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This study reports the cradle-to-wheel life cycle greenhouse gas (GHG) emissions resulting from enhanced oil recovery (EOR) using CO2 sourced from direct air capture (DAC). A Monte Carlo simulation model representing variability in technology, location, and supply chain is used to model the possible range of carbon intensities (CI) of oil produced through DAC-EOR. Crude oil produced through DAC-EOR is expected to have a CI of 449 tCO2/ mbbl. With 95% confidence, the CI is between 345 tCO2/mbbl to 553 tCO2/mbbl. Producing net-zero GHG emission oil through DAC-EOR is thus highly improbable. An example case of DAC-EOR in the U.S. Permian Basin shows that only in the unlikely instance of the most storage efficient sites using 100% renewable energy does DAC-EOR result in “carbon-negative” oil production. 

Abstract Several fishes swim by undulating a thin and elongated median fin while the body is mostly kept straight, allowing them to perform forward and directional maneuvers. We used a robotic vessel with similar fin propulsion to determine the thrust scaling and efficiency. Using precise force and swimming kinematics measurements with the robotic vessel, the thrust generated by the undulating fin was found to scale with the square of the relative velocity between the free streaming flow and the wave speed. A hydrodynamic efficiency is presented based on propulsive force measurements and modelling of the power required to oscillate the fin laterally. It was found that the propulsive efficiency has a broadly high performance versus swimming speed, with a maximum efficiency of 75%. An expression to calculate the swimming speed over wave speed was found to depend on two parameters: A p / A e (ratio between body frontal area to fin swept area) and C D / C x (ratio of body drag to fin thrust coefficient). The models used to calculate propulsive force and free-swimming speed were compared with experimental results. The broader impacts of these results are discussed in relation to morphology and the function of undulating fin swimmers. In particular, we suggest that the ratio of fin and body height found in natural swimmers could be due to a trade-off between swimming efficiency and swimming speed. 

Abstract The leakage of quantum information out of the two computational states of a qubit into other energy states represents a major challenge for quantum error correction. During the operation of an error-corrected algorithm, leakage builds over time and spreads through multi-qubit interactions. This leads to correlated errors that degrade the exponential suppression of the logical error with scale, thus challenging the feasibility of quantum error correction as a path towards fault-tolerant quantum computation. Here, we demonstrate a distance-3 surface code and distance-21 bit-flip code on a quantum processor for which leakage is removed from all qubits in each cycle. This shortens the lifetime of leakage and curtails its ability to spread and induce correlated errors. We report a tenfold reduction in the steady-state leakage population of the data qubits encoding the logical state and an average leakage population of less than 1 × 10⁻³throughout the entire device. Our leakage removal process efficiently returns the system back to the computational basis. Adding it to a code circuit would prevent leakage from inducing correlated error across cycles. With this demonstration that leakage can be contained, we have resolved a key challenge for practical quantum error correction at scale.