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Fostering a Guiding Multiscale Model for the Development of Advanced MgB 2 Hydrogen Storage Materials (Final Technical Report)

Project Goal and Objective. The demand for energy and for an upgraded energy infrastructure has steadily grown, as have the needs for energy independence and alternatives to our reliance on petroleum. Hydrogen is considered the most viable fuels for wide-scale implementation in the near future as it is less-polluting, non-toxic, and has more stored energy than petroleum. It is envisioned that hydrogen can eventually become the prime energy carrier, integrating the transportation, grid, and chemical sectors in a way that improves resiliency, diversifies feedstocks, and affords new economic opportunities. A key remaining challenge is the development materials with enhanced gravimetric and volumetric hydrogen storage capacities that offer a higher performance than compressed gas. These materials would eliminate the need for large-scale compression, thereby dramatically reducing the footprint and cost of gas storage. The high gravimetric and volumetric hydrogen capacities of complex hydrides has prompted an intensive investigation of the potential of this class of materials as hydrogen storage media over the past 25 years. Among the many complex hydrides that have been explored, magnesium borohydride, Mg(BH 4 ) 2 , has been found to possess the best combination of practical thermodynamic properties. These include a gravimetric H 2 density of 14.9 wt% H 2 and thermodynamics for the dehydrogenation of Mg(BH 4 ) 2 to MgB 2 (equation 1) (ΔH° = 39 kJ/mol H 2 , ΔS = 112 J/K mol H 2 ) which lie in the narrow window required Mg(BH 4 ) 2 $\Leftrightarrow$ MgB 2 + 4 H 2 (1) for reversibility under moderate pressure and temperature. However, overcoming the extremely slow kinetics of the reversible release of hydrogen by this material in the solid state is a daunting challenge. At temperatures greater than 400 °C, the borohydride releases up to 14 wt% hydrogen giving MgB 2 . We discovered that the direct re-hydrogenation of MgB 2 to Mg(BH 4 ) 2 can be accomplished under 950 bar H 2 at 400 °C. While this demonstrated that complete reversibility can be achieved, the conditions employed are far too extreme for commercial hydrogen storage applications. More recently, we found through US DOE funded research projects (EERE HyMARC and HySCOR), that hydrogen cycling, can be accomplish at much milder conditions upon modification of the borohydride or boride. Guided by these discoveries these discoveries, the objective of this research project was to obtain key information that will enable the development of a model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The ultimate goal of our efforts is to attain a model of this transformation that can be utilized to accelerate development further advanced materials. This project directly follows on discoveries that were made over the course of a US DOE, EERE HyMARC project that was focused on improvement of the hydrogen cycling kinetics of modified MgB 2 . We found that that mechanical milling with graphene results the desired, pronounced kinetic enhancement. The dramatic lowering of the conditions required for the hydrogenation of MgB 2 is a significant step towards overcoming its chemical inertness allowing its development as a practical onboard hydrogen storage material. However, the exact nature of the modification(s) of MgB 2 that is responsible for its activation towards hydrogenation is completely unknown. This situation is not unique, as efforts to develop hydrogen storage materials typically have a narrow focus rather than a comprehensive approach that takes atomic level bonding and structure; molecular dynamics; long range, nano- and mesoscale-structure and their interconnection all into account. The goal of this project was the development of a comprehensive, multi-scale computational model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 that can be utilized for development of higher performance versions of the modified material. Development of the model requires determination of: 1) the bulk, nano-scale, and meso-scale structural changes occurring at elevated pressure following mechano-chemical modification of MgB 2 ; 2) the reaction pathway of the reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 ; 3) the effect of elevated pressure and mechano-chemical modification on the chemical reaction pathways; 4) the interactions at solid-gas interfaces; and particle surfaces; and 5) the kinetics and thermodynamic parameters associated with each step of the hydrogenation reaction pathway. This investigation required advanced techniques as preliminary, standard XRD, 11 B NMR, and FTIR analysis showed no signs of material modification. In order to gain this level of understanding of modified MgB 2 , required the teaming of a diverse group of experts and state-of-the art experimental capabilities at the University of Hawaii at Manoa (UHM) and collaborating National Laboratories: Craig Jensen , Department of Chemistry (PI and Project Director), solid state, solution, and high pressure NMR spectroscopy; solid-state synthesis; and high pressure hydrogenation (collaboration with SNL); Godwin Severa , Hawaii Natural Energy Institute (co-PI) calorimetry; infrared and Raman spectroscopy (collaboration with NREL); Dera , high pressure X-ray diffraction including in situ experiments (collaboration with ANL); Hope Ishii , Hawaii Institute of Geophysics electron microscopy investigations (collaboration with LBNL); and Joe Brown , Mechanical Engineering , material electronic structure and electric field effects.

08 HYDROGEN↗

Automating the Solar Interconnection Technical Evaluation Process: PREconfiguring and Controlling Inverter SEt-Points (PRECISE)

Utilities are receiving an increasing number of interconnection requests for distributed solar photovoltaic (PV) systems from their customers, requiring a solution to quickly and intelligently perform technical assessments of these requests and to manage these new renewable energy assets. In this paper, we present a stand-alone interconnection tool, PREconfiguring and Controlling Inverter SEt-points (PRECISETM), and how it overcomes the challenges of accelerating technical evaluations and leverages smart inverter functionality to provide local voltage support on an as-needed basis. The paper details the purpose and architecture of PRECISE, including tools, data source requirements, the model-based interconnection evaluation process, and technical results. PRECISE is an integrated software tool that customizes PV inverter settings for utilities by modeling and assessing impacts on local voltages and the need for advanced inverter functions (AIFs) (e.g., volt-VAR and volt-watt). PRECISE maximizes the use of readily available utility data sets to make fast online assessments of incoming PV interconnection requests and makes accept/reject recommendations along with custom settings for AIFs.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

GEOS-5↗

Roadmap for IES Modeling and Simulation Activities: Update 2023

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2020, a last comprehensive roadmap for the DOE-NE Integrated Energy Systems program was published. In 2017, a separate modeling and simulation capability development plan was published that was extensively updated in 2022. The current report incrementally updates the 2022 modeling and simulation capability roadmap. This is not a new report, but individual sections have been updated to reflect recent accomplishments and new directions of the program. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations (i.e., support component design and real-time operations of experimental demonstration systems). Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis, and proposes next steps for a time horizon over the next years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning Tools Set for Natural Gas Fuel Cell System Design

This study is focusing on leveraging the system design tools set for the next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system. Conventionally, system design and optimization of NGFC systems rely heavily on traditional reduced order model (ROM) techniques and designers’ experience level. For overcoming the technical barriers of system design, multiple multi-physics models and machine learning (ML) tools have been utilized to automate the conceptual design process and enhance the reliability of solutions for the NGFC system. The proposed tools set includes a physics-informed ML tool for automated ROM construction that leverages advances in deep neural networks to significantly reduce ROM prediction error for the NGFC power island compared to traditional approaches. The constructed physics-informed ML ROM can be used in system design, and optimization tools set Institute for the Design of Advanced Energy Systems (IDAES) Process Systems Engineering (PSE) framework. The tools set also provides a user-friendly graphic user interface built within Jupyter Notebooks, and the complete tools set is open-source public available.

Wang, Dewei↗

Roadmap for IES Modeling and Simulation Activities

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2017, the last modeling and simulation capability development plan was published. In 2020, a comprehensive roadmap for the DOE-NE Integrated Energy Systems program has been published. The current report is meant to update the 2017 modeling and simulation capability roadmap and complement the IES overall program roadmap published in 2020. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations, i.e., support component design and real time operations of experimental demonstration systems. Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis and proposes next steps for a time horizon over the next 4 to 5 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transmission Interconnection Roadmap: Transforming Bulk Transmission Interconnection by 2035

The U.S. electricity system is amid a rapidly occurring and widespread energy transition. Regional, Tribal, state, and customer demand for new energy resources, combined with favorable policies, is driving a rapid rise of interconnection requests. Interconnection processes will need to evolve to handle this larger number of requests today and into the future, as policy and economic drivers continue to motivate significant resource development. This roadmap identifies and organizes nearer- and longer-term solutions to enable transmission interconnection processes to meet this expected demand, and it is intended for a diverse audience of stakeholders participating within transmission interconnection processes. The roadmap is a result of the Interconnection Innovation e-Xchange (i2X) program launched by the U.S. Department of Energy (DOE) in June 2022 to convene stakeholders and address interconnection challenges. The roadmap is organized into four primary goal areas, each important to the overall i2X mission to enable a simpler, faster, and fairer interconnection of clean energy resources while enhancing the reliability, resiliency, and security of our electric grid. The first goal aims to improve interconnection data transparency, to aid interconnection customers’ ability to screen and site potential projects, better enable third-party modeling, facilitate more process automation, enhance competition while ensuring equitable outcomes, and enable benchmarking, tracking, and auditing of interconnection processes and reforms. The second goal covers solutions to improve queue management practices, affected system studies, fair processes, and workforce development. The third goal incorporates solutions that aim to improve cost allocation, reduce costs to electricity consumers, enhance the coordination between transmission planning and the interconnection process, and optimize the rightsizing of transmission investment through improvements in interconnection studies. The fourth and final goal aims to reduce the performance issues not identified during interconnection studies by updating technical requirements within interconnection studies, models, and tools while also improving industry interconnection standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Parametric Thermal Soak Model for Earth Entry Vehicles

The analysis and design of an Earth Entry Vehicle (EEV) is multidisciplinary in nature, requiring the application many disciplines. An integrated tool called Multi Mission System Analysis for Planetary Entry Descent and Landing or M-SAPE is being developed as part of Entry Vehicle Technology project under In-Space Technology program. Integration of a multidisciplinary problem is a challenging task. Automation of the execution process and data transfer among disciplines can be accomplished to provide significant benefits. Thermal soak analysis and temperature predictions of various interior components of entry vehicle, including the impact foam and payload container are part of the solution that M-SAPE will offer to spacecraft designers. The present paper focuses on the thermal soak analysis of an entry vehicle design based on the Mars Sample Return entry vehicle geometry and discusses a technical approach to develop parametric models for thermal soak analysis that will be integrated into M-SAPE. One of the main objectives is to be able to identify the important parameters and to develop correlation coefficients so that, for a given trajectory, can estimate the peak payload temperature based on relevant trajectory parameters and vehicle geometry. The models are being developed for two primary thermal protection (TPS) materials: 1) carbon phenolic that was used for Galileo and Pioneer Venus probes and, 2) Phenolic Impregnated Carbon Ablator (PICA), TPS material for Mars Science Lab mission. Several representative trajectories were selected from a very large trade space to include in the thermal analysis in order to develop an effective parametric thermal soak model. The selected trajectories covered a wide range of heatload and heatflux combinations. Non-linear, fully transient, thermal finite element simulations were performed for the selected trajectories to generate the temperature histories at the interior of the vehicle. Figure 1 shows the finite element model that was used for the simulations. The results indicate that it takes several hours for the thermal energy to soak into the interior of the vehicle and achieve maximum payload temperatures. In addition, a strong correlation between the heatload and peak payload container temperature is observed that will help establishing the parametric thermal soak model.

Agrawal, Parul↗

AN AUTOMATED MACHINE LEARNING-GENETIC ALGORITHM FRAMEWORK WITH ACTIVE LEARNING FOR DESIGN OPTIMIZATION

The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, training the ML models requires hyperparameter selection, which is often done using trial-and-error and domain expertise. Another challenge is that the data required to train these models are often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a super learner model. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization while also reducing the number of simulations needed for performing surrogate-based design optimization.

Owoyele, Opeoluwa↗

Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase) (Final Report)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership (RCSP) Initiative. The public/private consortium, funded through the MRCSP, brings together nearly 40 industry partners in 10 contiguous states in Mid-West and North-East regions. Battelle, as the project lead, oversees research & development, operations, and coordinates activities among various partners. Since its founding, MRCSP has made significant progress towards advancing CCS and CCUS technologies for participating states in the region. Between 2008 to 2020, Phase III of the MRCSP program focused on the development of large-scale injection tests. This report is part of a series of topical reports prepared under the MRCSP Phase III. The MRCSP Final Technical Report summarizes the research conducted while monitoring large-scale injection tests at a CO 2 -EOR facility in Northern Michigan. The project successfully injected more than one million metric tons of CO 2 into depleted oil fields in the Northern Niagaran Pinnacle Reef Trend (NNPRT) for enhanced oil recovery (EOR). These commercial-scale tests provided valuable real-world knowledge that has been used to refine technologies and methods, reduce uncertainties, and demonstrate safety and effectiveness of CCUS technologies to increase public acceptance. The Final Technical Report provides an overview of Phase III efforts including advancing the understanding of the regional geology, storage capacities, deployment of many monitoring and modeling techniques and its efficacy, and technical demonstration of large-scale CO 2 injection, containment, and associated storage in the NNPRT region. Specific topical reports on the subjects covered in the Final Technical Report are also available through EDX/OSTI.

01 COAL, LIGNITE, AND PEAT↗

Modeling Charge Transfer Excitation with Variation After Response Quantum Monte Carlo (Final Technical Report)

The electronically excited states of molecules play critical roles both in spectroscopy and in technological application, ranging from UV/Vis absorption experiments to the production of solar fuels. However, certain types of excitations, such as charge transfer excitations, remain difficult to treat with existing methods such as time dependent density functional theory or linear response coupled cluster. Under this Early Career Research Award, we developed a number of different theoretical methods to address this issue, which began with Variational Monte Carlo methods and branched into multiple types of excited-state-specific quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parametric Flutter Analysis of the TCA Configuration and Recommendation for FFM Design and Scaling

The current HSR Aeroelasticity plan to design, build, and test a full span, free flying transonic flutter model in the TDT has many technical obstacles that must be overcome for a successful program. One technical obstacle is the determination of a suitable configuration and point in the sky to use in setting the scaling point for the ASE models program. Determining this configuration and point in the sky requires balancing several conflicting requirements, including model buildability, tunnel test safety, and the ability of the model to represent the flutter mechanisms of interest. As will be discussed in detail in subsequent sections, the current TCA design exhibits several flutter mechanisms of interest. It has been decided that the ASE models program will focus on the low frequency symmetric flutter mechanism, and will make no attempt to investigate high frequency flutter mechanisms. There are several reasons for this choice. First, it is believed that the high frequency flutter mechanisms are similar in nature to classical wing bending/torsion flutter, and therefore there is more confidence that this mechanism can be predicted using current techniques. The low frequency mode, on the other hand, is a highly coupled mechanism involving wing, body, tail, and engine motion which may be very difficult to predict. Second, the high frequency flutter modes result in very small weight penalties (several hundred pounds), while suppression of the low frequency mechanism inside the flight envelope causes thousands of pounds to be added to the structure. In order to successfully test the low frequency flutter mode of interest, a suitable starting configuration and point in the sky must be identified. The configuration and point in the sky must result in a wind tunnel model that (1) represents the low-frequency wing/body/engine/empennage flutter mechanisms that are unique to HSCT configurations, (2) flutters at an acceptably low frequency in the tunnel, (3) flutters at an acceptably low dynamic pressure in the tunnel, (4) allows sufficient weight for model buildability without inordinately high cost, and (5) has significant separation between the target flutter mechanism and other, potentially catastrophic, flutter mechanisms.

Baker, Myles↗

Uranus Global Reference Atmospheric Model (Uranus-GRAM) 2024: User Guide

Engineers and mission planners designing vehicles that pass through Uranus’ atmosphere require an atmospheric model that calculates the mean values and variations of atmospheric properties. The Uranus Global Reference Atmospheric Model(Uranus-GRAM)is an engineering- oriented model that provides this information based on data from Voyager observations. Uranus- GRAM is designed to offer mission planners the flexibility to select input parameters such as time, latitude, and longitude. Uranus-GRAM outputs atmospheric constituent data and mean values for atmospheric density, temperature, pressure, and zonal wind along a user defined path. Uranus-GRAM also provides dispersions of density and zonal wind. Uranus-GRAM is one option in the GRAM Suite that shares a common software core with the other planetary GRAMs while maintaining Uranus specific models. Additionally, documentation, including this User Guide, a Programmer’s Manual, and trajectory code interfaces has been made available with the software release. This Technical Memorandum summarizes the atmospheric data model in Uranus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Section 2 describes the input atmospheric data files and how they are used in Uranus-GRAM. Section 3 explains the process to obtain the Uranus-GRAM code, the data files, and how to set up and run the program. Appendices A through E provide additional details regarding the Uranus-GRAM input and output files. Appendix F provides a history of Uranus-GRAM revisions.

atmospheric models↗

Pair Production and Annihilation in Strong Magnetic Fields

Electromagnetic phenomena occurring in the presence of strong magnetic fields are currently of great interest in high-energy astrophysics. In particular, the process of pair production by single photons in the presence of fields of order 10 to the 12th power Gauss is of importance in cascade models of pulsar gamma ray emission, and may also become significant in theories of other radiation phenomena whose sources may be neutron stars (e.g., gamma ray bursts). In addition to pair production, the inverse process of pair annihilation is greatly affected by the presence of superstrong magnetic fields. The most significant departures from annihilation processes in free space are a reduction in the total rate for annihilation into two photons, a broadening of the familiar 511-keV line for annihilation at rest, and the possibility for annihilation into a single photon (which dominates the two-photon annihilation for B ( 10 the 13th power Gauss). The physics of these pair conversion processes, which is reviewed briefly, can become quite complex in the teragauss regime, and can involve calculations which are technically difficult to incorporate into models of emission mechanisms in neutron star magnetospheres. However, theoretical work, especially the case of pair annihilation, also suggests potential techniques for more direct measurements of field strengths near the stellar surface.

Daugherty, J. K.↗

Pair production and annihilation in strong magnetic fields

Electromagnetic phenomena occurring in the presence of strong magnetic fields are currently of great interest in high-energy astrophysics. In particular, the process of pair production by single photons in the presence of fields of order 10 to the 12th power Gauss is of importance in cascade models of pulsar gamma ray emission, and may also become significant in theories of other radiation phenomena whose sources may be neutron stars (e.g., gamma ray bursts). In addition to pair production, the inverse process of pair annihilation is greatly affected by the presence of superstrong magnetic fields. The most significant departures from annihilation processes in free space are a reduction in the total rate for annihilation into two photons, a broadening of the familiar 511-keV line for annihilation at rest, and the possibility for annihilation into a single photon which dominates the two-photon annihilation for B (10 to 13th power Gauss) The physics of these pair conversion processes, which is reviewed briefly, can become quite complex in the teragauss regime, and can involve calculations which are technically difficult to incorporate into models of emission mechanisms in neutron star magnetospheres. However, theoretical work, especially the case of pair annihilation, also suggests potential techniques for more direct measurements of field strengths near the stellar surface.

Daugherty, J. K.↗

The Next Higgs Boson(s) and a Higgs-Yukawa Universality

We consider multi-Higgs-doublet models which, for symmetry reasons, have a universal Higgs-Yukawa (HY) coupling, $g$. This is identified with the top quark $g=g_t\approx 1$. The models are concordant with the quasi-infrared fixed point, and the top quark mass is correctly predicted with a compositeness scale (Landau pole) at $M_{planck}$, with sensitivity to heavier Higgs states. The observed Higgs boson is a $\bar{t}t$ composite, and a first sequential Higgs doublet, $H_b$, with $g\approx g_t\approx 1$ coupled to $\bar{b}_R(t,b)_L$ is predicted at a mass $3.0 \lesssim M_b \lesssim 5.5$ TeV and accessible to LHC and its upgrades. This would explain the mass of the $b-$quark, and the tachyonic SM Higgs boson mass$^2$. The flavor texture problem is no longer associated with the HY couplings, but rather is determined by the inverted multi-Higgs boson mass spectrum, e.g., the lightest fermions are associated with heaviest Higgs bosons and vice versa. The theory is no less technically natural than the standard model. The discovery of $H_b$ at the LHC would confirm the general compositeness idea of Higgs bosons and anticipate additional states potentially accessible to the $100$ TeV $pp$ machine.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗