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At least 145 records · Page 8

Positioning Accuracy in a Concurrent Robot-CNC Hybrid Manufacturing System

Abstract Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.

Goodwin, Jesse↗

Porous but Mechanically Robust All-Inorganic Antireflective Coatings Synthesized using Polymers of Intrinsic Microporosity

Herein, we introduce polymer of intrinsic microporosity 1 (PIM-1) to design single-layer and multilayered all-inorganic antireflective coatings (ARCs) with excellent mechanical properties. Using PIM-1 as a template in sequential infiltration synthesis (SIS), we can fabricate highly uniform, mechanically stable conformal coatings of AlO x with porosities of ~50% and a refractive index of 1.41 compared to 1.76 for nonporous AlO x that is perfectly suited for substrates commonly used in high-end optical systems or touch screens (e.g., sapphire, conductive glass, bendable glass, etc.). We show that such films can be used as a single-layer ARC capable of reduction of the Fresnel reflections of sapphire to as low as 0.1% at 500 nm being deposited only on one side of the substrate. We also demonstrate that deposition of the second layer with higher porosity using block copolymers enables the design of graded-index double-layered coatings. AlO x structures with just two layers and a total thickness of less than 200 nm are capable of reduction of Fresnel reflections under normal illumination to below 0.5% in a broad spectral range with 0.1% reflection at 700 nm. Additionally, and most importantly, we show that highly porous single-layer and graded-index double-layered ARCs are characterized by high hardness and scratch resistivity. The hardness and the maximum reached load were 7.5 GPa and 13 mN with a scratch depth of about 130 nm, respectively, that is very promising for the structures consisting of two porous AlO x layers with 50% and 85% porosities, correspondingly. Such mechanical properties of coatings can also allow their application as protective layers for other optical coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗

Heterologous Assembly of Pleomorphic Bacterial Microcompartment Shell Architectures Spanning the Nano- to Microscale

Many bacteria use protein-based organelles known as bacterial microcompartments (BMCs) to organize and sequester sequential enzymatic reactions. Regardless of their specialized metabolic function, all BMCs are delimited by a shell made of multiple structurally redundant, yet functionally diverse, hexameric (BMC-H), pseudohexameric/trimeric (BMC-T), or pentameric (BMC-P) shell protein paralogs. When expressed without their native cargo, shell proteins have been shown to self-assemble into 2D sheets, open-ended nanotubes, and closed shells of ≈40 nm diameter that are being developed as scaffolds and nanocontainers for applications in biotechnology. Here, by leveraging a strategy for affinity-based purification, it is demonstrated that a wide range of empty synthetic shells, many differing in end-cap structures, can be derived from a glycyl radical enzyme-associated microcompartment. The range of pleomorphic shells observed, which span ≈2 orders of magnitude in size from ≈25 nm to ≈1.8 µm, reveal the remarkable plasticity of BMC-based biomaterials. In addition, new capped nanotube and nanocone morphologies are observed that are consistent with a multicomponent geometric model in which architectural principles are shared among asymmetric carbon, viral protein, and BMC-based structures.

36 MATERIALS SCIENCE↗

Iron precipitation under controlled oxygen flow: Mineralogical implications for BIF precursors in the Archean ocean

Banded iron formation (BIF) deposition in the Archean ocean is thought to have been initiated by the oxidation of dissolved iron into ferric primary precursor phases that descended through the water column and were deposited on the seafloor. Effective interpretation of the trace element and isotopic composition of BIFs in the geologic record requires an understanding of the identity and longevity of those precursor phases. Temporal and spatial variation in oxidant concentration and ocean chemistry may have driven precursor mineralogy. Furthermore, precursor phases may undergo transitions during descent and burial. This experimental study follows the evolution of iron mineralogy, speciation, and redox state during the precipitation of iron under variable oxygen fluxes and in fluids containing different iron-complexing anions (chloride, sulfate, and phosphate). Additionally, suspensions collected after incomplete oxidation were anoxically aged to simulate changes to precursor mineralogy during descent below the seawater redoxcline. Results from X-ray diffraction, sequential dissolution, colorimetric determination of Fe redox state, and Fe K-edge X-ray absorption fine structure spectroscopy showed that under all experimental conditions, intermediate precipitates collected before complete iron uptake contained mineralized ferrous iron. Purely ferric mineral assemblages were not observed until iron was removed from solution. In low-oxygen experiments, intermediate precipitates contained phases with stoichiometric Fe 2+ , including magnetite, vivianite, and green rust (GR). Chloride green rust (GR1) had more ferric iron than sulfate green rust (GR2) and more readily transitioned to magnetite via disproportionation. GR2 was stable over a broader range of iron uptake; magnetite appeared mainly as an additional oxidation product in sulfate solution. In high oxygen experiments, mineralized ferrous iron occurred in amorphous phases or as a non-stoichiometric component in ferric oxides; final ferric assemblages were less crystalline than in low-oxygen equivalents. Low concentrations of phosphate increased the total iron oxidation rate, but also increased the ferrous content of intermediate precipitates. The incorporation of phosphate stabilized GR2 and facilitated GR2 precipitation over a larger range of iron uptake. In higher concentrations of phosphate, vivianite and poorly crystalline ferric hydroxides formed in place of GR. Here, these findings suggest that over a range of possible ocean chemistries, mixed-valence phases may have been short lived but relevant precursors to BIF. Additionally, anionic chemistry and oxidant concentration are shown to influence the crystallinity and chemical resistivity of final ferric assemblages, affecting their reactivity during later anoxic burial.

58 GEOSCIENCES↗

Multilayered Cu-Carbon Nanotube Composites for Advanced Conductors

Improving the efficiency of electrical components is critical in reducing energy consumption for various industrial and residential applications, ranging from rotating machinery to all electric devices and electric vehicle (EV) components to power grid systems. Substituting Cu wires with reduced resistance conductors that incorporate carbon nanotubes (CNTs) into Cu─ultraconductive Cu (UCC) composites─has recently been considered a promising strategy to improve energy efficiency, power density, and/or performance across various applications. Here, in this study, we created stable material formulations [CNT-containing polyvinylpyrrolidone (PVP) in dimethylformamide (DMF) solution] and utilized commercially viable fabrication approaches (electrospinning and magnetron sputtering) that produced high-performance multilayered tape-based UCC composite architectures. Increasing the CNT volume fraction by sequential layering of the structure with additional Cu-CNT layers showed a nearly stepwise improved performance in electrical and mechanical properties. This study also provides valuable insight into the effectiveness of nitrogen doping in modifying the conductivity of the CNT matrix. Fabricated prototypes demonstrated a >10% increase in current carrying capacity and >10% improvement in mechanical strength compared to those obtained on pure Cu. We believe that the properties demonstrated here, combined with the scalable manufacturing pathway of our approach, pave the way in designing future advanced conductors for diverse energy efficient and high-performance electrical systems and applications.

Carbon nanotubes↗

Multiplication of Freestanding Compound Semiconductor Membranes from a Single Wafer by Alternating Growth with 2D Materials

Single-crystal compound semiconductors, such as III-N and III-V, are important building blocks for functional devices due to their high electron mobilities, wide range of bandgaps, and excellent optoelectronic properties. However, current methods to produce their freestanding membranes for heterointegration suffer from slow processes or poor material quality. Here, we demonstrate an approach to grow and harvest multiple wafer-scale single-crystal membranes with high throughput by introducing weak van der Waals interfaces between epitaxial layers. This is achieved by directly growing two-dimensional (2D) materials on compound semiconductors in their native deposition systems, which enables alternating growth of 2D material and compound semiconductor epitaxial layers in a single run. Each epilayer in the multi-stack structure is then sequentially harvested by mechanical exfoliation, producing multiple freestanding single-crystal membranes with extremely high throughput from a single wafer, primed for integration in mixed-dimensional heterostructures.

Han, Ne Myo↗

Multiplication of Freestanding Compound Semiconductor Membranes from a Single Wafer by Alternating Growth with 2D Materials

Single-crystal compound semiconductors, such as III-N and III-V, are important building blocks for functional devices due to their high electron mobilities, wide range of bandgaps, and excellent optoelectronic properties. However, current methods to produce their freestanding membranes for heterointegration suffer from slow processes or poor material quality. Here, we demonstrate an approach to grow and harvest multiple wafer-scale single-crystal membranes with high throughput by introducing weak van der Waals interfaces between epitaxial layers. This is achieved by directly growing two-dimensional (2D) materials on compound semiconductors in their native deposition systems, which enables alternating growth of 2D material and compound semiconductor epitaxial layers in a single run. Each epilayer in the multi-stack structure is then sequentially harvested by mechanical exfoliation, producing multiple freestanding single-crystal membranes with extremely high throughput from a single wafer, primed for integration in mixed-dimensional heterostructures.

Han, Ne Myo↗

Population-based heteropolymer design to mimic protein mixtures

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

59 BASIC BIOLOGICAL SCIENCES↗

Defect-mediated diffusion of implanted Mg in GaN: Suppressing dopant redistribution by sequential thermal and microwave annealing

The diffusion behavior of Mg in Mg/N co-implanted GaN is investigated in response to a set of annealing conditions and methodologies, namely, 1000 °C/30 min thermal anneal, by high-temperature pulsed gyrotron microwave annealing at 1420 or 1500 °C, or by thermal and microwave annealing, sequentially. After 1000 °C annealing, the diffusion of Mg in GaN is found to be negligible, as measured by secondary ion mass spectrometry. Annealing by gyrotron microwave annealing alone induces the diffusion of Mg at a rate on the order of 10 −12 cm 2 /s. However, the use of a thermal anneal before microwave gyrotron annealing reduces this rate by an order of magnitude to 10 −13 cm 2 /s. We find that a model that considers Mg diffusion from an inhomogeneous medium that contains a defect-rich implanted region near-surface to a relatively pristine region below the implant range better explains the observed diffusion behavior than a conventional model that assumes a homogeneous medium. By analyzing the diffusion behavior using the Boltzmann–Matano method, we present a discussion of reduction in [V Ga ] by thermal annealing at 1000 °C, leading to a suppressed diffusion coefficient during subsequent high-temperature annealing relative to diffusion after 1420/1500 °C annealing alone. This effect holds potential for improvement in the precision of selectively doped regions for future applications based on the (Al)GaN material system. An improved field profile control in real devices can increase the breakdown and current-handling capabilities in power electronic applications.

Meyers, V.↗

Dynamic deuterium retention properties of tungsten measured using laser-induced breakdown spectroscopy

Dynamic deuterium (D) retention properties of tungsten (W) are investigated under steady-state D plasma exposure in the PISCES-A linear plasma device. In contrast to static retention, dynamic retention is quickly released from the material at the termination of the incident plasma flux, and thus in-operando laser-induced breakdown spectroscopy (LIBS) measurements have been conducted during steady-state D plasma exposure. A procedure is, first, established to extract the dynamic retention component from the in-operando LIBS D I 656.1 nm line intensity, which can contain contributions from dynamic and static retention as well as background D/D 2 gas, excited by both steady-state and laser-induced plasmas. Using the developed procedure, the dynamic D retention in W is systematically examined while scanning the following plasma exposure parameters: incident ion energy, E i , sample temperature, T s , incident ion flux, Γ i . No clear E i dependence is seen in the range of E i ~ 45–175 eV, as expected from a small variation in the average implantation depth (~3-6 nm) of D in W. The dynamic retention is found to monotonously decrease with increasing T s from 348 to 573 K, while the total static retention is reported to peak at T s ~ 500–600 K. It is revealed that the dynamic retention linearly increases with increasing Γ i , and then saturates at Γ i ≥ 0.75 × 10 21 m –2 s –1 . Possible physical mechanisms for the observed dependence of the dynamic retention on T s and Γ i are discussed. Furthermore, sequential pure He, followed by pure D, plasma exposures show that the dynamic D retention is not strongly affected by He bubbles in the near-surface region.

super-saturated surface layer↗

Nuclear temperature and its dependence on the source neutron-proton asymmetry deduced using the Albergo thermometer

Albergo thermometers with double isotope, isotone and isobar yield ratio pairs with one proton or/and neutron difference are investigated. Without any extra sequential decay correction, a real temperature value of 4.9 ± 0.5 MeV is deduced from the yields of the experimentally reconstructed primary hot intermediate mass fragments (IMFs) from 64 Zn + 112 Sn collisions at 40 MeV/nucleon using the Albergo thermometer for the first time. An experimental sequential decay correction from the apparent temperatures to the real ones for twelve other reaction systems with different neutron-proton (N/Z) asymmetries in the same experiment, 70 Zn, 64 Ni on 112,124 Sn, 58,64 Ni, 197 Au, 232 Th at 40 MeV/nucleon, is performed using an empirical correction factor approach of Tsang et al. with the deduced 4.9 MeV temperature value. The dependence of nuclear temperature on the source N/Z asymmetry is further investigated using these deduced real source temperature values from the present thirteen systems. It is found that the deduced real source temperatures at the present source N/Z range show a rather weak dependence on the source N/Z asymmetry. In conclusion, by comparison between our previous results and those from other independent experiments, a consistent description for the N/Z asymmetry dependence of nuclear temperature is addressed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Polystyrene Hydrogenolysis to High-Quality Lubricants Using Ni/SiO 2

Pyrolytic and light-activated oxidation processes are leading technologies for utilizing polystyrene (PS) wastes. These approaches exhibit poor selectivities, use complex reactors, and require solvents. Hydrogenolysis is effective for deconstructing polyolefins, but its application to PS feedstocks has been limited. Herein, we demonstrate Ni/SiO 2 catalysts to facilitate PS (M w ≈ 97 kDa) hydrogenolysis to produce lubricant base oils possessing group IV properties, achieving maximum yields of 70% within 6 h at 300 °C and 70 bar of H 2 . Gas, liquid, and oil product yields are stable across reaction conditions, whereas hydrogenation of the PS aromaticity and reduction of the molecular weight benefit from higher temperatures and H 2 pressures. Time-dependent experiments underscore the importance of elevated H 2 pressure, revealing that PS hydrogenolysis occurs sequentially, with aromatic ring hydrogenation preceding degradation of the C–C backbone. Kinetic measurements with 1,2-diphenylethane as a probe molecule demonstrate that ring hydrogenation pis 3 orders of magnitude faster than internal C–C bond cleavage over Ni/SiO 2 . Ni/SiO 2 proves to be effective in the hydrogenolysis of heavier PS polymers and rigid commercial PS products. Conversely, flexibility and foam PS feeds result in Ni/SiO 2 deactivation, attributed to performance additives. Unlike polyolefins, the process produces very little methane and other light hydrocarbons. Furthermore, these findings expand the applicability of hydrogenolysis to PS feedstocks, offering a versatile solution and broadening the range of high-value products from PS to include lubricant base oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗

Heat rectification through single and coupled quantum dots

We study heat rectification through quantum dots in the Coulomb blockade regime using a master equation approach. We consider both cases of two-terminal and four-terminal devices. In the two-terminal configuration, we analyze the case of a single quantum dot with either a doubly-degenerate level or two non-degenerate levels. In the sequential tunneling regime we analyze the behaviour of heat currents and rectification as functions of the position of the energy levels and of the temperature bias. In particular, we derive an upper bound for rectification in the closed-circuit setup with the doubly-degenerate level. We also prove the absence of a bound for the case of two non-degenerate levels and identify the ideal system parameters to achieve nearly perfect rectification. The second part of the paper deals with the effect of second-order cotunneling contributions, including both elastic and inelastic processes. In all cases we find that there exists ranges of values of parameters (such as the levels' position) where rectification is enhanced by cotunneling. In particular, in the doubly-degenerate level case we find that cotunneling corrections can enhance rectification when they reduce the magnitude of the heat currents. For the four-terminal configuration, we analyze the non-local situation of two Coulomb-coupled quantum dots, each connected to two terminals: the temperature bias is applied to the two terminals connected to one quantum dot, while the heat currents of interest are the ones flowing in the other quantum dot. Remarkably, in this situation we find that non-local rectification can be perfect as a consequence of the fact that the heat currents vanish for properly tuned parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗