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At least 523 records · Page 29

Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis (BSA) project uses systems thinking and analysis to assess how techno economics, research and development, deployment strategies, policy, and market conditions affect the potential development trajectories of the developing bioenergy industry. This project informs researchers, decision makers, and industry by identifying opportunities for and constraints to industrial development and quantifying important industry metrics (e.g., energy, economic, environmental) towards a sustainable domestic bioenergy system. One of the tools used in this project, the Bioenergy Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. Analysis products from this effort enable the development of the bioenergy industry by (1) encouraging policy-makers to explore multiple levers simulating outside impacts on biofuels production, identifying policy actions; (2) improving industry's understanding of growth potential under different market conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with analysis tools and analyses that can be adapted to meet research and teaching objectives, thus connecting students with careers that build the industry.

bioenergy↗

Modeling the effects of molecular disorder on the properties of Frenkel excitons in organic molecular semiconductors

The Frenkel exciton model offers a convenient framework for simulating electronic excitations in organic conjugated systems that are too large to address with atomistic level electronic structure methods. Parameterization of this model is typically based on analytical expressions that incompletely describe the spatial and temporal correlations that are inherent to many condensed phase molecular systems. In this manuscript, we introduce a general procedure for including these correlations in the Frenkel exciton model, by mapping them directly from all-atom molecular configurations, for instance from classical molecular dynamics. Regardless of system morphology, this mapping automatically captures the spatial and temporal molecular correlations that are otherwise difficult or impossible to represent in terms of low-dimensional correlation functions. We apply this procedure to study the excited state properties of condensed phase materials made up of thiophene oligomers. We demonstrate that Frenkel model parameters can be mapped from a series of single molecule electronic structure calculations, and that for these materials efficient semi-empirical methods are sufficient to accurately reproduce experimental spectral measurements. By analyzing the statistics of model parameters derived from materials with different characteristic morphologies, we highlight failures in some assumptions that are commonly applied when generating model parameters. Finally, by simulating exciton dynamics on a mapped Frenekel exciton model, we demonstrate the ability to quantify the effect of material morphology on the dynamic properties of excitons.

74 ATOMIC AND MOLECULAR PHYSICS↗

On classification of models of large local-type non-Gaussianity

We classify models generating large local-type non-Gaussianity into some categories by using some ''consistency relations'' among the non-linearity parameters f{sub NL}{sup local},τ{sub NL}{sup local} and g{sub NL}{sup local}, which characterize the size of bispectrum for the former and trispectrum for the latter two. Then we discuss how one can discriminate models of large local-type non-Gaussianity with such relations. We first classify the models by using the ratio of τ{sub NL}{sup local}/(6f{sub NL}{sup local}/5){sup 2}, which is unity for ''single-source'' models and deviates from unity for ''multi-source'' ones. We can make a further classification of models in each category by utilizing the relation between f{sub NL}{sup local} and g{sub NL}{sup local}. Our classification suggests that observations of trispectrum would be very helpful to distinguish models of large non-Gaussianity and may reveal the generation mechanism of primordial fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗

Utilizing guanine-coordinated Zn 2+ ions to determine DNA crystal structures by single-wavelength anomalous diffraction

The experimental phase determination of crystal structures of nucleic acids and nucleic acid–ligand complexes would benefit from a facile method. Even for double-stranded DNA, software-generated models are generally insufficiently accurate to serve as molecular replacement search models, necessitating experimental phasing. Here, it is demonstrated that Zn 2+ ions coordinated to the N7 atom of guanine bases generate sufficient anomalous signal for single-wavelength anomalous diffraction (SAD) phasing of DNA crystal structures. Using zinc SAD, three crystal structures of double-stranded DNA oligomers, 5'-AGGGATCCCT-3', 5'-GGGATCCC-3' and 5'-GAGGCCTC-3', were determined. By determining the crystal structure of one of these oligomers, GAGGCCTC, in the presence of Mg 2+ instead of Zn 2+ , it was demonstrated that Zn 2+ is not structurally perturbing. These structures allowed the analysis of structural changes in the DNA on the binding of analogues of the natural product mithramycin to two of these oligomers, AGGGATCCCT and GAGGCCTC. Zinc SAD may become a routine approach for determining the crystal structures of nucleic acids and their complexes with small molecules.

DNA–drug complexes↗

MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

60 APPLIED LIFE SCIENCES↗

LeWRON: Learning ElectroWeak phase tRansitiON with agentic architecture

An agent to analyze electroweak phase transition. LeWRON turns a BSM model description or a reproduction target into a structured run: symbolic setup, effective-potential artifacts, finite-temperature machinery, generated model code, a scientific report, and an interactive exploration session. It keeps both machine-readable artifacts and human-readable notes, so a run can be resumed, audited, revised, and shared.

Wang, Isaac [Fermi National Accelerator Laboratory↗

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗

Twistact techno-economic analysis for wind turbine applications.

This report is the final deliverable for a techno-economic analysis of the Sandia National Laboratories-developed Twistact rotary electrical conductor. The U.S. Department of Energy Wind Energy Technologies Office supported a team of researchers at Sandia National Laboratories and the National Renewable Energy Laboratory to evaluate the potential of the Twistact technology to serve as a viable replacement to rare-earth materials used in permanent-magnet direct-drive wind turbine generators. This report compares three detailed generator models, two as baseline technologies and a third incorporating the Twistact technology. These models are then used to calculate the levelized cost of energy (LCOE) for three comparable offshore wind plants using the three generator topologies. The National Renewable Energy Laboratory s techno-economic analysis indicates that Twistact technology can be used to design low-maintenance, brush-free, and wire-wound (instead of rare-earth-element (REE) permanent-magnet), direct-drive wind turbine generators without a significant change in LCOE and generation efficiency. Twistact technology acts as a hedge against sources of uncertain costs for direct-drive generators. On the one hand, for permanent-magnet direct-drive (PMDD) generators, the long-term price of REEs may increase due to increases in future demand, from electric vehicles and other technologies, whereas the supply remains limited and geographically concentrated. The potential higher prices in the future adversely affect the cost competitiveness of PMDD generators and may thwart industry investment in the development of the technology for wind turbine applications. Twistact technology can eliminate industry risk around the uncertainty of REE price and availability. Traditional wire-wound direct-drive generators experience reliability issues and higher maintenance costs because of the wear on the contact brushes necessary for field excitation. The brushes experience significant wear and require regular replacement over the lifetime of operation (on the order of a year or potentially less time). For offshore wind applications, the focus of this study, maintenance costs are higher than typical land-based systems due to the added time it often requires to access the site for repairs. Thus, eliminating the need for regular brush replacements reduces the uncertain costs and energy production losses associated with maintenance and replacement of contact brushes. Further, Twistact has a relatively negligible impact on LCOE but hedges risks associated with the current dominant designs for direct-drive generators for PMDD REE price volatility and wire-wound generator contact brush reliability. A final section looks at the overall supply chain of REEs considering the supply-side and demand-side drivers that encourage the risk of depending on these materials to support future deployment of not only wind energy but other industries as well.

17 WIND ENERGY↗

Investigating a Potential Hafnium Bias in SCALE [Slides]

Previous work has examined the evidence for a gadolinium bias within SCALE. This work extends the previous work to include benchmark models with hafnium experiments from the ICSBEP Handbook. VALID contains only one experiment with hafnium: MIX-COMP-THERM-008. Newly generated models provide an opportunity to assess the potential presence of a hafnium bias.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Scalable Truck Charging Demand Simulation for Cost-Optimized Infrastructure Planning

This project developed a scalable, high-resolution model to simulate medium- and heavy-duty (MHD) electric truck charging demand and assess its impact on grid infrastructure. Using generative modeling, simulation, and cost optimization, the project delivered an end-to-end software pipeline and a library of 96 real-world scenarios for the Dallas–Houston megaregion. We demonstrated a modular architecture for transportation and grid modeling, implemented cost-optimized infrastructure planning methods, and quantified grid capital, operational, and environmental costs across a wide range of truck electrification scenarios. The results have been adopted by major utility stakeholders and contributed to regional planning efforts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computational model for autophagic vesicle dynamics in single cells

Macroautophagy (autophagy) is a cellular recycling program essential for homeostasis and survival during cytotoxic stress. This process, which has an emerging role in disease etiology and treatment, is executed in four stages through the coordinated action of more than 30 proteins. An effective strategy for studying complicated cellular processes, such as autophagy, involves the construction and analysis of mathematical or computational models. When developed and refined from experimental knowledge, these models can be used to interrogate signaling pathways, formulate novel hypotheses about systems, and make predictions about cell signaling changes induced by specific interventions. Here, we present the development of a computational model describing autophagic vesicle dynamics in a mammalian system. We used time-resolved, live-cell microscopy to measure the synthesis and turnover of autophagic vesicles in single cells. The stochastically simulated model was consistent with data acquired during conditions of both basal and chemically induced autophagy. The model was tested by genetic modulation of autophagic machinery and found to accurately predict vesicle dynamics observed experimentally. Furthermore, the model generated an unforeseen prediction about vesicle size that is consistent with both published findings and our experimental observations. Taken together, this model is accurate and useful and can serve as the foundation for future efforts aimed at quantitative characterization of autophagy.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of Neutron Spectrum and Control Rod Worth Measurements in Several ZPPR-15 Loadings

This paper discusses the analysis of neutron spectrum and control rod reactivity worth measurements with deterministic and Monte Carlo methods. Deterministic results are obtained with 3D reactor models generated with the BuildZPRModel tools developed at ANL. The Monte Carlo simulations are performed with MCNP6 and are based on 3D models that include all geometric details ('as built' models). This study also shows the application of the cross section processing options recently implemented in BuildZPRModel that are based on the leakage and TWODANT method to take better into account the coupling effects among the different reactor zones.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Data from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamicin vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. The surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone. Conclusions: In this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. The model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Big Data Mining for Applied Energy Savings in Buildings

Residential and commercial buildings in China, India, the United States (US), United Kingdom (UK), and Italy consume 39-45% of each nation's primary energy (approximately 73% of electricity). Building energy models can be used to automatically optimize the return-on-investment for retrofits to improve a building’s energy efficiency. However, with an average of 3,000 building descriptors necessary to accurately simulate a single building, there is a market need to reduce the transaction cost for creating a simulatable model for every building in a city and calibrate the models to utility data prior to capital expenditures. Oak Ridge National Laboratory has utilized two of the world’s fastest supercomputers, assembled unique datasets, and developed innovative algorithms for big data mining to produce the Automatic detection and creation of Building Energy Models (AutoBEM) technology for urban-scale energy modeling. The project developed the world’s most accurate method for determining building footprints from satellite imagery and the world’s fastest building energy model generator. The team has also leveraged a total of eight supercomputers to analyze the best methods, metrics, and algorithms for calibrating building models to measured data within 4% of hourly electricity use; well beyond current industry standards necessary for private-sector financing. The project developed the world’s fastest buildings simulator, over 8 million simulations totaling over 200TB, and mined this data with over 130,000 parallel artificial intelligence algorithmic instances to develop the world’s best calibration algorithm in terms of accuracy, runtime, and robustness.

New, Joshua↗

Accurate parameterization of the kinetic energy functional for calculations using exact-exchange

In this report, electronic structure calculations based on Kohn-Sham density functional theory (KSDFT) that incorporate exact exchange or hybrid functionals are associated with large computational expense, a consequence of the inherent cubic scaling bottleneck and large associated prefactor, which limits the length and time scales that can be accessed. Though orbital-free density functional theory (OFDFT) calculations scale linearly with system size and are associated with significantly smaller prefactor, they are limited by the absence of accurate density-dependent kinetic energy functionals. Therefore, the development of accurate density-dependent kinetic energy functionals is important for OFDFT calculations of large realistic systems. To this end, we propose a method to train kinetic energy functional models at the exact-exchange level of theory by using a dictionary of physically relevant terms that have been proposed in the literature in conjunction with linear or nonlinear regression methods to obtain the fitting coefficients. For our dictionary, we use gradient expansion of the kinetic energy, nonlocal models proposed in the literature and their nonlinear combinations, such as a model that incorporates spatial correlations between higher order derivatives of electron density at two points. The predictive capabilities of these models are assessed by using a variety of model one-dimensional systems that exhibit diverse bonding characteristics, such as a chain of eight hydrogens, LiF, LiH, C 4 H 2 , C 4 N 2 and C 3 O 2 . We show that by using data from model one-dimensional KSDFT calculations performed using the exact-exchange functional for only a few neutral structures, it is possible to generate models with high accuracy for charged systems as well as electron and kinetic energy densities during self-consistent field iterations. In addition, we show that it possible to learn both the orbital dependent terms, i.e., the kinetic energy and the exact-exchange energy, and models that incorporate additional nonlinearities in spatial correlations, such as a quadratic model, are needed to capture subtle features of the kinetic energy density that are present in exact-exchange-based KSDFT calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SU-E-J-151: Day-To-Day Variations in Fraction-Specific Motion Modeling Using Patient 4DCBCT Images

Purpose: The goal of this study is to quantify the interfraction reproducibility of patient-specific motion models derived from 4DCBCT acquired on the day of treatment of lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived from patient 4DCBCT images acquired daily over 3–5 fractions of treatment by 1) applying deformable image registration between each 4DCBCT image and a reference phase from that day, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs to derive a motion model. The motion model from the first day of treatment is compared to motion models from each successive day of treatment to quantify variability in motion models generated from different days. Four SBRT patient datasets have been acquired thus far in this IRB approved study. Results: Fraction-specific motion models for each fraction and patient were derived and PCA eigenvectors and their associated eigenvalues are compared for each fraction. For the first patient dataset, the average root mean square error between the first two eigenvectors associated with the highest two eigenvalues, in four fractions was 0.1, while it was 0.25 between the last three PCA eigenvectors associated with the lowest three eigenvalues. It was found that the eigenvectors and eigenvalues of PCA motion models for each treatment fraction have variations and the first few eigenvectors are shown to be more stable across treatment fractions than others. Conclusion: Analysis of this dataset showed that the first two eigenvectors of the PCA patient-specific motion models derived from 4DCBCT were stable over the course of several treatment fractions. The third, fourth, and fifth eigenvectors had larger variations.

60 APPLIED LIFE SCIENCES↗

EMPIRE-3.2 Malta: modular system for nuclear reaction calculations and nuclear data evaluation [User's Manual]

EMPIRE is a modular system of nuclear reaction codes, comprising various nuclear models, and designed for calculations over a broad range of energies and incident particles. The system can be used for theoretical investigations of nuclear reactions as well as for nuclear data evaluation work. Photons, nucleons, deuterons, tritons, helions (3He), α’s, and light or heavy ions can be selected as projectiles. The energy range starts just above the resonance region in the case of a neutron projectile, and extends up to few hundred MeV for heavy ion induced reactions. The code accounts for the major nuclear reaction models, such as optical model, Coupled Channels and DWBA (ECIS06 and OPTMAN), Multi-step Direct (ORION + TRISTAN), NVWY Multi-step Compound, exciton model (PCROSS), hybrid Monte Carlo simulation (DDHMS), and the full featured Hauser-Feshbach model including width fluctuations and the optical model for fission. Heavy ion fusion cross section can be calculated within the simplified coupled channels approach (CCFUS). A comprehensive library of input parameters based on the RIPL-3 library covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers, and γ-ray strength functions. Effects of the dynamic deformation of a fast rotating nucleus can be taken into account in the calculations (BARFIT, MOMFIT). The results can be converted into the ENDF-6 format using the accompanying EMPEND code. Modules of the ENDF Utility Codes and the ENDF Pre-Processing codes are applied for ENDF file verification. The package contains the full EXFOR library of experimental data in computational format C4 that are automatically retrieved during the calculations. EMPIRE contains the resonance module that retrieves data from the electronic version of the Atlas of Neutron Resonances by Mughabghab (not provided with the EMPIRE distribution), to produce resonance section and related covariances for the ENDF-6 formatted files. EMPIRE can be used to determine covariances of the calculated data using either sensitivity matrices along with the KALMAN code or employing Monte Carlo approach to produce model generated covariances. In both cases experimental data can be taken into account, either directly (KALMAN) or by feeding the EMPIRE calculated Monte Carlo modelling covariance as a prior to the least square fitting GANDR system. Publication quality graphs can be obtained using the powerful and flexible plotting package ZVView. Interactive plots with ZVView comparing experimental results with calculations can be produced with ENDVER modules. The backbone of the EMPIRE system are bash-shell UNIX scripts that provide for seamless console operation of EMPIRE on Linux, Mac OS X, and Microsoft Windows with GNU gfortran compiler installed. Additionally, the graphical interface, provides for an easy operation of the system on Linux, Mac OS X and virtual Linux machines running on Microsoft Windows.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A new Monte Carlo generator for BSM physics in B → K*ℓ+ℓ− decays with an application to lepton non-universality in angular distributions

Abstract Within the widely used EvtGen framework, we have added a new event generator model forB → K * ℓ + ℓ − with improved standard model (SM) decay amplitudes and possible BSM physics contributions, which are implemented in the operator product expansion in terms of Wilson coefficients. This event generator can then be used to estimate the statistical sensitivity of a simulated experiment to the most general BSM signal resulting from dimension-six operators. We describe the advantages and potential of the newly developed ‘Sibidanov Physics Generator’ in improving the experimental sensitivity of searches for lepton non-universal BSM physics and clarifying signatures. The new generator can properly simulate BSM scenarios, interference between SM and BSM amplitudes, and correlations between different BSM observables as well as acceptance bias. We show that exploiting such correlations substantially improves experimental sensitivity. As a demonstration of the utility of the MC generator, we examine the prospects for improved measurements of lepton non-universality in angular distributions forB→K * ℓ + ℓ − decays from the expected 50 ab −1 data set of the Belle II experiment, using a four-dimensional unbinned maximum likelihood fit. We describe promising experimental signatures and correlations between observables. The use of lepton-universality violating ∆-observables significantly reduces uncertainties in the SM expectations due to QCD and resonance effects and is ideally suited for Belle II with the large data sets expected in the next decade. Thanks to the clean experimental environment of ane + e − machine, Belle II should be able to probe BSM physics in the Wilson coefficientsC 7 and$$ {C}_7^{\prime } $$ C 7 ′ , which appear at lowq 2 in the di-electron channel.

Physics↗