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Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations 

Nanoscale surface morphologies generated by ultrashort laser pulses are products of a complex interplay of laser energy deposition, pressure generation, melt dynamics, and rapid resolidification. In this work, we investigate the physical factors controlling the formation of laser-induced surface nanostructures using a combined data-driven and physics-based approach. A machine learning (ML) model is developed to predict the number density of surface nanoprotrusions formed during single-pulse laser processing of metals, using a compact set of physically motivated dimensionless descriptors derived via dimensional analysis. These descriptors capture key stages of surface morphology generation, including energy deposition, pressure buildup, liquid filament breakup, and solidification. The ML model is trained on quantitative features extracted from experimental scanning electron microscopy images spanning 39 data points across nine metals. Post hoc model explanation analysis identifies the absorbed fluence and the Ohnesorge number as the most influential descriptors. The electron-phonon coupling strength emerges as a key material parameter through its control of the effective energy deposition depth and the characteristic length scale of transient liquid structures. These trends are further examined using large-scale two-temperature molecular dynamics simulations, which confirm the predicted sensitivity of surface morphology to electron–phonon coupling near the spallation threshold. 

Abstract Laser ablation is a process that bears both fundamental physics interest and has wide industrial applications. For decades, the lack of probes on the relevant time and length scales has prevented access to the highly nonequilibrium phase decomposition processes triggered by laser excitation. In this study, a close integration of time-resolved probing by intense femtosecond X-ray pulses with large-scale atomistic modeling has yielded unique insights into the ablation dynamics of thin gold films irradiated by femtosecond laser pulses. The emergence and growth of nanoscale density heterogeneities in the expanding ablation plume, predicted in the simulations, are mapped to the rapid evolution of distinct small angle diffraction features. This mapping enables identification of the characteristic signatures of different phase decomposition processes occurring simultaneously in the plume, which are driven by photomechanical and thermodynamic driving forces. Beyond the specific insights into the ablation phenomenon, this study demonstrates the power of joint X-ray probing and atomistic modeling of material dynamics under extreme conditions of thermal and mechanical nonequilibrium.