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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cross Section Generation Capability in Griffin

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of steady-state solvers for fixed-source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code reads multigroup cross sections in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. The implementation of the cross section generation capability in Griffin was initiated last year by plugging in the cross section application programming interface (CSAPI) and reviewing the methodologies for treating particulate fuels. The focus this year was on improving the CSAPI integration and implementing advanced self-shielding methods for applications to advanced reactor problems with TRISO fuels. First, the process for cross section library generation was updated to accurately and rigorously produce isotopic cross section data. Second, the on-the-fly slowing down method for the resonance treatment was implemented in CSAPI to improve the accuracy of effective multigroup cross sections in the resonance energy range. Among various on-the-fly slowing down methods, the equivalent Dancoff factor cell method was employed. Third, the iterative local spatial self-shielding method was implemented under the calculation framework of the equivalent Dancoff factor cell method to accurately deal with the double heterogeneity effect of particulate fuel. The updated CSAPI with the advanced self-shielding methods, together with the cross section libraries generated based on the improved process, were tested for the very high temperature reactor (VHTR), high temperature test reactor (HTTR), and Empire benchmark problems with various resonance self-shielding conditions, indicating that the updated CSAPI in Griffin is able to produce multigroup cross sections accurately and efficiently. We also show that the methodology works well for pebble bed fuel from HTR-10, but the capability still needs to be fully integrated into CSAPI. In the future, further benchmark tests will be performed for various thermal reactor core problems, including particulate fuel-based pebble bed reactors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Titanium-Cerium Electrode-Decoupled Redox Flow Batteries Integrated With Fossil Fuel Assets For Load-Following, Long-Duration Energy Storage

Operation of fossil plants at partial capacity with frequent cycling results in decreased efficiency, increased emissions and increased wear and maintenance. The objective of this project is to advance the integration of a titanium-cerium electrode-decoupled redox flow battery (RFB) system with conventional fossil-fueled power plants through technical and economic system-level studies and component scale-up and R&D. The Ti-Ce chemistry has a pathway to meet the DOE cost targets of $\$$100/kWh and $\$$0.05/kWh-cycle owing to the use of low-cost, earth abundant elemental actives and incorporation of inexpensive carbon felt electrodes and non-fluorinated anion exchange membrane (AEM) separators. The initial unit cell design was scaled up, with some modifications made to improve ease of manufacturing, from 25 cm 2 cell area to 400 cm 2 . Electrochemical tests demonstrated operation at a current density up to 50 mA/cm 2 , which is on par with other commercial RFB offerings. Furthermore, the Ti-Ce technology developed by WashU was evaluated and tested by industrial team partner, Giner, Inc., in their modular 3-cell stack. Several cell design modifications and alternate component material selections were successfully implemented to accommodate this chemistry while reducing polarization and leakage. Results from stack testing show high columbic efficiency and indicate that further optimization of cell compression and components will lead to successful operation of the Ti-Ce ED-RFB over longer duration at the multi-cell stack level. Engineering and cost analysis showed that an RFB system with power output on the order of 100 MW and with a charge/discharge duration of approx. 12 hours is the most cost effective for integration with fossil plants. At this scale, projected cycling of fossil fuel power plants can be significantly reduced. The use of a storage system is shown to reduce the fossil plant standalone cost of electricity by $\$$7/MWh, through increased capacity factor and improved average efficiency, in the scenario of high penetration of renewable power.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Microstructure Experiments-Enabled MARMOT Simulations of SiC/SiC-based Accident Tolerant Nuclear Fuel System

We have undertaken an experimental-computational project that addresses a few key technology gaps associated with the use of SiC/SiC composites for light water reactor fuel cladding. Two principal endeavors in this project are to assess the irradiation-induced microstructural changes and swelling in SiC/SiC composites, and to characterize and model the porous oxide surface layer (when exposed to steam) along SiC recession that is detrimental to the clad integrity under accident conditions. The project tasks are: (i) ion irradiation and characterization (University of Tennessee, Knoxville), (ii) mechanical tests and analysis (University of South Carolina), (iii) steam exposure tests (Oak Ridge National Laboratory), (iv) electron microscopy and spectroscopic characterization (NC State University), (v) x-ray microscopy and reconstruction (University of South Carolina and NC State University), (vi) phase field modeling and simulations (NC State University and Idaho National Laboratory). The effects of 10 MeV Au ion irradiation at 350°C on the microstructure evolution in SiC/SiC composites are investigated at doses up to 400 displacements per atom (dpa) at the University of Tennessee, Knoxville. Atomic force microscopy and optical profilometry reveal irradiation induced axial and radial shrinkage of the fibers for doses greater than 10 dpa. Based on detailed electron microscopy characterization, the primary cause of the fiber shrinkage is attributed to irradiation-induced loss of carbon packets. Additionally, the multilayer PyC interface is observed to portray high resistance to irradiation damage. The mechanical response and failure mechanisms of un-irradiated samples is also assessed through loading tests and X-ray imaging at the University of South Carolina. Steam exposure tests are performed at the Oak Ridge National Laboratory in a facility that represents a reactor pressure vessel under a loss-of-coolant-accident scenario. The samples that are analyzed methodically in this report are tested for 32/31 hours at 1200°C with a velocity of 0.25 cm/s for the pressures: 0.1 MPa, 0.45 MPa, 0.92 MPa and 1.38 MPa. Scanning/transmission electron microscopy analysis conducted at the NC State University (NCSU) shows that the oxide layer thickness increases with the steam pressure. While the oxide layer is crystalline (α- cristobalite) for the pressures 0.45 MPa, 0.92 MPa and 1.38 MPa, the layer is amorphous at 0.1 MPa. Results from Raman spectroscopy have also confirmed the formation of α-cristobalite phase of SiO₂. The abrupt increase in the integrated Raman intensity ratio between steam pressures 0.1 and 0.45 MPa suggests the onset of accelerated crystallization. Non-destructive three dimensional X-ray microscopy/tomography (XCT) and computational image processing techniques are employed by the University of South Carolina to probe the porous oxidation features on SiC samples at varying pressures. Interestingly, most pores are observed to be located away from the surface as well as the oxide-SiC interface. The average oxide layer thickness assessed from the XCT analysis is seen to be in excellent agreement with the values determined through scanning electron microscopy analysis for the highest pressures where the oxide layer is relatively more uniform. A phase-field model developed by the NC State University and Idaho National Laboratory for simulating oxidation of SiC by steam captures the paralinear kinetics of SiC oxidation with a high degree of fidelity. Results from quasi-one-dimensional and two dimensional simulations show that the pores with oxidizing species lead to a higher volatilization rate. These simulations indicate that the enhanced apparent volatilization rates at higher pressures observed in experiments can be rationalized by the increased volatilization from the pores. The project team has also successfully developed the capability to import images from experiments for realistic evolution of the oxidizing microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A modified thermodynamic sea ice model and its application

This paper presents a modified thermodynamic sea ice model based on the Winton’s three-layer model framework. Several improvements focused on the vertical thermodynamics have been made in the model. Results from a series of one-dimensional experiments show that equilibrium ice thickness in our modified model is increased by about 45 cm when compared with the original Winton’s model. Sensitivity tests indicate that all modifications mentioned above contribute to this change of ice thickness, among which the increase of ice layer has the most significant effect followed by the sea ice conductivity parameterization. The modified thermodynamic sea ice model is then coupled into the sea ice component SIS in GFDL MOM4 to exert long-term integration experiments forced by CORE2.0 data. Results indicate that the modified model shows significant improvement in simulating the Arctic sea ice, including an increase in both the sea ice thickness and volume over the whole Arctic region. This confirms the above founding from 1-D simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Exploring the structural uniformity and integrity of protonic ceramic thin film electrolyte using wet powder spraying

Thin protonic ceramic electrolyte contributes to lower ohmic resistance and enhances electrochemical performance of protonic ceramic electrochemical cells. However, manufacturing of large-scale thin electrolyte remains a challenge. Wet powder spraying is an attractive technique to deposit <10 µm thin electrolyte when advanced atomizing techniques and optimized spraying process are integrated. Here ultrasonic atomization is integrated in the wet powder spray technique to reduce the thickness of electrolyte. Moreover, a parametric study is conducted to optimize the wet powder spray process to deposit uniform and crack-free electrolyte film. It is illustrated that tuning of solid loading rates and spray passes can affect the morphology of the as-sprayed electrolyte film, enabling the structural compactness of the sintered electrolyte layer. To maintain chemical stability of the electrolyte layer during sintering, effect of sintering temperature is further investigated to produce a physically thin, structurally dense, and chemically homogeneous electrolyte layer. The protonic ceramic electrochemical cells fabricated with optimized spraying and sintering parameters demonstrate excellent performance under both fuel cell and electrolysis modes. In addition, the cells exhibit remarkable structural integrity during redox and long-term stability tests.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Absorbing boundary conditions in material point method adopting perfectly matched layer theory

This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work integrates the Perfectly Matched Layer (PML) theory into the implicit MPM framework. The proposed approach introduces absorbing particles surrounding the computational domain that efficiently absorb outgoing waves and reduce reflections, allowing for accurate modeling of wave propagation and its further impact on geotechnical slope stability analysis. The study also includes several benchmark tests to validate the effectiveness of the proposed method, such as several types of impulse loading and symmetric and asymmetric base shaking. The conducted numerical tests also demonstrate the ability to handle large deformation problems, including the failure of elasto-plastic soils under gravity and dynamic excitations. The findings extend the capability of MPM in simulating continuous analysis of earthquake-induced landslides, from shaking to failure.

58 GEOSCIENCES↗
DOE OSTI2021

Cross Section Generation Capability in Griffin

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of steady-state solvers for fixed-source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code reads multigroup cross sections in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. The implementation of the cross section generation capability in Griffin was initiated last year by plugging in the cross section application programming interface (CSAPI) and reviewing the methodologies for treating particulate fuels. The focus this year was on improving the CSAPI integration and implementing advanced self-shielding methods for applications to advanced reactor problems with TRISO fuels. First, the process for cross section library generation was updated to accurately and rigorously produce isotopic cross section data. Second, the equivalent Dancoff factor cell method performing slowing down calculations on the fly for the resonance treatment was implemented in CSAPI to improve the accuracy of effective multigroup cross sections in the resonance energy range. Third, the iterative local spatial self-shielding method was implemented under the calculation framework of the equivalent Dancoff factor cell method to accurately deal with the double heterogeneity effect of particulate fuel. The updated CSAPI with the advanced self-shielding methods, together with the cross section libraries generated based on the improved process, were tested for pin-cell, unit-cell, and fuel assembly problems with various resonance self-shielding conditions based on very high temperature reactor, high temperature test reactor, and Empire benchmark cores, indicating that the updated CSAPI in Griffin is able to produce multigroup cross sections accurately and efficiently. We also showed that the methodology worked well for pebble bed fuel from HTR-10, but the capability still needs to be fully integrated into CSAPI. In the future, further benchmark tests will be performed for various thermal reactor core problems, including particulate fuel-based pebble bed reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Benchmarking Solid-State Batteries Containing Sulfide Separators: Effects of Electrode Composition and Stack Pressure

Integrating sulfide separators into solid-state batteries (SSBs) containing high energy cathodes typically requires one or more materials and engineering solutions including: (i) applying interfacial coatings to mitigate electrolyte decomposition, (ii) applying high stack pressures to form robust solid-solid contacts, and (iii) using alloying anodes to avoid Li dendrite formation. Despite the promise of these approaches, a lack of standardized testing protocols makes it difficult to directly compare results among different studies. To address this problem, the present work benchmarks the performance of SSBs containing β-Li 3 PS 4 (LPS) separators and composite cathodes. By systematically varying the anode/cathode composition and stack pressure, this work demonstrates that cathode design is a major bottleneck for solid-state cells cycled at low rates (<100 µA cm -2 ). Operando stack pressure measurements show that, while mechanical confinement generally promotes higher active material utilization and cycling stability, this strategy alone does not address interfacial reactivity between LPS and high voltage cathodes. Here, these results also demonstrate that stress evolution during cycling is dominated by volume changes at the Li metal anode. Finally, we show that FeS 2 cathodes with moderate operating voltages (<3 V vs Li/Li + ) exhibit superior cycling performance compared to high voltage cathodes by facilitating formation of stable cathode/electrolyte interfaces.

25 ENERGY STORAGE↗
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Type IIB at eight derivatives: insights from Superstrings, Superfields and Superparticles

We study the non-linear structure of Type IIB eight-derivative couplings involving the metric and the complexified three-form G 3 . We show that, at the level of five-point string amplitudes, the kinematics in the maximally R-symmetry-violating sector is fully matched by standard superspace integrals and by superparticle amplitudes in M-theory on a two-torus. The latter approach is used to determine the complete effective action in this sector and to verify its invariance under SL(2, Z) duality. We further comment on the general structure of the higher-point kinematics. Compactifications to lower dimensions provide both tests for our results and the arena for their applications. We verify that K 3 reductions are fully consistent with the constraints of six-dimensional supersymmetry, and derive the four-dimensional flux scalar potential and axion kinetic terms at order (α') 3 in Calabi-Yau threefold reductions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Stabilizing a Li–Mn–O Cathode by Blocking Lattice O Migration through a Nanoscale Phase Complex

Among all intercalation cathodes for Li-ion batteries, Li–Mn–O layered oxides offer the highest initial energy density at the lowest cost, due to the joint contribution from cationic and anionic redox chemistry. However, the poor cycling capability, resulting from the continuous lattice O loss at high potentials (>4.5 V), hinders practical applications. Herein, we employed phase complex engineering to obtain a new Li–Mn–O nanohybrid cathode featuring the uniform and coherent integration of layered nanodomains and spinel nanodomains. The combination of DFT calculations, synchrotron-based transmission X-ray microscopy, in situ differential electrochemical mass spectrometry, in situ synchrotron XRD, and electrochemical tests demonstrated that the O migration path in layered nanodomains was blocked by the neighboring spinel nanodomains with a higher oxygen vacancy migration energy, thus effectively suppressing the irreversible lattice O loss at high potentials and enhancing the cycling stability in both capacity and average voltage. Finally, the strategy is experimentally demonstrated to be effective and it leads to a new path for developing stable high-energy-density cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Twenty Years of Progress, Challenges, and Opportunities in Measuring and Understanding Soil Respiration

Abstract Soil respiration (Rs), the soil‐to‐atmosphere flux of CO 2 , is a dominant but uncertain part of the carbon cycle, even after decades of study. This review focuses on progress in understanding Rs from laboratory incubations to global estimates. We survey key developments of in situ ecosystem‐scale Rs observations and manipulations, synthesize Rs meta‐analyses and global flux estimates, and discuss the most compelling challenges and opportunities for the future. Increasingly sophisticated lab experiments have yielded insights into the interaction among heterotrophic respiration, substrate supply, and enzymatic kinetics, and extended incubation‐based analyses across space and time. Observational and manipulative field‐based experiments have used improved measurement approaches to deepen our understanding of the integrated effects of environmental change and disturbance on Rs. Freely‐available observational databases have enabled meta‐analyses and studies probing the magnitude of, and constraints on, the global Rs flux. Key challenges for the field include expanding Rs measurements, experiments, and opportunities to under‐represented communities and ecosystems; reconciling independent estimates of global respiration fluxes and trends; testing and leveraging the power of machine learning and process‐based models, both independently and in conjunction with each other; and continuing the field's tradition of using novel experiments to explore diverse mechanisms and ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Open Call LDRD: Physically Informed Autoencoders for Galactic Redshift Regression

Physical constraints have been suggested to make neural network models more generalizable, act scientifically plausible, and be more data-efficient over unconstrained baselines. In this report, we present preliminary work on evaluating the effects of adding soft physical constraints to computer vision neural networks trained to estimate the conditional density of redshift on input galaxy images for the Sloan Digital Sky Survey. We introduce physically motivated soft constraint terms that are not implemented with differential or integral operators. We frame this work as a simple ablation study where the effect of including soft physical constraints is compared to an unconstrained baseline. We compare networks using standard point estimate metrics for photometric redshift estimation, as well as metrics to evaluate how faithful our conditional density estimate represents the probability over the ensemble of our test dataset. We find no evidence that the implemented soft physical constraints are more effective regularizers than augmentation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Computationally evaluating high-yield metabolites for sustainable aviation fuel (SAF) using machine learning

The computational tool described in this report helps identify promising biological pathways that produce SAF platform molecules (either a drop-in SAF, or a precursor that can be easily converted to a drop-in SAF). The workflow the computational tool follows first identifies possible biological pathways from a user-defined metabolite. These pathways may, or may not lead to a SAF platform molecule, thus the second step involves insilico testing of the end product of each pathway to assess whether it is, or is not, a SAF platform molecule. The identification of biological pathways performed in the first step is facilitated by linking the metabolite to a biological reaction database. Pathways are found by identifying pathways in the reaction database that include the metabolite. The computational tool includes an alternative way to find pathways. The alternative way develops a Flux Balanced Analysis (FBA), and modifying the FBA to include reactions that transform the metabolite. These modifications serve as a basis for understanding, in a semi-quantitative way, if there is an increase in the flux to desirable products. The second step, in silico testing of the end-products, is accomplished by estimating key physical properties relevant to SAF. When good models are available, we have integrated those models into the computational tool. In a few instances, we have developed our own models. In all instances, we have validated the models against available measured data. Finally, we have evaluated the effectiveness of our computational tool by genetically engineering Rhodosporidium toruloides. Validation occurred without the use of a FBA, and further validation is required.

09 BIOMASS FUELS↗
DOE OSTI2025

Resonant shattering flares as asteroseismic tests of chiral effective field theory

Chiral effective field theory (𝜒⁢EFT) has proved to be a powerful microscopic framework for predicting the properties of neutron-rich nuclear matter with quantified theoretical uncertainties up to about twice the nuclear saturation density. Tests of 𝜒⁢EFT predictions are typically performed at low densities using nuclear experiments, with neutron star (NS) constraints only being considered at high densities. In this work, we discuss how asteroseismic quasinormal modes within NSs could be used to constrain specific matter properties at particular densities not just the integrated quantities to which bulk NS observables are sensitive. We focus on the crust-core interface mode, showing that measuring this mode's frequency would provide a meaningful test of 𝜒⁢EFT at densities around half the saturation density. Conversely, we use nuclear matter properties predicted by 𝜒⁢EFT to estimate that this mode's frequency is around 185 ± 50Hz. Asteroseismic observables such as resonant phase shifts in gravitational-wave signals and multimessenger resonant shattering flare timings, therefore, have the potential to provide useful tests of 𝜒⁢EFT.

effective field theory↗
DOE OSTI2021

Differential cross-section measurements for the electroweak production of dijets in association with a Z boson in proton–proton collisions at ATLAS

Differential cross-section measurements are presented for the electroweak production of two jets in association with a Z boson. These measurements are sensitive to the vector-boson fusion production mechanism and provide a fundamental test of the gauge structure of the Standard Model. The analysis is performed using proton–proton collision data collected by ATLAS at √s=13 TeV and with an integrated luminosity of 139 fb -1 . The differential cross-sections are measured in the Z→ℓ + ℓ - decay channel (ℓ=e,μ) as a function of four observables: the dijet invariant mass, the rapidity interval spanned by the two jets, the signed azimuthal angle between the two jets, and the transverse momentum of the dilepton pair. The data are corrected for the effects of detector inefficiency and resolution and are sufficiently precise to distinguish between different state-of-the-art theoretical predictions calculated using Powheg+Pythia8, Herwig7+Vbfnlo and Sherpa 2.2. The differential cross-sections are used to search for anomalous weak-boson self-interactions using a dimension-six effective field theory. The measurement of the signed azimuthal angle between the two jets is found to be particularly sensitive to the interference between the Standard Model and dimension-six scattering amplitudes and provides a direct test of charge-conjugation and parity invariance in the weak-boson self-interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗