Liquid cooling has been increasing in use for many years and this corresponds to the increase in the power and density of electronics. Indeed, “The increase in computer density will continue to make air cooling less and less feasible, compared with liquid cooling. Between 2018 and 2023, the engineered fluids market is projected to grow at a CAGR of 8.8% to reach $1,304 million, from $854 million in 2018, Out of all the market’s sub sectors, it is the heat transfer fluids (cooling) segment that is expected to register the highest CAGR. ” According to an article in Electropages by Nnamdi Anyadike.
So it is important for engineers to have the tools and knowledge necessary to implement liquid cooling. And we have 3 resources that are helpful:
First, our webinar on 9-17-20 “Selecting and Designing Liquid Cold Plates for Deployment in Electronic Systems”. This webinar is live and our speaker is Dr. Kaveh Azar, Ph.D. Here’s what we’ll cover:
The use of liquid cooling systems is becoming more practical and effective for managing skyrocketing increases in power dissipation. But how do you decide when you need to cool with liquid? How do you find the right liquid cooling system for your application? This section provides the best practices for implementing a liquid cooling system at the device level.
Second, is a tutorial on liquid cooling simulation from our webinar sponsor 6SigmaET. In this tutorial, engineers will learn how to conduct and analyze liquid cooling using thermal simulation using 6SigmaET. Click the image to get to the tutorial.
Third, we have an Engineering eBook from ATS available on liquid cooling. Engineers are welcome to download it without registering, just click the following link and get your PDF copy:
ATS Heat Sinks, including our extrusions, maxiFLOW heat sinks, and maxiGRIP and superGRIP heat sink clip attachment
ATS will also be discuss our thermal management design services and how we can work with companies with our team in India to create specific solutions for even the hottest or coldest thermal management challenge.
Applications needing much higher processing power than from today’s most powerful supercomputers will very likely have to run on quantum computers. These devices have the potential to solve complex problems in seconds that would take a conventional computer millions of years to complete. While relatively few quantum computers are in regular use, their applications include simulating the behavior of matter down to the molecular level.
Quantum computers are now powering advances in materials science, cryptography, transportation and other areas. Auto manufacturers use quantum computing to simulate the chemical composition of electric vehicle batteries to help find new ways to improve performance. And pharmaceutical companies are leveraging them to analyze and compare compounds that could lead to the creation of new drugs.
Airbus uses quantum computing devices to help calculate the most fuel-efficient ascent and descent paths for aircraft. Volkswagen has unveiled a service that calculates the optimal routes for buses and taxis to minimize congestion. Some researchers will use quantum machines will accelerate artificial intelligence.
But, along with the unusual appearance of quantum computer hardware, the technology faces several strong challenges. These include cost, physical and environmental requirements, and reliability. And, of course, just understanding how quantum computing works can be hard to grasp.
Qubits and Superposition
The secret to a quantum computer’s power lies in its ability to generate and manipulate quantum bits, or qubits. Qubits are typically subatomic particles such as electrons or photons working together to act as computer memory and a processor.
Contrary to a classical bit that can only be in the state corresponding to 0 or the state corresponding to 1, a qubit may have multiple values at the same time. Until they are read out (i.e. measured), qubits can exist in an indeterminate state where it is not known whether they’ll be measured as a 0 or a 1. This is a fundamental principle of quantum mechanics referred to as superposition. It means a quantum computer can theoretically perform two tests simultaneously. Add more qubits and this computational power increases.
This quantum superposition quality in qubits can be explained by flipping a coin. The coin will land in one of two states: heads or tails. This is the way bits are observed in binary computers. But when the coin is still spinning in the air, and a side – or state – can’t be observed, the coin can be considered to be in both states at the same time. Essentially, until the coin lands it must be considered both heads and tails. Because a quantum computer can contain these multiple states simultaneously, it has the potential to be millions of times more powerful than today’s most powerful supercomputers. 
Or, per the Association for Computing Machinery: A quantum degree of freedom, such as the spin of an electron or the polarization of a photon, can exist concurrently in a weighted mixture of two states. For example, a set of 50 of qubits can represent all 250 (∼1015) combinations of the individual states. Manipulations of this assembly can be viewed as simultaneously performing a quadrillion calculations. 
Entanglement and Decoherence
Engineers can generate pairs of qubits that are entangled. This means both members of the pair are in a single quantum state. And these entangled, common state qubits affect each other instantly when measured, no matter how far apart they are. Any change made to one particle instantly influences the state of the other in a predictable way.
While entanglement remains mysterious, it is the key to the power of quantum computers. In a conventional computer, doubling the number of bits doubles its processing power. But with entanglement, adding extra qubits to a quantum machine exponentially increases its number-crunching abilities. The quantum computer process harnesses entangled qubits in a kind of quantum daisy chain. As a result, they can speed up calculations using specially designed quantum algorithms.
Unfortunately, entangled qubits don’t maintain their entangled state, known as coherence, for very long. This makes using them quite tricky. Quantum computers are programmed using sequences of logic gates of various kinds, but their programs need to run quickly enough that the qubits don’t lose coherence before they’re measured. When that occurs, it is called decoherence. 
What leads to decoherence? Qubits need to operate under extremely specific conditions that prevent them from interacting with other measuring factors, like heat waves. Their quantum state is extremely fragile. The slightest vibration or change in temperature—disturbances known as “noise” in quantum-speak—will cause them to decohere.
In the process of quantum computing, decoherence technically happens when something outside the computer performs an unidentified measurement on a qubit. This introduces an unwanted element of uncertainty or randomness into a quantum computer. Basically, there is no way to predict the result of another measurement. 
the causes of decoherence are vibrations, temperature fluctuations,
electromagnetic waves and other interactions with the outside environment. The effects
can result in the loss of the computer’s exotic quantum properties. In fact,
the issue of decoherence, how it negatively affects correct calculations, and
its prevention are among the biggest obstacles to wider use of quantum
While competing technologies and competing architectures are attacking these problems, no existing hardware platform can maintain coherence and provide the robust error correction required for large-scale computation. A breakthrough is probably several years away. 
Noise and Cooling
Qubits must be shielded from all external noise, since the slightest interference will destroy their two state superposition, resulting in calculation errors. Well-isolated qubits heat up easily, so keeping them cool is a challenge. Also, unlike in a classical computer, qubits must start in their low-temperature ground states to run an algorithm. Qubits heat up during calculations, so running several quantum algorithms one after the other means the cooling method must be able to do its job very quickly.
At extremely cold temperatures, atoms and molecules simply move around less. Generally speaking, the lower a temperature is the more stable a molecule becomes. Less movement means less energy being expelled. At a molecular level, that means that less energy is flying around, and consequently (since voltage and energy are directly related) less volatility in the voltage. This in turn means there is less of a chance that something outside of a human’s control will cause a qubit’s voltage to spike, causing the qubit to flip from one quantum state to another. Thus, keeping the computer cold introduces less energy into the system. This minimizes the chances of qubits incorrectly flipping in between quantum states. 
Researchers are trying to protect qubits from the outside world using supercooling and vacuums. But despite their efforts, noise still causes lots of errors to creep into calculations. Smart quantum algorithms can compensate for some of these, and adding more qubits also helps. However, it will likely take thousands of standard qubits to create a single, highly reliable one, known as a “logical” qubit. This will sap a lot of a quantum computer’s computational capacity.
Cooling the quantum computer chip to near absolute zero helps suppress heat waves and stabilize the motion of qubits, making them more controllable and reducing their interaction with each other. By keeping the computer cold, less energy is introduced into the system, thus minimizing the chances of qubits incorrectly flipping in between quantum states.
As described above, in quantum computing, sub-atomic particles must be as close as possible to a stationary state to be measured. Quantum computer maker D-Wave keeps core temperatures at -460°F, or -273°C, which is 0.02 degrees away from absolute zero. D-Wave uses liquid helium as a coolant for their refrigeration. The D-Wave refrigerators are dry dilution, which means that the liquid helium is in a closed cycle system. A pulse tube technology recycles and re-condenses the liquid helium. 
In IBM’s 50 qubit computer (see Figure 5) the system gradually cools from four Kelvin — liquid-helium temperatures — to 800 milliKelvin, 100 milliKelvin and, finally, 10 milliKelvin. Inside the canister, that is 10 thousandths of a degree above absolute zero. The wires, meanwhile, carry RF-frequency signals down to the chip. These are then mapped onto the qubits, executing whatever program the research team wishes to run. The wiring is also designed in a way to ensure that no extraneous noise — including heat — is transported to the quantum computer chip at the bottom. 
Researchers at Aalto University in Finland have built a tiny nanoscale refrigerator to keep qubits cold enough to function. It is the first standalone cooling device for a quantum circuit. Basically, they are tunneling single electrons through a 2nm insulator. The tunneling electrons take energy from the quantum hardware, cooling it down The circuit has an energy gap dividing two channels: a superconducting fast lane, where electrons move along with zero resistance, and a slow resistive (non-superconducting) lane.
Only electrons with enough energy to jump across the gap can get to the superconductor lane; the rest stay in the slow lane. An electron falling just short of having enough energy to make the jump can get a boost by capturing a photon from a nearby resonator – a device that can function as a qubit.
As a result of the photon losses, the resonator gradually cools down. Over time this has a selective chilling effect on the electrons as well: the hotter electrons jump the gap, while the cooler ones are left behind. The process removes heat from the system, much like how a refrigerator functions. 
One day, such aggressive and exotic cooling methods may not be needed. Researchers at the University of Pennsylvania demonstrated a new hardware platform based on isolated electron spins in a two-dimensional material. The electrons are trapped by defects in sheets of hexagonal boron nitride, a one-atom-thick semiconductor material, and the researchers were able to optically detect the system’s quantum states.
Quantum technology like this may someday be built from other materials. One promising system involves electron spins in diamonds: these spins are also trapped at defects in diamond’s regular crystalline pattern where carbon atoms are missing or replaced by other elements. The defects act like isolated atoms or molecules, and they interact with light in a way that enables their spin to be measured and used as a qubit.
These systems are attractive for quantum technology because they can operate at room temperatures, unlike other prototypes based on ultra-cold superconductors or ions trapped in vacuum. [15,16]
The point at which a quantum computer can complete a mathematical calculation that is demonstrably beyond the reach of even the most powerful supercomputer is referred to as quantum supremacy. Reaching this is likely to take many more qubits than have been put into use so far. And it will very likely require some sophisticated cooling technology to keep these qubits functioning properly. 
Advanced Thermal Solutions, Inc. (ATS) is hosting a series of monthly, online webinars covering different aspects of the thermal management of electronics. This month’s webinar will be held on Thursday, April 25 from 2-3 p.m. ET and will cover the use of thermal interface materials to enhance heat sink performance. Learn more and register at https://qats.com/Training/Webinars.
Liquid cooling has been increasing in use for many years and this corresponds to the increase in the power and density of electronics. Indeed, “The increase in computer density will continue to make air cooling less and less feasible, compared … Continue reading →