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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Visible spectroscopy diagnostics for tungsten source assessment in the WEST tokamak: First measurements

The present work concerns the measurements obtained with the Tungsten (W) Environment in Steady-state Tokamak (WEST) visible spectroscopy system during the first experimental campaign. This system has been developed in the framework of the WEST project that equipped the existing Tore Supra device with a tungsten divertor in order to test actively cooled tungsten Plasma Facing Components (PFC) in view of preparing for ITER operation. The goal of this diagnostic is to measure the PFC sources and the deuterium recycling with spectral, spatial, and temporal resolution adapted to the predicted power deposition profiles on the objects observed. Three kinds of PFCs are monitored: the Ion Cyclotron Resonance Heating (ICRH) antenna and Low Hybrid Current Drive (LHCD) launcher W limiters; one of the 6 W inner bumpers; and the upper and lower W divertors. Large-aperture in-vessel actively cooled optical systems (f-number ~ 3) were installed for each view and connected to optical fibres. A total of 240 optical fibers can be distributed on various detection systems including a fast response-time, multi-channel, filtered photodetector-based “Filterscope” system, developed by Oak Ridge National Laboratory (USA) as well as grating spectrometers optimized for multi-sightline analysis. The first WEST experimental campaign conducted in 2017 has been dedicated to plasma start-up development during which the visible spectroscopy system has provided crucial information related to the impurity content first and then impurity sources. The diagnostic setup for that first experimental campaign was limited to the inner bumper and outer limiters but was sufficient to demonstrate that the optical setup was in accordance with the specifications. The radiance calibration procedure allowed us to estimate fluxes from the main limiter of about 8 × 10 18 atoms/(s m 2 ) and to show a first W source radial profile along the outboard limiter.

Meyer, O.↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Lead optimization and efficacy evaluation of quinazoline-based BET family inhibitors for potential treatment of cancer and inflammatory diseases

Extensive optimization of quinazoline-based lead 8 is described. The structure-activity relationship studies indicate the S-configuration is preferred for the phenylmorpholine substitution. Together with incorporation of a (2-hydroxyl-2-methylpropyl)pyrazole moiety at the 2-position leads to analogs with comparable potency and marked improvement in the pharmacokinetic profile over our previously reported lead compounds. Further in vivo efficacy studies in Kasumi-1 xenograft mouse model demonstrates that the selected inhibitors are well tolerated and highly efficacious in the inhibition of tumor growth. Additionally, the representative analog 19 also demonstrated significant improvement of arthritis severity in a collagen-induced arthritis (CIA) mouse model. These results indicate potential use of these quinazoline-based BET inhibitors for treatment of cancer and inflammatory diseases. Finally, a brief discussion of the co-crystallized structure of 19 with BRD4 (BD1) is also highlighted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Time of Flight Secondary Ion Mass Spectrometry for Characterization of Pt-Coated Porous Transport Layers in PEM Water Electrolyzers

Titanium-based porous transport layers (PTLs) and iridium-based catalyst layers (CLs) are two main components of proton exchange membrane water electrolyzers (PEMWEs). PTLs are typically coated with platinum to minimize interfacial losses and to support long-term operation. Optimizing coatings and the PTL-CL interface requires comprehensive characterization. This study establishes time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a valuable technique for PTL characterization, addressing capabilities and limitations related to PTL morphology. A methodology was developed that uses a Cs + sputter beam for dynamic depth profiling, with data collected in both positive-ion (MCs + ) and negative-ion modes to generate depth profiles, 2D ion maps, and 3D ion reconstructions. ToF-SIMS detected relative differences in platinum-layer thickness between samples; these trends were validated by cross-sectional scanning transmission electron microscope (STEM) measurements and flat-titanium substrate controls. Interfacial oxide layers are identified in both ion modes, with enhanced oxide sensitivity in negative mode. The technique’s high sensitivity enables detection of nanometer-scale coatings and trace impurities within the bulk PTL structure. These results provide a methodological framework for analyzing Pt-coated PTLs, with the potential to extend to other components in PEMWEs and other electrolyzer systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wake forces in a background of quadratically coupled mediators

Two particles can exert forces on each other when embedded in a sea of weakly coupled particles. These “wake forces” occur whenever the source and target particles have quadratic interactions with the mediating particles; they are proportional to the ambient energy density and typically have a range of order the characteristic de Broglie wavelength of the background. The effect can be understood as source particles causing a disturbance in the background waves—a wake—which subsequently interacts with the target particles. Wake forces can be mediated by bosons or fermions, can have spin dependence, may be attractive or repulsive, and have a generally anisotropic spatial profile and range that depends on the phase-space distribution of the ambient particles. In this work, I investigate the application of wake forces to dark matter searches, recast existing limits on short-range forces into leading constraints on dark matter with quadratic couplings, and sketch out potential experimental modifications to optimize sensitivity. Wake forces occur in the Standard Model: the presence of the cosmic neutrino background induces a millimeter-range force about 22 orders of magnitude weaker than gravity. Wake forces may also be relevant in condensed-matter and atomic physics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) [SWR-20-115]

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) can be used to estimate behind the meter (BTM) solar generation from limited datasets. Using distributed sets of diverse solar sites, but with close spatial proximity, and/or limited historical PV generation information can be used to generate of solar profiles. This is useful for applications where partial solar generation data is available, and on-site irradiance data is not available. GET-Solar calculates PV technical data parameters and calculates output by modeling shading and cloud cover impacts. Clear sky irradiance profiles are used to calculate base generation profiles on which the local shading and cloud cover layers are added. In order to arrive at clear sky generation data, PV mounting information like panel tilt and and angle is needed. For cases where PV mounting information is missing, panel tilt and azimuth angle can be estimated using a non-linear optimization algorithm. GET-Solar can also be used for forecasting applications where historical PV data is available to estimate local shading at various solar positions. This overall framework can be used for estimation of solar parameters, and assisting in analyzing and modeling diverse sets of DER where solar generation is also present in utility meter data. GET-Solar has been developed in Python and uses the Pyomo optimization language.

Abraham, Sherin Ann↗
DOE OSTI2018

Optimization of Zero Emission Hydrogen Fuel Cell Ferry Design, With Comparisons to the SF-BREEZE

Zero emission hydrogen fuel cell technology has the potential to drastically reduce total “well-to-waves” maritime emissions. Through realistic design studies of five commercially-relevant passenger vessels, this study examines the most cost-effective entry points in the US fleet for deploying today’s available technology, and includes analysis of resulting well-to-waves emission profiles. The results show that per-passenger mile vessel energy use is directly correlated to increased emissions, capital costs, and operating costs. As a consequence, low speed, large capacity vessels offer a cost-effective starting place today. Increases in vessel efficiency through such measures as hull design and light-weighting can have large impacts in reducing cost and emissions of these systems. Overall this work showed all five vessel types to be feasible with today’s hydrogen fuel cell technology and presents more options to fleets that are committed to reducing maritime emissions in cost effective ways.

08 HYDROGEN↗
DOE OSTI2016

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinForms to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model

Power is a fundamental constraint as supercomputing advances to exascale. Efficient operation within strict power budgets requires application-aware power management based on a detailed understanding of application-level power behavior. This work analyzes the Energy Exascale Earth System Model (E3SM) atmosphere component, SCREAM, on Perlmutter (NERSC) and Frontier (OLCF). We characterize power variation across inputs, concurrency levels, and power caps, evaluate the energy impact of code optimizations, and attribute energy within the code using a newly developed GPU energy model. Results show that SCREAM’s peak power remains stable during its core execution phase and decreases gradually as concurrency increases. Power capping experiments reveal a performance–energy "sweet spot". On Perlmutter, limiting GPU power to 50% of thermal design power (TDP) achieves up to 15% energy savings with a 7% performance penalty. On Frontier, a 40% TDP cap yields up to 10% energy savings with less than 10% performance loss. Code optimizations reduce SCREAM energy by shortening run time without increasing power. Modeling reveals a critical insight: data movement accounts for approximately 70% of SCREAM’s GPU energy. This fundamentally shifts the optimization focus from FLOPS to data transfer reduction for this class of applications, offering the most impactful strategy for improving energy efficiency. This work establishes a foundation for practical, application-aware power management at exascale.

Zhao, Zhengji [Lawrence Berkeley National Laborato↗
DOE OSTI2020

Structural and antibacterial properties of NSAID-loaded ultra-high molecular weight polyethylene

Peri-articular delivery of pain medication in joint arthroplasty has the potential to address post-operative pain and decrease the use of systemic opioids. Additionally, the sustained release from a delivery vehicle may be especially impactful in the initial post-operative period when pain is most severe. We recently described a novel approach for the sustained intra-articular delivery of an analgesic (bupivacaine) from an ultra-high molecular weight polyethylene (UHMWPE) bearing surface. A secondary but very significant effect of incorporating bupivacaine in UHMWPE was its antibacterial effect against Staphylococcal species, which are associated with the majority of periprosthetic joint infections. Here, we report on the structure, properties, elution characteristics and antibacterial properties of UHMWPE loaded with the non-steroidal anti-inflammatory drug (NSAID) — tolfenamic acid. We showed that 6 wt% drug loading was optimal for eluting clinically relevant intra-articular and systemic concentrations, for maintaining mechanical properties at a clinically relevant level, and for providing anti-colonization potential against low risk (planktonic) and high risk (biofilm forming) Staphylococcal species. We determined the osteoblast response to the tolfenamic acid-loaded UHMWPE to evaluate the cytotoxicity profile of this novel material. Tolfenamic acid-loaded UHMWPE has the potential to be used as a part of multimodal pain management therapy following arthroplasty and may provide prophylaxis for periprosthetic infection.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Reinforcement Learning for Autonomous Water Heater Control

Electric water heaters represent 14% of the electricity consumption in residential buildings. An average household in the United States (U.S.) spends about USD 400–600 (0.45 ¢/L–0.68 ¢/L) on water heating every year. In this context, water heaters are often considered as a valuable asset for Demand Response (DR) and building energy management system (BEMS) applications. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity cost of a water heater under a time-of-use (TOU) electricity pricing policy by only using standard DR commands. In this approach, a set of RL agents, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on an unseen pair of price and hot water usage profiles. The testing results showed that the RL agents can help save electricity cost in the range of 19% to 35% compared to the baseline operation without causing any discomfort to end users. Additionally, the RL agents outperformed rule-based and model predictive control (MPC)-based controllers and achieved comparable performance to optimization-based control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

MALDI Orbitrap Mass Spectrometry Profiling of Dysregulated Sulfoglycosphingolipids in Renal Cell Carcinoma Tissues

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗
DOE OSTI2025

Esterification of 3-quinuclidinol, a marker for the incapacitant BZ, for analysis by EI-GC-MS in OPCW test matrices

The analysis by EI-GC-MS of 3-quinuclidinol (3Q), a marker for the riot control and incapacitating agent quinuclinidyl benzilate (BZ), using several, new acylation strategies is described. After evaluating and optimizing conditions for the acylations, these were tested on their ability to successfully derivatize 3Q in three different matrices featured in the 44th Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency test (PT). As 3Q is a highly polar compound, the work here describes acylation strategies that generate 3Q analogs with superior gas chromatographic profiles relative to the underivatized material. The acyl groups studied in this work included acetyl, benzoyl, pentafluorobenzoyl and the bis(3,5-trifluoromethyl)benzoyl. The acylated 3Q products provide sharp, detectable peaks with significantly different retention times from that of the unmodified 3Q. Thus, the retention times for acetyl-, benzoyl-, pentafluorobenzoyl- and 3,5-bis(trifluoromethyl)benzoyl-3Q were determined to be 15.9, 24.9, 22.8 and 22.1 min respectively, in stark contrast to the unmodified 3Q which provides a sharp peak with a retention time centered at ~ 13.5 min only at high concentrations (> 10 µg/mL or µg/g) while a broad peak (RT ~ 15–15.5 min) at low concentrations (< 5 µg/mL or µg/g). The developed protocol was used to derivatize 3Q in three separate matrices. The first two matrices were liquid samples featured during the 44th OPCW PT at two separate concentrations in each (5 and 50 µg/mL). The last matrix was a soil sample featured in the same 44th OPCW PT wherein the 3Q had been spiked at a 12 µg/g concentration. The approach involves the extraction of 3Q from all matrices followed by its acylation resulting in a second reportable analytical method for an OPCW PT. The presented derivatization strategies should find wide applicability particularly in laboratories involved with the analysis of this chemical weapon agent degradation product and those participating in the yearly OPCW PTs.

3-quinuclidinol↗
DOE OSTI2016

Photodynamics of oxybenzone sunscreen: Nonadiabatic dynamics simulations

Herein we have used combined static electronic structure calculations and “on-the-fly” global-switching trajectory surface-hopping dynamics simulations to explore the photochemical mechanism of oxybenzone sunscreen. We have first employed the multi-configurational CASSCF method to optimize minima, conical intersections, and minimum-energy reaction paths related to excited-state intramolecular proton transfer (ESIPT) and excited-state decays in the {sup 1}ππ{sup ∗}, {sup 1}nπ{sup ∗}, and S{sub 0} states (energies are refined at the higher MS-CASPT2 level). According to the mapped potential energy profiles, we have identified two ultrafast excited-state deactivation pathways for the initially populated {sup 1}ππ{sup ∗} system. The first is the diabatic ESIPT process along the {sup 1}ππ{sup ∗} potential energy profile. The generated {sup 1}ππ{sup ∗} keto species then decays to the S{sub 0} state via the keto {sup 1}ππ{sup ∗}/gs conical intersection. The second is internal conversion to the dark {sup 1}nπ{sup ∗} state near the {sup 1}ππ{sup ∗} /{sup 1}nπ{sup ∗} crossing point in the course of the diabatic {sup 1}ππ{sup ∗} ESIPT process. Our following dynamics simulations have shown that the ESIPT and {sup 1}ππ{sup ∗} → S{sub 0} internal conversion times are 104 and 286 fs, respectively. Finally, our present work demonstrates that in addition to the ESIPT process and the {sup 1}ππ{sup ∗} → S{sub 0} internal conversion in the keto region, the {sup 1}ππ{sup ∗} → {sup 1}nπ{sup ∗} internal conversion in the enol region plays as well an important role for the excited-state relaxation dynamics of oxybenzone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Sap flux measurements in wet tropical forests: unique challenges and opportunities

Tropical rainforests often have great tree species and functional diversity, complex age and stand structure, deep active sapwood, and potential factors that reduce transpiration, such as frequent cloud cover and wet leaves. Such factors generate challenges for estimating transpiration from sap flux measurements. In fact, upscaling approaches have rarely been attempted for diverse tropical forests. Thus, the objective of this paper is to build upon past efforts to scale transpiration and optimize strategies for wet tropical forests. Over a five-year period, we instrumented 44 trees with heat dissipation sap flow sensors within a premontane wet tropical rainforest in Costa Rica (5000 mm MAP). Given high diversity, few instrumented trees belonged to the same species, genus, or even family. In a subset of trees, radial profiles across the full range of active xylem were examined. Measurements were scaled to the stand in two plots using sapwood area. In association with extensive micrometeorological measurements, only ~10% of rainfall was transpired from this forested watershed due to persistent low radiation, evaporative demand, and frequent wet canopy conditions. Contrary to temperate trees, we observed minimal flow reductions in deeper sapwood among the largest trees, whose water use amounted to nearly 80% of the total stand water use, even though they contributed less than 15% to total stand basal area. We found that transpiration was suppressed when leaves were wet, even after accounting for lower vapor pressure deficit and reduced solar radiation. Since soil moisture conditions at this site remain continually above deficit levels, flow reversal has been assumed to be minor and thus has not yet been investigated. The driest month on record resulted in higher, not lower transpiration. Given the high diversity of these forests, herein we propose practical and innovate approaches to group trees by function or degree of canopy exposure. Finally, these efforts are critical for accurate scaling of measurements from individual sensors to stands and for improving global land surface models that increasingly partition canopy components to better represent these functionally and structurally diverse ecosystems.

54 ENVIRONMENTAL SCIENCES↗