The ultimate goal?
Invent a new type of logic/computational platform powered by magnets that will eventually lead to the development and commercialization of an all-magnetic information processing system. Notre Dame researchers have projected that NML processes consume up to 100 times less power than current computer technologies.
Another advantage of magnetic memory is that it is “nonvolatile” — in other words, it doesn’t lose the information it is using when it shuts down. Any computation with NML devices will start up instantly. The DARPA program is scheduled to run 4.5 years. At the end of that time, there should be enough experimental data to show if commercialization of this technology is feasible.
Quick Summary of Relevant Nanomagnet Logic Research
There is a lot of research to determine the right configurations, architecture and operating modes to capture the desired energy efficiency while maximizing speed.
1. This is either the same DARPA funding or related to DARPA funding of Grandis and Notre Dame's work on spin transfer torque random access memory.
The program will be carried out through a collaboration between the University of Notre Dame and Grandis. Development work will focus on integrating magnetic tunnel junction (MTJ) materials capable of sensing very small magnetic fields with nano-magnets performing logic operations. The goal is to demonstrate non-volatile spin logic circuits operating at ultra-fast speeds of less than 1 nanosecond and ultra-low power consumption of less than 10 atto-Joules (Atto stands for 10^-18) per operation. Such performance coupled with the inherent non-volatility of spin logic devices will enable not just significant reductions in the active power consumption of microprocessors but also the virtual elimination of standby power consumption.
2. Arxiv - Simulation Studies of Nanomagnet-Based Logic Architecture (14 pages)
There was a simulation study (2008) on interacting ensembles of Co nanomagnets that can perform basic logic operations and propagate logic signals, where the state variable is the magnetization direction. Dipole field coupling between individual nanomagnets drives the logic functionality of the ensemble and coordinated arrangements of the nanomagnets allow for the logic signal to propagate in a predictable way. Problems with the integrity of the logic signal arising from instabilities in the constituent magnetizations are solved by introducing a biaxial anisotropy term to the Gibbs magnetic free energy of each nanomagnet. The enhanced stability allows for more complex components of a logic architecture capable of random combinatorial logic, including horizontal wires, vertical wires, junctions, fanout nodes, and a novel universal logic gate. Our simulations define the focus of scaling trends in nanomagnet-based logic and provide estimates of the energy dissipation and time per nanomagnet reversal.
3. Purdue University researchers had a proposed architecture for all-spin logic (Arxiv 6 pages). Switching energy-delay of all spin logic devices
The need to find low power alternatives to digital electronic circuits has led to increasing interest in alternative switching schemes like the magnetic quantum cellular automata(MQCA) that store information in nanomagnets which communicate through their magnetic fi elds. A recent proposal called all spin logic (ASL) proposes to communicate between nanomagnets using spin currents which are spatially localized and can be conveniently routed. The objective of this paper is to present a model for ASL devices that is based on established physics and is benchmarked against available experimental data and to use it to investigate switching energy-delay of ASL devices.
It has been argued that ASL devices could potentially lead to ultralow power switches since a stable nanomagnet with an activation barrier of 40 kT could be switched with less than an attoJoule (aJ). Experimentally, however, nanomagnet memory devices typically require tens of fJs to switch at speeds that are a factor of 100 to 1000 lower, raising questions about the potential of ASL devices to provide a low-power alternative to today's transistors. This is because most of the dissipation in switching magnets is associated not with the dynamics of magnets but with the spin transport process and we need a suitable model that incorporates both to make reliable predictions. This paper presents such a model that is based on established physics and is benchmarked against the recent experimental result.
Presently the low voltage operation of ASL devices is off set by the large total charge, arising from a combination of large magnets and low switching efficiency. If
these numbers (i.e. Ns and f1f2I=Is) can be reduced, the advantages of low voltage operation (less parasitic capacitance and stray charge) and non-volatility (less leakage) would make ASL look attractive.
In summary, we have presented a model that combines the physics of spin transport with that of nanomagnet dynamics that agrees well with available experimental data.
Using this model we investigate the switching of ASL devices and show how the energy-delay scales with Ns. It is also shown that for identical input/output magnets, switching can be non-reciprocal based on the applied voltages. Suitable cascading schemes will be discussed elsewhere.
4. Arxiv / Applied Physics Letters - Energy-efficient mixed mode switching of a multiferroic nanomagnet for logic and memory (23 pages)
In magnetic memory and logic devices, a magnet’s magnetization is usually flipped with a spin polarized current delivering a spin transfer torque (STT). This mode of switching consumes too much energy and considerable energy saving can accrue from using a multiferroic nanomagnet switched with a combination of STT and mechanical stress generated with a voltage (VGS). The VGS mode consumes less energy than STT, but cannot rotate magnetization by more than 90◦, so that a combination of the two modes is needed for energy-efficient switching.
5. There is other research which suggest the possibility that single molecular nanomagnets or nanoparticle nanomagnets could be used to create powerful quantum computers.
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