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Analytic rate theory of polariton relaxation that explains long polariton lifetime

Hybridization of a molecular exciton with a quantized photon creates a polariton. Despite extensive experimental investigations, the apparent lifetime of the exciton–polariton is not well-understood. For this work, we examined the steady-state population dynamics for a Holstein–Tavis–Cumming Hamiltonian to illuminate the long-term polaritonic dynamics and lifetime of the exciton–polariton in an optical cavity. For a realistic description of polariton relaxation, cavity loss and various exciton decay channels are included in the model. We found that in the presence of weak but finite exciton loss, the apparent lifetime of the lower polariton coincides with the out-of-cavity exciton lifetime and is independent of cavity-matter detuning. This is a simple explanation for the experimentally observed lifetimes for exciton polaritons and theoretically justifies the dark state reservoir hypothesis. Furthermore, if the upper polariton is initially populated, the system reaches the steady state very quickly, leading to single-exponential polariton relaxation. Starting from the lower polariton leads to a longer pre-steady-state time period, leading to double-exponential relaxation. Finally, we considered the effect of site orientational disorders and the exciton frequency disorderers. Under the collective limit, the effects of this disorder can be included in Fermi’s golden rule population dynamics without explicit sampling. For the exciton energy disorders, numerical calculations are needed. Our theoretical framework is applicable to interpret exciton–polariton experiments, especially related to the measured apparent lifetime of polaritons.

Chemical dynamics↗

Requirements Description of GAMSOR and GAMSRC

This report presents the modeling and simulation capabilities of Argonne National Laboratory’s GAMSOR and GAMSRC code that is used in present reactor analysis activities. These capabilities will then be used to establish the set of verification tasks necessary to verify GAMSOR for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The GAMSOR program is a modified version of DIF3D used to obtain the coupled neutron gamma flux distributions for a given reactor system. GAMSOR was first developed in the 1980s and its work has progressed in parallel with DIF3D throughout its various development phases. While GAMSOR is compatible with DIF3D-FD and DIF3D-Nodal, DIF3D-VARIANT is most commonly used today and will be the focus of the present verification effort. As covered in [1], GAMSOR was built to provide more accurate heating distributions by explicitly solving for both the gamma and neutron heating distributions. Without this consideration, gamma heat is normally assumed to be deposited locally at the site of gamma production. This is acceptable for modeling some phenomena because the total energy production is preserved, but it can lead to inaccurate approximations of fluence-dependent behaviors such as fuel performance, swelling, cladding embrittlement, radiation induced creep, and power peaking. The outputs from GAMSOR are contained in multiple intermediate and final output files: FIXSRC, VARSRC, GTFLUX, GHFLUX, PWDINT, NPDINT, and GPDINT. DIF3D normally produces a PWDINT file containing power density results, with the assumption that gamma rays are absorbed where they are emitted (i.e., energy deposition is local with no modeled transport). With GAMSOR, neutron power density (NPDINT) and gamma power density (GPDINT) are both produced, with their summed power densities replacing the results in PWDINT for total heating (i.e., recoverable) power density.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗

Unraveling Fundamental Activity–Stability Relationships in Rutile Oxides

The oxygen evolution reaction (OER) is a key anodic half-cell reaction that accompanies several critical electrochemical reduction reactions of interest to a variety of applications. Despite steady advances in understanding and qualitatively predicting OER activity and selectivity trends, a comprehensive description or prediction of material aqueous (in)stability and degradation mechanisms remains elusive, even though these processes critically influence device lifetime and economic feasibility. In this work, we investigate the interplay, or lack thereof, between OER activity and material aqueous stability across rutile oxides, with a particular focus on iridium oxide (IrO 2 ). By applying a Born–Haber cycle, we calculate the thermodynamic driving force for metal dissolution as a function of the applied bias and electrolyte conditions. We apply interpretable machine learning techniques, including principal component analysis and symbolic regression, to analyze trends across rutile oxides and find that key thermodynamic descriptors for OER activity and surface stability are only very weakly correlated. Instead, the local atomic environment─especially electronic structure signatures for interactions between the active site and its neighbors─plays a more important role in predicting material stability. Leveraging these insights, we investigate the impact of doping IrO 2 with a range of transition metals and show that the stability of Ir active sites can be tuned largely independently of its predicted OER activity. These insights lay the foundation for material design to improve stability with respect to corrosion, with the ultimate aim to enhance long-term stability without sacrificing catalytic performance in the OER.

evolution reactions↗

Dimer description of the SU(4) antiferromagnet on the triangular lattice

In systems with many local degrees of freedom, high-symmetry points in the phase diagram can provide an important starting point for the investigation of their properties throughout the phase diagram. In systems with both spin and orbital (or valley) degrees of freedom such a starting point gives rise to SU(4)-symmetric models. Here we consider SU(4)-symmetric "spin" models, corresponding to Mott phases at half-filling, i.e. the six-dimensional representation of SU(4). This may be relevant to twisted multilayer graphene. In particular, we study the SU(4) antiferromagnetic "Heisenberg" model on the triangular lattice, both in the classical limit and in the quantum regime. Carrying out a numerical study using the density matrix renormalization group (DMRG), we argue that the ground state is non-magnetic. We then derive a dimer expansion of the SU(4) spin model. An exact diagonalization (ED) study of the effective dimer model suggests that the ground state breaks translation invariance, forming a valence bond solid (VBS) with a 12-site unit cell. Finally, we consider the effect of SU(4)-symmetry breaking interactions due to Hund's coupling, and argue for a possible phase transition between a VBS and a magnetically ordered state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Higher Dimensionality in the Mg–Co–B System: Synthesis and Structure of Incommensurate Composite Mg 1+ε Co 4 B 4

Guided by high-temperature in situ X-ray diffraction, the discovery and synthesis of Mg 1+ε Co 4 B 4 (ε ≈ 0.272) using a MgH 2 hydride precursor is reported, along with a detailed crystal structure description and measurement of magnetic properties. The mismatch in lattice periodicities between Mg and Co–B substructures places Mg 1+ε Co 4 B 4 in the family of incommensurate composite crystals and prompted structural refinement in a (3 + 1)-dimensional model. The structure of Mg 1+ε Co 4 B 4 (P4 2 /ncm(00γ)s00s, a = 6.75847(7) Å, c = 3.94007(8) Å, q = (0, 0, 1.2721(3))) was refined from neutron powder diffraction and high-resolution powder X-ray diffraction data and confirmed by scanning transmission electron microscopy and electron diffraction. Mg 1+ε Co 4 B 4 is isostructural to Nd 1+ε Fe 4 B 4 and several related ternary borides with 0.07 ≤ ε ≤ 0.17, with Mg occupying the rare-earth site. Satellite reflections in the electron diffraction patterns hinted at positional modulation of the transition metal–boron substructure by Mg atoms, but this could not be refined from the neutron or X-ray diffraction data. Low-temperature magnetic measurements show no indications of long-range magnetic ordering or superconductivity down to 5 K. DFT calculations confirmed the absence of a magnetically ordered ground state and the stability of a 5:4 supercell (ε = 0.25) relative to the fully commensurate structure. Neutron diffraction and synthesis from elemental Mg demonstrated that Mg 1+ε Co 4 B 4 is not a hydrogen-stabilized phase. Mg 1+ε Co 4 B 4 represents the second compound reported in the Mg–Co–B system and the first superspace symmetry model of a Nd 1+ε Fe 4 B 4 -type incommensurate composite compound refined from powder diffraction data.

chemical structure↗

Measurement of particulated matter (PM1, PM2.5, PM10) using a PM sensor during the SAIL campaign in Gothic, CO and Mt. Crested Butte, CO

We deployed another PM sensor (Modulair-PM, QuantAQ) to measure the mass concentration of particulate matter (PM) for three size cuts at both the main site (M1) and supplementary site (S2) of the SAIL from 14 June 2022 to 14 June 2023. The instruments provide the mass concentration of PM1, PM2.5 and PM10. Mass concentrations were calculated based on measurements made with a nephelometer and an OPC. We used Quant-AQ's algorithm [please see their documentation here and the references within] to determine the mass concentrations reported. Here, we present the time series of sample relative humidity, temperature, pressure, and the mass concentration of PM1, PM2.5 and PM10. We also present the size distribution of the aerosol particles within a diameter range of 0.35 - 40 micron, measured by the OPC of the pm-modulair. However, we encourage caution while using the size distribution data, since it is operated only with the factory calibration. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2022ssb.

54 ENVIRONMENTAL SCIENCES↗

Atomic-Level Structure of Mesoporous Hexagonal Boron Nitride Determined by High-Resolution Solid-State Multinuclear Magnetic Resonance Spectroscopy and Density Functional Theory Calculations

Mesoporous hexagonal boron nitride (p-BN) has received significant attention over the last decade as a promising candidate for water cleaning/pollutant removal and hydrogen storage applications. In this work, high-resolution solid-state NMR spectroscopy and plane-wave density-functional theory (DFT) calculations are used to obtain an atomic-level description of p-BN. 1 H– 15 N or 1 H– 14 N heteronuclear (HETCOR) correlation experiments recorded with either conventional NMR at room temperature or dynamic nuclear polarization surface-enhanced spectroscopy (DNP-SENS) at ca. 100 K reveal NB 2 H, NBH 2 , NBH 3 + species residing on the edges of BN sheets. Ultra-high field 35.2 T 11 B NMR spectroscopy was used to resolve 11 B NMR signals from BN 3 , BN 2 O x (OH) 1–x (x = 0–1), BNO x (OH) 2–x (x = 0–2), BO x (OH) 3–x (x = 0–3), and BO x (OH) 4–x – (x = 0–4). Importantly, 2D 11 B dipolar double-quantum–single-quantum homonuclear correlation spectra reveal that many pore/defect sites are composed of boron oxide/hydroxide clusters connected to the BN framework through BN 2 O units. 1D and 2D 11 B{ 15 N} HETCOR NMR experiments, in addition to plane-wave DFT calculations of nine different structural models, further confirm the assignment of all NMR signals. The detailed structure determination of the pore and edge/defect sites within p-BN should further enable the rational design and development of next-generation p-BN-based materials. In addition, the techniques outlined here should be applicable to determine structure within other porous and/or boron-based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of the Role of the Role of Nuclear Physics in Heavy Element Nucleosynthesis, through the Study of Key Reactions, and the Improvement of Theoretical Reaction Rates (Final Report)

Neutrino-driven winds in core-collapse supernovae have been identified as a possible site for the production of elements heavier than iron. Traditionally, these neutrino-driven winds have been proposed as the site of the main r-process. Recent simulations fail to reproduce the conditions required for the main r-process. while they remain a promising site for producing the lightest elements beyond iron, e.g., Sr, Y, and Zr through the νp process. The efficiency of the νp process depends on the hydrodynamical conditions, the electron fraction (which is related to the neutrino properties), and the nuclear reactions on many short-lived nuclei with limited (if at all) experimental information. The reaction rates on these nuclei are based on theoretical predictions using the Hauser-Feshbach model. Recent sensitivity studies have highlighted the importance of neutron-induced reactions on these nuclei along the νp process path. This work aimed to experimentally constrain reaction rates that are known to play a key role in the neutrino-p process nucleosynthesis. A secondary subsequently-added objective was to start the implementation of techniques that improve the description of nuclear properties in the Hauser-Feshbach model by extending the microscopic nuclear level density description offered via the shell model to high excitation energies without using experiment-based renormalizations. The main objective of this work was the experimental constraint of the 56 Ni(n,p) 56 Co reaction rate via a measurement of the inverse reaction 56 Co(p,n) 56 Ni at the National Superconducting Cyclotron Laboratory (NSCL) and later the Facility for Rare Isotope Beams (FRIB). This reaction is considered the key one for determining the yields possible by the neutrino-p process. A technique for this type of measurement in inverse kinematics at low energies did not exist before this work. The work also had two secondary objectives. First, to contribute to efforts to measure the same reaction in direct kinematics using a radioactive target at Los Alamos National Laboratory (LANL), and second, to advance work to implement shell-model-deduced microscopic level densities in Hauser-Feshbach calculations. The project has resulted in the development of the first technique to perform (p,n) cross-section measurements in relevant-for-astrophysics low energies in inverse kinematics using a magnetic spectrometer or separator, and neutron detectors for neutron tagging. It has also resulted in the precise measurement of the cross-section of the 40 Ar(p,n) 40 K reaction in a proof-of-principle experiment realized by using a beam-line quadrupole of the ReA3 accelerator of NSCL/FRIB. As part of this project the technique was successfully adapted to make use of the superior acceptance of the Separator for Capture Reactions (SECAR) at FRIB. In this project, the required experimental setup simulations and beam optics were developed and tested with the measurement of the 58 Fe(p,n) 58 Cu reaction cross-section. Additionally, this project contributed with simulation work to the development of a technique to measure (n,p) reactions with radioactive targets at LANL, and which resulted in the measurement of the key 56 Ni(n,p) 56 Co reaction cross-section at neutron energies above ≈1 MeV. Last, the project initiated work in the development of shell model based level densities using the moments method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantum Monte Carlo Methods for Astrophysical Applications

In recent years, new astrophysical observations have provided a wealth of exciting input for nuclear physics. For example, the observations of two-solar-mass neutron stars put strong constraints on possible phase transitions to exotic phases in strongly interacting matter at high densities. Furthermore, the recent observation of a neutron-star merger in both the electromagnetic spectrum and gravitational waves has provided compelling evidence that neutron-star mergers are an important site for the production of extremely neutron-rich nuclei within the r-process. In the coming years, an abundance of new observations is expected, which will continue to provide crucial constraints on the nuclear physics of these events. To reliably analyze such astrophysical observations and extract information on nuclear physics, it is very important that a consistent approach to nuclear systems is used. Such an approach consists of a precise and accurate method to solve the nuclear many-body problem in nuclei and nuclear matter, combined with modern nuclear Hamiltonians that allow to estimate the theoretical uncertainties. Quantum Monte Carlo methods are ideally suited for such an approach and have been successfully used to describe atomic nuclei and nuclear matter. In this contribution, I will present a detailed description of Quantum Monte Carlo methods focusing on the application of these methods to astrophysical problems. In particular, I will discuss how to use Quantum Monte Carlo methods to describe nuclear matter of relevance to the physics of neutron stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗

Greenhouse Rhizobox Experiment with Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry data, Seward Peninsula, Alaska, 2024

Data collected from a greenhouse rhizobox experiment (2024) using soils and plants collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by porewater samplers (rhizons). Gas data consists of CO2 and CH4 surface soil fluxes measured with an FTIR (Fourier-transformed infrared red) analyzer. Plant and root data consists of biomass, root length. This study is a part of The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2 and CH4?Description of the contents of this data package: Rhizobox2024_Data.csv: This dataset contains plant, water and gas data. No software is needed to utilize them.nga535_flmd.csv: The file contains file level metadatanga535.dd.csv: This file contains the data dictionaryMethods.pdf: This file contains the data collection methods

54 ENVIRONMENTAL SCIENCES↗

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗

Fungal mat growth and leaf colonization at the TRACE warming experiment, Mar - Aug 2024, Luquillo, Puerto Rico

This data package contains processed measurements on the growth of litter mat-forming fungi and the time to leaf colonization at the Tropical Responses to Altered Climate Experiment (TRACE). Located near the Sabana Field Research Station in Luquillo, Puerto Rico, the TRACE site is located in a mature, closed-canopy tropical rainforest within the Luquillo Experimental Forest (LEF). These data quantify fungal mat growth and the time to leaf colonization of fungi species Gymnopus johnstonii and Marasmius crinis-equi. The experiment was conducted in ambient (control) and experimentally warmed plots (4°C above ambient) during spring and summer periods to assess how litter mat-forming fungi respond to a range of environmental conditions of tropical wet forests. The data files include tables of relative fungal mat growth rates, time to leaf colonization, averages of soil temperature (°C), and number of dry days before leaf attachment. The data are stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement descriptions, and processing steps.

Agaric fungi↗

A Systematic Framework for Projecting the Future Cost of Offshore Wind Energy

Offshore wind costs are expected to decline rapidly in the short and medium term future as the industry grows and gains experience in manufacturing, installing, and operating commercial scale projects. Estimating the future costs of offshore wind energy is critical for evaluating the technology's economic performance, how it can fit into a broader clean energy economy, and how R&D investment can be allocated to advance the technology. We present a newly developed approach for forecasting these costs which focuses on an empirically-derived learning rate for capital costs and prescribed cost and performance improvements for operational costs and capacity factor. We establish baseline costs for a series of reference fixed-bottom and floating projects in 2021 and project cost trajectories to 2035, presenting both an average cost trajectory as well as describing the range of potential future costs associated with site-specific cost variations and uncertainty in the estimate of the learning rate. We also conduct sensitivity analyses showing the impact of different global deployments by 2035 and variations in the prescribed operational costs and capacity factors. The results show that fixed-bottom and floating offshore wind capital costs could decrease to around $\$$2,400/kW and $\$$3,300/kW by 2035, respectively, with ranges of $\$$2,100/kW - $\$$2,750/kW for fixed-bottom projects and $\$$2,850/kW - $\$$5,500/kW for floating projects. The levelized cost of energy of fixed-bottom and floating wind projects could decrease to $\$$53.1/MWh and $\$$63.9/MWh by 2035, with ranges of $\$$48.4/MWh - $\$$59.7/MWh for fixed-bottom projects and $\$$46.5/MWh - $\$$99.9/MWh for floating projects. By presenting the uncertainty associated with the forecast we provide a transparent description of the spectrum of potential cost trajectories for offshore wind.

17 WIND ENERGY↗

Time-evolution methods for matrix-product states

Highlights: • Introductory review of time-evolution methods for matrix-product states. • Detailed description of five state-of-the-art algorithms. • Extended comparison of numerical examples. • Extended error analysis of each algorithm. • Pseudo-code examples towards an implementation where necessary. - Abstract: Matrix-product states have become the de facto standard for the representation of one-dimensional quantum many body states. During the last few years, numerous new methods have been introduced to evaluate the time evolution of a matrix-product state. Here, we will review and summarize the recent work on this topic as applied to finite quantum systems. We will explain and compare the different methods available to construct a time-evolved matrix-product state, namely the time-evolving block decimation, the MPO W{sup I,II} method, the global Krylov method, the local Krylov method and the one- and two-site time-dependent variational principle. We will also apply these methods to four different representative examples of current problem settings in condensed matter physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integrating crop growth models with remote sensing for predicting biomass yield of sorghum

Abstract Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programmes to develop varieties aimed at performance in the target environments. Crop models can improve this testing regime by providing a predictive framework to (i) augment field phenotyping data and derive hard-to-measure phenotypes and (ii) estimate performance across geographical regions using historical weather data. The goal of this study was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits in 18 commercial grain and biomass sorghum hybrids. Genotype parameters for each hybrid were estimated using remote-sensing measurements combined with manual phenotyping in West Lafayette, IN, in 2018. The models were validated in hybrid performance trials in two additional seasons at that site and against yield trials conducted in Bushland, TX, between 2001 and 2018. These trials demonstrated that (i) maximum plant height, final dry biomass and radiation use efficiency (RUE) of photoperiod-sensitive and -insensitive forage sorghum hybrids tended to be higher than observed in grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass production in longer growing environments and (iii) the parameterized and validated models perform well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize larger plant breeding populations.

Yang, Kai-Wei↗

Building a Collaborative Relationship between Contractor and Oversight at SRPPF

The success of Department of Energy (DOE) projects is dependent on a functional, healthy, and collaborative relationship between the contractor and the federal oversight. A healthy relationship marked by a collaborative mindset between these two groups, can facilitate better operational safety, operational efficiency, and regulatory compliance. This paper will explore aspects of such a relationship, the roles and responsibilities of the contractor and federal oversight, the present and historical relationships in the DOE complex, and best practices considered by the contractor and federal oversight used at the Savannah River Plutonium Processing Facility (SRPPF) at the Savannah River Site (SRS). Due to the current design phase of the SRPPF, the contractor and federal oversight have a unique opportunity to begin establishing a strong relationship early in the project’s life. As a result of this dynamic, the two groups have already demonstrated their ability to successfully respond to ongoing design issues. In general, a strong criticality safety program is beginning to mature for the SRPPF alongside a developing criticality safety federal oversight group. This paper will discuss the various factors that have brought about this collaborative relationship. Lastly, a case study will be incorporated into this paper demonstrating the ability of the SRPPF contractor and federal oversight to overcome challenges relating to the SRPPF project. This case study may guide groups around the DOE Complex to create better, more functional relationships between the two parties. The case study will provide a detailed description of the issue and parties involved, highlight the factors that allowed the group to overcome the challenge via effective collaboration, and the outcome of the event. Increasing collaboration may benefit the complex, as a whole, in order to meet the mission demands of the DOE.

collaboration↗