Theoretical Physics

A Prize-Winning User

“That’s a completely fair statement,” says Johnson, who was an early adopter of high-performance computing, dating back to her student days at Carleton University, Queen’s University and Dalhousie University, as well as her post-doctoral work at Duke University. She’s now a professor and Herzberg-Becke chair in theoretical chemistry at Dalhousie University.

Asked how she would explain her job to a guest at a cocktail party, Johnson says she studies intermolecular interactions within the materials all around us.

“These are the weaker interactions between molecules as opposed to the stronger bonds within a molecule,” Johnson explains. “So, we would, for example, at a cocktail party look at the interactions in beer or wine in a glass — those types of interactions within a liquid or a gas or within a molecular crystal.”

She does this to predict such properties as reactivity, hardness, and conductivity, among others.

“Any chemical observable is something that we can predict through this type of modelling,” she says.

Johnson’s lab, however, might surprise those who envision her working in a chemistry lab full of beakers and bunsen burners. Rather, it’s a computer lab from which she’s developed methods for modeling that are some of the most accurate and efficient available. It was those methods that won her the Steacie Prize.

“We then take those methods and apply them to problems in chemistry,” she explains. “One of the particular problems we’re focusing on is the problem of molecular crystal structure prediction or how molecules would come together to form a 3D solid.”

She likened the ways molecules come together to the ways in which Lego bricks do.

“There are many ways you could conceive of molecules coming and packing together, but not all of those are going to be stable,” she says. “So the challenge is trying to predict how they will actually pack in a solid.”

Once you solve that puzzle, there are applications across several industries, one of the most recognizable being pharmaceuticals.

“If you are producing a drug and you want it in pill form, you want a solid but soluble state,” Johnson says. “When you try to formulate new drugs, you want to screen for all the possible polymorphs (transformations to another form) and find out which ones are the most stable. What you don’t want is for it to easily form a particular polymorph that’s not a very stable one and then change over time so that it’s no longer soluble.”

These methods also have applications for electronics, but instead of looking at solubility, the property of interest would be conductivity.

“Like the solubility, the ability of charge to flow through a material is also dependent on the particular polymorph” Johnson explains. “You can think of many applications where the different solid state properties between polymorphs would affect whether a material was promising or not.”

Johnson says her work would be “completely impossible” without ACENET’s services.

Putting the Stars in Perspective

Catherine Lovekin’s main research is dedicated to understanding the heat-transfer process in stars. In particular, she studies the “convective overshoot” where the circular currents that exist in stars go a little beyond their theoretical boundaries.

“We don’t really know how much of this overshoot there should be, so I use asteroseismology, which is a way of measuring the variations in stars, to try to figure that out,” explains Lovekin, associate professor of physics at New Brunswick’s Mount Allison University. “Stars pulsate and they have variations like waves on a head of a drum or something. And I’m trying to use those waves to understand the interior of the stars.”

The overshoot is important, she says, as it changes how big the core of the star is, so it also changes all kinds of things about the subsequent evolution, and what elements are produced — for example, how much fuel it has for nuclear fusion. It can change the lifetime of the star.

The hope is that eventually she and others who are working on the same question will get enough of a sample that they can start to see patterns. For example, maybe the overshoot behaves differently in high mass stars compared to low mass stars, or maybe it changes as stars evolve, meaning that older stars have different values than younger stars.

While Lovekin is working mostly on individual stars, her students are looking at stars that have pulsations and that are part of a binary system — in effect, two stars in orbit around each other. Looking at the stars this way, she says, is a good way to constrain things such as the diameter, temperature and mass of the star.

As her research has expanded to the way in which binary stars behave, her models have become that much more computationally intensive, to the point where she now can’t do her work without the services of high-performance computing (HPC) — in this case, from ACENET.

“I could do some aspects of my work without those resources, but it would take me years longer without something like ACENET.”

Lovekin’s relationship with HPC goes back a long way. She was an early user of the HPC computing from the Digital Research Alliance of Canada, then called Compute Canada, which is the national partner of ACENET. And today, her students are all using ACENET.

“The ACENET training that is offered every May is so useful,” she says. “I just tell my students to sign up. It really helps get them started. The ACENET folks have so much more experience with helping to train people on the system. When my students start working with me, they all know how to run these models because of their ACENET training.”

A Prize-Winning User

Erin Johnson wouldn’t have won the prestigious Steacie Prize, awarded to early-career scientists, in 2021, without the Digital Research Alliance of Canada’s high-performance computing and the services of ACENET. “That’s a completely fair statement,” says Johnson, who was an early adopter of high-performance computing, dating back to her student days at Carleton University, Queen’s University and Dalhousie University, as well as her post-doctoral work at Duke University. She’s now a professor and Herzberg-Becke chair in theoretical chemistry at Dalhousie University. Asked how she would explain her job to a guest at a cocktail party, Johnson says she studies intermolecular interactions within the materials all around us. “These are the weaker interactions between molecules as opposed to the stronger bonds within a molecule,” Johnson explains. “So, we would, for example, at a cocktail party look at the interactions in beer or wine in a glass — those types of interactions within a liquid or a gas or within a molecular crystal.” She does this to predict such properties as reactivity, hardness, and conductivity, among others. “Any chemical observable is something that we can predict through this type of modelling,” she says. Johnson’s lab, however, might surprise those who envision her working in a chemistry lab full of beakers and bunsen burners. Rather, it’s a computer lab from which she’s developed methods for modeling that are some of the most accurate and efficient available. It was those methods that won her the Steacie Prize. “We then take those methods and apply them to problems in chemistry,” she explains. “One of the particular problems we’re focusing on is the problem of molecular crystal structure prediction or how molecules would come together to form a 3D solid.” She likened the ways molecules come together to the ways in which Lego bricks do. “There are many ways you could conceive of molecules coming and packing together, but not all of those are going to be stable,” she says. “So the challenge is trying to predict how they will actually pack in a solid.” Once you solve that puzzle, there are applications across several industries, one of the most recognizable being pharmaceuticals. “If you are producing a drug and you want it in pill form, you want a solid but soluble state,” Johnson says. “When you try to formulate new drugs, you want to screen for all the possible polymorphs (transformations to another form) and find out which ones are the most stable. What you don’t want is for it to easily form a particular polymorph that’s not a very stable one and then change over time so that it’s no longer soluble.” These methods also have applications for electronics, but instead of looking at solubility, the property of interest would be conductivity. “Like the solubility, the ability of charge to flow through a material is also dependent on the particular polymorph” Johnson explains. “You can think of many applications where the different solid state properties between polymorphs would affect whether a material was promising or not.” Johnson says her work would be “completely impossible” without ACENET’s services.

Why Materials Do the Things They Do

Dr. Geoffrey Lee-Dadswell is a theoretical physicist at Cape Breton University, who for the past 15 years has been studying why materials do the things they do. Specifically, he studies heat and momentum transport on a very small scale. For an example of large scale heat transport, take a frying pan on a stove. We know that the stove element heats the bottom of a pan to the point that food cooks. However, the handle of the pan doesn’t get as hot. Why? The answer lies in understanding the transport of heat, which obeys Fourier’s Law of Heat Conduction. This law has been known for almost 200 years, but surprisingly, is not well understood. One of the mysteries about Fourier’s Law is that it doesn’t seem to work for some objects on the nanometre-scale. A nanometre is one billionth of a metre. If you were to lay atoms across a nanometre, you might fit only about 10! Computers for example have become faster largely because the parts of their chips have been made smaller over the years. As this process continues, more and more parts of an ordinary desktop computer or smart phone are nano-electronics. Lee-Dadswell studies nano-systems that are one-dimensional, which is to say that for theoretical purposes, they have only length. Now because we live in a three-dimensional world, everything has a width and a depth. However, in some nano-systems, these are so small that they can be ignored. Examples of one-dimensional systems are carbon nano-tubes (think of these like a sheet of graphite that’s been rolled up into a tube) and polymer chains such as the polyethylene chains that pop bottles are made of. Carbon nano-tubes are often a few micrometres long, but can be only five to ten nanometres wide. Physicists once believed that everything obeyed Fourier’s Law of Heat Conduction, but researchers have found that these one-dimensional systems behave differently from other systems –disobeying Fourier’s Law. Moreover, they don’t know why, which also means that they don’t have a solid understanding of why everything else does obey Fourier’s Law. Physical laws are preferably derived from the more fundamental mechanics, but nobody knows how to derive Fourier’s Law from mechanics. If they can’t derive it, then they really don’t understand the law. This drives physicists nuts! It means that we don’t understand things like heat flow as well as we thought. This puzzle began to surface in the early 1900s, but didn’t come to the forefront until the 1970s. It’s challenging to make progress on such a long-standing mystery, and tackling it is therefore rather scary. Lee-Dadswell is one of only a few researchers in the world doing so. Lee-Dadswell generally has one or two undergraduate students working with him. He develops models, and the students then run dozens of simulations in parallel on ACENET systems, each running for possibly weeks and involving tens or hundreds of thousands of atoms interacting with each other. By understanding the fundamental laws of transport, solving problems such as removing heat from nano-electronics and improving refrigeration technology become possible.