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At least 289 records · Page 16

Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods

Carbon capture and storage is one strategy to reduce greenhouse gas emissions. One approach to storing the captured CO2 is to inject it into deep saline aquifers. However, dynamics of the injected CO2 plume is uncertain and the potential for leakage back to the atmosphere must be assessed. Thus, accurate and timely forecasts of CO2 storage via real-time measurements integration becomes very crucial. This study proposes a learning-based, inverse-free prediction method that can accurately and rapidly forecast CO2 movement and distribution with uncertainty quantification based on limited simulation and observation data. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO2 storage site operators with an effective tool for real-time decision making.

Lu, Dan↗

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗

Topology Hierarchy of Transition Metal Dichalcogenides Built from Quantum Spin Hall Layers

The evolution of the physical properties of 2D material from monolayer limit to the bulk reveals unique consequences from dimension confinement and provides a distinct tuning knob for applications. Monolayer 1T'-phase transition metal dichalcogenides (1T'-TMDs) with ubiquitous quantum spin Hall (QSH) states are ideal 2D building blocks of various 3D topological phases. However, the stacking geometry has been previously limited to the bulk 1T'-WTe 2 type. Here, the novel 2M-TMDs consisting of translationally stacked 1T'-monolayers are introduced as promising material platforms with tunable inverted bandgaps and interlayer coupling. By performing advanced polarization-dependent angle-resolved photoemission spectroscopy as well as first-principles calculations on the electronic structure of 2M-TMDs, a topology hierarchy is revealed: 2M-WSe 2 , MoS 2 , and MoSe 2 are weak topological insulators (WTIs), whereas 2M-WS 2 is a strong topological insulator (STI). Further demonstration of topological phase transitions by tunning interlayer distance indicates that band inversion amplitude and interlayer coupling jointly determine different topological states in 2M-TMDs. Finally, it is proposed that 2M-TMDs are parent compounds of various exotic phases including topological superconductors and promise great application potentials in quantum electronics due to their flexibility in patterning with 2D materials.

36 MATERIALS SCIENCE↗

Elucidation of puzzling questions regarding the CrO x /Al 2 O 3 catalyst I. X-ray absorption spectroscopy aided identification of the nature of the chromium oxide species in the CrO x /Al 2 O 3 dehydrogenation catalyst system

The CATOFIN© process produces propylene from propane using a CrO x /Al 2 O 3 catalyst. Despite its use, there are still uncertainties surrounding the nature of Cr species formed during synthesis, regeneration, and aging. It has been observed that ppm levels of Cr 2 O 3 can be oxidized to Cr(VI) in air; however, when Cr 2 O 3 is in direct contact with Al 2 O 3 , Cr(VI) formation increased more than 100-fold. Here, to confirm physical contact between Cr 2 O 3 and Al 2 O 3 results in increased Cr(VI) formation, Cr 2 O 3 and Cr 2 O 3 /Al 2 O 3 samples were synthesized, calcined, and characterized. Catalytic activity measurements confirm propylene selectivity inversely tracks with Cr(VI). Wet chemical titration and X-ray absorption spectroscopy (XAS) quantified and determined the structure of the Cr(VI) species. FEFF X-ray absorption near edge structure simulations determined the potential sensitivity of the XAS to the presence of Al 3+ /Cr 3+ neighboring atoms. XAS correlated to FEFF simulations suggested that Al 3+ x Cr 3+ 2–x Cr 6+ 3 O 12 comprises a significant fraction of the Cr(VI) species formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of 17 N as a time-tagged neutron source for calibration of large antineutrino detectors

Large antineutrino detectors hold the potential for remote nuclear reactor monitoring and discovery, which is of great interest for nonproliferation and treaty verification applications. Correlated-particle calibration sources are especially useful for large-volume designs based on detection of inverse beta-decay events, as the timing information of the coincident particles improves background rejection and event reconstruction. 17 N is a promising calibration source since it emits beta-correlated delayed neutrons and can be produced relatively easily using high-energy neutrons. In this work, we examine the feasibility of 17 N as a time-tagged calibration source for large antineutrino detectors. 17 N was produced using a DT neutron generator from a water sample enriched in 17 O, and the observed production rates were found to be consistent with previous measurements of the 17 O(n,p) 17 N reaction cross-section. As a result, time-tagging of 17 N delayed neutrons is demonstrated via beta-neutron coincidence measurements conducted using a specialized beta detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ferrorotational domain walls revealed by electric quadrupole second harmonic generation microscopy

Domain walls are ubiquitous in materials that undergo phase transitions driven by spontaneous symmetry breaking. Domain walls in ferroics and multiferroics have received tremendous attention recently due to their emergent properties distinct from their domain counterparts—for example, their high mobility and controllability, as well as their potential applications in nanoelectronics. However, it is extremely challenging to detect, visualize, and study the ferrorotational (FR) domain walls because the FR order, in contrast to ferromagnetism and ferroelectricity, is invariant under both the spatial-inversion and the time-reversal operations and, thus, hardly couple with conventional experimental probes. Here, a FR candidate NiTi⁢O 3 is investigated by ultrasensitive electric quadrupole (EQ) second-harmonic generation rotational anisotropy (SHG RA) to probe the point symmetries of the two degenerate FR domain states, showing their relation by the vertical mirror operations that are broken below the FR critical temperature. We then visualize the real-space FR domains by scanning EQ SHG microscopy, and further, resolve the FR domain walls by revealing a suppressed SHG intensity at the domain walls. By taking local EQ SHG RA measurements, we show the restoration of the mirror symmetry at FR domain walls and prove their unconventional nonpolar nature. In conclusion, our findings not only provide a comprehensive insight into FR domain walls, but also demonstrate a unique and powerful tool for future studies on domain walls of unconventional ferroics both of which pave the way towards future manipulations and applications of FR domain walls.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A chiral switchable photovoltaic ferroelectric 1D perovskite

Spin and valley degrees of freedom in materials without inversion symmetry promise previously unknown device functionalities, such as spin-valleytronics. Control of material symmetry with electric fields (ferroelectricity), while breaking additional symmetries, including mirror symmetry, could yield phenomena where chirality, spin, valley, and crystal potential are strongly coupled. Here we report the synthesis of a halide perovskite semiconductor that is simultaneously photoferroelectricity switchable and chiral. Spectroscopic and structural analysis, and first-principles calculations, determine the material to be a previously unknown low-dimensional hybrid perovskite (R)-(-)-1-cyclohexylethylammonium/(S)-(+)-1 cyclohexylethylammonium) PbI 3 . Optical and electrical measurements characterize its semiconducting, ferroelectric, switchable pyroelectricity and switchable photoferroelectric properties. Temperature dependent structural, dielectric and transport measurements reveal a ferroelectric-paraelectric phase transition. Circular dichroism spectroscopy confirms its chirality. The development of a material with such a combination of these properties will facilitate the exploration of phenomena such as electric field and chiral enantiomer–dependent Rashba-Dresselhaus splitting and circular photogalvanic effects

36 MATERIALS SCIENCE↗

Three-Dimensional Aerodynamics and Vortex-Shedding Characteristics of Wind Turbine Airfoils over 360-Degree Angles of Attack

In this work, we present the first three-dimensional (3D) computational investigation of wind turbine airfoils over 360° angles of attack to predict unsteady aerodynamic loads and vortex-shedding characteristics. To this end, static–airfoil simulations are performed for the FFA-W3 airfoil family at a Reynolds number of 107 with the Improved Delayed Detached Eddy Simulation turbulence model. Aerodynamic forces reveal that the onset of boundary-layer instabilities and flow separation does not necessarily coincide with the onset of stall. In addition, a comparison with two-dimensional simulation data and flat plate theory extension of airfoil polars, suggest that, in the deep stall regime, 3D effects remain critical for predicting both the unsteady loads and the vortex-shedding dynamics. For all airfoils, the vortex-shedding frequencies are found to be inversely proportional to the wake width. In the case of slender airfoils, the frequencies are nearly independent of the airfoil thickness, and their corresponding Strouhal number St is approximately 0.15. Based on the calculated St, the potential for shedding frequencies to coincide with the natural frequencies of the International Energy Agency 15 MW reference wind turbine blades is investigated. The analysis shows that vortex-induced vibrations occur primarily at angles of attack of around ±90° for all airfoils.

17 WIND ENERGY↗

Biogeochemical Equilibrium Responses to Maximal Productivity in High Nutrient Low Chlorophyll Regions

Whether ocean iron fertilization in high nutrient low chlorophyll (HNLC) regions is a practical geoengineering strategy to combat climate warming has been debated because the fate of absorbed carbon by the ocean remains unclear. Here, we use an optimized oceanic biogeochemical inverse model to explore the equilibrium responses to increased productivity in major HNLC regions. We find that an overall downward shift of nutrients and carbon from the surface and intermediate to the deep waters with maximal productivity in the HNLC Southern Ocean (SO), North Pacific (NP) and eastern equatorial Pacific (EP). The efficiency of soft tissue pump is increased by 37.8%, 2.7% and 5.4% in the SO, EP and NP simulation while atmospheric CO 2 concentration is drawn down by 45.1, 3.4 and 6.7 ppm, respectively. Meanwhile, global mean oxygen is decreased by 21.1%, 1.3% and 2.4% in the SO, EP and NP simulation, accompanied by an expansion of oxygen minimum zones by 400%, 26% and 63%, respectively. Our study indicates that iron fertilization has the potential to be an effective geoengineering approach to mitigate climate warming but also has a strong impact on the development of ocean hypoxia.

59 BASIC BIOLOGICAL SCIENCES↗

Time-resolved site-selective imaging of predissociation and charge transfer dynamics: the CH 3 I B-band

The predissociation dynamics of the 6s (B 2 E) Rydberg state of gas-phase CH 3 I were investigated by time-resolved Coulomb-explosion imaging using extreme ultraviolet (XUV) free-electron laser pulses. Inner-shell ionization at the iodine 4d edge was utilized to provide a site-specific probe of the ensuing dynamics. The combination of a velocity-map imaging (VMI) spectrometer coupled with the pixel imaging mass spectrometry (PImMS) camera permitted three-dimensional ionic fragment momenta to be recorded simultaneously for a wide range of iodine charge states. In accord with previous studies, initial excitation at 201.2 nm results in internal conversion and subsequent dissociation on the lower-lying A-state surface on a picosecond time scale. Examination of the time-dependent yield of low kinetic energy iodine fragments yields mechanistic insights into the predissociation and subsequent charge transfer following multiple ionization of the iodine products. The effect of charge transfer was observed through differing delay-dependencies of the various iodine charge states, from which critical internuclear distances for charge transfer could be inferred and compared to a classical over-the-barrier model. Time-dependent photofragment angular anisotropy parameters were extracted from the central slice of the Newton sphere, without Abel inversion, and highlight the effect of rotation of the parent molecule before dissociation, as observed in previous works. Our results demonstrate the ability to perform three-dimensional ion imaging at high event rates and showcase the potential benefits of this approach, particularly in relation to further time-resolved studies at free-electron laser facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗

Stochastic evaluation of four-component relativistic second-order many-body perturbation energies: A potentially quadratic-scaling correlation method

A second-order many-body perturbation correction to the relativistic Dirac-Hartree-Fock energy is evaluated stochastically by integrating 13-dimensional products of four-component spinors and Coulomb potentials. The integration in the real space of electron coordinates is carried out by the Monte Carlo (MC) method with the Metropolis sampling, whereas the MC integration in the imaginary-time domain is performed by the inverse-CDF (cumulative distribution function) method. The computational cost to reach a given relative statistical error for spatially compact but heavy molecules is observed to be no worse than cubic and possibly quadratic with the number of electrons or basis functions. This is a vast improvement over the quintic scaling of the conventional, deterministic second-order many-body perturbation method. The algorithm is also easily and efficiently parallelized with demonstrated 92% strong scalability going from 64 to 4096 processors for a fixed job size.

74 ATOMIC AND MOLECULAR PHYSICS↗

Nearly-frustration-free ground state preparation

Solving for quantum ground states is important for understanding the properties of quantum many-body systems, and quantum computers are potentially well-suited for solving for quantum ground states. Recent work [1] has presented a nearly optimal scheme that prepares ground states on a quantum computer for completely generic Hamiltonians, whose query complexity scales as &#x03B4; &#x2212; 1 , i.e. inversely with their normalized gap. Here we consider instead the ground state preparation problem restricted to a special subset of Hamiltonians, which includes those which we term "nearly-frustration-free": the class of Hamiltonians for which the ground state energy of their block-encoded and hence normalized Hamiltonian &#x03B1; &#x2212; 1 H is within &#x03B4; y of -1, where &#x03B4; is the spectral gap of &#x03B1; &#x2212; 1 H and 0 &#x2264; y &#x2264; 1 . For this subclass, we describe an algorithm whose dependence on the gap is asymptotically better, scaling as &#x03B4; y / 2 &#x2212; 1 , and show that this new dependence is optimal up to factors of log &#x2061; &#x03B4; . In addition, we give examples of physically motivated Hamiltonians which live in this subclass. Finally, we describe an extension of this method which allows the preparation of excited states both for generic Hamiltonians as well as, at a similar speedup as the ground state case, for those which are nearly frustration-free.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO 2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO 2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO 2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO 2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO 2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

58 GEOSCIENCES↗

Insights into factors that affect non-Arrhenius migration of a simulated incoherent Σ3 grain boundary

Non-Arrhenius grain boundary migration, sometimes referred to as antithermal migration where temperature and GB velocity values are inversely related to each other, is examined in an incoherent twin Σ3 [111] 60° (11 8 5) nickel grain boundary. Molecular dynamics is used to simulate migration and examine the effect of various factors on the migration, including interatomic potential, system size, driving force, and variation of atomic grain boundary structure. A classical model for grain boundary migration, in its unsimplified form, is used to analyze the results. The grain boundaries exhibit migration mechanisms with very low apparent barrier heights to migration. As a result, the boundaries migrate quickly but exhibit a velocity saturation similar to that of dislocations. Furthermore, the various interatomic potentials exhibit different migration velocities, but their similarities suggest they all predict similar overall behaviors of migration. The variation of atomic structure in the same incoherent twin grain boundary leads to diverse behaviors with barrier heights that vary from non-Arrhenius to Arrhenius migration. Facet nucleation is confirmed not to be a requirement for this boundary based on an examination of simulation cell size; however, the presence and/or interaction between numerous facets does suggest a slowing and increased barrier height to migration for larger boundaries.

36 MATERIALS SCIENCE↗

Origins of Electrostriction in Poly(vinylidene fluoride)-Based Ferroelectric Polymers

Although electrostriction is ubiquitous for dielectric polymers, giant electrostriction has not been observed until relaxor ferroelectric (RFE) poly(vinylidene fluoride) (PVDF)-based polymers are achieved. However, the exact origin for giant electrostriction in these polymers has not been fully understood. By studying the electrostriction in the uniaxially stretched films of a ferroelectric poly(VDF-co-trifluoroethylene) [P(VDF-TrFE)] random copolymer and an RFE poly(VDF-co-TrFE-co-chlorotrifluoroethylene) [P(VDF-TrFE-CTFE)] random terpolymer in this work, we confirmed that ferroelectric switching with large hysteresis, such as in the case of P(VDF-TrFE), was not genuine electrostriction. By decreasing large ferroelectric domains to the nanometer scale (i.e., 2–3 nm), such as in the case of the P(VDF-TrFE-CTFE) terpolymer, electrostriction with low hysteresis could be achieved. Here, two origins of the large electrostriction in these polymers were identified. The first was the mechano-electrostriction due to the poling field-induced conformation transformation of oriented polymer chains. The second was the electric repulsion of electrically aligned nanodomains. These effects could occur in both crystals and the oriented amorphous fraction, which links between the nanocrystals and the isotropic amorphous fraction. When the poling field was relatively low (e.g., <40 MV/m), the mechano-electrostriction was the major contribution and the electric repulsion effect was a minor contribution to electrostriction. Meanwhile, a strong temperature dependence of the low-field electrostriction coefficient was observed. Finally, we found an empirical inverse relationship between the electrostriction coefficient and the product of Young’s modulus and dielectric constant. The knowledge obtained from this study provides an insightful understanding of the electrostriction mechanism in PVDF-based electroactive polymers, which will find potential applications in sensors and actuators for wearable electronics and soft robotics.

36 MATERIALS SCIENCE↗

Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account for a large source of uncertainty in the global CH 4 budget. Data-driven upscaling of CH 4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH 4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH 4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH 4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ~0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH 4 emissions of 146 ± 43 TgCH 4 y –1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH 4 y –1 ) and overlaps with top-down atmospheric inversion models (155–200 TgCH 4 y –1 ). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH 4 fluxes has the potential to produce realistic extra-tropical wetland CH 4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions.

54 ENVIRONMENTAL SCIENCES↗