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At least 415 records · Page 23

Collective aspects of singlet fission in molecular crystals

We present a model to describe collective features of singlet fission in molecular crystals and analyze it using many-body theory. The model we develop allows excitonic states to delocalize over several chromophores which is consistent with the character of the excited states in many molecular crystals, such as the acenes, where singlet fission occurs. As singlet states become more delocalized and triplet states more localized, the rate of singlet fission increases. We also determine the conditions under which the two triplets resulting from fission are correlated. Using the Bethe Ansatz and an entanglement measure for indistinguishable bipartite systems, we calculate the triplet-triplet entanglement as a function of the biexciton interaction strength. The biexciton interaction can produce bound biexciton states and provides a source of entanglement between the two triplets even when the triplets are spatially well separated. Significant entanglement between the triplet pair occurs well below the threshold for bound pair formation. Our results paint a dynamical picture that helps to explain why fission has been observed to be more efficient in molecular crystals than in their covalent dimer analogues and have consequences for photovoltaic efficiency models that assume that the two triplets can be extracted independently.

74 ATOMIC AND MOLECULAR PHYSICS↗

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗

Simplified Models for LHC New Physics Searches

This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the 'Topologies for Early LHC Searches' workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first {approx} 50-500 pb{sup -1} of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

43 PARTICLE ACCELERATORS↗

Model Evaluation and Intercomparison Using Data Collected by the Langley Mobile Ozone Lidar in Hampton, Virginia

Throughout the year 2022, the Langley Mobile Ozone Lidar (LMOL) has been frequently collecting ozone and aerosol measurements in the lower troposphere. The lidar is located in the parking lot behind the Atmospheric Sciences building at NASA Langley in Hampton, Virginia, approximately 37.095 N, -76.389 W. The data was collected during a range of several distinct atmospheric conditions, including stratospheric intrusions, surface frontal passages, and long-range transported wildfire smoke plumes. We use this data to evaluate and intercompare the forecast accuracy of two atmospheric chemistry models: the GEOS Composition Forecasting model (GEOS-CF) and the Weather Research and Forecasting model with Chemistry (WRF-Chem). Both models make daily three-dimensional forecasts of many trace gases and species for the contiguous United States. Over a range of ten distinct collection events, each spanning 36 hours to nearly seven days, the forecast models predict tropospheric ozone at NASA Langley with reasonable accuracy. The models best predict the timing and shape of the observed stratospheric intrusions in the middle troposphere but often vary in the magnitude of the ozone mixing ratios. For other atmospheric conditions, there is more variability in the model accuracy. Here, we summarize the accuracy of the models for all events and investigate reasons for differences between the models and the lidar.

Daniel B. Phoenix↗

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗

Using Open Standards and NASA Open Source Simulation Tools to Model Artemis Base Camp Mission Timelines

The United States’ National Aeronautics and Space Administration (NASA) has announced that the Artemis Program will return humans to the Moon, establishing a persistent presence with the Artemis Base Camp (ABC), and extend human exploration to Mars. The NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center is using internationally developed simulation interoperability standards and NASA open source simulation tools to support Artemis concept, analysis, designs, development, training, and ultimately operations. The NExSyS team has been tasked to support early ABC architecture and mission analysis using mission time lines developed by the crew operations mission planning team. The NExSyS team is developing a distributed simulation framework with initial Artemis element implementations to model the ABC mission timelines using the international simulation interoperability standard High Level Architecture (HLA), the Simulation Interoperability Standards Organization’s Space Reference Federation Object Model (SpaceFOM), the NASA open source Trick Simulation Environment, and another NASA open source interface package called TrickHLA. The ABC architecture is composed of a number of key surface elements and resources. Some examples of modeled elements (also known as entities) are landers, habitats, rovers, logistics carriers, and astronauts. Some examples of modeled transferable and consumable resources are power, water, oxygen, nitrogen, scientific samples, and food. These entities and resources are modeled in a collection of individual simulations called Federates. A coordinated collection of interoperable federates is called a Federation and when these federates are tied together in a coordinated simulation run, it is referred to as a Federation Execution. The federates communicate through HLA using data exchange formats defined by a collection of machine readable files called Federation Object Models (FOMs). These FOM files are based on extensions to the SpaceFOM. This enables the instantiation and sharing of objects and interactions between federates in the federation. These provide for entity and resource tracking, object transfer, and data collection. Federate interactions are used to trigger events and notify federates of entity or resource transfers. For the initial implementation, the constituent federates are Trick-based simulations that use TrickHLA to provide the required HLA-base interoperability. These Trick-based simulations provide the required modeling for the individual Artemis elements along with the associated element resources. These federates provide a means to explore traverses between surface elements and exploration sites as scheduled in a mission timeline and explore the affects traverse times have on the overall mission timeline. The mission time lines are modeled using a Trick input file event handling capabilities. Each timeline operation is handled as individual simulation events, and triggered based on previous event status, time of operation, and simulated task completions. In addition, the ABC Federation can be used to perform Monte Carlo analysis. The Monte Carlo tool can vary the inputs, timings, and malfunctions to show how various contingencies in the mission can affect the mission timeline.

Keaton Craig Dodd↗

Idea2Data: Toward a New Paradigm for Drug Discovery

Increasing the success rate and throughput of drug discovery will require efficiency improvements throughout the process that is currently used in the pharmaceutical community, including the crucial step of identifying hit compounds to act as drivers for subsequent optimization. Hit identification can be carried out through large compound collection screening and frequently involves the generation and testing of many hypotheses based on available knowledge. In practice, hypothesis generation can involve the selection of promising chemical structures from compound collections using predictive models built from previous screening/ assay results. Available physical collections, typically used during hit identification, are of the order of 10 6 compounds but represent only a small fraction of the small molecule drug-like chemical space. In an effort to survey a larger portion of chemical space and eliminate inefficiencies during hit identification, we introduce a new process, termed Idea2Data (I2D) that tightly integrates computational and experimental components of the drug discovery process. I2D provides the ability to connect a vast virtual collection of compounds readily synthesizable on automated synthesis systems with computational predictive models for the identification of promising structures. This new paradigm enables researchers to process billions of virtual molecules and select structures that can be prepared on automated systems and made available for biological testing, allowing for timely hypothesis testing and follow-up. Since its introduction, I2D has positively impacted several portfolio efforts through identification of new chemical scaffolds and functionalization of existing scaffolds. In this Innovations paper, we describe the I2D process and present an application for the discovery of new ULK inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Current-Produced Magnetic Field Effects on Current Collection

Current collection by an infinitely long, conducting cylinder in a magnetized plasma, taking into account the magnetic field of the collected current, is discussed. A region of closed magnetic surfaces disconnects the cylinder from infinity. Due to this, the collected current depends on the ratio between this region and the plasma sheath region and, under some conditions, current reduction arises. It is found that the upper-bound limit of current collection is reduced due to this change of magnetic field topology. The effect can be essential even if the orbit-limited model of current collection is valid. This model is used to find the reduction of the total current collected by a cylinder (e.g., a bare tether). Such effect strongly depends on plasma density. The results are applied to a tether system in the ionosphere. For this case, it is found that current reduction can be significant for long tethers in typical dayside ionospheric conditions.

Khazanov, G. V.↗

Current-Produced Magnetic Field Effects on Current Collection

Current collection by an infinitely long, conducting cylinder in a magnetized plasma, taking into account the magnetic field of the collected current, is discussed. A region of closed magnetic surfaces disconnects the cylinder from infinity. Owing to this, the collected current depends on the ratio between this region and the plasma sheath region and, under some conditions, current reduction arises. It is found that the upper bound limit of current collection is reduced due to this change of magnetic field topology. The effect can be substantial even if the orbit-limited model of current collection is valid. This model is used to find the reduction of the total current collected by a cylinder (e.g., a bare tether). It is shown that this effect strongly depends on plasma density. The results are applied to a tether system in the ionosphere, and it is found that current reduction can be significant for long tethers in typical dayside ionospheric conditions.

Khazanov, G. V.↗

Deformation of the $0^+_{1,2}$ states in 110 Cd from low-energy Coulomb excitation

Electromagnetic properties of 110 Cd were studied via low-energy Coulomb excitation with 32 S and 14 N beams. Magnitudes and relative signs of eight E2 matrix elements, including quadrupole moments of the $2^+_1$ and $2^+_2$ states, were determined using the least-squares code GOSIA. From those, quadrupole deformation parameters of the $0^+_{1,2,3}$ states were inferred, providing for the first time conclusive evidence for the non-axial character of the ground state in 110 Cd. The experimental results were compared with new calculations using the general quadrupole collective Bohr Hamiltonian model with SLy4 and UNEDF0 interactions. The non-axiality of the ground state is reproduced by the present calculations, independently of the interaction used.

Collective models↗

Photogrammetry using Apollo 16 orbital photography, part B

Discussion is made of the Apollo 15 and 16 metric and panoramic cameras which provided photographs for accurate topographic portrayal of the lunar surface using photogrammetric methods. Nine stereoscopic models of Apollo 16 metric photographs and three models of panoramic photographs were evaluated photogrammetrically in support of the Apollo 16 geologic investigations. Four of the models were used to collect profile data for crater morphology studies; three models were used to collect evaluation data for the frequency distributions of lunar slopes; one model was used to prepare a map of the Apollo 16 traverse area; and one model was used to determine elevations of the Cayley Formation. The remaining three models were used to test photogrammetric techniques using oblique metric and panoramic camera photographs. Two preliminary contour maps were compiled and a high-oblique metric photograph was rectified.

Wu, S. S. C.↗

Component based development of computer-aided tools for different applications

Computer-aided methods and tools are used at different stages of chemical process development. However new tools are needed to meet the current and future challenges through innovative and more sustainable solutions that the currently available tools may not be able to provide. This work focuses on component-based software architecture for development of tailor-made computer-aided tools for specific application objectives. The architecture is based on “components”, which can be model-objects that are stored in a library; collection of property models; databases; numerical solvers; design-algorithms (work-flows) etc. Furthermore, the main idea of these components is to incorporate a plug & play framework, where for a specific purpose, after the work-flow and associated data-flow are established, a specific computer-aided tool can be configured through a library of software components. Also, through the use of software components that are based on predictive model-based solution techniques, the final software can be reliably used to provide innovative and more sustainable solutions over a wide range of problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient structure-factor modeling for crystals with multiple components

Diffraction intensities from a crystallographic experiment include contributions from the entire unit cell of the crystal: the macromolecule, the solvent around it and eventually other compounds. These contributions cannot typically be well described by an atomic model alone, i.e . using point scatterers. Indeed, entities such as disordered (bulk) solvent, semi-ordered solvent ( e.g. lipid belts in membrane proteins, ligands, ion channels) and disordered polymer loops require other types of modeling than a collection of individual atoms. This results in the model structure factors containing multiple contributions. Most macromolecular applications assume two-component structure factors: one component arising from the atomic model and the second one describing the bulk solvent. A more accurate and detailed modeling of the disordered regions of the crystal will naturally require more than two components in the structure factors, which presents algorithmic and computational challenges. Here an efficient solution of this problem is proposed. All algorithms described in this work have been implemented in the computational crystallography toolbox ( CCTBX ) and are also available within Phenix software. These algorithms are rather general and do not use any assumptions about molecule type or size nor about those of its components.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of cubic Li$_{2}$$^{100}$MoO$_4$ crystals for the CUPID experiment

The CUPID Collaboration is designing a tonne-scale, background-free detector to search for double beta decay with sufficient sensitivity to fully explore the parameter space corresponding to the inverted neutrino mass hierarchy scenario. One of the CUPID demonstrators, CUPID-Mo, has proved the potential of enriched Li$_{2}$$^{100}$MoO$_4$ crystals as suitable detectors for neutrinoless double beta decay search. In this work, we characterised cubic crystals that, compared to the cylindrical crystals used by CUPID-Mo, are more appealing for the construction of tightly packed arrays. We measured an average energy resolution of (6.7$\pm$0.6) keV FWHM in the region of interest, approaching the CUPID target of 5 keV FWHM. We assessed the identification of $\alpha$ particles with and without a reflecting foil that enhances the scintillation light collection efficiency, proving that the baseline design of CUPID already ensures a complete suppression of this $\alpha$-induced background contribution. We also used the collected data to validate a Monte Carlo simulation modelling the light collection efficiency, which will enable further optimisations of the detector.

100Mo↗

Artificial Intelligence for Data Center Operations (AI Ops)

HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.

97 MATHEMATICS AND COMPUTING↗

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

New Constraints on Titan's Stratospheric n-Butane Abundance

Curiously, n-butane has yet to be detected at Titan, though it is predicted to be present in a wide range of abundances that span over 2.5 orders of magnitude. We have searched infrared spectroscopic observations of Titan for signals from n-butane (n-C4H10) in Titan's stratosphere. Three sets of Cassini Composite Infrared Spectrometer Focal Plane 4 (1050–1500 cm−1) observations were selected for modeling, having been collected from different flybys and pointing latitudes. We modeled the observations with the Nonlinear Optimal Estimator for MultivariatE Spectral AnalySIS radiative transfer tool. Temperature profiles were retrieved for each of the data sets by modeling the ν4 emission from methane near 1305 cm−1. Then, incorporating the temperature profiles, we retrieved abundances of all of Titan's known trace gases that are active in this spectral region, reliably reproducing the observations. We then systematically tested a set of models with varying abundances of n-butane, investigating how the addition of this gas affected the fits. We did this for several different photochemically predicted abundance profiles from the literature, as well as for a constant-with-altitude profile. Ultimately, though we did not produce any firm detection of n-butane, we derived new upper limits on its abundance specific to the use of each profile and to multiple different ranges of stratospheric altitudes. These results will tightly constrain the C4 chemistry of future photochemical modeling of Titan's atmosphere and also motivate the continued search for n-butane and its isomer, isobutane.

Brendan L. Steffens↗