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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

High Performance-Multidisciplinary Simulation for Regional Scale Earthquake Hazard and Risk Assessments

Moderate-to-large magnitude earthquakes represent a significant risk around the world and a major issue across the Department of Energy (DOE) mission interests, ranging from DOE's one-of-a-kind mission critical facilities to national energy systems (nuclear power plants, electric/gas distribution systems, and renewable energy production facilities). As a result, for the DOE there is a strong motivation in promoting and developing a risk-informed and performance-based approach for both the assessment of existing facilities and the design of new structures. DOE National Labs have historically made multidisciplinary contributions to the solution of challenging seismic hazard and risk problems and have been at the forefront for the development of design standards for major facilities. The current approach for estimating the ground motion hazard for critical facilities is based upon a Probabilistic Seismic Hazard Analysis (PSHA), whereby measured ground motion data are collected and homogenized into a probabilistic framework to estimate the hazard for future events. However, recent studies have highlighted the site-specific nature of earthquakes and shown the limitations of a purely empirical approach. Moreover, the design of infrastructure systems has been moving toward a performance-based approach, in which specific performance goals are specified at different levels of excitation and for different limit states. Such an approach requires the availability of robust and reliable computational tools for the nonlinear dynamic analysis of complex structural systems. Ongoing research at Lawrence Berkeley National Laboratory (LBNL) and Lawrence Livermore National Laboratory (LLNL) aims at developing an advanced simulation environment at the exascale for a coupled assessment of earthquake hazard (ground motions) and earthquake risk (structural demands)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

The Simons Observatory: HoloSim-ML: machine learning applied to the efficient analysis of radio holography measurements of complex optical systems

Near-field radio holography is a common method for measuring and aligning mirror surfaces for millimeter and sub-millimeter telescopes. In instruments with more than a single mirror, degeneracies arise in the holography measurement, requiring multiple measurements and new fitting methods. We present HoloSim-ML, a Python code for beam simulation and analysis of radio holography data from complex optical systems. This code uses machine learning to efficiently determine the position of hundreds of mirror adjusters on multiple mirrors with few micron accuracy. We apply this approach to the example of the Simons Observatory 6m telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Analysis and Mitigation of Cascading Failures Using a Stochastic Interaction Graph with Eigen-analysis

In studies on complex network systems using graph theory, eigen-analysis is typically performed on an undirected graph model of the network. However, when analyzing cascading failures in a power system, the interactions among failures suggest the need for a directed graph beyond the topology of the power system to model directions of failure propagation. To accurately quantify failure interactions for effective mitigation strategies, this paper proposes a stochastic interaction graph model and associated eigen-analysis. Different types of modes on failure propagations are defined and characterized by the eigenvalues of a stochastic interaction matrix, whose absolute values are unity, zero, or in between. Finding and interpreting these modes helps identify the probable patterns of failure propagation, either local or widespread, and the participating components based on eigenvectors. Then, by lowering the failure probabilities of critical components highly participating in a mode of widespread failures, cascading can be mitigated. Here, the validity of the proposed stochastic interaction graph model, eigen-analysis and the resulting mitigation strategies is demonstrated using simulated cascading failure data on an NPCC 140-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

REopt: Energy Decision Analysis

REopt transforms complex energy project decisions into actionable results for building owners, utilities, and industry. Based on decades of NREL decision-support expertise, REopt guides investment in economic, resilient energy technologies. This presentation provides an overview of how REopt can help building owners, utilities, developers, and industry optimize the economic and resilience benefits of distributed energy resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Abnormal Current–Voltage Hysteresis Induced by Reverse Bias in Organic–Inorganic Hybrid Perovskite Photovoltaics

In this study, reverse bias (RB)-induced abnormal hysteresis is investigated in perovskite solar cells (PVSCs) with nickel oxide (NiOx)/methylammonium lead iodide (CH 3 NH 3 PbI 3 ) interfaces. Through comprehensive current-voltage (I-V) characterization and bias-dependent external quantum efficiency (EQE) measurements, we demonstrate that this phenomenon is caused by the interfacial ion accumulation intrinsic to CH 3 NH 3 PbI 3 . Subsequently, via systematic analysis we discover that the abnormal I-V behavior is remarkably similar to tunnel diode I-V characteristics and is due to the formation of a transient tunnel junction at NiO x /CH 3 NH 3 PbI 3 interfaces under RB. The detailed analysis navigating the complexities of I-V behavior in CH 3 NH 3 PbI 3 -based solar cells provided here ultimately illuminates possibilities in modulating ion motion and hysteresis via interfacial engineering in PVSCs. Moreover, this work shows that RB can alter how CH 3 NH 3 PbI 3 contributes to the functional nature of devices and provides the first steps toward approaching functional perovskite interfaces in new ways for metrology and analysis of complex transient processes.

14 SOLAR ENERGY↗
DOE OSTI2023

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

New water soluble heterometallic complex showing unpredicted coordination modes of EDTA

A mesoporous 3D polymeric complex (I) having formula ([Zr(IV)O-μ{sup 3}-(EDTA)Fe(III)OH]·H{sub 2}O){sub n} has been crystallized and characterized by various techniques. Single-crystal X-ray diffraction analysis revealed that complex (I) crystallized in chiral monoclinic space group Cc (space group no. 9) with unexpected coordination modes of EDTA and mixture of two transition metal ions. In this complex, the coordination number of Zr(IV) ion is seven where four carboxylate oxygen atoms, two nitrogen atoms, one oxide atom are coordinating with Zr(IV). Fe(III) is four coordinated and its coordination environment is composed of three different carboxylic oxygen atoms from three different EDTA and one oxygen atom of –OH group. The structure consists of 4-c and 16-c (2-nodal) net with new topology and point symbol for net is (3{sup 36}·4{sup 54}·5{sup 30})·(3{sup 6}). TGA study and XRPD pattern showed that the coordination polymer is quite stable even after losing water molecule and –OH ion. Quenching behavior in fluorescence of ligand is observed by complexation with transition metal ions is due to n–π⁎ transition. The SEM micrograph shows the morphology of complex (I) exhibits spherical shape with size ranging from 50 to 280 nm. The minimum N{sub 2} (S{sub BET}=8.7693 m{sup 2}/g) and a maximum amount of H{sub 2} (high surface area=1044.86 m{sup 2}/g (STP)) could be adsorbed at 77 K. From DLS study, zeta potential is calculated i.e. −7.94 shows the negative charges on the surface of complex. Hirshfeld surface analysis and fingerprint plots revealed influence of weak or non bonding interactions in crystal packing of complex. - Graphical abstract: The complex (I) crystallized with unexpected coordination modes of EDTA having 4-c, 16-c net with new topology and point symbol is (3{sup 36}·4{sup 54}·5{sup 30})·(3{sup 6}). TGA study and XRPD pattern proved its stability with high preference of H{sub 2} uptake by complex. - Highlights: • 3D complex having unexpected coordination modes of EDTA with Zr(IV) and Fe(III). • The structure consists of 4-c and 16-c (2-nodal) net with new topology. • Reasonable S{sub BET} (8.7693 m{sup 2}/g) but high H{sub 2} uptake (1044.86 m{sup 2}/g) due to limited pore size. • Quenching behavior due to n–π⁎ transition by complexation with transition metal ions. • From DLS study, zeta potential value is −7.94.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Top-Down Mass Spectrometry Analysis of Membrane-Bound Light-Harvesting Complex 2 from Rhodobacter sphaeroides

We show a top-down proteomic analysis of the membrane-bound peripheral light-harvesting complex LH2 isolated from the purple photosynthetic bacterium Rhodobacter sphaeroides. The LH2 complex is coded for by the puc operon. The Rb. sphaeroides genome contains two puc operons, designated puc1BAC and puc2BA. Although previous work has shown consistently that the LH2 β polypeptide coded by the puc2B gene was assembled into LH2 complexes, there are contradictory reports as to whether the Puc2A polypeptides are incorporated into LH2 complexes. Furthermore, post-translational modifications of this protein offer the prospect that it could coordinate bacteriochlorophyll a (Bchl a) by a modified N-terminal residue. Here, we describe the components of the LH2 complex on the basis of electron-capture dissociation fragmentation to confirm the identity and sequence of the protein’s subunits. We found that both gene products of the β polypeptides are expressed and assembled in the mature LH2 complex, but only the Puc1A-encoded polypeptide α is observed here. The methionine of the Puc2B-encoded polypeptide is missing, and a carboxyl group is attached to the threonine at the N-terminus. Surprisingly, one amino acid encoded as an isoleucine in both the puc2B gene and the mRNA is found as valine in the mature LH2 complex, suggesting an unexpected and unusual post-translational modification or a specific tRNA recoding of this one amino acid.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Safety Analysis Report for Packaging, Y-12 National Security Complex, Model ES-3100 Package with Bulk HEU Contents

This safety analysis report for packaging (SARP) presents the results of the safety analysis prepared in support of the Consolidated Nuclear Security, LLC (CNS) request for licensing of the Model ES-3100 package with bulk highly enriched uranium (HEU) contents and issuance of a Type B(U) Fissile Material Certificate of Compliance. This SARP, published in the format specified in the U.S. Nuclear Regulatory Commission (NRC) Regulatory Guide 7.9 and using information provided in UCID-21218 and NRC Regulatory Guide 7.10, demonstrates that the Y-12 National Security Complex (Y-12) ES-3100 package with bulk HEU contents meets the established NRC regulations for packaging, preparation for shipment, and transportation of radioactive materials given in Title 10, Part 71, of the Code of Federal Regulations (CFR) [10 CFR 71] as well as U.S. Department of Transportation (DOT) regulations for packaging and shipment of hazardous materials given in Title 49 CFR. To protect the health and safety of the public, shipments of radioactive materials are made in packaging that is designed, fabricated, assembled, tested, procured, used, maintained, and repaired in accordance with the provisions cited above. Safety requirements addressed by the regulations that must be met when transporting radioactive materials are containment of radioactive materials, radiation shielding, and assurance of nuclear subcriticality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Safety Analysis Report For Packaging, Y-12 National Security Complex, Model ES-3100 Package with Bulk HEU Contents

This safety analysis report for packaging (SARP) presents the results of the safety analysis prepared in support of the Consolidated Nuclear Security, LLC (CNS) request for licensing of the Model ES-3100 package with bulk highly enriched uranium (HEU) contents and issuance of a Type B(U) Fissile Material Certificate of Compliance. This SARP, published in the format specified in the U.S. Nuclear Regulatory Commission (NRC) Regulatory Guide 7.9 and using information provided in UCID-21218 and NRC Regulatory Guide 7.10, demonstrates that the Y-12 National Security Complex (Y-12) ES-3100 package with bulk HEU contents meets the established NRC regulations for packaging, preparation for shipment, and transportation of radioactive materials given in Title 10, Part 71, of the Code of Federal Regulations (CFR) [10 CFR 71] as well as U.S. Department of Transportation (DOT) regulations for packaging and shipment of hazardous materials given in Title 49 CFR.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Molecular and Electronic Structure, and Hydrolytic Reactivity of a Samarium(II) Crown Ether Complex

The reaction of SmI 2 with dibenzo-30-crown-10 (DB30C10), followed by metathesis with [Bu 4 N][BPh 4 ], allows for the isolation of [Sm II (DB30C10)][BPh 4 ] 2 as bright-red crystals in good yield. Moreover, exposure of [Sm(DB30C10)] 2+ to solvents containing trace water results in the conversion to the dinuclear Sm III complex, Sm 2 (DB30C10)(OH) 2 I 4 . Structural analysis of both complexes shows substantial rearrangement of the crown ether from a folded, Pac-Man form with Sm II to a twisted conformation with Sm III . The optical properties of [Sm II (DB30C10)][BPh 4 ] 2 exhibit a strong temperature dependence and change from broad-band absorption features indicative of domination by 5d states to fine features characteristic of 4f → 4f transitions at low temperatures. Here, exploration of the electronic structure of these complexes via ab initio wave function calculations (SO-CASSCF) reflects that the ground state of Sm II in [Sm II (DB30C10)] 2+ is a 4f 6 state with low-lying 4f 5 5d 1 states, where the latter states have been lowered in energy by ~12 000 cm –1 with respect to the free ion. The decacoordination of the Sm II cation by the crown ether is responsible for this alteration in the energies of the excited state and demonstrates the ability to tune the electronic structure of Sm II .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗