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DOE OSTI2025

Optimization of the BDX experiment for Light Dark Matter searches at JLab

The Light Dark Matter (LDM) hypothesis postulates the existence of a new class of sub GeV particles, neutral under Standard Model (SM) interactions. In its simplest form, LDM consists of particles ¿ with masses below 1 GeV/c2, interacting with SM particles via a new force mediated by a light, spin-1 boson A0, commonly referred to as “Dark Photon”. This framework envisions a distinct “Dark Sector” with its own particles and interactions, offering a theoretically well motivated explanation for Dark Matter, consistent with astrophysical observations and a thermal production mechanism. The Beam Dump eXperiment (BDX) is an approved experiment at Jefferson Lab designed to search for Light Dark Matter. BDX will utilize an 11 GeV electron beam impinging on a thick target to produce a forward-boosted secondary beam of Light Dark Matter particles, which will then be detected by a dedicated downstream detector. Approved in 2018, BDX is expected to be commissioned in 2026 and run in 2027-2029. My thesis focuses on the preparatory work to deploy the BDX experiment. The detector design has been optimized to balance practicality with enhanced Light Dark Matter detection capabilities. Extensive characterization of detector components has been performed to ensure a precise understanding of detector response. A custom Monte Carlo framework has been developed to simulate Light Dark Matter signal and explore various theoretical models of interest. Additionally, a comprehensive data analysis framework has been developed to maximize the experiment sensitivity to Light Dark Matter, with optimizations based on expected detector performance. The ultimate goal of this thesis is to optimize BDX as a flagship experiment in Light Dark Matter searches, enabling it to probe different Dark Matter models.

Spreafico, M. [Univ. of Genova (Italy)]↗

DOE OSTI2022

Search for Lepton Flavor Violation in Two Body Muon and Pion Decay at Rest

The ability of the Mu2e experiment to probe, or discover beyond the Standard Model physics in direct Charged Lepton Flavor Violation $\mu^+$ and $\pi^+$ decay modes is estimated. These direct modes are searched for simultaneously with proposed Mu2e detector validation runs, and are complementary to the Mu2e main search goal, an indirect search for $\mu^- \to e^-$ conversion at the sensitivity level of $\sim 10^{-17}$. The $\mu^+$ validation run will operate at 50% nominal magnetic field and reduced proton beam intensity to less than 1/100th nominal, in order to observe the e+ spectrum from $\mu^+$ decay, at and below the Michel edge Ee . 53 MeV. The $\pi^+$ validation run, based on measuring the mono-energetic e+ emission in the decay $\pi^+ \to e+\nu$, at 76% of nominal magnetic field and reduced beam intensity less than 1/5th nominal. Both of these runs can be used to fix the momentum scale for the Mu2e conversion search. In addition the muon validation dataset can be used to correct for systematic errors in the detector response by mapping the well known to O(\u03B13) corrected theoretical Michel spectrum, to the observed spectrum. One direct search is for two-body Charged Lepton Flavor Violation $\mu^+ \to e^+X$ decay, where $X$ is a light new physics particle. This allows Mu2e to explore well motivated models including axion like particles with flavor violating couplings and massive $Z^0$ bosons with more sensitivity then present astrophysical and laboratory constraints. In two weeks of data-taking, Mu2e can achieve direct mode 90% confidence level branching ratio limits of $10^{-7}$ over the mass range $20 \le m_X \le 50$ MeV, improving the current experimental limit at $10^{-5}$ by two orders of magnitude. In the mass range $m_X \le 20$ MeV, assuming systematic error corrections can be made by correcting the Monte Carlo mapping, the achievable search sensitivity is found to be $2.3\times 10^{-7}$ for $m_X =0$, an order of magnitude improvement over the current best limit at $2.6\times 10^{-6}$, when assuming $V+A$ or isotropic coupling. The $\pi^+$ validation run, allows searching for $\pi^+ \to e^+N$ decay, where $N$ is a heavy neutral lepton such as a heavy sterile neutrino, in the mass region $20 \le m_N \le 65$ MeV. A branching ratio limit at 90% confidence level of $3\times 10^{-8}$ can be achieved in two weeks, an improvement of the current search sensitivity limit by an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2006

An Overview of Space Exploration Simulation (Basis of Confidence) Documentation

Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations by providing critical information that supports key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision making. In this presentation we will describe how development of simulation capability documentation will be used to form a Basis of Confidence (Basis of Confidence) for National Aeronautics and Space Administration (NASA) M&S. The process by which BOC documentation is developed will be addressed, as well as the structure and critical concepts that are essential for establishing credibility of NASA's Exploration Systems Mission Directorate (ESMD) legacy M&S. We will illustrate the significance of BOC documentation in supporting decision makers and Accreditation Authorities in M&S risk management.

Bray, Alleen↗

DOE OSTI2024

Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets

Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a “fossil-fueled development” scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8–2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2008

Automatic Testcase Generation for Flight Software

The TacSat3 project is applying Integrated Systems Health Management (ISHM) technologies to an Air Force spacecraft for operational evaluation in space. The experiment will demonstrate the effectiveness and cost of ISHM and vehicle systems management (VSM) technologies through onboard operation for extended periods. We present two approaches to automatic testcase generation for ISHM: 1) A blackbox approach that views the system as a blackbox, and uses a grammar-based specification of the system's inputs to automatically generate *all* inputs that satisfy the specifications (up to prespecified limits); these inputs are then used to exercise the system. 2) A whitebox approach that performs analysis and testcase generation directly on a representation of the internal behaviour of the system under test. The enabling technologies for both these approaches are model checking and symbolic execution, as implemented in the Ames' Java PathFinder (JPF) tool suite. Model checking is an automated technique for software verification. Unlike simulation and testing which check only some of the system executions and therefore may miss errors, model checking exhaustively explores all possible executions. Symbolic execution evaluates programs with symbolic rather than concrete values and represents variable values as symbolic expressions. We are applying the blackbox approach to generating input scripts for the Spacecraft Command Language (SCL) from Interface and Control Systems. SCL is an embedded interpreter for controlling spacecraft systems. TacSat3 will be using SCL as the controller for its ISHM systems. We translated the SCL grammar into a program that outputs scripts conforming to the grammars. Running JPF on this program generates all legal input scripts up to a prespecified size. Script generation can also be targeted to specific parts of the grammar of interest to the developers. These scripts are then fed to the SCL Executive. ICS's in-house coverage tools will be run to measure code coverage. Because the scripts exercise all parts of the grammar, we expect them to provide high code coverage. This blackbox approach is suitable for systems for which we do not have access to the source code. We are applying whitebox test generation to the Spacecraft Health INference Engine (SHINE) that is part of the ISHM system. In TacSat3, SHINE will execute an on-board knowledge base for fault detection and diagnosis. SHINE converts its knowledge base into optimized C code which runs onboard TacSat3. SHINE can translate its rules into an intermediate representation (Java) suitable for analysis with JPF. JPF will analyze SHINE's Java output using symbolic execution, producing testcases that can provide either complete or directed coverage of the code. Automatically generated test suites can provide full code coverage and be quickly regenerated when code changes. Because our tools analyze executable code, they fully cover the delivered code, not just models of the code. This approach also provides a way to generate tests that exercise specific sections of code under specific preconditions. This capability gives us more focused testing of specific sections of code.

Bushnell, David Henry↗

DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2013

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System↗

DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

NESC Peer Review of Exploration Systems Development (ESD) Integrated Vehicle Modal Test, Model Correlation, Development Flight Instrumentation (DFI) and Flight Loads Readiness; Uncertainty Propagation for Model Validation Sub-task

This report details a sub-task (regarding Uncertainty Propagation for Model Validation) from a NASA Engineering and Safety Center assessment that is a multi-year activity spanning the complete development of the Space Launch System integrated vehicle structural dynamic models, and the development of the certification of flight readiness for the Artemis 1 and Artemis 2 vehicles and their variants.

Exploration Systems Development; Development Fligh↗

DOE OSTI2025

Functional but not taxonomic diversity increases productivity of Populus in the southeastern United States

Plant interactions like competition and facilitation impact ecosystem function and resilience. Improving our understanding of the relationships between these interactions and community productivity has important implications for managers of production systems in forestry and agriculture as well as conservation science. Populus spp. are an excellent model system for exploring how inter‐ and intraspecific interactions impact ecosystem functions, such as productivity, in forest plantations. In this study, we compared aboveground productivity of six Populus clones from three different taxa grown in monoclonal and mixed‐clonal plots. The different mixture treatments were intended to experimentally test aboveground biomass response to contrasting levels of taxonomic diversity and functional diversity based on nitrogen use characteristics of Populus clones. We hypothesize that functional diversity would be more important than taxonomic diversity in increasing aboveground productivity of mixed‐clonal plantings compared to monocultures. In addition, a subset of treatments was carried out on additional sites representing a productivity gradient in order to determine if the relationship between biodiversity and productivity in these systems diminished at more productive sites as suggested by the stress‐gradient hypothesis. We found that functionally diverse mixtures of clones had greater yield of aboveground biomass than the average of their constituent monocultures, while more taxonomically diverse mixes of clones did not differ from the average of their constituent monocultures. However, when reestablished on sites with extremely high or low productivity, the best performing clone mixture also did not differ from the average of its constituent monocultures. Our results suggest that intimate clone mixtures of Populus have the potential to significantly increase productivity, but results vary by mixture and by site. To capitalize on positive biodiversity effects on yield in production systems, targeted mixtures based on divergent functional traits linked to different use and acquisition strategies for site‐specific limiting resources are most likely to be successful.

BEF↗

DOE OSTI2022

Implementing the three-particle quantization condition for π + π + K + and related systems

Recently, the formalism needed to relate the finite-volume spectrum of systems of nondegenerate spinless particles has been derived. In this work we discuss a range of issues that arise when implementing this formalism in practice, provide further theoretical results that can be used to check the implementation, and make available codes for implementing the three-particle quantization condition. Specifically, we discuss the need to modify the upper limit of the cutoff function due to the fact that the left-hand cut in the scattering amplitudes for two nondegenerate particles moves closer to threshold; we describe the decomposition of the three-particle amplitude K df,3 into the matrix basis used in the quantization condition, including both s and p waves, with the latter arising in the amplitude for two nondegenerate particles; we derive the threshold expansion for the lightest three-particle state in the rest frame up to O(1/L 5 ); and we calculate the leading-order predictions in chiral perturbation theory for K df,3 in the π + π + K + and π + K + K + systems. We focus mainly on systems with two identical particles plus a third that is different (“2+1” systems). We describe the formalism in full detail, and present numerical explorations in toy models, in particular checking that the results agree with the threshold expansion, and making a prediction for the spectrum of π + π + K + levels using the two- and three-particle interactions predicted by chiral perturbation theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗

DOE OSTI2023

The role of nonmetallic ion substitution in perovskite LaCoO 3 for improved oxygen evolution reaction activity

Transition metal perovskite (ABO 3 ) is an emerging type of oxygen evolution reaction (OER) electrocatalyst that shows reasonably good activity and moderate stability. Although efforts have been made to improve perovskite’ OER performance by various element substitution at A/B-site, the influence of ion, particularly non-metallic ion, substitutions on the OER mechanism are rarely studied. More and more evidence has shown that the metal-center theory has failed to explain lots of OER-related phenomena. Therefore, it is urgent to understand how the cation and anion sites in perovskite determine OER performance. In this work, we used a Fe and P co-doped LaCoO 3 as a model system to explore the influence of substitution in perovskite by combining operando/ex-situ X-ray characterization and density functional theory (DFT). We observed enhanced OER catalytic activities in co-doped materials, which are attributed to the stronger transition-metal-oxygen-bonding-covalency (TMOBC). The detailed analyses by O K-edge XAS, electrochemical performance, and DFT suggest that the hybridization between O 2p and transition metal 3d e g orbitals could be a more credible descriptor of perovskite for OER, which is the combination of e g orbital theory and TMOBC theory. The finding in our work provides insights into the OER catalysis mechanism on metal oxides, which could guide new design of cost-effective oxide electrocatalysts.

25 ENERGY STORAGE↗

DOE OSTI2020

Vertical meteorological patterns and their impact on the energy demand of tall buildings

In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Finally, guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Experimental and numerical investigation of fracture conductivity between non-smooth rock surfaces with and without proppant

The enhancement of fracture conductivity is vital for the efficient recovery of subsurface resources, such as geothermal energy and petroleum hydrocarbons. Proppants, granular materials injected into hydraulic fractures to maintain their conductivity, have been studied primarily in the context of smooth fractures (i.e., fractures between smooth rock surfaces). However, non-smooth fractures (i.e., fractures between rough rock surfaces) are common in geoenergy reservoirs and thus require further investigations. In this study, we conducted laboratory measurements of fracture conductivity on shale slabs with non-smooth surfaces and carried out numerical simulation using the lattice Boltzmann (LB) method, which aimed to investigate the conductivity of non-smooth fractures with and without proppants placement. When ceramic proppant with an areal concentration of 2 lb/ft 2 was placed in the fracture, the conductivity was enhanced by roughly 3-8 times compared to fractures without proppant. In fractures with proppant, gas-measured conductivity was higher than that measured with water due to proppant embedment caused by water. The experiments demonstrate the advantages of using proppant in fractures, even if the rock surface roughness can provide certain fracture conductivity via the self-propping mechanism. For fractures without proppants, high rock surface roughness is not necessarily favorable for enhancing fracture conductivity because the self-propping mechanism requires shear slip along the fracture surface. If there is no shear slip, high rock surface roughness can cause a detrimental effect on the fracture conductivity due to the interlocking effect. Utilizing advanced experimental equipment and LB modeling, this research explores the interplays between proppant placement, fracture geometry, and stress conditions to develop a comprehensive understanding of the productivity in non-smooth fractures. Further, the outcomes of this investigation indicate the importance of creating fractures with surface roughness during hydraulic fracturing and will contribute to the development of more efficient stimulation techniques for subsurface energy extraction.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Hydrogenation of calcite and change in chemical bonding at high pressure: Diamond formation above 100GPa

Synchrotron X-ray diffraction (XRD) and Raman spectroscopy in laser heated diamond anvil cells and first principles molecular dynamics (FPMD) calculations have been used to investigate the reactivity of calcite and molecular hydrogen (H 2 ) at high pressures up to 120 GPa. We find that hydrogen reacts with calcite starting below 0.5 GPa at room temperature forming chemical bonds with carbon and oxygen. This results in the unit cell volume expansion; the hydrogenation level is much higher for powdered samples. Single-crystal XRD measurements at 8–24 GPa reveal the presence of previously reported III, IIIb, and VI calcite phases; some crystallites show up to 4% expansion, which is consistent with the incorporation of ≤ 1 hydrogen atom per formula unit. At 40–102 GPa XRD patterns of hydrogenated calcite demonstrate broadened features consistent with the calcite VI structure with incorporated hydrogen atoms. Above 80 GPa, the C–O stretching mode of calcite splits suggesting a change in the coordination of C–O bonds. Laser heating at 110 GPa results in the formation of C–C bonds manifested in the crystallization of diamond recorded by in situ XRD at 300 K and 110 GPa and by Raman spectroscopy on recovered samples commenced with C 13 calcite. We explored several theoretical models, which show that incorporation of atomic hydrogen results in local distortions of CO 3 groups, formation of corner-shared C–O polyhedra, and chemical bonding of H to C and O, which leads to the lattice expansion and vibrational features consistent with the experiments. In conclusion, the experimental and theoretical results support recent reports on tetrahedral C coordination in high-pressure carbonate glasses and suggest a possible source of the origin of ultradeep diamonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Shared mooring system designs and cost estimates for wave energy arrays

For floating renewable energy devices to become more cost-efficient and commercially scalable, their mooring system designs must be low-cost and suited for large-scale installations. Large arrays of floating devices, such as wave energy converters (WECs), will likely be designed with an individual mooring system for each device in the array. However, new mooring technology advancements provide options to use shared mooring lines to connect adjacent devices to one another, reducing the total number of anchors in the array, thereby reducing material use and cost. Here, this paper explores the design, modeling, and cost analysis of shared mooring systems for various sizes of arrays consisting of heaving oscillating water column (OWC) WECs. Shared mooring systems for WEC arrays sized in 2 x N and N x N grid layouts are designed to meet the relevant design standards, checking their performance with a nonlinear time-domain dynamic simulation, and the costs of each are calculated and compared. Several assumptions are taken in the design process to produce efficient results, providing a preliminary optimization for guidance on design decisions rather than a full, detailed design analysis. Mooring system costs per WEC were found to decrease as the number of WECs in the array increase, up to certain array sizes. The 2 x 3 array had the lowest mooring system cost per WEC out of all arrays considered, with a 60% cost reduction relative to using individual mooring systems. The 3 x 3 and 4 x 4 arrays achieved a 50% cost per WEC reduction. In addition to these significant cost reductions, the shared mooring system designs can provide advantages through smaller mooring system footprints, lower installation times, and less seabed disturbance.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Construction of extracellular matrix-based 3D hydrogel and its effects on cardiomyocytes

Highlights: • SOD and Triton X-100 could efficiently decellularize cells to get cardiac ECM. • Main proteins of cECM were fibronectin, collagen, elastin, fibrillin, laminin, etc. • 75% cECM-containing 3D hydrogel promoted cell proliferation and anti-apoptosis. • cECM3DH facilitated the differentiation of ESCs into CMs. • APcECM3DH was more conducive to NCM and ESC-derived CM maturation. Some discoveries resulted from 2-dimensional (2D) cultured cardiac cells have been disqualified in animal testing and later clinical trials. Extracellular matrix (ECM) plays a vital role in cardiac homeostasis, cardiac ECM (cECM)-based 3D cell cultures can mimics the physiological and pathological conditions in vivo closely, it is hopeful of addressing this challenge. Construction of cECM-based 3-dimensional (3D) hydrogel (cECM3DH) and its effects on cell behaviors were studied here. The results indicated that cellular compartments could be efficiently removed from heart tissue via sodium dodecyl sulfonate (SDS)- and Triton X-100-mediated decellularization, remaining the natural fibrous network structure and major proteins. 3D hydrogel consisted of 1 × 10{sup 7} cells/mL cells and 75% cECM could promote the proliferation and anti-apoptosis ability of human embryonic kidney (HEK)-293T cells. 0.25% trypsin or 0.20% collagenase was suitable to retrieve these cells from 3D hydrogel for further researches. Compared with 2D culture system, cECM3DH could significantly increase the proportion of GATA 4{sup +} cardiomyocytes (CMs) derived from heart tissue of neonatal mouse or induced differentiation of embryonic stem cells (ESCs) (P < 0.05) The expression levels of mature genes including cTnT, JCN, CaV1.2, MYL2, CASQ2, NCX1, and Cx43 of these CMs in adult pig cECM-based 3D hydrogel (APcECM3DH) were significantly higher than that in 2D culture system and in newborn piglet cECM-based 3D hydrogel (NPcECM3DH), respectively (P < 0.05). Therefore, cECM3DH supports the generation of primary CMs and ESC-derived CMs, APcECM3DH was more conducive to promoting CM maturation, which contributes to building 3D model for pathogenesis exploration, drug screening, and regenerative medicine of heart diseases.

60 APPLIED LIFE SCIENCES↗