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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Utah FORGE Project 3-2417: DAS Microseismic Event Catalog from the 16A/16B Circulation Test, 2023

This preliminary data archive includes the relocated microseismic event catalog, 1D velocity model, and methods report from DAS acquisition conducted during the Well 16A and 16B circulation test (July 19th and 20th, 2023) at Utah FORGE. The methods report describes all processing steps, including real-time event detection, hierarchical clustering, joint velocity/hypocenter inversion, and relocation. The resulting work is accepted and will be presented at IMAGE 2024. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Geothermal Fault Zone and Fluid Imaging through Joint Airborne ZTEM and Ground MT Data Inversion Analysis

This project has aimed to achieve detailed electrical resistivity resolution at geothermal reservoir scales by combining airborne natural electromagnetic (EM) field surveying (ZTEM) with ground magnetotelluric (MT) measurements to approximate an airborne MT geophysical method. MT alone is relatively expensive and may have permitting challenges in sensitive areas. Airborne ZTEM field data contains only the magnetic field, requires a background assumption, and has been limited to relatively high frequencies, thus suffering uniqueness problems. Based on proto-type 2D simulations, ZTEM ambiguities may be reduced through formal incorporation with possibly sparse ground MT soundings, which we pursued in full 3D for this project. The methodology was tested at the high-temperature Roosevelt Hot Springs geothermal system, Utah, which was considered advantageous given the near total exposure of crystalline reservoir rocks across the project area. ZTEM and ground MT survey data were acquired in 2017, subcontracted to outside parties with which we have worked in the past. These included 80 remote-referenced tensor MT soundings over the Mineral Mountains and adjacent Roosevelt Hot Spring producing geothermal system. These MT stations abut later coverage of a similar number of MT stations taken for the Utah FORGE project providing excellent total data aperture to re-solve structure beneath both project areas better than either set alone. The airborne ZTEM survey covered 704 line kilometers in E-W flight lines with a 250 m line spacing. Although this survey was timed during a maintenance-related shutdown of power production at the Roosevelt Hot Springs, other noise sources difficult to identify but including two high-voltage state-scale transmission lines compromised the ZTEM survey badly leading to unusable responses. Thus, with DOE management concurrence, the project proceeded to emphasize inversion and interpretation of the joint SubTER-FORGE MT data sets with regard to the Roosevelt Hot Springs reservoir recharge and to deep heat sources for both it and the Utah FORGE EGS project area. We also investigated the joint ZTEM-MT sampling concept with data sets from the Eleven Mile Canyon prospect area donated by the U.S. Navy (A. Sabin, PoC). Inversion of the SubTER-FORGE MT data using the HexMT 3D finite element algorithm reveals a large, low-resistivity anomaly extending sub-vertically through the depth range of the crust beneath the western Mineral Mountains. The steep conductive zone connects in the lower crust to a more tabular conductor characteristic of much of the Great Basin that generally is ascribed to current mafic magmatic underplating, hybridization and fluid release. The location of the resolved anomaly relative to the recent (0.5-0.8 Ma) eruptive centers of the Mineral Mountains implicates it as remnants of the magma body which fed these centers. This structure appears to be currently feeding heat and fluids upward into the Roosevelt Hot Springs hydrothermal system, as well as heat laterally to the FORGE project area. Separate and joint inversion models were carried out for the donated Eleven Mile Canyon MT-ZTEM data set to demonstrate concept. ZTEM only inversion showed two main alteration zones in the western portion of the project area known from geological mapping. Joint inversion including an E-W profile of MT soundings sharpened these features considerably. It also resolved in much greater detail the graben related normal faulting structure of the central project area which lies at depths exceeding the sensitivity of ZTEM alone. The sparse number of MT da-ta relative to the ZTEM required upweighting the former by a factor of several, but an exact procedure awaits future research. Our final impression is that sparse MT data can improve resolution of the subsurface over that of ZTEM alone. However, well sampled MT data are to be preferred and offer the simplicity of interpreting just one data type, and possess the superior resolution capability coming with the electric field everywhere, and from their high bandwidth.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Composite Structured Surfaces for Durable Dropwise Condensation

Dropwise condensation of steam on hydrophobic substrates has a 10X higher heat transfer coefficient compared to filmwise condensation. To promote dropwise condensation, low surface energy hydrophobic coatings (polymers) are typically utilized. The low intrinsic thermal conductivity (k < 1 W/(m · K)) of polymers, coupled with high heat transfer coefficient of dropwise condensation (100 kW/(m 2 · K)), necessitates that the coating be thin (< 1µm) in order to avoid reducing the overall heat exchanger conductance. However, thin polymeric films easily degrade. The two opposing requirements result in the need for optimization between the durability (thick coating) and the heat transfer (thin coating). To enable high thermal conductivity in thicker coatings, we develop metal-polymer structured surfaces. By using porous structures as inter-connected heat-conducting backbones that are filled with hydrophobic materials, we enable tuning of the coating effective thermal conductivity and surface energy. Three metal structures were studied; micro/nanowires, inverse opals, and sintered spheres. Heat transfer performance was calculated using three-dimensional finite element method simulations with two distinct boundary conditions; convection at the walls and isothermal walls. Interestingly, the overall conductance shows up to 40% difference depending on the boundary condition used in calculating the composite coating effective thermal conductivity. We use our model to predict the heat transfer performance as a function of metal fraction by volume and by surface area for condensation. By coupling our thermal simulations with a previously verified analytical model for predicting wetting behavior on heterogeneous surfaces, we propose a regime map to predict dropwise-to-filmwise transition. Furthermore, our work not only forms a starting point for the development of durable dropwise condensing surfaces, it identifies important considerations needed for computing effective thermal conductivity of composites.

42 ENGINEERING↗
DOE OSTI2023

Tunable ferroelectricity in oxygen-deficient perovskites with Grenier structure

Using first-principles calculations, we predict that tunable ferroelectricity can be realized in oxide perovskites with the Grenier structure and ordered oxygen vacancies. Specifically, we show that R 1/3 A 2/3 FeO 2.67 solids (where R is a rare-earth ion and A an alkaline-earth cation) exhibit polar phases, with a spontaneous polarization tunable by an appropriate choice of R and A. We find that larger cations combined with small R elements lead to a maximum in the polarization and to a minimum in the energy barriers required to switch the sign of the polarization. Ferroelectricity arises from cooperative distortions of octahedral and tetrahedral units, where a combination of rotational and sliding modes controls the emergence of polarization within three-dimensional connected layers. Our results indicate that polar Grenier phases of oxide perovskites are promising materials for microelectronic applications and, in general, for the study of phenomena emerging from breaking inversion symmetry in solids.

Electronic devices↗
DOE OSTI2025

Application of physics-informed neural networks (PINNs) solution to coupled thermal and hydraulic processes in silty sands

Abstract The accurate modeling of water and heat transport in soils is crucial for both geo-environmental and geothermal engineering. Traditional modeling methods are problematic because they require well-defined boundaries and initial conditions. Recently, physics-informed neural networks (PINNs), which incorporate partial differential equations (PDEs) to solve forward and inverse problems, have attracted increasing attention in machine learning research. In this study, we applied PINNs to tackle hydraulic and thermal transport coupling forward problems in silty sands. A fully connected deep neural network was utilized for training. This neural network model leverages automatic differentiation to apply the governing equations as constraints, based on the mathematical approximations established by the neural network itself. We conducted forward problems and compared the solutions derived from PINNs with those from Finite Element Method (FEM) simulations. The forward problem results demonstrate the PINNs model’s capability in predicting hydraulic transport, heat transport, and thermal–hydraulic coupling in silty sands under various boundary conditions. The PINNs exhibited great performance in simulating the thermal–hydraulic coupling problem. The accuracy of the PINNs solutions shows its potential for simulation in geotechnical engineering.

Feng, Yuan↗
DOE OSTI2023

The Effect of Monomer Size on Fusion and Coupling in Colloidal Quantum Dot Molecules

The fusion step in the formation of colloidal quantum dot molecules, constructed from two core/shell quantum dots, dictates the coupling strength and hence their properties and enriched functionalities compared to monomers. Herein, studying the monomer size effect on fusion and coupling, we observe a linear relation of the fusion temperature with the inverse nanocrystal radius. This trend, similar to that in nanocrystal melting, emphasizes the role of the surface energy. The suggested fusion mechanism involves intraparticle ripening where atoms diffuse to the reactive connecting neck region. Moreover, the effect of monomer size and neck filling on the degree of electronic coupling is studied by combined atomistic-pseudopotential calculations and optical measurements, uncovering strong coupling effects in small QD dimers, leading to significant optical changes. Understanding and controlling the fusion and hence coupling effect allows tailoring the optical properties of these nanoscale structures, with potential applications in photonic and quantum technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chiral Magnetic Josephson Junction as a Base for Low-Noise Superconducting Qubits

The lack of space inversion symmetry endows non-centrosymmetric superconducting materials with various interesting parity-breaking phenomena, including the anomalous Josephson effect. Our paper considers a Josephson junction of two non-centrosymmetric superconductors connected by a uniaxial ferromagnet. We show that this “Chiral Magnetic Josephson junction” (CMJ junction) exhibits a direct analog of the Chiral Magnetic Effect, which has already been observed in Weyl and Dirac semimetals. We suggest that the CMJ can serve as an element of a qubit with a Hamiltonian tunable by the ferromagnet’s magnetization. The CMJ junction avoids using an offset magnetic flux in inductively shunted qubits, thus enabling a simpler and more robust architecture. Furthermore, when the uniaxial ferromagnet’s easy axis is directed across the junction, the resulting “chiral magnetic qubit” provides robust protection from the noise caused by magnetization fluctuations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Degrees of Rate Control in Interconnected Reaction Networks

Overall reactions in interconnected networks exhibit net, forward, and reverse rates that are governed by both constitutive elementary steps in the pathway of interest and branching elementary steps that lead to alternative products. Accordingly, steps in branching pathways exhibit negative net, forward, and reverse degrees of rate control, as they reduce reaction flux to the desired product. We here contextualize the forward and reverse degrees of rate control in terms of kinetic resistances (inverse of rates) and leverage the additive nature of kinetic resistance to decouple kinetic driving forces contributed by constitutive elementary steps and branching points (nodal species) in interconnected networks. Regardless of the network connectivity, forward and reverse degrees of rate control are shown to converge at equilibrium. Away from equilibrium, we identify two critical features of interconnected networks: stoichiometric regularity─condition where all stoichiometric numbers are unity─and pathway symmetry around nodal species─condition where branching pathways share the same rate constants, stoichiometry, and species concentrations/activities─that result in (i) equal forward, reverse, and consequently net degrees of rate control and (ii) forward and reverse degrees of rate control that exhibit constant offsets, respectively, across all extents of reaction. Furthermore, our discourse further provides a mathematical description for the influence of stoichiometric irregularity and pathway asymmetry on forward and reverse degrees of rate control. Altogether, the presented work details the effects of network (inter)connectivity and stoichiometry on reaction kinetics and, in doing so, establishes general protocols for capturing these effects as additive terms in the formulation of forward and reverse degrees of rate control.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Unveiling the Significance of Correlations in K-Space and Configuration Space for Drift Wave Turbulence in Tokamaks

Turbulence and transport phenomena play a crucial role in the confinement and stability of tokamak plasmas. Turbulent fluctuations in certain physical quantities, such as density or temperature fluctuations, can have a wide range of spatial scales, and understanding their correlation length is important for predicting and controlling the behavior of the plasma. The correlation length in the radial direction is identified as the critical length in real space. The dynamics in real space are of significant interest because transport in configuration space is primarily focused on them. When investigating transport caused by the E×B drift, the correlation length in real space represents the size of E×B whirls. It was numerically discovered that in drift wave turbulence, this length is inversely proportional to the normalized mode number of the fastest growing mode relative to the drift frequency. Considerable time was required before a proper analytical derivation of this condition was accomplished. Therefore, a connection has been established between phenomena occurring in real space and those occurring in k-space. Although accompanied by a turbulent spectrum in k-space with a substantial width, transport in real space is uniquely determined by the correlation length, allowing for accurate transport calculations through the dynamics of a single mode. Naturally, the dynamics are subject to nonlinear effects, with resonance broadening in frequency being the most significant nonlinear effect. Thus, mode number space is once again involved. Resonance broadening leads to the detuning of waves from particles, permitting a fluid treatment. It should be emphasized that the consideration here involves the total electric field, including the induction part, which becomes particularly important at higher beta plasmas.

Weiland, Jan (ORCID:0000000253496025)↗
DOE OSTI2021

Multiterminal Inverse AC Josephson Effect

When a Josephson junction is exposed to microwave radiation, it undergoes the inverse AC Josephson effect–the phase of the junction locks to the drive frequency. As a result, the I–V curves of the junction acquire “Shapiro steps” of quantized voltage. If the junction has three or more superconducting contacts, coupling between different pairs of terminals must be taken into account and the state of the junction evolves in a phase space of higher dimensionality. Here, we study the multiterminal inverse AC Josephson effect in a graphene sample with three superconducting terminals. We observe robust fractional Shapiro steps and correlated switching events, which can only be explained by considering the device as a completely connected Josephson network. We successfully simulate the observed behaviors using a modified two-dimensional RCSJ model. Our results suggest that multiterminal Josephson junctions are a playground to study highly connected nonlinear networks with novel topologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Connecting Hindered Transport in Porous Media across Length Scales: From Single-Pore to Macroscopic

Hindered mass transport is widely observed in various porous media, including filtration membranes and porous rocks. However, there is no universal model capable of predicting transport in porous media due to the heterogeneity of porous structures and the complexity of the underlying microscopic mechanisms, including electrostatic and hydrodynamic effects. Here, we used a highly ordered porous medium (i.e. a silica inverse opal film) as a model system to directly explore the effects of geometric parameters (i.e. pore size, pore throat size and tracer particle size) and microscopic interaction parameters (e.g. controlled by ionic strength) on nanoparticle transport in porous environments using three-dimensional single-particle tracking. We found a linear scaling relation between the macroscopic diffusion coefficient and microscopic diffusion behaviors and a combination of parameters associated with microscopic features and phenomena, including both geometric effects and particle-level interactions. The proportionality coefficient relating micro and macro behaviors was complex and related to the connectivity of the matrix and pore-size variation, which could lead to tortuous diffusion pathways, hindering macroscopic transport. Furthermore, these findings provide important insights into nanoparticles and macromolecules transport in various porous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantum algorithms from fluctuation theorems: Thermal-state preparation

Fluctuation theorems provide a correspondence between properties of quantum systems in thermal equilibrium and a work distribution arising in a non-equilibrium process that connects two quantum systems with Hamiltonians H 0 and H 1 = H 0 + V. Building upon these theorems, we present a quantum algorithm to prepare a purification of the thermal state of H 1 at inverse temperature β ≥ 0 starting from a purification of the thermal state of H 0 . The complexity of the quantum algorithm, given by the number of uses of certain unitaries, is $\mathcal{O}$ (e β(ΔA - w l )/2 ), where ΔA is the free-energy difference between H 1 and H 0 , and w l is a work cutoff that depends on the properties of the work distribution and the approximation error ϵ > 0. If the non-equilibrium process is trivial, this complexity is exponential i β∥V∥, where ∥V∥ is the spectral norm of V. This represents a significant improvement of prior quantum algorithms that have complexity exponential in β∥H 1 ∥ in the regime where ∥V∥$\ll$ ∥H 1 ∥. The dependence of the complexity in ϵ varies according to the structure of the quantum systems. It can be exponential in 1/ϵ in general, but we show it to be sublinear in 1/ϵ if H 0 and H 1 commute, or polynomial in 1/ϵ if H 0 and H 1 are local spin systems. The possibility of applying a unitary that drives the system out of equilibrium allows one to increase the value of w l and improve the complexity even further. To this end, we analyze the complexity for preparing the thermal state of the transverse field Ising model using different non-equilibrium unitary processes and see significant complexity improvements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Tunable Metal–Organic Frameworks Based on 8-Connected Metal Trimers for High Ethane Uptake

Metal trimers [M 3 (O/OH)](OOCR) 6 are among the most important structural building blocks. From these trimers, a great success has been achieved in the design of 6- or 9-connected framework materials with various topological features and outstanding gas-sorption properties. In comparison, 8-connected trimer-based MOFs are rare. Given multiple competitive pathways for the formation of 6- or 9-connected frameworks, it remains challenging to identify synthetic or structural parameters that can be used to direct self-assembly process towards trimer-based 8-connected materials. Here, we reveal a viable strategy called angle bending modulation for creating a prototypical MOF type based on 8-connected M 3 (OH)(OOCR) 5 (Py-R) 3 trimers, M = Zn, Co, Fe). As a proof of concept, we synthesized six members in this family using three types of ligands (CPM-80, -81, and -82). These materials do not possess open-metal sites and show excellent uptake capacity for various hydrocarbon gas molecules and inverse C 2 H 6 /C 2 H 4 selectivity. CPM-81-Co, made from 2,5-furandicarboxylate and isonicotinate, features selectivity of 1.80 with high uptake capacity for ethane (123 cm 3 /g -1 ) and ethylene (113 cm 3 /g -1 ) at 298 K and 1 bar.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2021

Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss

Proteinaceous aggregates containing ?-synuclein protein called Lewy bodies in the substantia nigra is a hallmark of Parkinson’s disease. The molecular mechanisms of Lewy body formation and associated neuronal loss remain largely unknown. To gain insights on proteins and pathways associated with Lewy body pathology, we performed quantitative profiling of the proteome. We analyzed substantia nigra tissue from 51 subjects arranged into three groups: cases with Lewy body pathology, Lewy body-negative controls with matching neuronal loss and controls with no neuronal loss. Using label-free LC-MS/MS approach we quantified the 2,963 most abundant proteins. Statistical testing for differential protein abundance, followed by pathway enrichment and Bayesian learning of the causal network structure were performed to identify likely drivers of Lewy body formation and dopaminergic neuronal loss. The identified pathways include (1) Arp2/3 complex-mediated actin nucleation; (2) synaptic function; (3) poly(A) RNA binding; (4) basement membrane and endothelium; and (5) hydrogen peroxide metabolic process. According to the data, the endothelial/basement membrane pathway is tightly connected with both pathologies and likely to be one of the drivers of the neuronal loss. The poly(A) RNA-binding proteins, including the ones relevant to other neurodegenerative disorders (e.g. TDP-43 and FUS) have strong inverse correlation with Lewy bodies and may reflect alternative mechanism of nigral neurodegeneration.

Petyuk, Vladislav A.↗
DOE OSTI2025

Non-equilibrium anti-Stokes Raman spectroscopy for investigating Higgs modes in superconductors

Abstract Even before its role in electroweak symmetry breaking, the Anderson-Higgs mechanism was introduced to explain the Meissner effect in superconductors. Spontaneous symmetry-breaking yields massless phase modes representing the low-energy excitations of the Mexican-Hat potential. Only in superconductors the phase mode is shifted towards higher energies owing to the gauge field of the charged condensate. This results in a low-energy excitation spectrum governed by the Higgs mode. Consequently, the Bardeen-Cooper-Schrieffer-like Meissner effect signifies a macroscopic quantum condensate in which a photon acquires mass, representing a one-to-one analogy to high-energy physics. We report on an innovative spectroscopic technique to study symmetries and energies of the Higgs modes in the high-temperature superconductor Bi 2 Sr 2 CaCu 2 O 8 after a soft quench of the Mexican-Hat potential. Population inversion induced by an initial laser pulse leads to an additional anti-Stokes Raman-scattering signal, which is consistent with polarization-dependent Higgs modes. Within Ginzburg-Landau theory, the Higgs-mode energy is connected to the Cooper-pair coherence length. Within a Bardeen-Cooper-Schrieffer weak-coupling model we develop a quantitative and coherent description of single-particle and two-particle channels. This opens the avenue for Higgs Spectroscopy in quantum condensates and provides a unique pathway to control and explore Higgs physics.

Science & Technology - Other Topics↗
DOE OSTI2021

Underestimated marine stratocumulus cloud feedback associated with overly active deep convection in models

Cloud feedback remains the largest source of uncertainty in equilibrium climate sensitivity (ECS). Many studies have attempted to narrow uncertainties in cloud feedback and ECS by proposing observable metrics with high skill at predicting future climate, referred to as emergent constraints. These constraints are often associated with clouds, convection, and circulation, and are interrelated. However, physical explanations for these connections remain unclear. Here, we propose a new mechanism relating convection and clouds across multiple climate models. Some models show overly active deep convection on daily timescales in the subtropical low cloud regions, which contributes to weaker subsidence inversion and smaller amounts of low-level clouds. Such models predict smaller shortwave (SW) cloud feedback. Using precipitation frequency in these regions as an emergent constraint, encapsulating this mechanism, models with lower SW cloud feedback (<0.50 W m -2 °C - 1) are found to exhibit erroneously frequent convection. Our results suggest that further improvements in understanding and better modeling of cloud and convective systems are necessary for accurate climate predictions.

54 ENVIRONMENTAL SCIENCES↗