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Abstract Fragmentation of marine snow affects the downward flux of organic matter, and other aggregate‐associated compounds such as oil. Using phytoplankton aggregates, we demonstrate that marine snow with oil, termed marine oil snow, had a higher resistance to fragmentation compared to marine snow without oil when exposed to turbulence ex situ. At moderate shear levels, typical of the ocean mixed layer, 17% of marine snow without oil broke, whereas 63% of marine snow fragmented at intermediate shear. In contrast, only 17% and 33% of marine oil snow fragmented at the intermediate and highest shear levels, respectively. Our results suggest that oil increases the cohesion and stability of aggregates making them less susceptible to breaking. This work contributes toward explaining the exceptional oil sedimentation event following the 2010 spill in Gulf of Mexico. It also enhances our understanding of the factors that determine the probability of sinking aggregates to fragment. 

Abstract Complex oxides offer rich magnetic and electronic behavior intimately tied to the composition and arrangement of cations within the structure. Rare earth iron garnet films exhibit an anisotropy along the growth direction which has long been theorized to originate from the ordering of different cations on the same crystallographic site. Here, we directly demonstrate the three-dimensional ordering of rare earth ions in pulsed laser deposited (Eu_xTm_1-x)₃Fe₅O₁₂garnet thin films using both atomically-resolved elemental mapping to visualize cation ordering and X-ray diffraction to detect the resulting order superlattice reflection. We quantify the resulting ordering-induced ‘magnetotaxial’ anisotropy as a function of Eu:Tm ratio using transport measurements, showing an overwhelmingly dominant contribution from magnetotaxial anisotropy that reaches 30 kJ m⁻³for garnets with x = 0.5. Control of cation ordering on inequivalent sites provides a strategy to control matter on the atomic level and to engineer the magnetic properties of complex oxides. 

Understanding the effect of hydrodynamics on aggregate size and structure is key to predicting mass transport in the aquatic environment. Aggregation theory of particles is well established but our knowledge of deformation processes, biological bonding forces, and their effects on fragmentation of aquatic aggregates is still limited. To better comprehend fragmentation processes and adhesion forces we implemented breakup experiments with diatom and microplastic aggregates made in the laboratory. We captured a substantial number of events showing deformation and subsequent fragmentation of these aggregates in an oscillatory shear flow. Polystyrene and polyethylene aggregates showed distinct fragmentation strengths and provided comparative upper and lower limits to the biological bonding strength of the diatom aggregates. Additionally, we employed a force balance model to evaluate attractive interactions within clusters of particles using the Lagrangian stress history and morphology. We found that the fractal structures of aggregates led to a power law of breakup strength with size and that time-integrated stress governed the overall fragmentation process. We also found that the weakening of the aggregates through deformation with shear exposure enabled their disaggregation at very low shear rates typical of the ocean environment. 

Abstract Ferrimagnetic oxide thin films are important material platforms for spintronic devices. Films grown on low symmetry orientations such as (110) exhibit complex anisotropy landscapes that can provide insight into novel phenomena such as spin‐torque auto‐oscillation and spin superfluidity. Using spin‐Hall magnetoresistance measurements, the in‐plane (IP) and out‐of‐plane (OOP) uniaxial anisotropy energies are determined for a thickness series (5–50 nm) of europium iron garnet (EuIG) and thulium iron garnet (TmIG) films epitaxially grown on a gadolinium gallium substrate with (110) orientation and capped with Pt. Pt/EuIG/GGG exhibits an (001) easy plane of magnetization perpendicular to the substrate, whereas Pt/TmIG/GGG exhibits an (001) hard plane of magnetization perpendicular to the substrate with an IP easy axis. Both IP and OOP surface anisotropy energies comparable in magnitude to the bulk anisotropy are observed. The temperature dependence of the surface anisotropies is consistent with first‐order predictions of a simplified Néel surface anisotropy model. By taking advantage of the thickness and temperature dependence demonstrated in these ferrimagnetic oxides grown on the low symmetry (110) orientations, the complex anisotropy landscapes can be tuned to act as a platform to explore rich spin textures and dynamics. 

We present an efficient microwave and optical interface for quantum memories at 1.3 K based on tin-vacancy color centers in diamond and scalable integrated photonics. 

Particle size and settling speed determine the rate of particulate mass transfer from the ocean surface to the sea bed. Turbulent shear in the ocean can act on large, faster-settling flocculated particles to break them into slower-settling primary particles or sub-aggregates. However, it is difficult to understand the disruption behavior of aggregates and their response to varying shear forces due to the complex ocean environment. A study was conducted to simulate the disruption behavior of marine aggregates in the mixed layer of the ocean. The breakup process was investigated by aggregating and disrupting flocs of bentonite clay particles in a rotating and oscillating cylindrical tank 10 cm in diameter filled with salt water. This laboratory tank, which operated based on an extension of Stokes’ second problem inside a cylinder, created laminar oscillating flow superimposed on a constant rotation. This motion allowed the bentonite particles to aggregate near the center of the tank but also exposed large aggregates to high shear forces near the wall. A high-speed camera system was used, along with particle tracking measurements and image processing techniques, to capture the breakup of the large particle aggregates and locate their radial position. The breakup response of large aggregates and the sizes of their daughter particles after breakup were quantified using the facility. The disruption strength of the aggregated particles is presented and discussed relative to their exposure to varying amounts of laminar shear. 

The fate of particulate matter in the ocean is determined in large part by its size and settling rate. Disaggregation, caused by turbulence-induced shear, acts to fracture or erode large particles into slower-settling sub-aggregates and primary particles. The strength and breakup response of organic marine aggregates (i.e. marine snow particles consisting of phytoplankton) is poorly understood, limiting our ability to accurately predict marine particle transport effects on the global carbon cycle. A study was conducted to enable the investigation of disaggregation effects on these organic marine particle aggregates. Due to the fragile nature of the Phytoplankton cells and their resulting aggregates, test facilities that do not rely on external sampling or pumps are required. A novel rolling aggregation tank was developed that can both aggregate phytoplankton cells under varying hydrodynamic conditions and then expose them to calibrated shear forces using laminar oscillating flow. The theory behind the operation of this tank is presented along with the necessary operating conditions to create stable regions within the tank where particle settling effects are minimal but shear is still representative of values expected in the open ocean. Phytoplankton was cultured in the laboratory to create simulated marine snow particles in the open ocean for disaggregation experiments. The procedure to calculate and track the shear-history of each aggregate is described and how the data generated from this facility will be used to quantify disaggregation parameters relevant for population balance modeling is discussed. 

Abstract Diffusion in alloys is an important class of atomic processes. However, atomistic simulations of diffusion in chemically complex solids are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interest. In this work, long‐timescale simulation methods are developed using reinforcement learning (RL) that extends simulation capability to match the duration of experimental interest. Two special limits, RL transition kinetics simulator (TKS) and RL low‐energy states sampler (LSS), are implemented and explained in detail, while the meaning of general RL are also discussed. As a testbed, hydrogen diffusivity is computed using RL TKS in pure metals and a medium entropy alloy, CrCoNi, and compared with experiments. The algorithm can produce counter‐intuitive hydrogen‐vacancy cooperative motion. We also demonstrate that RL LSS can accelerate the sampling of low‐energy configurations compared to the Metropolis–Hastings algorithm, using hydrogen migration to copper (111) surface as an example.