applications, but there are relatively few attempts to exploit magnetic phenomena for logic applications. In this presentation, we review our recent work on logic functionality in systems of physically-coupled nanometer-scale magnets. Nanomagnets are special in that they exhibit only two distinct stable states of magnetization, which is the basis for their use in magnetic random access memories and in hard disk drives. These latter applications, for which fabrication of dense arrays is under development, face the challenge of avoiding magnetic dipole interactions between individual elements, which limits data storage density. In contrast, these interactions are exploited in the magnetic quantum-dot cellular automata (MQCA) system, which is a network of closely-spaced, dipole-coupled, single-domain nanomagnets designed for digital computation. Our work demonstrates that logic functions can be realized in properly-structured arrays of physically-coupled nanomagnets, and points to the possibility of all-magnetic information processing systems that incorporate both memory and logic.

This paper looks at designing circuit elements that will be constructed with nanoscale magnets within the Quantum-dot Cellular Automata (QCA) computational paradigm. In magnetic QCA (MQCA) logical operations and dataflow are accomplished by manipulating the polarizations of nanoscale magnets. Wires and gates have already been experimentally demonstrated at room temperature. However, to realize more complex circuits - and eventually systems - more than just wires and gates in isolation are required. For example, gates must be inter-connected, signals must cross, etc. All structures must be controlled by the envisioned drive circuitry. In this paper, structures that will facilitate these circuit-level tasks are presented for the first time.

Logical devices made from nano-scale magnets have many potential advantages - systems should be non-volatile, dense, low power, radiation hard, and could have a natural interface to MRAM. Initial work includes experimental demonstrations of logic gates and wires and theoretical studies that consider their power dissipation. This paper looks at power dissipation too, but also considers the circuitry needed to drive a computation. Initial results are very encouraging and indicate that clocked magnetic logic could - in the worst case - match equivalent low power CMOS circuits and - in the best-case - potentially provide more than 2 orders of magnitude improvement when one considers energy per operation.

We introduce some CNN and analogic feature extraction algorithms for artificial immune systems, which are able to convert grayscale or color to binary images storing as much information as possible for further processing. We define a statistical property called immune histogram based on sub-patterns of these images. Our results and measurements show that these algorithms can be implemented in real-time applications. A sample application, which detects new textures in a familiar environment, is also presented.

We review some of our previous work on field-coupling in nano-scale cellular arrays. Electronic devices based on metallic and magnetic nanoscale dots and molecular structures have been suggested, however, no technologically viable architecture for nanoelectronic circuit integration has emerged so far. A natural architecture on the nanoscale appears to be near-neighbor cellular networking, and we explore promising alternative ways of integrating nanodevices by direct physical field coupling, i.e. either by Coulomb or by magnetic interactions. We review new architectures for such field-coupled nanocircuits.

A novel nanometer-scale electronic technology, called nanoelectronics is emerging. Nanoelectronic discrete devices, such as resonant tunneling diodes and transistors, single-electron transistors, bistable quantum-cells, quantum interference devices, etc. have been proposed and built. Technology and physics of the devices are reasonably well understood, but there exists a gap between device physics and nanoelectronic systems integration. In this paper it is shown that in case of local quantum coherence, i.e., if coherence is restricted to the internal dynamics of Coulomb-coupled devices, system dynamics can be described by a set of coupled ordinary nonlinear differential equations. In this case virtual charges, voltages and currents, obeying Kirchoff's equations, can be assigned to the dynamic variables of the state equations, thus circuit models can be introduced. We also show that edge-driven arrays performing ground state computing are locally passive systems if the Coulomb-coupled devices are excited by the input signals only. In order to perform signal processing or computing, external energy should be pumped into the array, and the pumped array should be locally active. Adiabatic pumping is one way of injecting energy to the signal path.

Summary form only given, as follows. We investigate the use of nanoelectronic structures in cellular neural network (CNN) architectures, for future high-density and low-power CMOS-nanodevice hybrid circuits. We present simulation results for Single Electron Tunneling (SET) transistors configured as a voltage-to-current transducer for CNN cells. We also present an example of quantum-dot cellular arrays which may be used to realize binary CNN algorithms. Nanoelectronics offers the promise of ultra-low power and ultra-high integration density. Several device structures have been proposed and realized experimentally, yet the main challenge remains the organization of these devices in new circuit architectures. Here, we investigate the use of nanodevices in CNN architectures. Specifically, we focus on nanostructures based on SET devices and Coulomb-coupled quantum-dot arrays, the so-called Quantum-Dot Cellular Automata (QCA). CNN-type architectures for nanostructures are motivated by the following considerations: on the one hand, locally-interconnected architectures appear to be natural for nanodevices where some of the connectivity may be provided by direct physical device-device interactions. On the other hand, CNN arrays with sizes on the order of 1000-by-1000 (which are desirable for applications such as image processing) will require the use of nanostructures since such integration densities are beyond what can be achieved by scaling conventional CMOS devices.

Summary form only given, as follows. New nanodevices which encode information into the geometrical charge distribution of artificial (or natural) molecules have been proposed. Functional units are composed by exploiting the electrostatic coupling between neighboring devices. In these units, processing takes place by reshaping the electron density of the molecules, and not by switching electron currents. It has been proposed and demonstrated that high speed, extremely low loss logic gates (e.g. inverters, majority gates) can be realized. It will be shown that Coulomb-coupled time-invariant or stationary artificial molecules behave like nonlinear locally passive systems for small-signal excitations, thus multiple equilibria cannot be achieved by integrating them. Without multiple equilibrium write-hold-read memories, and thus signal processors, cannot be realized. However, the signal transfer-function of strongly nonlinear molecules can be varied in time by adiabatic control, called clock control. It will be shown that strongly nonlinear time-varying molecules can transform the necessary amount of clock-energy into the flow of signals, thereby enabling the network of molecules to perform multiple equilibria. It is envisaged that, by a proper integration of clock-controlled artificial molecules, universal digital signal processors can be built.

A low power CMOS clock buffer based on charge recycling technique is presented. To accomplish the charge recycling process and avoid introducing the extra short circuit current during the recycling phase, an extra switching circuit and control signal are utilized to keep inverters momentarily tri-state. The feasibility of this design and its improved power efficiency are demonstrated by simulations.