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State of Innovation 2025: Progress in Accelerating Next-Generation Cement and Concrete Technologies

The cement and concrete sectors are entering a decisive period as next-generation technologies advance from laboratory research to demonstration, early deployment, and first-of-a-kind commercial plants. Building on the 2024 State of Innovation report, the 2025 outlook highlights both the rapid acceleration of innovation and the urgent need for coordinated action across the value chain. Venture capital activity into the cement and concrete space stabilized following the record surge of 2022-2023, yet landmark financings, such as Sublime Systems' $200 million round and Terra CO2's $124 million Series B, signal continued investor confidence in companies approaching commercialization. Corporate procurement has become a powerful new catalyst, with Microsoft, Amazon, and CRH (Cement Roadstone Holdings) Ventures providing long-term commitments that underpin the first wave of next-generation cementitious products. The sector is shifting from early-stage experimentation toward the scaling of well-capitalized leaders capable of bridging the critical "capitalization gap." Early innovators continue to expand the toolkit through novel binders, electrochemical cements, biogenic limestone, and carbonate mineralization pathways. Going into 2026, cost competitiveness, durability validation, and scalability enabled by resilient supply chains remain the decisive factors for market adoption. At the 2025 Next Generation Cement and Concrete Critical Technologies Meeting, attendees emphasized dual-track funding strategies that integrate federal grants with private capital as key to enabling market breakthrough. State programs and corporate demand are sustaining momentum, while successful companies increasingly demonstrate both economic value and reduced dependence on imported materials. The National Concrete Pavement Technology Center and others underscored that broad integration of next-generation materials will hinge on standards compatibility, verified field performance, and workforce readiness. Colorado continues to serve as a proving ground through pilot programs that combine supplier training, phased implementation, and real-world data to de-risk innovation and provide replicable models for other regions. The 2025 Cement and Concrete Critical Technologies Workshop reinforced that scaling next-generation materials will require alignment among technology innovation, performance validation, and market demand. Stakeholders must move beyond siloed efforts toward collaborative frameworks that coordinate standards, funding, and infrastructure deployment. As a neutral convener and technical validator, the National Laboratory of the Rockies (NLR) plays a pivotal role in bridging innovation and market adoption through collaborative research, technology validation, and entrepreneurship programs. By uniting innovators, incumbents, policymakers, contractors, and investors, NLR and its partners are helping chart a credible pathway toward widespread commercialization in the decade ahead.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗

Celeritas Midterm SciDAC Report

Celeritas is a new Monte Carlo (MC) code that helps satisfy the increasing demand for high energy physics (HEP) detector simulation, using Graphics Processing Unit (GPU) hardware on high performance computing (HPC) systems to model Large Hadron Collider (LHC) experiments and beyond. This report details the project’s progress midway through its SciDAC funding period, highlighting the first complete implementation of standard electromagnetic (EM) physics on GPUs, initial results for performance and scalability on Leadership Computing Facilities (LCFs), and preliminary integration into the CMS and ATLAS experiments. By integrating HEP domain knowledge with expertise in MC transport, Celeritas has catalyzed a shift in the HEP community’s perception of GPU platforms as the future for HPC simulations.

97 MATHEMATICS AND COMPUTING↗

The motivation and status of two-body resonance decays after the LHC Run 2 and beyond

Searching for two-body resonance decays is a central component of the high energy physics energy frontier research program. While many of the possibilities are covered when the two bodies are Standard Model (SM) particles, there are still significant gaps. If one or both of the bodies are themselves non-SM particles, there is very little coverage from existing searches. We review the status of two-body searches and motivate the need to search for the missing combinations. It is likely that the search program of the future will be able to cover all possibilities with a combination of dedicated and model agnostic search approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6

The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O 3 ), methane (CH 4 ), and carbon dioxide (CO 2 ) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO 2 ). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.

54 ENVIRONMENTAL SCIENCES↗

Ratio-preserving approach to cosmological concordance

Cosmological observables are particularly sensitive to key ratios of energy densities and rates, both today and at earlier epochs of the Universe. Well-known examples include the photon-to-baryon and the matter-to-radiation ratios. Equally important, though less publicized, are the ratios of pressure-supported to pressureless matter and the Thomson scattering rate to the Hubble rate around recombination, both of which observations tightly constrain. Preserving these key ratios in theories beyond the Λ Cold-Dark-Matter ( Λ CDM ) model ensures broad concordance with a large swath of datasets when addressing cosmological tensions. We demonstrate that a mirror dark sector, reflecting a partial Z 2 symmetry with the Standard Model, in conjunction with percentage level changes to the visible fine-structure constant and electron mass which represent a phenomenological change to the Thomson scattering rate, maintains essential cosmological ratios. Incorporating this ratio-preserving approach into a cosmological framework significantly improves agreement to observational data ( Δ χ 2 = - 35.72 ) and completely eliminates the Hubble tension with a cosmologically inferred H 0 = 73.80 ± 1.02 km / s / Mpc when including the S H 0 ES calibration in our analysis. While our approach is certainly nonminimal, it emphasizes the importance of keeping key ratios constant when exploring models beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗

Leveraging Large Language Models for Real-World Data Evidence: A Framework for Automated Treatment Extraction and Data Harmonization

Background: The ability to comprehensively collect treatment information from cancer patient medical records would enable studies to evaluate real-world benefits and risks tied to specific treatments. Currently, it is difficult to system- atically collect high-quality treatment information because it is often stored in unstructured text. Manually extracting and standardizing drug and regimen data is time-intensive. Recent advances in large language models (LLMs) offer a potential solution for automated extraction of structured treatment information from clinical text. Objective: This study systematically evaluates the utility of four LLMs from the Llama family for automated extraction of oncology treatment information from clinical text. This information can guide researchers using cancer registry data to provide insights into cancer care and outcomes beyond clinical trials. Methods: Four instruction-tuned Llama models with varying parameter counts (1B, 3B, 8B, and 70B) were evaluated for their ability to extract treatment information from clinical documents. A unified oncology knowledge base integrating seven major public data sources was developed to standardize and normalize extracted entities—a critical step for harmonizing data from diverse sources. Extracted treatment data were compared against expert-annotated ground truth. Model performance was assessed using accuracy metrics (Precision, Recall, F1-Score) and opera- tional feasibility metrics, including processing speed and structural compliance of the output. Results: A strong positive correlation was observed between model size and extraction accuracy. F1-score improved from 0.609 for the 1B model to 0.710 (3B), 0.807 (8B), and 0.828 (70B). While larger models demonstrated superior accuracy and compliance, they incurred higher computational costs. The modest performance difference between 8B and 70B suggests diminishing returns with increasing model size. Conclusions: LLMs represent a viable technology for automating oncology treatment extraction. The 8B-parameter model emerged as a highly effective option, balancing high accuracy and computational efficiency. Selecting an appropriate LLM for deployment in cancer registries involves a trade-off between desired accuracy and available operational resources. Harmonizing extracted entities with the oncology knowledge base facilitates standardized integration into common data models, enhancing data quality for real-world evidence analyses.

artificial intelligence↗

Hadronic uncertainties versus new physics for the W boson mass and Muon g – 2 anomalies

There are now two single measurements of precision observables that have major anomalies in the Standard Model: the recent CDF measurement of the W mass shows a 7σ deviation and the Muon g – 2 experiment at FNAL confirmed a long-standing anomaly, implying a 4.2σ deviation. Doubts regarding new physics interpretations of these anomalies could stem from uncertainties in the common hadronic contributions. We demonstrate that these two anomalies pull the hadronic contributions in opposite directions by performing electroweak fits in which the hadronic contribution was allowed to float. The fits show that including the g – 2 measurement worsens the tension with the CDF measurement and conversely that adjustments that alleviate the CDF tension worsen the g – 2 tension beyond 5σ. This means that if we adopt the CDF W mass measurement, the case for new physics in either the W mass or muon g – 2 is inescapable regardless of the size of the SM hadronic contributions. Lastly, we demonstrate that a mixed scalar leptoquark extension of the Standard Model could explain both anomalies simultaneously.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

BrickQA: Bridging the Semantic Gap in Building Operations with Dynamic Graph Exploration

While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher token cost-efficiency. Beyond these metrics, the framework maintains structural fidelity across heterogeneous buildings and remains resilient to ambiguous queries without requiring site-specific fine-tuning. Furthermore, a case study on operational analytics validates the framework’s capability to handle temporal and aggregation constraints, effectively transforming abstract semantic models into actionable facility management insights.1

Ko, Yun-Dam↗

Framework for simulating gauge theories with dipolar spin systems

Gauge theories appear broadly in physics, ranging from the standard model of particle physics to long-wavelength descriptions of topological systems in condensed matter. However, systems with sign problems are largely inaccessible to classical computations and also beyond the current limitations of digital quantum hardware. In this work, we develop an analog approach to simulating gauge theories with an experimental setup that employs dipolar spins (molecules or Rydberg atoms). We consider molecules fixed in space and interacting through dipole-dipole interactions, avoiding the need for itinerant degrees of freedom. Each molecule represents either a site or gauge degree of freedom, and Gauss's law is preserved by a direct and programmatic tuning of positions and internal state energies. This approach can be regarded as a form of analog systems programming and charts a path forward for near-term quantum simulation. As a first step, we numerically validate this scheme in a small-system study of U(1) quantum link models in (1+1) dimensions with link spin S = 1/2 and S =1 and illustrate how dynamical phenomena such as string inversion and string breaking could be observed in near-term experiments. Our work brings together methods from atomic and molecular physics, condensed matter physics, high-energy physics, and quantum information science for the study of nonperturbative processes in gauge theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nonrenormalization and Operator Mixing via On-Shell Methods

Using on-shell methods, we present a new perturbative nonrenormalization theorem for operator mixing in massless four-dimensional quantum field theories. By examining how unitarity cuts of form factors encode anomalous dimensions, we show that longer operators are often restricted from renormalizing shorter operators at the first order where Feynman diagrams exist. The theorem applies quite generally and depends only on the field content of the operators involved. We apply our theorem to operators of dimension five through seven in the standard model effective field theory, including examples of nontrivial zeros in the anomalous-dimension matrix at one through four loops. The zeros at two and higher loops go beyond those previously explained using helicity selection rules. We also include explicit sample calculations at two loops.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

$\mu$-distortion around stupendously large primordial black holes

In a variety of mechanisms generating primordial black holes, each black hole is expected to form along with a surrounding underdense region that roughly compensates the black hole mass. This region will propagate outwards and expand as a shell at the speed of sound in the homogeneous background. Dissipation of the shell due to Silk damping could lead to detectable μ-distortion in the CMB spectrum: if black holes are rare on the last scattering surface, the signal(s) would be pointlike; whereas if there are a sufficient number of them, we could have a uniform distortion in the CMB sky. While the current bound on the average μ-distortion is |$\bar{μ}$| ≲ 10>- 4 , the standard ΛCDM model predicts |$\bar{μ}$| ~10 -8 , which could possibly be detected in future missions. It is shown in this work that the non-observation of $\bar{μ}$ beyond ΛCDM can place a new upper bound on the density of supermassive primordial black holes within the mass range 10 6 M ⊙ ≲ M ≲ 10 15 M ⊙ . Finally, black holes with initial mass M ≳ 10 12 M ⊙ could leave a pointlike distortion with μ ≳10-8> at an angular scale ~ 1° in CMB, and its non-observation would impose an even more stringent bound on the population of these stupendously large primordial black holes.

79 ASTRONOMY AND ASTROPHYSICS↗

Status of Lattice QCD Calculations of One and Two-Nucleon Matrix Elements

Lattice QCD calculations of basic hadronic quantities are now often performed with systematic control over the physical pion mass, continuum and infinite volume limits. This progress signals a new era in which lattice QCD will be used to compute basic properties of hadrons, nucleons and light nuclei directly from the Standard Model (SM). In particular, we will be able to use lattice QCD, combined with Effective Field Theory, to make quantitative statements about the interaction of SM matter and potential beyond the SM physics ranging from direct dark matter detection to permanent electric dipole moments. I will briefly review the status and challenges of lattice QCD calculations of select one- and two-nucleon matrix elements. These calculations are significantly more challenging than the basic quantities computed with all systematics controlled, but substantial progress is being made.

Walker-Loud, Andre↗

Hanford Waste Treatment Plant LAB Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The WTP LAB stack monitor locations were qualified using scale model stacks to mitigate the risk of identifying that sampling locations do not meet the qualification criteria on the full-scale stack. As required by the ANSI/HPS N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the DV of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAB stacks were performed at normal operating conditions. The maximum 6 DV value from the scale model testing determines the maximum conditions for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be = 20°. Second, the velocity uniformity at the full-scale stack must be = 20% COV. Finally, the velocity uniformity results for the actual and scale model stacks must agree within 5% COV. In general, these criteria were met through the full-scale stack tests at the LAB facility. Some specific items for each scale model and full-scale stack comparison should be noted in assessing the validity of the verification tests. The LB-C2 scale model stacks were performed with single fan operations at then-minimum flow conditions. These conditions resulted in DV values that were too low to meet the DV range criterion, and therefore are unable to be used in qualifying single fan operations on the full-scale stack. However, the single fan operations demonstrated COV values for velocity uniformity as well as flow angles that were comparable to the dual-fan operations at high flows. Overall, the test conditions and test results were within the range of acceptable values based on current design flow rates. Single fan operations are expected to only occur infrequently for maintenance needs and is therefore not a planned operating condition at this time. The LB-S1 scale model stacks were performed at three fan combinations, and in each combination, at least one test was performed at the then-minimum flow conditions as well as at then-maximum flow conditions. While the then-minimum flow conditions result in a DV range that is lower than the verification test DV value, and therefore does not meet the criterion, these tests are un-necessary for the verification test acceptance. The normal and maximum flow conditions from the scale model stack tests meet the DV range criterion, and the velocity uniformity test results compare favorably with the full-scale stack results. The LB-S2 scale model stacks were performed at nominally the same maximum flow condition; however, the 6 DV value for Fan A operation was slightly lower than the full-scale stack test DV. The COV values from the scale model stacks were comparable between the Fan A and Fan B results, and the overall test conditions are within the range of acceptable values. The stack verification is therefore considered acceptable for both Fan A and Fan B operations. The verification tests were performed at flows that were appreciably higher than the design conditions, and further elevated flow rates would be beyond the range of acceptable DV. Based on these stack verification test results, the three LAB filtered exhaust stacks meet the qualification criteria provided in the ANSI/HPS N13.1-1999 standard. Further changes to the system configuration or operating conditions that are outside the bounds described in this and the scale model test reports (Glissmeyer, Flaherty, and Piepel (2001), Glissmeyer and Geeting (2013)) may require additional tests and additional analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predicting Drug Effects from High-dimensional Asymmetric Drug Data Sets using Graph Neural Networks: A Comprehensive Analysis of Multi-target Drug Effect Prediction

Graph neural networks (GNNs) have emerged as one of the most effective Machine learning (ML) techniques for drug effect prediction from drug molecular graphs. Despite having immense potential, GNN models lack performance when using data sets that contain high dimensional asymmetrically co-occurrent drug effects as targets with complex correlations between them. Training individual learning models for each drug effect and incorporating every prediction result for a wide spectrum of drug effects is beyond practicality. Such an implication provides a testbed to address this challenge as multi-target prediction problems, aiming to predict all drug effects at a time. We develop standard and hybrid graph neural networks (GNNs)to perform two separate tasks that are multi-regression for continuous values and multi-label classification for categorical values contained in our data sets. Since this step makes the target data even more sparse and introduces asymmetric label co-occurrence, the learning of multi-label classification models becomes difficult and heavily impacts the GNN's performance. To address these challenges, we propose a new data oversampling technique to improve multi-label classification performances on all the given imbalanced molecular graph data sets. Using the technique, we improve the data imbalance ratio of the drug effects better than before while protecting the data set's integrity. Finally, we evaluate multi-label classification performance using the best-performant hybrid GNN model on all the oversampled data sets obtained from the proposed oversampling technique. These results outperform those of other ML models including GNN models when they are trained on the original data sets or oversampled data sets using MLSMOTE (a well-known oversampling technique) in all evaluation metrics precision, recall, and F1 score by a significant margin.

Bose, Avishek [ORNL]↗

Beyond leading twist: 𝜌 meson decay constants and distribution amplitudes in a self-consistent light-front quark model

In this study, we present a comprehensive analysis of decay constants and chiral-even and chiral-odd distribution amplitudes (DAs) up to twist 4 for the 𝜌 meson in the standard light-front quark model (LFQM) based on the Bakamjian-Thomas (BT) construction. For the 𝜌 meson, which possesses both longitudinal (ℎ=0) and transverse (ℎ =±1) polarizations, two types of decay constants, 𝑓$^{∥}_{𝜌}$ and 𝑓$^{⊥}_{𝜌}$, arises accordingly. We demonstrate that these decay constants can be self-consistently extracted from both local (𝑧𝜇 =0) and nonlocal (𝑧𝜇 ≠0) matrix elements ⟨0⁢|$\overline{𝑞}$(𝑧)⁢Γ⁢𝑞⁡(−𝑧)|⁢𝜌⁡(𝑃,ℎ)⟩, with Γ=(𝛾 𝜇 ,𝜎 𝜇⁢𝜈 ,𝛾 𝜇 ⁢𝛾 5 ,𝟏), in a manner independent of current components, polarizations, and reference frames. In particular, we emphasize the role of nonlocal matrix elements involving axial-vector and scalar currents, where mixing between 𝑓$^{∥}_{𝜌}$ and 𝑓$^{⊥}_{𝜌}$ occurs. We show that this mixing is consistently resolved through the BT construction, ensuring the proper extraction of these decay constants.

Electroweak interaction↗

Real singlet scalar benchmarks in the multi-TeV resonance regime

Scalar extensions of the Standard Model (SM) are of much interest at the Large Hadron Collider (LHC) and future colliders. In particular, these models can give rise to resonant di-Higgs production and alter the Higgs trilinear coupling. In this paper, we study di-Higgs production in the Standard Model extended by a real scalar singlet with no additional symmetries. We determine how large the resonant di-Higgs rate and variation in the Higgs trilinear coupling can be in four scenarios: current LHC results and projected results at the high luminosity LHC (HL-LHC), the HL-LHC combined with a circular 𝑒 − ⁢𝑒 + collider such as the Circular Electron Positron Collider or Future Circular Collider with electron-positron collisions, and the HL-LHC combined with a linear 𝑒 − ⁢𝑒 + collider such as the International Linear Collider. While these are updated results from a previous study by [I. M. Lewis and M. Sullivan, Benchmarks for double Higgs production in the singlet extended standard model at the LHC, Phys. Rev. D 96, 035037 (2017).] using current LHC data, we go further and find benchmark points in the multi-TeV resonance regime for future colliders beyond the HL-LHC. Considering current LHC results, the resonant di-Higgs rate can still be an order of magnitude larger than the SM predicted di-Higgs rate. In the HL-LHC scenario, the Higgs trilinear coupling can still be a factor of three larger than the SM prediction for resonance masses in the 1.5–3.5 TeV range, where resonant searches may have less reach. This enhancement is just at the projected 2⁢𝜎 sensitivity of the HL-LHC. We find there are resonance masses for which the change in the Higgs trilinear is maximized while the resonant rate is negligible. We provide an analytical understanding of these effects with a discussion on the interplay of various constraints on the parameter space and the Higgs trilinear coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Semiconductor Nanostructures by Scientific Design (Final Technical Report)

We developed and used quantum simulation techniques to predict structural, electronic, optical and thermal properties affecting the scientific design of semiconductor nanostructures. We focused on the study of surfaces and interfaces at the nanoscale, in particular embedding and solvation of semiconductor nanoparticles, and provided a microscopic description of nanostructured materials in realistic environments, directly comparable with experimental conditions. We addressed three major problems: (i) the design of realistic structural models of integrated nanostructures, e.g. quantum dots embedded in solid matrices and nanostructures immersed in fluids; (ii) the development of efficient and accurate calculations to describe the excited state properties of nanostructures, beyond standard Density Functional Theory, so as to understand and predict electronic properties involved in renewable energy applications, for example solar conversion devices. In particular we developed and used methods based on a many body perturbation theory. (iii) the development of calculations of heat transport properties of nanostructured materials, for thermoelectric applications, including predictive calculations of thermal and electrical conductivity and of Seebeck coefficients. Specifically, we developed and used methods based on the Boltzmann transport equation and molecular dynamics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗