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Microsphere photolithography (MPL) is a promising technique for cost-effective fabrication of large-scale metasurfaces. This approach generates an array of photonic jets by the collimated illumination of self-assembled microspheres. The photonic jets can be precisely steered within the unit cell defined by each microsphere by changing the angle of incidence. This allows for the creation of complex metasurface element geometries. Computer controlled articulation of the substrate relative to a static UV source allows the direct-write of different metasurface elements. However, this is time-consuming and requires registration between each exposure for complex features. This paper investigates a single exposure method with the dynamic continuous angle of incidence control provided by a Digital Micromirror Device (DMD) in the front Fourier plane of the projection system. The grayscale values of the DMD pixels can be adjusted to provide optical proximity correction. Larger patterns can be achieved by scanning the substrate relative to the exposure beam. This approach is demonstrated with the creation of hierarchical patterns. This work greatly simplifies the MPL exposure process for complex resonators and provides potential for full light field control.

 

Rare earth elements (REE) are critical elements found in monazite, xenotime, and hydrated REE phosphates which typically form in hydrothermal mineral deposits. Accurate predictions of the solubility of these REE phosphates and the speciation of REE in aqueous fluids are both key to understanding the controls on the transport, fractionation, and deposition of REE in natural systems. Previous monazite and xenotime solubility experiments indicate the presence of large discrepancies between experimentally derived solubility constants versus calculated solubilities by combining different data sources for the thermodynamic properties of minerals and aqueous species at hydrothermal conditions. In this study, these discrepancies were resolved by using the program GEMSFITS to optimize the standard partial molal Gibbs energy of formation (ΔfG°298) of REE aqueous species (REE3+ and REE hydroxyl complexes) at 298.15 K and 1 bar while keeping the thermodynamic properties fixed for the REE phosphates. A comprehensive experimental database was compiled using solubility data available between 25 and 300 °C. The latter permits conducting thermodynamic parameter optimization of ΔfG°298 for REE aqueous species. Optimal matching of the rhabdophane solubility data between 25 and 100 °C requires modifying the ΔfG°298 values of REE3+ by 1–6 kJ/mol, whereas matching of the monazite solubility data between 100 and 300 °C requires modifying the ΔfG°298 values of both REE3+ and REEOH2+ by ∼ 2–10 kJ/mol and ∼ 15–31 kJ/mol, respectively. For xenotime, adjustments of ΔfG°298 values by 1–26 kJ/mol are only necessary for the REE3+ species. The optimizations indicate that the solubility of monazite in acidic solutions is controlled by the light (L)REE3+ species at <150 °C and the LREEOH2+ species at >150 °C, whereas the solubility of xenotime is controlled by the heavy (H)REE3+ species between 25 and 300 °C. Based on the optimization results, we conclude that the revised Helgeson-Kirkham-Flowers equation of state does not reliably predict the thermodynamic properties of REE3+, REEOH2+, and likely other REE hydroxyl species at hydrothermal conditions. We therefore provide an experimental database (ThermoExp_REE) as a basic framework for future updates, extensions with other ligands, and optimizations as new experimental REE data become available. The optimized thermodynamic properties of aqueous species and minerals are available open access to accurately predict the solubility of REE phosphates in fluid-rock systems. 

Instruction tuning is an effective technique to align large language models (LLMs) with human intent. In this work, we investigate how an adversary can exploit instruction tuning by injecting specific instruction-following examples into the training data that intentionally changes the model's behavior. For example, an adversary can achieve content injection by injecting training examples that mention target content and eliciting such behavior from downstream models. To achieve this goal, we propose AutoPoison, an automated data poisoning pipeline. It naturally and coherently incorporates versatile attack goals into poisoned data with the help of an oracle LLM. We showcase two example attacks: content injection and over-refusal attacks, each aiming to induce a specific exploitable behavior. We quantify and benchmark the strength and the stealthiness of our data poisoning scheme. Our results show that AutoPoison allows an adversary to change a model's behavior by poisoning only a small fraction of data while maintaining a high level of stealthiness in the poisoned examples. We hope our work sheds light on how data quality affects the behavior of instruction-tuned models and raises awareness of the importance of data quality for responsible deployments of LLMs. 

Microsphere photolithography (MPL) is an alternative low-cost technique for the large-scale fabrication of periodic structures, such as metasurfaces. This technique utilizes the photonic nanojet generated in the photoresist (PR), by microspheres in near proximity, which are exposed to collimated ultraviolet (UV) flood illumination. In the basic approach, a microsphere array is self-assembled on, or transferred to, the substrate prior to exposure. After exposure, the microspheres are washed away in the development step. The process to recover and clean these microspheres for reuse is complicated. This paper investigates the use of reusable microsphere masks created by fixing the microspheres on a UV transparent support. This is then brought into contact with the photoresist with controlled pressure. There is a trade-off between the quality of the fabricated samples and the wear of the mask determined by the contact pressure. The system is demonstrated using a digital micromirror device (DMD)-based direct-write exposure system to fabricate infrared (IR) metasurfaces. These metasurfaces are characterized and compared to simulation models. Finally, a series of 50 hierarchically patterned IR metasurfaces was fabricated using a single reusable mask. These samples had a <3% coefficient of variance when viewed with a thermal camera. This work shows the potential of mask-based MPL and other contact microlens array-based photolithography techniques for low-cost large-scale fabrication. 

(Per)alkaline complexes and carbonatites evolve through a complex sequence of magmatic-hydrothermal processes. Most of them are overprinted by late auto-metasomatic processes which involves the mobilization, fractionation and/or enrichment of critical elements, such as the rare earth elements (REE) [1]. However, our current ability to predict the behavior of REE in high temperature aqueous fluids and interpret these natural systems using geochemical modeling depends on the availability of thermodynamic data for the REE minerals and aqueous species. Previous experimental work on REE solubility has focused on acidic aqueous fluids up to ~300 °C and considered chloride, fluoride and sulfate as important ligands for their transport [2]. However, magmatic-hydrothermal systems that form these critical mineral deposits may cover a wider range of fluid chemistries spanning acidic to alkaline pH as well as temperatures and pressures at which the fluids are supercritical. A few recently published studies have shown that other ligands (e.g., REE carbonates and/or combined fluoride species) could become important in near-neutral to alkaline fluids [3,4], and that REE mobility can also be increased in saline alkaline fluids reacted with fluorite [5]. Here we present new hydrothermal REE hydroxyl/chloride speciation data and REE phosphate/hydroxide minerals [6,7], calcite and fluorite solubility experiments as a function of pH, salinity and temperature. We use an integrated approach to link a wide array of experimental techniques (solubility, calorimetry, and spectroscopy) with thermodynamic optimizations using GEMSFITS [8], and present the development of a new experimental database for REE and its integration into the MINES thermodynamic database (https://geoinfo.nmt.edu/mines-tdb). The latter permits simulating hydrothermal fluid-rock interaction and ore-forming processes in critical mineral deposits to better understand the behavior of REE during metasomatism.