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1. Self‐Affine Scaling of Earth's Islands

   https://doi.org/10.1029/2025GL121272  

   Oline, Matthew; Hoskins, Jeremy; Seekell, David; Silber, Mary; Cael, B B (April 2026, Geophysical Research Letters)

   Abstract Earth's relief is approximately self‐affine, meaning a zoom‐in on a small region looks statistically similar to a large region upon rescaling. Fractional Brownian surfaces give an idealized self‐affine model of Earth's relief with one parameter, the Hurst exponent , characterizing the roughness of the surface. We compile a large data set of topographic profiles of islands (N = 131,063 with the range of areas covering approximately 8 orders of magnitude) and obtain four estimates for the Hurst exponent of Earth's surface by fitting four statistical laws from the theory of self‐affine surfaces concerning islands: (a) distribution of areas, (b) volume‐area relationship, (c) perimeter‐area relationship, and (d) maximum height‐area relationship. The estimated Hurst exponents indicate different fractal scaling behavior for different geometric features, and are sorted in order of increasing expected influence of coastal processes. This sheds light on the impact of coastal erosion and sedimentation on island geomorphology. 

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2. Silicon/Glass Interposer Metrology and Inspection by Shadowgraphy

   Lu, Kuan; Lee, ChaBum (August 2026, US-Korea Conference)

   Through-glass vias (TGVs) and through-silicon vias (TSVs) are critical vertical interconnects in advanced 3D packaging, where geometric defects and sidewall roughness directly degrade electrical reliability and yield. Conventional methods such as SEM and AFM require destructive preparation and offer limited throughput. This work presents a shadowgraphy approach for non-destructive TGV/TSV array metrology with sub-micron accuracy in diameter, depth, and sidewall roughness. 

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3. A sensor-based monitoring approach to predict surface profile of vibration-assisted atomic force microscopy (AFM)-based nanofabrication

   https://doi.org/10.1016/j.mfglet.2023.08.109  

   Wang, Xinchen; Zhou, Huimin; Deng, Jia; Wang, Zimo (August 2023, Manufacturing Letters)

   The vibration-assisted atomic force microscope (AFM)-based nanomachining offers a promising opportunity for low-cost nanofabrication with high tunability. However, critical challenges reside in advancing the throughput and the quality assurance of the process due to extensive offline experimental investigations and characterizations, which in turn hinders the wide industry applications of current AFM-based nanomachining process. Hence, it is necessary to create an in-process monitoring for the nanomachining to allow real-time inspection and process characterizations. This paper reports a sensor-based analytic approach to allow real-time estimations of the AFM-based nanomachining process. The temporal-spectral features of collected acoustic emission (AE) sensor signals are applied to predict the depth morphology of nanomachined trenches under different machining conditions. The experimental case study suggests that the most significant frequency domain information from AE sensor can accurately predict (R-squared value around 92%) the nanomachined depth profile. It, therefore, breaks the current limitation of characterization tools at the nanoscale precision level, and opens up an opportunity to allow real-time estimation for quality inspection of vibration-assisted AFM-based nanofabrication process. 

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4. Roughness‐Limited Performance in Ultra‐Low‐Loss Lithium Niobate Cavities

   https://doi.org/10.1002/adom.202502355  

   Khalatpour, Ali; Qi, Luke; Fejer, Martin M; Safavi‐Naeini, Amir H (February 2026, Advanced Optical Materials)

   Abstract Achieving low optical loss is critical for scaling complex photonic systems. Thin‐film lithium niobate (TFLN) offers strong electro‐optic and nonlinear properties in a compact platform, making it ideal for quantum and nonlinear optics. WhileQfactors above 10⁷are achieved, they remain below the intrinsic material limit. A systematic study of scattering losses due to roughness in TFLN racetrack cavities is presented, with isolating contributions from sidewall and interface roughness. Quality factors up to 2.7 × 10⁷are demonstrated in waveguides with widths of 2.2λ (≈3.5 µm), where interface roughness dominates, and up to 1.2 × 10⁷in narrower waveguides 0.8λ wide (≈1.2 µm), where sidewall roughness is the primary limitation. The modelling framework, based on 3D wave simulations informed by roughness measured by AFM, is applicable to any index contrast between waveguide core and cladding and widely applicable on integrated photonic platforms. 

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5. Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

   https://doi.org/10.1364/OE.558186  

   Khurana, Mohit; Delfan, Sahar; Yi, Zhenhuan (January 2025, Optics Express)

   Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE₀) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs. 

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