Introduction

Alright, let's get this straight. Polymers, those long chains of molecules, don’t just sit there looking pretty – they fold, bend, and twist under different conditions. One minute, they’re these floppy, elongated messes (coil state), and the next, they’re a tiny, compact ball (globule state). This process, known as the coil-globule transition, is pretty much the "battle royale" of molecular physics. And guess what? We’re simulating it using some good ol' fashioned Langevin and Brownian dynamics – no shortcuts, no pre-built frameworks. Just raw code, a little elbow grease, and some serious computational muscle.

Challenge Overview

Now, here’s the thing. We’ve got a single-stranded polymer, and we want to figure out when and how it morphs from a coil to a globule. Is it all about temperature? Solvent conditions? A little bit of everything? That’s where this project comes in. By throwing this polymer into a simulation using custom Fortran code (because, honestly, why rely on someone else’s tools when you can build your own?), we’re going deep into how these chains behave under the influence of Langevin and Brownian dynamics. The goal? To pinpoint those critical moments when a polymer flips the switch and says, "I’m done being a mess, time to tighten up."

Methodologies Used

Here’s where it gets fun. To model the chaos that is polymer dynamics, we’re using two big guns:

Langevin Dynamics:
Think of it like driving a car, but the road’s full of potholes and unpredictable speed bumps. Langevin dynamics lets us simulate the motion of our polymer while factoring in all the random bumps from the environment and the constant friction from the medium it’s in. We’re talking random noise and forces that make sure our polymer doesn’t just sit there like a lump. It moves, it fluctuates, it’s alive.
Brownian Dynamics:
Now, Brownian dynamics takes things down a notch – the polymer just goes on a random walk, driven by all the invisible particles around it. No superpowers, just collisions and random movements, much like that random walk at 2 a.m. after a coffee bender. It’s messy, but it’s how particles behave in a solvent, and that’s what we need to understand for this project.

Results & Findings

Here’s where it gets fun. To model the chaos that is polymer dynamics, we’re using two big guns:

Langevin Dynamics:
Think of it like driving a car, but the road’s full of potholes and unpredictable speed bumps. Langevin dynamics lets us simulate the motion of our polymer while factoring in all the random bumps from the environment and the constant friction from the medium it’s in. We’re talking random noise and forces that make sure our polymer doesn’t just sit there like a lump. It moves, it fluctuates, it’s alive.
Brownian Dynamics:
Now, Brownian dynamics takes things down a notch – the polymer just goes on a random walk, driven by all the invisible particles around it. No superpowers, just collisions and random movements, much like that random walk at 2 a.m. after a coffee bender. It’s messy, but it’s how particles behave in a solvent, and that’s what we need to understand for this project.

Conclusion and Future Outlook

So, what have we learned here? The coil-globule transition is no joke. It’s driven by a combination of external conditions – temperature, solvent quality, random noise – and the way a polymer chain responds to these factors tells us a lot about its behavior. And that’s what we’ve just simulated: the exact moment when a polymer transitions from a carefree, extended chain to a compact globule. Looking ahead, we’re just getting started. What if we added some external forces to the mix, like electric or magnetic fields? What if we made the polymer chain more complicated, with real-world interactions like excluded volume effects or solvent-polymer attraction? The possibilities are endless. But one thing’s for sure: we’ve got the power of simulation on our side, and we’re just scratching the surface of what these transitions can tell us. Next step? Taking this raw simulation and pushing it further, faster, and harder – because just like with Iron Man, it’s all about upgrading the tech to push the limits of what’s possible.

Review on the dynamics and coil-globule phase transition of single-stranded polymers in two dimensions

Introduction

Challenge Overview

Methodologies Used

Results & Findings

Conclusion and Future Outlook

Have any queries? Ask me

Joydeep Das

HPC & Physics Researcher | Plasma Simulations | Machine Learning