Friction is perhaps the most ubiquitous force in our daily lives, yet it remains one of the most stubborn mysteries in physics. Since the days of Leonardo da Vinci, scientists have struggled to explain exactly how energy vanishes when two surfaces slide past one another. While we can measure the resistance of a sliding block or the wear on a car tire, the underlying atomic mechanism that converts kinetic energy into heat has lacked a complete, self-contained mathematical description. For decades, physicists relied on a mathematical "cheat code": they added an ad-hoc dissipation term to their equations to force the math to match reality. [arXiv:1708.03415]
The Core Finding
Researchers at the Universidad de Buenos Aires have successfully modified the classic Tomlinson model to explain friction without relying on these artificial dampening factors. By representing a surface as a periodic arrangement of atoms, each confined by its own independent harmonic potential, the team observed the emergence of non-conservative forces naturally. This is a significant departure from previous iterations of the model where energy loss was essentially programmed into the simulation from the start. The team found that the interaction between a single sliding atom and the vibrating lattice creates an "effective emerging friction" that matches experimental observations from Atomic Force Microscopy (AFM).
Think of it like a person running across a floor covered in trampolines; even if the trampolines are perfectly elastic, the runner slows down because their energy is transferred into the complex, messy vibrations of the springs beneath them. The authors state:
The novelty of our contribution resides in that we do not include an ad hoc dissipation term as all previous works have done.By solving Newton’s equations numerically, the researchers demonstrated that the simple act of one atom interacting with a flexible lattice is enough to simulate the energy loss we call friction.
The State of the Field
Before this breakthrough, the gold standard for atomic-scale friction was the Prandtl-Tomlinson model, first proposed in the 1920s. While highly successful at predicting the "stick-slip" motion observed in nanotechnology, it required a damping coefficient—a number inserted by hand to represent energy lost to the environment. Without this coefficient, the sliding atom in the model would simply oscillate forever, never coming to a rest. This created a theoretical gap: if we cannot explain where the energy goes without "fudging" the numbers, we do not truly understand the physics of the interface.
This research arrives at a critical moment for the quantum error correction landscape. As we move toward fault-tolerant quantum computing, the physical interactions at the atomic level—specifically how energy dissipates in the materials used for superconducting qubits—become a primary bottleneck. Understanding the "emerging friction" in the crystalline structures of a surface code or a logical qubit is essential for reducing the noise that leads to decoherence. If we can model dissipation from first principles, we can design materials that inherently minimize the energy loss that currently plagues quantum hardware.
From Lab to Reality
For scientists, this model unlocks a new path for studying the non-conservative lateral forces that govern nanomachines. By removing the ad-hoc terms, researchers can now investigate how specific lattice geometries or atomic masses influence friction without the bias of pre-set dissipation rates. This is particularly relevant for the development of topological qubits, where the movement of quasiparticles must be controlled with extreme precision. Engineers working on Micro-Electro-Mechanical Systems (MEMS) could use these findings to improve the longevity of microscopic gears and sensors, potentially extending the operational life of these devices by years.
For investors, this research impacts the broader quantum hardware market, which is increasingly focused on material science to achieve scalability. The quantum error correction market, estimated to reach billions by 2030, depends heavily on our ability to engineer chips with lower thermal noise. Companies that can translate first-principles friction models into better-performing superconducting circuits will hold a significant competitive advantage in the race for the first commercially viable quantum computer.
What Still Needs to Happen
Despite the elegance of the new model, several technical challenges remain before it can be fully integrated into industrial design. First, the current simulation is limited to a single sliding atom over a one-dimensional arrangement. Real-world applications involve complex, three-dimensional interfaces with millions of atoms and varying degrees of surface roughness. Groups at institutions like the Max Planck Institute are currently working on scaling these numerical simulations to handle more complex geometries, but the computational cost is immense.
Second, the model currently assumes a classical Newtonian framework. While this is sufficient for many dry sliding scenarios, the next frontier is a fully quantum-mechanical version of the Tomlinson model. This would account for phonon-electron interactions and quantum tunneling, which are critical at the ultra-low temperatures where fault-tolerant quantum computing operates. We are likely five to ten years away from seeing these first-principles models used in standard CAD software for quantum chip fabrication.