Friction and wear of diamond are controlled by its surface chemistry, which determines whether covalent bonds form across the sliding interface. First-principles simulations have explored the role of surface orientation and passivation, but are limited to a few hundred atoms and tens of picoseconds. To bridge this gap, we develop a reactive machine learning interatomic potential for the C/H/N/O/Si chemical space, covering diamond, silicon nitride, silicon oxide, their surfaces, interfaces, and environmental molecules. The potential is trained on a large dataset of diverse structures and is tested on multiple physical properties, including ab initio reaction barriers on diamond surfaces, and structural/mechanical properties of amorphous Si$_3$N$_4$ and SiO$_2$. We then simulate sliding of diamond-Si$_3$N$_4$ interfaces with four surface orientations, clean and H/OH-passivated terminations, and normal loads from 0.1 to 23 GPa. We identify two different regimes: one where sliding is localized at the interface, and shear stress is proportional to the interfacial bond density, and another where shear is distributed inside the softer material, and adhesion due to full interfacial bonding dominates. These results show how passivation, surface orientation and load together determine interfacial bonding and friction, with implications for the environmental sensitivity of diamond wear. More broadly, the potential enables reactive simulations of diamond, silicon nitride and silica with near-ab initio accuracy at length and time scales beyond first-principles methods, providing a useful tool for future studies of wear at plowing asperities, chemical-mechanical polishing, and properties of amorphous ceramic films.
In recent years, the effects of uniaxial strain on Sr$_2$RuO$_4$ have been extensively investigated, revealing a pronounced enhancement of the superconducting critical temperature accompanied by experimental indications of an emergent magnetically ordered state. In this Letter, we study the impact of strain on the spectral and magnetic properties of this material within an advanced many-body theoretical framework. We find that strain induces an anisotropic Lifshitz transition, which enhances the electron scattering rate along the elongation axis while simultaneously promoting coherent Fermi-liquid behavior in the perpendicular direction, in close agreement with experimental observations. Taking into account this anisotropic behavior allows us to capture the magnetic instability leading to a finite-temperature ordered state at large strain values. Our analysis further reveals that the magnetic response is dominated by two competing wave vectors associated with distinct nesting vectors: one within the $γ$ sheet and the other between the $α$ and $β$ sheets of the Fermi surface. Both wave vectors can stabilize magnetic order, with their competition depending sensitively on the coherence of the respective Fermi surface sheets.
A frequency-domain thermoreflectance (FDTR)-based technique is presented to measure the effective thermal properties of a material stack whose surface is patterned with metallic nanoline gratings that are heated and probed by lasers. An analytical heat diffusion model is derived for predicting the FDTR phase response that incorporates a finite laser spot radius with a Gaussian intensity profile for the pump and probe lasers, as well as the dimensions of the nanoline grating. The model is validated by comparing with measurements of Au nanoline gratings, with widths ranging from 100 to 1000 nm, fabricated on a-SiO$_2$ and $c$-sapphire substrates. Due to the short phonon mean free paths (MFPs) in these substrates, thermal transport remains in the diffusive regime for the whole range of nanoline widths. The model and the measurement show excellent agreement across different laser spot radii and nanoline widths, with a bulk thermal conductivity value of $c$-sapphire and the thermal boundary conductances at the Au-Cr/a-SiO$_2$ and Au-Cr/$c$-sapphire interfaces comparable to our prior measurements and the literature. The validated model will serve as a robust baseline for extending this method to measure effective thermal conductivity as a function of the heater size. This approach is particularly relevant for materials where non-diffusive thermal transport regimes enable probing phonon MFP dependent contributions to the thermal conductivity.
