Miniaturization and Complexity Scaling
Miniaturization is the process of making things very small using modern technology.
The silicon chip is a classic example of the benefits of miniaturization.
Miniaturization is a steady process that results in increasing the number of electronic elements in a volume unit. The trend to manufacture ever smaller mechanical, optical and electronic products and devices. Examples include miniaturization of mobile phones, computers and vehicle engine downsizing.
Michael Casey, Head of Extrusion Applications and Design at Minalex Corporation (a leading custom aluminium extrusion company) explains, “Just because something gets smaller does not change the expectation of performance. If anything, there’s a presumption of improved performance. Precision in manufacturing then becomes of greater importance.”
Impact of Miniaturization on Electronics Production
As per the Research by Toni T. Matilla, Tomi T. Laurila and Jorma K. Kivilahti, Helsinki University of Technology, Finland,
When we talk about Portable Electronics, then "Product Reliability" is a very important factor. This is so because, during their Service Environments, these items face a lot of Electrical, Mechanical, Thermal and Thermo - Mechanical strains and stresses.
There are two reasons which state that the solder interconnection reliability is important. Firstly, we can see in the above figure, e.g., in small-scale Ball Grid Array, Chip Scale Packaged or Flip Chip components,
that as the solder interconnections volume decrease, so this decreased size has brought the components closer to the PWB (Printed Wiring Boards), so the interconnection densities have increased and therefore the micro-interconnections face much higher stresses.
Secondly, the interconnection metallurgy becomes more complex due to the the employment of lead-free solders, components under bump or lead metalizations, and PWB protective coatings.
Now, many different lead - free alternatives have replaced the solders and protective coatings. Thus, the reliability of each material combination would be different because the reliability of the soldered interconnections is controlled by the microstructures. Thus, it is very much important to study the metallurgical reactions in the effective joining region and resulting microstructures within the solder interconnections and their impacts.
Also, the lead - free solder interconnections can contain more complex inter material layers such as phosphides, which weaken solder interconnections thus can encounter mechanical failures in future.
Also, Mechanical shocks and Thermochemical loadings are amongst some of the most critical kinds of loading conditions experienced by the Portable Electronic Equipments. These evoke different failure mechanisms leading to dissimilar failure modes.
Hence, all these factors make us realise the importance of Reliability Testing in the microstructures.
As per the 13 September 2019 online issue of Nature Communications,
Researchers say that owing to the non - scalability of traditional Von-Neumann Computer Architecture, the 'Complexity Scaling' is also declining and the impending 'Dark Silicon' era has presented a severe threat to multi-core processor technology.
The inability of most of the devices on a computer chip to be powered up at once is referred to as the 'Dark Silicon Era' . Since, a single device generates a large amount of heat, as a result this happens. Von - Neumann architecture working as the standard structure for the modern computers works on the yes- no approach, where program instructions and data are stored in the same memory and share the same communication channel.
According to Saptarshi Das, assistant professor of engineering science and mechanics,
"Because of this, data operations and instruction acquisition can not take place at the same time and for complex decision making process using neural networks, a cluster of supercomputers would be needed to be used trying to use parallel supercomputers, hence, to solve this problem, the solution would be to create brain-inspired, analog, statistical neural networks that do not rely on devices that are simply on or off, but provide a range of probabilistic responses that are then compared with the learned database in the machine".
Hence, using the 2-D materials, molybdenum disulfide and black phosporus, the Researchers have developed a Gaussian field-effect transistor. These devices are more energy efficient and produce less heat, which makes them ideal for scaling up systems.
While computers have become smaller and more powerful and supercomputers and parallel computing have become the standard, we are about to hit a wall in energy and miniaturization. Now, Penn State researchers have designed a 2D device that can provide more than yes-or-no answers and could be more brain - like than current computing architectures.