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At least 937 records · Page 52

High–Performance NiCo 2 O 4 /Graphene Quantum Dots for Asymmetric and Symmetric Supercapacitors with Enhanced Energy Efficiency

For the sustainable growth of future generations, energy storage technologies like supercapacitors and batteries are becoming more and more common. However, reliable and high-performance materials’ design and development is the key for the widespread adoption of batteries and supercapacitors. Quantum dots with fascinating and unusual properties are expected to revolutionize future technologies. However, while the recent discovery of quantum dots honored with a Nobel prize in Chemistry, their benefits for the tenacious problem of energy are not realized yet. In this context, herein, chemical-composition tuning enabled exceptional performance of NiCo 2 O 4 (NCO)/graphene quantum dots (GQDs) is reported, which outperform the existing similar materials, in supercapacitors. A comprehensive study is performed on the synthesis, characterization, and electrochemical performance evaluation of highly functional NCO/GQDs in supercapacitors delivering enhanced energy efficiency. The high-performance, functional NCO/GQDs electrode materials are synthesized by the incorporation of GQDs into NCO. The effect of variable amount of GQDs on the energy performance characteristics of NCO/GQDs in supercapacitors is studied systematically. In-depth structural and chemical bonding analyses using X-ray diffraction (XRD) and Raman spectroscopic studies indicate that all the NCO/GQDs composites crystallize in the spinel cubic phase of NiCo 2 O 4 while graphene integration evident in all the NCO/GQDs. The scanning electron microscopy imaging analysis reveals homogeneously distributed spherical particles with a size distribution of 5–9 nm validating the formation of QDs. The high-resolution transmission electron microscopy analyses reveal that the NCOQDs are anchored on graphene sheets, which provide a high surface area of 42.27 m 2 g –1 and high mesoporosity for the composition of NCO/GQDs-10%. In addition to establishing reliable electrical connection to graphene sheets, the NCOQDs provide reliable 3D-conductive channels for rapid transport throughout the electrode as well as synergistic effects. Chemical-composition tuning, and optimization yields NCO/GQDs-10% to deliver the best specific capacitance of 3940 Fg –1 at 0.5 Ag –1 , where the electrodes retain ≈98% capacitance after 5000 cycles. The NCO/GQD-10%//AC asymmetric supercapacitor device demonstrates outstanding energy density and power density values of 118.04 Wh kg –1 and 798.76 W kg –1 , respectively. The NCO/GQDs-10%//NCO/GQDs-10% symmetric supercapacitor device delivers excellent energy and power density of 24.30 Wh kg –1 and 500 W kg –1 , respectively. These results demonstrate and conclude that NCO/GQDs are exceptional and prospective candidates for developing next-generation high-performance and sustainable energy storage devices.

25 ENERGY STORAGE↗

Minimum feature size control in level set topology optimization via density fields

A level set topology optimization approach that uses an auxiliary density field to nucleate holes during the optimization process and achieves minimum feature size control in optimized designs is explored. The level set field determines the solid-void interface and the density field describes the distribution of a fictitious porous material using the solid isotropic material with penalization. These fields are governed by two sets of independent optimization variables which are initially coupled using a penalty for hole nucleation. The strength of the density field penalization and projection is gradually increased during the optimization process to promote a 0-1 density distribution. In addition, a second penalty regulates the evolution of the density field in the void phase. The treatment of the density field combined with the second penalty mitigate the appearance of small design features. The minimum feature size of optimized designs is controlled by the radius of the linear filter applied to the density optimization variables. The structural response is predicted by the extended finite element method, the sensitivities by the adjoint method, and the optimization variables are updated by a gradient-based optimization algorithm. Numerical examples investigate the robustness of this approach with respect to algorithmic parameters and mesh refinement. The results show the applicability of the combined density level set topology optimization approach for both optimal hole nucleation and for minimum feature size control in 2D and 3D. This comes, however, at the cost of a more complex problem formulation and additional computational cost due to an increased number of optimization variables.

42 ENGINEERING↗

Suppressed-moment 2-k order in the canonical frustrated antiferromagnet Gd 2 Ti 2 O 7

In partially ordered magnets, order and disorder coexist in the same magnetic phase, distinct from both spin liquids and spin solids. Here, we determine the nature of partial magnetic ordering in the canonical frustrated antiferromagnet Gd 2 Ti 2 O 7 , in which Gd 3+ spins occupy a pyrochlore lattice. Using single-crystal neutron-diffraction measurements in applied magnetic field, magnetic symmetry analysis, inelastic neutron-scattering measurements, and spin-wave modeling, we show that its low-temperature magnetic structure involves two propagation vectors (2-k structure) with suppressed ordered magnetic moments and enhanced spin-wave fluctuations. Our experimental results are consistent with theoretical predictions of thermal fluctuation-driven order in Gd 2 Ti 2 O 7 , and reveal that inelastic neutron-scattering measurements on powder samples can solve the longstanding problem of distinguishing single-k and multi-k magnetic structures.

36 MATERIALS SCIENCE↗

Elementary Composite Binary and Grain Alignment Locked in Dust Growth

Abstract Planets are known to grow out of a star-encircling disk of the gas and dust inherited from an interstellar cloud; their formation is thought to begin with coagulation of submicron dust grains into aggregates, the first foundational stage of planet formation. However, with nanoscale and submicron solids unobservable directly in the interstellar medium (ISM) and protoplanetary disks, how dust grains grow is unclear, as are the morphology and structure of interstellar grains and the whereabouts and form of “missing iron.” Here we show an elementary composite binary in 3D sub-10 nm detail—and the alignments of its two subunits and nanoinclusions and a population of elongated composite grains locked in a primitive cosmic dust particle—noninvasively uncovered with phase-contrast X-ray nanotomography. The binary comprises a pair of oblate, quasi-spheroidal grains whose alignment and shape meet the astrophysical constraints on polarizing interstellar grains. Each member of the pair contains a high-density core of octahedral nanocrystals whose twin relationship is consistent with the magnetite’s diagnostic property at low temperatures, with a mantle exhibiting nanoscale heterogeneities, rounded edges, and pitted surfaces. This elongated binary evidently formed from an axially aligned collision of the two similar composite grains whose core–mantle structure and density gradients are consistent with interstellar processes and astronomical evidence for differential depletion. Our findings suggest that the ISM is threaded with dust grains containing preferentially oriented iron-rich magnetic nanocrystals that hold answers to astronomical problems from dust evolution, grain alignment, and the structure of magnetic fields to planetesimal growth.

Hu, Z. W. (ORCID:0000000278648830)↗

Whose Gas is it anyway? Differentiating the Source of a Large Soil Vapor Plume beneath Two Adjacent Waste Sites - 20487

DOE contractor CH2M Hill Plateau Remediation Company is currently responsible for conducting groundwater contamination monitoring at several RCRA treatment, storage, and disposal units located on the Hanford Site in Richland, Washington State. The Nonradioactive Dangerous Waste Landfill treatment, storage, and disposal unit presents a distinct groundwater monitoring problem because of a large multi-contaminant soil vapor plume beneath it that is a likely source of low-level volatile organic compound groundwater contamination. Adjacent to Nonradioactive Dangerous Waste Landfill is the Solid Waste Landfill. Volatile organic compounds are inventory components of both the Nonradioactive Dangerous Waste Landfill and the Solid Waste Landfill. Therefore, it is possible that both sites could be contributing to the soil vapor plume. For regulatory purposes, it is important to differentiate which site is the primary contributor of volatile organic compounds to the plume. An approach was developed to identify the primary volatile organic compound source of the soil vapor plume beneath Nonradioactive Dangerous Waste Landfill and Solid Waste Landfill. The site conceptual model hypothesis of vapor-phase volatile organic compound transport to the dissolved phase in groundwater was tested by a simple mathematical model of vapor/liquid equilibrium concentrations at the groundwater/air interface. Once it was shown that vapor-phase volatile organic compound transport to groundwater was a valid conceptual model for Nonradioactive Dangerous Waste Landfill and Solid Waste Landfill, spatial and statistical methods were used to determine the primary site contributing to the majority of volatile organic compounds to the soil vapor plume. Average groundwater chloroform, tetrachloroethene, and trichloroethene concentrations from Nonradioactive Dangerous Waste Landfill and Solid Waste Landfill monitoring network wells were plotted on maps of the facilities and immediate vicinities and compared to soil vapor sampling probe locations. Principal component analysis and mixing ratios were used to identify source contributions of each treatment, storage, and disposal unit to the plume. Results of the vapor/liquid equilibrium concentrations mathematical model showed that transport phenomena outweigh steady-state equilibria. Estimated vapor/liquid equilibrium concentrations were considerably lower than soil vapor measurements. The results indicate that dynamic vadose zone and groundwater factors such as decreased vapor concentrations with depth, vapor dilution from dispersion in the vadose zone, and advective and diffusional volatile organic compound dilution in groundwater result in groundwater volatile organic compound concentrations much less than would be measured under steady-state equilibrium conditions. Site source contribution differentiation by principal component analysis and mixing ratios was inconclusive using actual soil gas data because of the similarity in concentration values in both datasets for Nonradioactive Dangerous Waste Landfill and Solid Waste Landfill. Similar data populations suggest mixing of the vapor contributions from both sites by dispersion through the soil matrix pore spaces. However, when groundwater volatile organic compound data were compared between the Nonradioactive Dangerous Waste Landfill and Solid Waste Landfill monitoring networks, Solid Waste Landfill mean concentrations were higher, suggesting more vapor-phase volatile organic compound transport to groundwater at those locations. Simulated volatile organic compound soil vapor and groundwater datasets created to test the methods developed for this study show that the method can be successful in source differentiation when significantly different datasets are compared. This paper will describe a method of testing a conceptual model for vapor-phase contaminant transport to groundwater and for differentiating site sources of contaminants comprising a mixed-constituent soil vapor plume. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Enhanced MPM framework with multipatch isogeometric analysis for geotechnical applications

Achieving stable stress solutions at large strains using the Material Point Method (MPM) is challenging due to the accumulation of errors associated with geometry discretization, cell-crossing noise, and volumetric locking. Several simplified attempts exist in the literature to mitigate these errors, including higher-order frameworks. However, the stability of the MPM solution in such frameworks has been limited to simple geometries and the single-phase formulation (i.e., neglecting pore fluid). Although never explored, multipatch isogeometric analysis offers desirable qualities to simulate complex geometries while mitigating errors in the MPM. The degree of required high-order spatial integration has also never been investigated to infer a minimum limit for the stability of the stress solution in MPM. This paper presents a general-purpose numerical framework for simulating stable stresses in porous media, capturing both near incompressibility and multiphase interactions. First, the numerical framework is presented considering Non-Uniform Rational B-splines (NURBS) to perform isogeometric analysis (IGA) in MPM. Additionally, a volumetric strain smoothing algorithm is used to alleviate errors associated with volumetric locking. Second, the manifestation of cell-crossing errors is assessed via a series of problems with orders ranging from linear to cubic interpolation functions. Third, the use of NURBS is investigated and verified for problems with circular geometries. Finally, multipatch analysis is deployed to simulate plane strain and 3D penetration in soils, considering nearly incompressible elastoplastic (total stress) analysis and fully-coupled hydro-mechanical (effective stress) analysis. The stability of the solution is also analyzed for different constitutive models. From the results, it can be concluded that the framework using cubic interpolation functions with strain smoothing is the most convenient, presenting stable stress solutions for a broad range of multiphase geotechnical applications.

58 GEOSCIENCES↗

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrolytes Polymerization‐Induced Cathode‐Electrolyte‐Interphase for High Voltage Lithium‐Ion Batteries

Abstract Lithium‐ion batteries (LIBs) based on LiNi x Co y Mn 1‐x‐y O 2 (NCM) cathode materials have been widely commercialized, because of their high energy density, favorable rate performance, and relatively low cost. However, with increased Ni content to further increase their energy density, their cycling stability deteriorates dramatically and thus fails to meet the commercial application requirements. The artificial cathode‐electrolyte‐interphase (CEI) is a promising approach to solve this problem. Here, a robust CEI is fabricated through in situ polymerization of ethylene carbonate induced by aluminum isopropoxide (AIP). By adding 1 wt.% AIP in a commercial electrolyte, the capacity retention of LiNi 0.8 Co 0.1 Mn 0.1 O 2 ||Li cell at 1 C rate has been significantly increased from 80.8% to 97.8% with a highly reversible capacity of 176 mA h g −1 after 200 cycles. AIP can be also used as an additive during the slurry‐making process, enabling a reversible capacity of 170 mA h g −1 for LiCoO 2 after 200 cycles even at a high charge cut‐off voltage of 4.6 V. It is confirmed that the in situ formed CEI layer can prevent the cathodes from cracking and reduce the irreversible phase transformation.

Yang, Jixiang↗

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗

Silicate minerals as a direct source of limiting nutrients: Siderophore synthesis and uptake promote ferric iron bioavailability from olivine and microbial growth

Iron is a micronutrient critical to fundamental biological processes including respiration and photosynthesis, and it can therefore impact primary and heterotrophic productivity. Yet in oxic environments, iron is highly insoluble, rendering it, in principle, unavailable as a nutrient for biological growth. Life has “solved” this problem via the invention of iron chelates, known as siderophores, that keep iron available for microbial productivity. In this work, we examined the impact of siderophore synthesis on the speciation, mobility, and bioavailability of iron from rock-forming silicate minerals—shedding new light on the mechanisms by which microbes use mineral substrates to support primary productivity, as well as the consequent effects on silicate dissolution. Growth experiments were performed with Shewanella oneidensis MR-1 in an oxic, iron-depleted minimal medium, amended with olivine minerals as the sole source of iron. Experiments included the wild-type strain MR-1, and a siderophore synthesis gene deletion mutant strain (ΔMR-1). Relative to MR-1, ΔMR-1 exhibited a very pronounced growth penalty and an extended lag phase. However, substantial growth of ΔMR-1, comparable to MR-1 growth, was observed when the mutant strain was provided with siderophores in the form of either filtrate from a well-grown MR-1 culture, or commercially available deferoxamine. These observations suggest that siderophores are critical for S. oneidensis to acquire iron from olivine. Growth-limiting concentrations of deferoxamine amendments were observed to be ≤5–10 µM, concentrations significantly lower than previously recorded as necessary to impact mineral dissolution rates. X-ray photoelectric spectroscopy analyses of the incubated olivine surfaces suggest that siderophores deplete mineral surface layers of ferric iron. Combined, these results demonstrate that low micromolar concentrations of siderophores can effectively mobilize iron bound within silicate minerals, supporting very significant biological growth in limiting environments. The specific mechanism would involve siderophores removing a protective layer of nanometer-thick iron oxides, enhancing silicate dissolution and nutrient bioavailability.

59 BASIC BIOLOGICAL SCIENCES↗

2021 NIRT Mini Drill (After Action Report)

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Magic-Angle Twisted Bilayer Graphene as a Topological Heavy Fermion Problem

Magic-angle (θ=1.05°) twisted bilayer graphene (MATBG) has shown two seemingly contradictory characters: the localization and quantum-dot-like behavior in STM experiments, and delocalization in transport experiments. We construct a model, which naturally captures the two aspects, from the Bistritzer-MacDonald (BM) model in a first principle spirit. A set of local flat-band orbitals (f) centered at the AA-stacking regions are responsible to the localization. A set of extended topological semimetallic conduction bands (c), which are at small energetic separation from the local orbitals, are responsible to the delocalization and transport. The topological flat bands of the BM model appear as a result of the hybridization of f and c electrons. This model then provides a new perspective for the strong correlation physics, which is now described as strongly correlated f electrons coupled to nearly free c electrons—we hence name our model as the topological heavy fermion model. Using this model, we obtain the U(4) and U(4)×U(4) symmetries of Refs. [1–5] as well as the correlated insulator phases and their energies. Simple rules for the ground states and their Chern numbers are derived. Moreover, features such as the large dispersion of the charge ±1 excitations [2,6,7], and the minima of the charge gap at the Γ M point can now, for the first time, be understood both qualitatively and quantitatively in a simple physical picture. Our mapping opens the prospect of using heavy-fermion physics machinery to the superconducting physics of MATBG.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗

A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes

To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.

02 PETROLEUM↗

Easy-Processable and Aging-Free All-Polymer Polysiloxane Composites

In this work, we report all-polymer polysiloxane composites that overcome the long-standing processing problems of silica-reinforced silicone rubbers. Polystyrene fillers are dispersed with styrene/dimethylsiloxane symmetric diblock and triblock copolymers that control the filler morphology, filler–matrix interactions, and filler–filler interactions. Surprisingly, the composites not only rival the traditional silica-reinforced polysiloxane in mechanical properties of cured materials but also have better processability and stability than the silica-filled compound before curing. Large amplitude oscillatory shear experiments demonstrate that the triblock copolymer addition strongly affects the rheological properties. We hypothesize that the bridges and entangled loops that were formed by the triblock copolymer can connect different PS domains to provide additional reinforcement. The aging effect that originates from PDMS chain adsorption on the filler particle surface is also avoided because of the thermodynamic repulsion between PS and PDMS phases.

36 MATERIALS SCIENCE↗

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗

Porting Classical Approaches for Quantum Simulations to Quantum Computers

Simulating quantum many-body systems is one of the most promising problems in which we might anticipate that quantum computers should show quantum advantage. Unfortunately, there is still a gap between this promise and actual practice. New quantum algorithms need to be developed and the current quantum algorithms have various difficulties - e.g efficient state preparation - which must be overcome and improved upon. In many cases, classical approaches need to be ported over to quantum devices. In this project we have developed a suite of new quantum algorithms which makes progress in this regard. We developed a new optimization scheme for variational quantum eigensolvers, UBOS, which mitigates problems with local minimas and barren plateaus while improving convergence to the ground state by an order of magnitude. We developed a new way to utilize qubitization to find ground states of nearly frustration-free Hamiltonians faster than all previous methods. We developed a series of state preparation techniques which helps initialize parameterized quantum circuits into reasonable starting points on which quantum algorithms are then applied. In addition to the development of novel algorithms, it is critical to have classical simulation techniques for approximately simulating quantum circuits which can be used to benchmark and understand quantum algorithms. Toward that end, we developed a novel POVM formalism to simulate quantum circuits as well as exemplify the massive parallelization of tensor network methodologies. Finally, we developed physical understanding of entanglement phase transitions such as many-body localization and random tensor networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of a Portable In Situ Phosphorous Sensor

While phosphorus is a critical nutrient for all forms of life, runoff leads to phosphorus accumulation in surface water where it can cause a variety of health, environmental, and economic problems. The Department of Energy is interested in conducting long-term field experiments to monitor the impact of phosphorus in terrestrial and aquatic environments, and to better understand a cost vs. benefit analysis of reducing phosphorus pollution. Performing such long-term experiments requires affordable sensors capable of monitoring low-level phosphorus concentrations under challenging environmental conditions. However, such sensors are currently not available. The goal of this proposed project is to develop and demonstrate a low-cost portable phosphorus sensor suitable for in situ measurements. We will determine the technical requirements for a Raman-based sensor system, design and build a signal amplifier, integrate it with a Raman-based sensor, and demonstrate a proof-of-concept level sensor system. The expected accomplishments for Phase I include the identification of the technical requirements of a combined Raman laser/spectrometer and cavity enhancement system, building a proof-of-concept level sensor system capable of detecting orthophosphate compounds at the desired level of 0.25 mg P/L and organic P compounds, and verification of the sensor performance under laboratory and field conditions. In addition, we will identify initial hardening requirements that will need to be implemented during Phase II. While we plan to develop an integrated sensor system for monitoring phosphorus, the cavity-based enhancement system can also be used in combination with other (non-phosphorus) Raman sensors that we plan to develop or that are already commercially available. A recent market report highlights the increasing demand for such environmental monitoring applications, with the market for chemical detection anticipated to grow at a compound annual growth rate of 6.5% (2020-2025). Wide-spread monitoring of phosphorus could reduce the damage from eutrophication in freshwater, which is estimated to be $2.2 billion annually, thereby increasing biodiversity, reducing costs required for drinking water treatment, and decreasing economic losses related to recreation and angling and lake property values.

54 ENVIRONMENTAL SCIENCES↗