Abstract:
Conventional floating gate non-volatile memory (NVM) has been a dominating NVM
device until the date. Since the concept of semiconductor nanoparticles (NPs) based NVM
was first proposed, it has been widely explored as potential solution to the scaling down
needs of NVM device. NPs based floating gate NVM devices have several advantages as
compared to its continuous floating gate based NVM devices. Further, there is intense
research going on to overtake the dominance of the floating gate flash memory device
technology. Therefore, a number of emerging random access memory (RAM) which are
also possess nonvolatility, being investigated. These includes RRAM, MRAM, FeRAM
and PCM mainly. However, there is still a long way to cover before they can beat the flash
memory dominance, which has already adopted the three-dimensional (3D) architecture to
survive the scaling needs for, further next years. Therefore, the primary focus in the thesis
would be on mainly the NPs based NVM devices and extending it to RRAM synaptic
devices towards the end chapter.
A process for NPs synthesis and deposition is identified after reviewing a number of
research on NPs based NVM devices, which have used a number of different processes. In
summary, it is found that previous process lack in simplicity, control over the sizes of the
NPs, requiring high thermal budget, usually complex and costly in nature. In present thesis
work, a colloidal synthesis and spin-coating based process is proposed and studied for NPs
based NVM devices. The work start with identifying the suitable materials for NVM device
applications. In particular, Ni and Co are identified as potential candidates for device
experiments. A number of colloidal synthesis processes are studied in order to identify
suitable methods for synthesis and size control of metal (Ni and Co) NPs up to below 10
nm and 1-2 nm for some samples. Samples are characterized by DLS, HRTEM, SEM/EDX,
XRD and AFM characterization techniques. The spin coating and experimental conditions,
which provide the most uniformly distributed NPs over a device substrate, are selected for
the further device fabrication. AFM and SEM/EDX study is also done to confirm the NPs
sizes and material presence at the NPs spin-coated device substrates. After having done the
process optimizations and identification of optimized process parameters, the devices are
fabricated and characterized. The MOS NVM devices which are fabricated usually have 3-4 nm thick tunnel dielectric of SiO2, typically a monolayer of spin coated NPs and 10-13
nm of control dielectric in different fabricated samples. Co-NPs of an average size of 5 nm
are used for MOS NVM device fabrication and they result in very big memory window of
8V after application of sweep voltage of ±6V. The big memory window by the devices are
one of the excellent finding of the work. In addition, devices are tested for actual device
program/erase and retention. Device show a robust retention trend and extrapolated
calculation indicated the retention more than 10 years. Ni-NPs based MOS NVM devices
also show reasonably good memory window of 4V at ±10V and good retention trend.
Further chapters shows Co-NPs scaling down to 1-2 nm size and being used for MOS NVM
devices fabrication. These devices results in a shift in flat band voltage, ΔVFB of 0.35‒1.5V
by applying 1.2‒4V sweep voltages, which evidences the low operating voltage, low power
and highly scalable NVM applications. In this section, the fabrication of devices are
repeated for a number of times to check reproducibility and it is found to be reasonably
good reproducibility for device characteristics from device to device and from one sample
to another sample. In the end section, a study on application of 1-2 nm Co-NPs for the
RRAM synaptic devices is done. The primary analysis of the fabricated NPs based RRAM
synaptic devices show very useful I-V characteristics. The RRAM devices demonstrate
switching with dual mode interchangeable SET and RESET characteristics where it opens
on SET side at higher voltage while other side it RESET at relatively low voltage.
Characteristics of such a RRAM device is useful in neuromorphic applications, primarily
by embedding them crossbar arrays. These devices are the capable of Hebbian spiking
timing dependent plasticity (STDP) and anti-Hebbian STDP that can be used in supervised
spiking neural network for neuromorphic computing applications.