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Dynamics of the Molten Contact Line

The purpose of this program is to develop a basic understanding of how a molten material front spreads over a solid that is below its melting point, arrests, and freezes. Our hope is that the work will contribute toward a scientific knowledge base for certain new applications involving molten droplet deposition, including the "printing" of arbitrary three-dimensional objects by precise deposition of individual molten microdrops that solidify after impact. Little information is available at this time on the capillarity-driven motion and arrest of molten contact line regions. Schiaffino and Sonin investigated the arrest of the contact line of a molten microcrystalline wax spreading over a subcooled solid "target" of the same material. They found that contact line arrest takes place at an apparent liquid contact angle that depends primarily on the Stefan number S=c(T(sub f) -T(sub t)/L based on the temperature difference between the fusion point and the target temperature, and proposed that contact line arrest occurs when the liquid's dynamic contact angle approaches the angle of attack of the solidification front just behind the contact line. They also showed, however, that the conventional continuum equations and boundary conditions have no meaningful solution for this angle. The solidification front angle is determined by the heat flux just behind the contact line, and the heat flux is singular at that point. By comparing experiments with numerical computations, Schiaffino and Sonin estimated that the conventional solidification model must break down within a distance of order 0.1 - 1 microns of the contact line. The physical mechanism for this breakdown is as yet undetermined, and no first-principles theory exists for the contact angle at arrest. Schiaffino and Sonin also presented a framework for understanding how to moderate Weber number molten droplet deposition in terms of similarity laws and experimentation. The study is based on experiments with three molten materials- molten wax on solid wax, water on ice, and mercury on frozen mercury- which between them span a considerable range of the deposition/solidification similarity parameters. Correlations are obtained for the spreading velocity, spreading time scales, the spreading factor (i.e. ratio of deposited drop's final footprint radius and the drop's initial radius), post-spreading liquid oscillation amplitudes and time scales, and bulk solidification time scales. Duthaler carried out an experimental and theoretical investigation of the relationship between the liquid's apparent contact angle and the Capillary number Ca=mu U/sigma based on contact line speed, for molten materials spreading over subcooled solids. This relationship is required for modeling of melt spreading. We have adapted Voinov's methodology to the molten contact line and formulated a theoretical model for the Ca vs. contact angle relationship, based Schiaffino and Sonin#s (1997a,b) wedge-like solidification front model. With the solidification front angle taken from Schiaffino and Sonin, the model is in good agreement with the experimental results for Ca vs. contact angle. Duthaler also extended the experimental investigation of droplet deposition and contact line freezing to more materials, including solder on glass, solder on solder, water on ice, and molten microcrystalline wax on wax. The latter also included tests on inclined targets. Deposition tests have also been done with molten octacosane (C28H58) on various targets. An important objective of our program has been the development of micron-scale sensors for measuring the transient temperature at a point on the substrate surface as a molten contact line moves over it. The expectation is that this temperature history will yield a better understanding of the thermal process in the contact line region. The sensors are of the thermistor type, either 2.5 microns or 1.5 microns square, microfabricated with silicon-based technology on either pure silicon or amorphous silicon dioxide chips. Each chip has 32 sensors distributed on its surface in arrays. The time response is better than 10 ms. At the time of writing, sensor calibration is in progress. Results on thermal transients during contact line passage will be discussed at the conference. While we expect that the data will provide information on the near-contact-line heat transfer process, we also foresee possible problems. First, the spatial resolution of the sensors may be insufficient to resolve the near-contact-line region. Second, the sensors protrude about 0.5 microns above the substrate surface, and may affect the contact line motion. Third, a sensor's temperature history depends on both the heat flux distribution into it from the fusion front and the thermal properties of the substrate below it and the solidified melt between it and the fusion front. The heat flux distribution in the contact line region must therefore be unfolded from computations of the overall system's transient thermal response.

Sonin, Ain A.↗

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗