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  1. Zuun Mod is a porphyry-type Mo-Cu deposit located in the Edren terrane in Southwest Mongolia. The deposit has estimated resources of 218 Mt with an average Mo grade of 0.057% and Cu grade of 0.069%, and significant amounts of Re. The deposit is characterized by multiple pulses of magmatism and exsolution of magmatic ore fluids and associated alteration and mineralization. The timing of these events and the tectonic environment were unconstrained, and the deposit’s origin remains controversial. Based on drill core and field examinations, four lithological units of the Bayanbulag intrusive complex are identified in the deposit area including quartz syenite, quartz monzonite, granodiorite, and granite. The majority of Mo mineralization at Zuun Mod occurs in sheeted and stockwork quartz veins that crosscut units of the Bayanbulag complex as well as disseminations within altered granitoids wherein the mineralized quartz veins occur with potassic and phyllic alteration selvages. Zircon U-Pb age dating for quartz monzonite and granodiorite defined the timing of magmatic events at 305.3 ± 3.6 Ma and 301.8 ± 2.7 Ma, respectively. Molybdenite Re-Os geochronology on grains from a quartz vein with potassic alteration selvage determined the age of Mo mineralization at 297 ± 4.8 Ma. Lithogeochemical data of intrusive units suggest the granitoid rocks show calc-alkaline to high-K calc-alkaline, I-type, and metaluminous to slightly peraluminous affinities that formed in a post-collisional setting and were likely sourced from subduction-modified lithosphere. Lithogeochemical signatures and the tectonic environment classify Zuun Mod into neither Climax nor Endako-types, but as a Mo-rich porphyry Cu deposit. 
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    Free, publicly-accessible full text available November 1, 2024
  2. Abstract Uncertainties in ocean-mixing parameterizations are primary sources for ocean and climate modeling biases. Due to lack of process understanding, traditional physics-driven parameterizations perform unsatisfactorily in the tropics. Recent advances in the deep-learning method and the new availability of long-term turbulence measurements provide an opportunity to explore data-driven approaches to parameterizing oceanic vertical-mixing processes. Here, we describe a novel parameterization based on an artificial neural network trained using a decadal-long time record of hydrographic and turbulence observations in the tropical Pacific. This data-driven parameterization achieves higher accuracy than current parameterizations, demonstrating good generalization ability under physical constraints. When integrated into an ocean model, our parameterization facilitates improved simulations in both ocean-only and coupled modeling. As a novel application of machine learning to the geophysical fluid, these results show the feasibility of using limited observations and well-understood physical constraints to construct a physics-informed deep-learning parameterization for improved climate simulations. 
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  3. Abstract

    The erratic, intermittent, and unpredictable nature of sweat production, resulting from physiological or psychological fluctuations, poses intricacies to consistently and accurately sample and evaluate sweat biomarkers. Skin‐interfaced microfluidic devices that rely on colorimetric mechanisms for semi‐quantitative detection are particularly susceptible to these inaccuracies due to variations in sweat secretion rate or instantaneous volume. This work introduces a skin‐interfaced colorimetric bifluidic sweat device with two synchronous channels to quantify sweat rate and biomarkers in real‐time, even during uncertain sweat activities. In the proposed bifluidic‐distance metric approach, with one channel to measure sweat rate and quantify collected sweat volume, the other channel can provide an accurate analysis of the biomarkers based on the collected sweat volume. The closed channel design also reduces evaporation and resists contamination from the external environment. The feasibility of the device is highlighted in a proof‐of‐the‐concept demonstration to analyze sweat chloride for evaluating hydration status and sweat glucose for assessing glucose levels. The low‐cost yet highly accurate device provides opportunities for clinical sweat analysis and disease screening in remote and low‐resource settings. The developed device platform can be facilely adapted for the other biomarkers when corresponding colorimetric reagents are exploited.

     
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  4. Abstract Studies of molecular mixtures containing hydrogen sulfide (H 2 S) could open up new routes towards hydrogen-rich high-temperature superconductors under pressure. H 2 S and ammonia (NH 3 ) form hydrogen-bonded molecular mixtures at ambient conditions, but their phase behavior and propensity towards mixing under pressure is not well understood. Here, we show stable phases in the H 2 S–NH 3 system under extreme pressure conditions to 4 Mbar from first-principles crystal structure prediction methods. We identify four stable compositions, two of which, (H 2 S) (NH 3 ) and (H 2 S) (NH 3 ) 4 , are stable in a sequence of structures to the Mbar regime. A re-entrant stabilization of (H 2 S) (NH 3 ) 4 above 300 GPa is driven by a marked reversal of sulfur-hydrogen chemistry. Several stable phases exhibit metallic character. Electron–phonon coupling calculations predict superconducting temperatures up to 50 K, in the Cmma phase of (H 2 S) (NH 3 ) at 150 GPa. The present findings shed light on how sulfur hydride bonding and superconductivity are affected in molecular mixtures. They also suggest a reservoir for hydrogen sulfide in the upper mantle regions of icy planets in a potentially metallic mixture, which could have implications for their magnetic field formation. 
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  5. Toll/Toll-like receptors (TLRs) are key regulators of the innate immune system in both invertebrates and vertebrates. However, while mammalian TLRs directly recognize pathogen-associated molecular patterns, the insect Toll pathway is thought to be primarily activated by binding Spätzle cytokines that are processed from inactive precursors in response to microbial infection. Phylogenetic and structural data generated in this study supported earlier results showing that Toll9 members differ from other insect Tolls by clustering with the mammalian TLR4 group, which recognizes lipopolysaccharide (LPS) through interaction with myeloid differentiation-2 (MD-2)–like proteins. Functional experiments showed that BmToll9 from the silkmothBombyx morialso recognized LPS through interaction with two MD-2–like proteins, previously named BmEsr16 and BmPP, that we refer to in this study as BmMD-2A and BmMD-2B, respectively. A chimeric BmToll9–TLR4 receptor consisting of the BmToll9 ectodomain and mouse TLR4 transmembrane and Toll/interleukin-1 (TIR) domains also activated LPS-induced release of inflammatory factors in murine cells but only in the presence of BmMD-2A or BmMD-2B. Overall, our results indicate that BmToll9 is a pattern recognition receptor for LPS that shares conserved features with the mammalian TLR4–MD-2–LPS pathway.

     
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  6. Abstract

    Cutaneous muscles drive the texture‐modulation behavior of cephalopods by protruding several millimeters out of the skin. Inspired by cephalopods, a self‐morphing, stretchable smart skin containing embedded‐printed electrodes and actuated by Twisted Spiral Artificial Muscles (TSAMs) is proposed. Electrothermally actuated TSAMs are manufactured from inexpensive polymer fibers to mimic the papillae muscles of cephalopods. These spirals can produce strains of nearly 2000% using a voltage of only 0.02 V mm−1. Stretchable and low‐resistance liquid metal electrodes are embedded‐printed inside the self‐morphing skin to facilitate the electrothermal actuation of TSAMs. Theoretical and numerical models are proposed to describe the embedded printing of low‐viscosity Newtonian liquid metals as conductive electrodes in a soft elastomeric substrate. Experimental mechanical tests are performed to demonstrate the robustness and electrical stability of the electrodes. Two smart skin prototypes are fabricated to highlight the capabilities of the proposed self‐morphing system, including a texture‐modulating wearable soft glove and a waterproof skin that emulates the texture‐modulation behavior of octopi underwater. The proposed self‐morphing stretchable smart skin can find use in a wide range of applications, such as refreshable Braille displays, haptic feedback devices, turbulence tripping, and antifouling devices for underwater vehicles.

     
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