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At least 271 records · Page 15

Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation

Carbon capture, utilization, and storage (CCUS) technology has significant potential to reduce greenhouse gas (GHG) emissions and mitigate the impact of climate change, particularly in hard to decarbonize industrial and commercial sectors. CCUS involves capturing carbon dioxide (CO 2 ) from industrial processes or power generation and utilizing it for other purposes, such as enhanced oil recovery (EOR), or storing the captured CO 2 underground. CCUS technology can reduce the environmental impact of continued fossil fuel use while smoothing the transition to a low-carbon economy. CCUS can create new economic opportunities, such as the development of new industries and job creation, and can enhance energy security by diversifying energy sources. For these reasons, enabling CCUS has become a key objective of the Biden-Harris administration’s clean energy policy and has received bipartisan support. Despite its environmental and economic potential, CCUS faces multiple barriers to widespread deployment. One of the main challenges is the high cost and technical difficulty of implementing and operating large-scale CCUS infrastructure. CCUS remains a relatively expensive way to reduce carbon emissions (e.g., compared to solar photovoltaic technology’s displacement of coal generation). Additionally, financial incentives and supportive policies like those enacted to support solar photovoltaic development, especially at the state level, are inconsistent or nonexistent, which can discourage investment in CCUS projects. There are also technical challenges associated with safe and secure underground CO 2 storage and the development of new carbon utilization technologies. Public opposition to various aspects of CCUS technologies, ranging from concerns that CCUS will extend reliance on fossil fuels to CCUS infrastructure being sited in disadvantaged communities, is a growing challenge. This paper focuses on another significant barrier to broad CCUS deployment: the need for considerable expansion of the dedicated land-based CO 2 pipeline network in the United States to meet CCUS goals and the unique regulatory challenges to its development. To reach carbon emissions targets in the United States by 2050, CCUS technology will need to be supported by tens of thousands of miles of CO 2 pipelines. Estimates range from a minimum of roughly 29,000 pipeline miles (according to a 2020 Great Plains Institute study) to 66,000 pipeline miles (as per a 2021 Princeton University–led study). As of October 2022, however, the U.S. Department of Transportation (U.S. DOT) reports fewer than 5,400 miles of U.S. pipelines carrying CO 2 . This deficit—and what it means for the prospect of moving substantially larger quantities of CO 2 from source to use or storage—threatens to stifle the development of CCUS projects and technologies identified as an important tool to meet emissions targets. The current regulatory landscape facing CO 2 pipeline development can best be described as uncertain. At the federal level, the U.S. DOT Pipeline and Hazardous Materials Safety Administration (PHMSA) oversees safety regulation of pipelines transporting hazardous materials, including CO 2 upon commencement of operation. However, PHMSA’s definition of CO 2 as “a fluid consisting of more than 90 percent CO 2 molecules compressed to a supercritical state” has not been updated since its 1991 addition to the Federal Register. Because CO 2 can be transported in a gaseous, liquid, or supercritical state (indeed, the physical state of CO 2 can fluctuate within a single pipeline due to environmental changes), doubts persist about the extent of PHMSA’s purview—and raise questions about what, if anything, states should do to address this apparent gap. PHMSA has begun a major revision of its existing rules, but the agency does not expect a first draft before 2024. Economic oversight of CO 2 pipelines is even less clear. The Federal Energy Regulatory Commission (FERC) and Surface Transportation Board (STB)—which regulate the rates of interstate oil/natural gas and non-energy pipelines, respectively—have both declined jurisdiction over interstate CO 2 pipelines. This presumably leaves economic regulation to state and/or local governments, but few if any states have the laws or resources in place to oversee just and reasonable rates. Further, the interstate nature of CO 2 pipeline development creates questions around how different states should align their rate-making decisions. Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation Currently, regulatory responsibilities regarding CO 2 pipeline siting and permitting fall to state and local governments. The variety of laws and regulations across the country, however, creates a maze of requirements for pipeline developers to navigate. To secure necessary permits, most states require pipeline companies to be “common carriers” that provide transport service to the public at uniform rates. However, the specific definition of that term varies. Some states require clear evidence that a pipeline services the public, while others automatically deem any pipeline company transporting energy products or hazardous materials to be a “common carrier”—with little consideration for accessibility to third parties. Other states have eschewed common-carrier terminology entirely, placing private and publicly accessible pipelines on equal footing. Much like the variation in common-carrier requirements, laws governing eminent domain authority to secure rights-of-way (ROW) to commence construction on a planned pipeline route differ by state. Several states have no laws or rules governing CO 2 pipelines. In addition to creating questions about whether long-standing rules for other pipelines (e.g., natural gas or petroleum products) apply to CO 2 , this policy vacuum leaves local governments as the sole authority over sections of pipe within their boundaries. With dozens of counties along a given route, the probability of inconsistent regulation of the same pipeline is significant. Even in states with CO 2 pipeline laws in place, local regulatory attempts to address rising concerns over pipeline routing and safety have triggered lawsuits by pipeline companies seeking to delimit areas of federal, state, and local government responsibility. Meanwhile, legislators across the country have introduced bills to restrict the application of eminent domain to CO 2 pipeline projects, which could threaten a key means of securing ROW that companies cannot secure through negotiation with landowners. Taken separately, any of these regulatory issues—the narrow federal definition of CO 2 , FERC’s and STB’s decisions that CO 2 pipelines are not within their jurisdiction, and the considerable variation in state and local governments’ laws regulating CO 2 pipeline technologies—are extremely difficult to resolve. Adding the required scale of CO 2 pipeline expansion and the currently identified narrow window of time in which to reach climate target goals, the task becomes even more difficult—and raises a host of urgent questions for regulators. How should CO 2 be defined in federal regulations to ensure consistent safety standards across the country? What is the potential impact radius of a CO 2 pipeline rupture, and how should that inform local emergency response? In the absence of centralized federal oversight, what should state legislatures do to increase alignment for interstate CO 2 pipeline projects? This paper intends to serve as a primer for regulators and stakeholders who seek to better understand the regulatory challenges and opportunities facing this critical infrastructure.

42 ENGINEERING↗

Kinetics and mechanism of light-induced phase separation in a mixed-halide perovskite

Halide ion phase separation is a barrier to the application of mixed-halide perovskites, whereby the presence of large populations of photo-generated or injected carriers causes undesirable changes in the local band gap. Here, we investigate the mechanism of phase separation in CsPbI x Br 3-x perovskite single crystals driven by light. The phase separation process and its dynamics are visualized at the nanometer scale at cryogenic temperatures using in-situ scanning transmission electron microscopy and cathodoluminescence. Combined with phase field modeling that accounts for the coupling between electronic and chemical driving forces, our observations point to a spinodal decomposition mechanism in which both the amplitude of composition fluctuation and the characteristic length scale grow non-linearly with time. Our findings provide microscopic insights that can assist in further engineering mixed-halide perovskites either for stability or for intentional programming of the local halide ion composition, opening pathways to a wide range of applications.

36 MATERIALS SCIENCE↗

Enabling Microscale Processing: Combined Raman and Absorbance Spectroscopy for Microfluidic On-Line Monitoring

Microfluidics have many potential applications including characterization of chemical processes on a reduced scale, spanning the study of reaction kinetics using on-chip liquid–liquid extractions, sample pretreatment to simplify off-chip analysis, and for portable spectroscopic analyses. The use of in situ characterization of process streams from laboratory-scale and microscale experiments on the same chemical system can provide comprehensive understanding and in-depth analysis of any similarities or differences between process conditions at different scales. A well-characterized extraction of Nd(NO 3 ) 3 from an aqueous phase of varying NO 3– (aq) concentration with tributyl phosphate (TBP) in dodecane was the focus of this microscale study and was compared to an earlier laboratory-scale study utilizing counter current extraction equipment. Here, we verify that this same extraction process can be followed on the microscale using spectroscopic methods adapted for microfluidic measurement. Concentration of Nd (based on UV–vis) and nitrate (based on Raman) was chemometrically measured during the flow experiment, and resulting data were used to determine the distribution ratio for Nd. Extraction distributions measured on the microscale were compared favorably with those determined on the laboratory scale in the earlier study. Both micro-Raman and micro-UV–vis spectroscopy can be used to determine fundamental parameters with significantly reduced sample size as compared to traditional laboratory-scale approaches. This leads naturally to time, cost, and waste reductions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The anomaly of the CMB power with the latest Planck data

Abstract The lack of power anomaly is an unexpected feature observed at large angular scales in the maps of Cosmic Microwave Background (CMB) produced by the COBE, WMAP andPlancksatellites. This signature, which consists in a missing of power with respect to that predicted by the ΛCDM model, might hint at a new cosmological phase before the standard inflationary era.The main point of this paper is taking into account the latestPlanckpolarisation data to investigate how the CMB polarisation improves the understanding of this feature. With this aim, we apply to the latestPlanckdata, both PR3 (2018) and PR4 (2020) releases, a new class of estimators capable of evaluating this anomaly by considering temperature and polarisation data both separately and in a jointly way. This is the first time that the PR4 dataset has been used to study this anomaly. To critically evaluate this feature, taking into account the residuals of known systematic effects present in thePlanckdatasets, we analyse the cleaned CMB maps using different combinations of sky masks, harmonic range and binning on the CMB multipoles.Our analysis shows that the estimator based only on temperature data confirms the presence of a lack of power with a lower-tail-probability (LTP), depending on the component separation method, ≤ 0.33% and ≤ 1.76% for PR3 and PR4, respectively. To our knowledge, the LTP≤ 0.33% for the PR3 dataset is the lowest one present in the literature obtained fromPlanck2018 data, considering thePlanckconfidence mask. We find significant differences between these two datasets when polarisation is taken into account most likely due to a different level of systematics. Especially, the analysis with PR3 data, unlike that with PR4, seems to point towards a lack of power at large scales also for polarisation.Moreover, we also show that for the PR3 dataset the inclusion of the subdominant polarisation information provides estimates that are less likely accepted in a ΛCDM cosmological model than the only-temperature analysis over the entire harmonic-range considered. In particular, at ℓ max = 26, we found that no simulation has a value as low as the data for all the pipelines.

Astronomy & Astrophysics↗

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Asteroseismological analysis of the polluted ZZ Ceti star G 29 – 38 with TESS

G29 – 38 (TIC 422526868) is one of the brightest (V = 13.1) and closest (d = 17.51 pc) pulsating white dwarfs with a hydrogen-rich atmosphere (DAV/ZZ Ceti class). It was observed by the TESS spacecraft in sectors 42 and 56. The atmosphere of G 29 – 38 is polluted by heavy elements that are expected to sink out of visible layers on short time-scales. Here, the photometric TESS data set spans ~51 d in total, and from this, we identified 56 significant pulsation frequencies, that include rotational frequency multiplets. In addition, we identified 30 combination frequencies in each sector. The oscillation frequencies that we found are associated with g-mode pulsations, with periods spanning from ~ 260 to ~ 1400 s. We identified rotational frequency triplets with a mean separation δν ℓ = 1 of 4.67 μHz and a quintuplet with a mean separation δν ℓ = 2 of 6.67 μHz, from which we estimated a rotation period of about 1.35 ± 0.1 d. We determined a constant period spacing of 41.20 s for ℓ = 1 modes and 22.58 s for ℓ = 2 modes. We performed period-to-period fit analyses and found an asteroseismological model with M * /M ⊙ = 0.632 ± 0.03, K, and log g = 8.048 ± 0.005 (with a hydrogen envelope mass of M H ~ 5.6 × 10 –5 M * ), in good agreement with the values derived from spectroscopy. We obtained an asteroseismic distance of 17.54 pc, which is in excellent agreement with that provided by Gaia (17.51 pc).

79 ASTRONOMY AND ASTROPHYSICS↗

Identification and Online Updating of Dynamic Models for Demand Response of an Industrial Air Separation Unit

Demand-response operation of air separation units requires frequent changes in production rate(s), and scheduling calculations must explicitly consider process dynamics to ensure feasibility of the solutions. To this end, scale-bridging models (SBMs) approximate the scheduling-relevant dynamics of a process and its controller in a low-order representation. In contrast to previous works that have employed nonlinear SBMs, this paper proposes linear SBMs, developed using time-series analysis, to facilitate online scheduling computations. Using a year-long industrial dataset, we nd that compact linear SBMs are suitable approximations over typical scheduling horizons, but that their accuracies are unpredictable over time. We introduce a strategy for online updating of the SBMs, based on Kalman ltering schemes for online parameter estimation. The approach greatly improves the accuracy of SBM predictions and will enable the use of linear SBM-based demand-response scheduling in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards modelling AR Sco: calibration – reproducing high-energy pulsar emission and testing convergence to Aristotelian electrodynamics

In recent years, kinetic simulations have been crucial to further our understanding of pulsar electrodynamics. Yet, due to the large-scale separation between the gyro-period and the stellar rotation period, resolving the particle gyration has been computationally unfeasible for realistic pulsar parameters. The main aim of this work is comparing our gyro-phase-resolved model with a gyro-centric pulsar model, where our model solves the general equations of motion with included radiation reaction using a higher order numerical solver with adaptive time-steps. Specifically, we aim to (i) reproduce a pulsar’s high-energy emission maps, namely one with 10 per cent of the surface B-field strength of Vela, and the spectra produced by an independent gyro-centric pulsar emission model; and (ii) test convergence of these results to the radiation-reaction limit of Aristotelian electrodynamics. (iii) Additionally, we identify the effect that a large $E_{\parallel }$-field has on the trajectories and radiation calculations. We find that we can reproduce the curvature radiation emission maps and spectra well, using 10 per cent field strengths of the Vela pulsar and injecting our particles at a higher altitude in the magnetosphere. Using sufficiently large $E_{\parallel }$-fields, our numeric results converge to the analytic radiation-reaction limit trajectories. Additionally, we illustrate the importance of accounting for the $\mathbf {E}\times \mathbf {B}$-drift in the particle trajectories and radiation calculations, validating the Harding and collaborators’ model approach. Lastly, we found that our model deals very well with the high-radiation-reaction and high-field regimes present in pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗

Mission Analysis for Marine Renewable Energy to Provide Power for Marine Carbon Dioxide Removal

The mission of this project was to provide a preliminary feasibility assessment of powering different marine carbon dioxide removal (mCDR), marine carbon capture, and marine carbon sequestration strategies with marine energy. In this report, carbon capture refers to methods that can separate or capture carbon dioxide (CO 2 ) from the air or ocean; carbon sequestration refers to methods that store CO 2 obtained by capture methods out of the atmosphere for long periods of time; and carbon dioxide removal (CDR) refers to methods that do both. The project found that mCDR powered by marine energy and offshore wind energy available in the United States could meet global CDR scales needed by 2040 and 2050 to limit warming to 1.5 degrees C by 2100. Note that this preliminary estimate assumes that it is possible to harvest all the marine and offshore wind resources available in the United States with existing technology options, and it does not account for the power needed for monitoring these methods, as these power needs are not yet well defined and require further research. Additionally, these CDR scales will still require emissions reductions.

16 TIDAL AND WAVE POWER↗

The SiD Digital ECal Based on Monolithic Active Pixel Sensors

The SiD detector concept capitalizes on high granularity in its tracker and calorimeter to achieve the momentum resolution and particle flow calorimetry physics goals in a compact design. The collaboration has had a long interest in the potential for improved granularity in both the tracker and ECal with an application of monolithic active pixel sensors (MAPS) and a study of MAPS in the SiD ECal was described in the ILC TDR. Work is progressing on the MAPS application in an upgraded SiD design with a prototyping design effort for a common SiD tracker/ECal design based on stitched reticules to achieve 10 × 10 cm2 sensors with 25 × 100 micron2 pixels. Application of large area MAPS in these systems would limit delicate and expensive bump-bonding, provide possibilities for better timing, and should be significantly cheaper than the TDR concept due to being a more conventional CMOS foundry process. The small pixels significantly improve shower separation. Recent simulation studies confirm previous performance projections, indicating electromagnetic energy resolution based on digital hit cluster counting provides better performance than the SiD TDR analog design based on 13 mm2 pixels. Furthermore, the two shower separation is excellent down to the millimeter scale. Geant4 simulation results demonstrate these expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Capacitive Deionization for the Extraction and Recovery of Butyrate

Separation processes underpin chemical manufacturing, energy and fuel production, resource recovery, and water purification. Capacitive deionization (CDI) is an electrochemical separation technique based on electrosorption of charged species from an aqueous solution. This work reports the development and application of CDI for the extraction and recovery of butyrate, a carboxylate anion that is key to bioenergy production, among other applications. Electrosorption of sodium butyrate was evaluated using a bench-scale CDI system with activated carbon cloth electrodes. Applying an external potential (1.2 V) enhanced the adsorption capacity of activated carbon for butyrate by 250%. Reversible electrosorption was also demonstrated by extracting and recovering butyrate at 1.2 and 0 V, respectively. Performance metrics including butyrate adsorption and desorption capacities, adsorption and desorption rates, charge efficiency, energy consumption, and recovery are reported. Furthermore, this study also investigates the long-term operational stability of the system by cycling the cell more than 1000 times using 1.2 and 0 V for charging and discharging, respectively. Subsequent physicochemical characterization indicates increased oxygen content (from similar to 2% to >8%), decreased specific surface area (by similar to 20%), and decreased pore volume (by similar to 20%), attributed to carbon oxidation. Overall, this work informs the design of CDI for organic anion separation and recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aboveground and belowground contributions to ecosystem respiration in a temperate deciduous forest

In this study, we developed a three-way carbon dioxide (CO 2 ) flux-partitioning algorithm that separates net ecosystem exchange (NEE) into aboveground plant respiration (R above ), belowground root and soil respiration (R below ), and gross primary production (GPP). We applied this algorithm to a coupled dataset of continuous chamber-measured soil respiration and eddy covariance (EC)-measured NEE of CO 2 in an oak-hickory (Quercus-Carya) deciduous broadleaf forest from 2006 to 2015. We found that on annual time scale, R below dominated over R above with the former accounting for 66.9–86.4% and the latter 13.6–33.1%, of the total ecosystem respiration (R eco ). The ratio of R below to R above varied seasonally, ranging from 1.77 to 7.25 in growing season, and 1.02 to 4.57 in non-growing season. The temperature sensitivity (E 0 ) of R below was significantly higher than that of R above , and E 0 of R eco responded differently to air and soil temperature. Over the whole study period, annual mean R above , R below , and GPP were 243, 806, and 1170 g C m –2 , respectively, with annual R eco accounting for 89.6% of GPP, of which 68.8% was lost as R below and 20.8% lost as R above , and leaving only 10% of the carbon fixation in ecosystems. Furthermore, these estimates, however, did not consider potential light inhibition of leaf respiration. If we accept the presence of light inhibition, then the daytime three-way partitioning method would underestimate annual R above by 20.4% whereas the nighttime method would overestimate R above by 23.9% and GPP by 4.7%, compared with estimates accounting for light inhibition in leaves.

54 ENVIRONMENTAL SCIENCES↗

Three-dimensional realizations of flood flow in large-scale rivers using the neural fuzzy-based machine-learning algorithms

Machine learning methods have been extensively used to study the dynamics of complex fluid flows. One such algorithm, known as adaptive neural fuzzy inference system (ANFIS), can generate data-driven predictions for flow fields, but has not been applied to natural geophysical flows in large-scale rivers. Herein, we demonstrate the potential of ANFIS to produce three-dimensional (3D) realizations of the instantaneous flood flow field in several large-scale, virtual meandering rivers. The 3D dynamics of flood flow in large-scale rivers were obtained using large-eddy simulation (LES). The LES results, i.e., the 3D velocity components, were employed to train the learnable coefficients of an ANFIS. Further, the trained ANFIS, along with a few time-steps of LES results (precursor data) were then used to produce 3D realizations of flood flow fields in large-scale rivers with geometries other than the one the ANFIS was trained with. We also used the trained ANFIS to generate 3D realizations of river flow at a discharge other than that the ANFIS was trained with. The flow field results obtained from ANFIS were validated using separate LES runs to assess the accuracy of the 3D instantaneous realizations of the machine learning algorithm. An error analysis was conducted to quantify the discrepancies among the ANFIS and LES results for various flood flow predictions in large-scale rivers.

54 ENVIRONMENTAL SCIENCES↗

Nanoscale Confinement of Photo-Injected Electrons at Hybrid Interfaces

A prerequisite for advancing hybrid solar light harvesting systems is a comprehensive understanding of the spatiotemporal dynamics of photoinduced interfacial charge separation. Here, we demonstrate access to this transient charge redistribution for a model hybrid system of nanoporous zinc oxide (ZnO) and ruthenium bipyridyl chromophores. The site-selective probing of the molecular electron donor and semiconductor acceptor by time-resolved X-ray photoemission provides direct insight into the depth distribution of the photoinjected electrons and their interaction with the local band structure on a nanometer length scale. Our results show that these electrons remain localized within less than 6 nm from the interface, due to enhanced downward band bending by the photoinjected charge carriers. This spatial confinement suggests that light-induced charge generation and transport in nanoscale ZnO photocatalytic devices proceeds predominantly within the defect-rich surface region, which may lead to enhanced surface recombination and explain their lower performance compared to titanium dioxide (TiO 2 )-based systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale Temporal Variability of the Global Air‐Sea CO 2 Flux Anomaly

Abstract The global air‐sea CO 2 flux (F) impacts and is impacted by a plethora of climate‐related processes operating at multiple time scales. In bulk mass transfer formulations, F is driven by physico‐ and bio‐chemical factors such as the air‐sea partial pressure difference (∆pCO 2 ), gas transfer velocity, sea surface temperature, and salinity–all varying at multiple time scales. To de‐convolve the impact of these factors on variability in F at different time scales, time‐resolved estimates of F were computed using a global data set assembled between 1988 and 2015. The F anomalies were defined as temporal deviations from the 28‐year time‐averaged value. Spectral analysis revealed four dominant timescales of variability in F–subseasonal, seasonal, interannual, and decadal with relative amplitude differences varying across regions. A second‐order Taylor series expansion was then conducted along these four timescales to separate drivers across differing regions. The analysis showed that on subseasonal timescales, wind speed variability explains some 66% of the global F anomaly and is the dominant driver. On seasonal, interannual, and decadal timescales, the ∆pCO 2 effect controlled by the ∆pCO 2 anomaly, explained much of the F anomaly. On decadal timescales, the F anomaly was almost entirely governed by the ∆pCO 2 effect with large contributions from high latitudes. The main drivers across timescales also dominate the regional F anomaly, particularly in the mid‐high latitude regions. Finally, the driver of the ∆pCO 2 effect was closely connected with the relative strength of atmospheric pCO 2 and the nonthermal component of oceanic pCO 2 anomaly associated with dissolved inorganic carbon and alkalinity.

Environmental Sciences & Ecology↗

Appearance versus disappearance of broad absorption line troughs in quasars

ABSTRACT We present a new set of 84 broad absorption line (BAL) quasars (1.7 < zem < 4.4) exhibiting an appearance of C iv BAL troughs over 0.3–4.8 rest-frame years by comparing the Sloan Digital Sky Survey Data Release (SDSSDR)-7, SDSSDR-12, and SDSSDR-14 quasar catalogues. We contrast the nature of BAL variability in this appearing BAL quasar sample with a disappearing BAL quasar sample studied in the literature by comparing the quasar’s intrinsic, BAL trough, and continuum parameters between the two samples. We find that appearing BAL quasars have relatively higher redshift and smaller probed time-scales as compared to the disappearing BAL quasars. To mitigate the effect of any redshift bias, we created control samples of appearing and disappearing BAL quasars that have similar redshift distribution. We find that the appearing BAL quasars are relatively brighter and have shallower and wider BAL troughs compared to the disappearing BAL sample. The distribution of quasar continuum variability parameters between the two samples is clearly separated, with the appearance of the BAL troughs being accompanied by the dimming of the continuum and vice versa. Spectral index variations in the two samples also point to the anticorrelation between the BAL trough and continuum variations consistent with the ‘bluer when brighter’ trend in quasars. We show that the intrinsic dust model is less likely to be a favourable scenario in explaining BAL appearance/disappearance. Our analysis suggests that the extreme variations of BAL troughs like BAL appearance/disappearance are mainly driven by changes in the ionization conditions of the absorbing gas.

Mishra, Sapna↗

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗