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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

MicroShell Minimalist Shell for Xilinx Microprocessors

MicroShell is a lightweight shell environment for engineers and software developers working with embedded microprocessors in Xilinx FPGAs. (MicroShell has also been successfully ported to run on ARM Cortex-M1 microprocessors in Actel ProASIC3 FPGAs, but without project-integration support.) Micro Shell decreases the time spent performing initial tests of field-programmable gate array (FPGA) designs, simplifies running customizable one-time-only experiments, and provides a familiar-feeling command-line interface. The program comes with a collection of useful functions and enables the designer to add an unlimited number of custom commands, which are callable from the command-line. The commands are parameterizable (using the C-based command-line parameter idiom), so the designer can use one function to exercise hardware with different values. Also, since many hardware peripherals instantiated in FPGAs have reasonably simple register-mapped I/O interfaces, the engineer can edit and view hardware parameter settings at any time without stopping the processor. MicroShell comes with a set of support scripts that interface seamlessly with Xilinx's EDK tool. Adding an instance of MicroShell to a project is as simple as marking a check box in a library configuration dialog box and specifying a software project directory. The support scripts then examine the hardware design, build design-specific functions, conditionally include processor-specific functions, and complete the compilation process. For code-size constrained designs, most of the stock functionality can be excluded from the compiled library. When all of the configurable options are removed from the binary, MicroShell has an unoptimized memory footprint of about 4.8 kB and a size-optimized footprint of about 2.3 kB. Since MicroShell allows unfettered access to all processor-accessible memory locations, it is possible to perform live patching on a running system. This can be useful, for instance, if a bug is discovered in a routine but the system cannot be rebooted: Shell allows a skilled operator to directly edit the binary executable in memory. With some forethought, MicroShell code can be located in a different memory location from custom code, permitting the custom functionality to be overwritten at any time without stopping the controlling shell.

Werne, Thomas A.↗
NASA NTRSDate not supplied

Quality of Candidate Flights and Submission Prediction in Collaborative Digital Departure Reroute

Collaborative Digital Departure Reroute (CDDR) enables the reroute of flights using a flight operator proposed set of alternative route options, referred to as Trajectory Option Set (TOS), in order to reduce delay on the airport's surface and in the Metroplex environment. The reroute functionality is enabled through NASA's Digital Information Platform (DIP). TOS candidate flights are defined as flights with an alternative route with delay savings greater than the flight operator defined relative trajectory cost. This paper analyzes the TOS candidate flights at Dallas/Fort Worth International Airport (KDFW) in the North Texas Metroplex to gain insight into which candidate flights are higher quality through a scoring method. This insight will inform refinements to help CDDR focus on high quality reroute opportunities. Binary classification models for predicting the flight operator's submission of candidate flights are also explored in this paper.

Machine Learning↗
NASA NTRSDate not supplied

Quality of Candidate Flights and Submission Prediction in Collaborative Digital Departure Reroute

Collaborative Digital Departure Reroute (CDDR) enables the reroute of flights using a flight operator proposed set of alternative route options, referred to as Trajectory Option Set (TOS), in order to reduce delay on the airport's surface and in the Metroplex environment. The reroute functionality is enabled through NASA's Digital Information Platform (DIP). TOS candidate flights are defined as flights with an alternative route with delay savings greater than the flight operator defined relative trajectory cost. This paper analyzes the TOS candidate flights at Dallas/Fort Worth International Airport (KDFW) in the North Texas Metroplex to gain insight into which candidate flights are higher quality through a scoring method. This insight will inform refinements to help CDDR focus on high quality reroute opportunities. Binary classification models for predicting the flight operator's submission of candidate flights are also explored in this paper.

Machine Learning↗
DOE OSTI2017

Mechanical Properties in Metal-Organic Frameworks: Emerging Opportunities and Challenges for Device Functionality and Technological Applications

We report that some of the most remarkable recent developments in metal–organic framework (MOF) performance properties can only be rationalized by the mechanical properties endowed by their hybrid inorganic–organic nanoporous structures. While these characteristics create intriguing application prospects, the same attributes also present challenges that will need to be overcome to enable the integration of MOFs with technologies where these promising traits can be exploited. In this review, emerging opportunities and challenges are identified for MOF-enabled device functionality and technological applications that arise from their fascinating mechanical properties. This is discussed not only in the context of their more well-studied gas storage and separation applications, but also for instances where MOFs serve as components of functional nanodevices. Recent advances in understanding MOF mechanical structure–property relationships due to attributes such as defects and interpenetration are highlighted, and open questions related to state-of-the-art computational approaches for quantifying their mechanical properties are critically discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The effects of active site and support on hydrogen elimination over transition-metal-functionalized yttria-decorated metal–organic frameworks

Hydrogen elimination from a metal alkyl complex and its reverse reaction are critical elementary steps in many catalytic cycles. In understanding such catalytic cycles, it is important to learn about the effect of the active site as well as effects beyond the active site, especially support effects. Here we employ density-functional-theory-based computational screening of transition-metal-functionalized yttria-decorated NU-1000 metal–organic frameworks to study the effect of metal sites and supports on the hydrogen elimination reactions. In this work, we consider six transition metals. The screening shows that a Nb-based catalyst has the lowest free energy of activation for both α-H elimination and β-H elimination, but for the latter we must also consider the free energy of release of the alkene. By the Sabatier principle, the optimal catalyst for β-H elimination is the one that interacts with molecules with intermediate strength for easy reactant activation as well as easy product desorption. By employing a volcano plot to find the optimum compromise, we identified V-functionalized, yttria-decorated NU-1000 as the most active catalyst among the trial candidates for the β-H elimination reaction. The analysis also reveals a support-specific charge transfer process in which the yttria and carboxylate linkers enable electron transfer between the transition-metal site and organic linkers of the NU-1000 simultaneously with a coordinated change of spin at the metal site and in the linker groups. Based on our analyses, we hypothesize that the observed charge transfer enables certain functional groups, such as propyl, to interact more strongly with the support and stabilize the catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

LDRD 19A42-015, Multi-Wire Arc Additive Manufacturing

Additive manufacturing (AM) techniques can efficiently and cost-effectively fabricate components with both geometrical and compositional complexities, where functionally-graded compositions in a component allow multiple service requirements to be simultaneously addressed, such as corrosion and high temperature structural requirements. High cost alloy compositions need only be deposited in local areas where they are needed. A multi-wire arc additive manufacturing (m-WAAM) system was developed to enable functionally-graded, additively manufactured complex structures. The m-WAAM system utilizes multiple filler wire alloys, allowing control of composition and composition gradients in the component during additive fabrication. Ultimately, this project successfully developed a high deposition rate, arc-based, additive manufacturing process with the truly novel capability of enabling spatial composition tailoring during the build of the component. System capabilities and process science will be studied in a follow-on LDRD starting next year.

36 MATERIALS SCIENCE↗
NASA NTRS1999

MEMS Using SOI Substrate

At NASA, the focus for smaller, less costly missions has given impetus for the development of microspacecraft. MicroElectroMechanical System (MEMS) technology advances in the area of sensor, propulsion systems, and instruments, make the notion of a specialized microspacecraft feasible in the immediate future. Similar to the micro-electronics revolution,the emerging MEMS technology offers the integration of recent advances in micromachining and nanofabrication techniques with microelectronics in a mass-producible format,is viewed as the next step in device and instrument miniaturization. MEMS technology offers the potential of enabling or enhancing NASA missions in a variety of ways. This new technology allows the miniaturization of components and systems, where the primary benefit is a reduction in size, mass and power. MEMS technology also provides new capabilities and enhanced performance, where the most significant impact is in performance, regardless of system size. Finally,with the availability of mass-produced, miniature MEMS instrumentation comes the opportunity to rethink our fundamental measurement paradigms. It is now possible to expand our horizons from a single instrument perspective to one involving multi-node distributed systems. In the distributed systems and missions, a new system in which the functionality is enabled through a multiplicity of elements. Further in the future, the integration of electronics, photonics, and micromechanical functionalities into "instruments-on-a-chip" will provide the ultimate size, cost, function, and performance advantage. In this presentation, I will discuss recent development, requirement, and applications of various MEMS technologies and devices for space applications.

Tang, Tony K.↗
DOE OSTI2024

A Mass‐Conserving‐Perceptron for Machine‐Learning‐Based Modeling of Geoscientific Systems

Although decades of effort have been devoted to building Physical-Conceptual (PC) models for predicting the time-series evolution of geoscientific systems, recent work shows that Machine Learning (ML) based Gated Recurrent Neural Network technology can be used to develop models that are much more accurate. However, the difficulty of extracting physical understanding from ML-based models complicates their utility for enhancing scientific knowledge regarding system structure and function. Here, we propose a physically interpretable Mass-Conserving-Perceptron (MCP) as a way to bridge the gap between PC-based and ML-based modeling approaches. The MCP exploits the inherent isomorphism between the directed graph structures underlying both PC models and GRNNs to explicitly represent the mass-conserving nature of physical processes while enabling the functional nature of such processes to be directly learned (in an interpretable manner) from available data using off-the-shelf ML technology. As a proof of concept, we investigate the functional expressivity (capacity) of the MCP, explore its ability to parsimoniously represent the rainfall-runoff (RR) dynamics of the Leaf River Basin, and demonstrate its utility for scientific hypothesis testing. To conclude, we discuss extensions of the concept to enable ML-based physical-conceptual representation of the coupled nature of mass-energy-information flows through geoscientific systems.

58 GEOSCIENCES↗
NASA NTRS2003

Enabling CSPA Operations Through Pilot Involvement in Longitudinal Approach Spacing

Several major airports around the United States have, or plan to have, closely-spaced parallel runways. This project complemented current and previous research by examining the pilots ability to control their position longitudinally within their approach stream.This project s results considered spacing for separation from potential positions of wake vortices from the parallel approach. This preventive function could enable CSPA operations to very closely spaced runways. This work also considered how pilot involvement in longitudinal spacing could allow for more efficient traffic flow, by allowing pilots to keep their aircraft within tighter arrival slots then air traffic control (ATC) might be able to establish, and by maintaining space within the arrival stream for corresponding departure slots. To this end, this project conducted several research studies providing an analytic and computational basis for calculating appropriate aircraft spacings, experimental results from a piloted flight simulator test, and an experimental testbed for future simulator tests. The following sections summarize the results of these three efforts.

Battiste, Vernol↗
DOE OSTI2023

Proactive Intrusion Detection and Mitigation System

SAND2023-05661O The proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. The PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. This hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for: • Distributed, real-time cyber-physical detection and mitigation analysis • Cybersecurity defense for grid-edge systems • Analysis framework that can provide situational awareness across the transmission, distribution, and DER systems The PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. With these goals, the main functional PIDMS objectives are: • Capability to collect cyber-physical data • Onboard storage of cyber-physical data • Peer-to-peer communication • Computationally efficient machine-learning algorithms • Online cyber-physical data analysis • Alerting/visualization capabilities • Mitigation deployment capability with bump-in-the-wire (BITW) implementation Each of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jones, Christian↗
DOE OSTI2013

Experiences Applying Data Staging Technology in Unconventional Ways

Several efforts have shown the potential of using additional compute-area resources to enhance the IO path to storage. Efforts like data staging, IO forwarding, and similar techniques can accelerate IO performance and reduce the impact of IO time to a compute application. Hybrid staging enhanced this path by adding processing functionality to locations along the data path to storage. While these efforts have been effective, they have taken a somewhat limited view of the potential benefits using some additional compute resources can offer both to enhance a compute application as well as to offering a way to exploit HPC-style resources for non-traditional tasks. Over the last few years, we have been experimenting with the potential for other sorts of activities using a staging style approach to add or enable new functionality. The efforts in this area have yielded a collection of small projects that yield some insights into both the potential and limitations of this approach for both achieving exascale computing and for enabling alternative uses for HPC resources.

Computer Science↗
DOE OSTI2014

Systematic Phenotypic Screen of Arabidopsis Peroxisomal Mutants Identifies Proteins Involved in β -Oxidation

Peroxisomes are highly dynamic and multifunctional organelles essential to development. Plant peroxisomes accommodate a multitude of metabolic reactions, many of which are related to the β-oxidation of fatty acids or fatty acid-related metabolites. Recently, several dozens of novel peroxisomal proteins have been identified from Arabidopsis (Arabidopsis thaliana) through in silico and experimental proteomic analyses followed by in vivo protein targeting validations. To determine the functions of these proteins, we interrogated their transfer DNA insertion mutants with a series of physiological, cytological, and biochemical assays to reveal peroxisomal deficiencies. Sugar dependence and 2,4-dichlorophenoxybutyric acid and 12-oxo-phytodienoic acid response assays uncovered statistically significant phenotypes in β-oxidation-related processes in mutants for 20 of 27 genes tested. Additional investigations uncovered a subset of these mutants with abnormal seed germination, accumulation of oil bodies, and delayed degradation of long-chain fatty acids during early seedling development. Mutants for seven genes exhibited deficiencies in multiple assays, strongly suggesting the involvement of their gene products in peroxisomal β-oxidation and initial seedling growth. Proteins identified included isoforms of enzymes related to β-oxidation, such as acyl-CoA thioesterase2, acyl-activating enzyme isoform1, and acyl-activating enzyme isoform5, and proteins with functions previously unknown to be associated with b-oxidation, such as Indigoidine synthase A, Senescence-associated protein/B12D-related protein1, Betaine aldehyde dehydrogenase, and Unknown protein5. This multipronged phenotypic screen allowed us to reveal b-oxidation proteins that have not been discovered by single assay-based mutant screens and enabled the functional dissection of different isoforms of multigene families involved in β-oxidation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Managing Mayhem

Research institutes, typically full of excellent scientists and engineers, tend to be very focused on the technical aspects of their work, but reluctant to put much energy into the management functions that enable a healthy, productive organization. This is not really surprising when one considers that scientists and engineers are well trained to measure and evaluate quantitative entities while the management arena is dominated by qualitative concepts. Management is generally considered to include planning, organizing, leading and controlling. This paper discusses the essential management functions and techniques that can be employed to maximize success in a research and development (R and D) organization. Successful management for production oriented businesses tends to rely heavily on the planning, organizing and controlling functions. To be successful in an R and D organization, the manager must be willing to relinquish some control and focus more effort on leading and coordinating the abilities of highly intelligent, educated and autonomous individuals. Good managers invest heavily in developing talented people and creating an environment that lets people do their best work.

42 ENGINEERING↗
DOE OSTI2026

Tensor renormalization group approach to critical phenomena via symmetry-twisted partition functions

The locality of field theories strongly constrains the possible behaviors of symmetry-twisted partition functions, and thus they serve as order parameters to detect low-energy realizations of global symmetries, such as spontaneous symmetry breaking (SSB). We demonstrate that the tensor renormalization group (TRG) offers an efficient framework to compute the symmetry-twisted partition functions, which enables us to detect the symmetry-breaking transition and also to study associated critical phenomena. As concrete examples of SSB, we investigate the two-dimensional (2D) classical Ising model and the three-dimensional (3D) classical 𝑂⁡(2) nonlinear sigma model, and we identify their critical points solely from the twisted partition function. By employing the finite-size scaling argument, we find the critical temperature 𝑇 𝑐 = 2.2017⁢(2) with the critical exponent 𝜈 = 0.663⁢(33) for the 3D 𝑂⁡(2) model. In addition, we also study the Berezinskii–Kosterlitz–Thouless (BKT) criticality of the 2D classical 𝑂⁡(2) model by extracting the helicity modulus from the twisted partition functions, and we obtain the BKT transition temperature, 𝑇 BKT = 0.8928⁢(2).

lattice field theory↗
DOE OSTI2017

Adaptively Compressed Exchange Operator for Large-Scale Hybrid Density Functional Calculations with Applications to the Adsorption of Water on Silicene

Density functional theory (DFT) calculations using hybrid exchange-correlation functionals have been shown to provide an accurate description of the electronic structures of nanosystems. However, such calculations are often limited to small system sizes due to the high computational cost associated with the construction and application of the Hartree-Fock (HF) exchange operator. Here, we demonstrate that the recently developed adaptively compressed exchange (ACE) operator formulation [J. Chem. Theory Comput. 2016, 12, 2242-2249] can enable hybrid functional DFT calculations for nanosystems with thousands of atoms. The cost of constructing the ACE operator is the same as that of applying the exchange operator to the occupied orbitals once, while the cost of applying the Hamiltonian operator with a hybrid functional (after construction of the ACE operator) is only marginally higher than that associated with applying a Hamiltonian constructed from local and semilocal exchange-correlation functionals. Therefore, this new development significantly lowers the computational barrier for using hybrid functionals in large-scale DFT calculations. We demonstrate that a parallel planewave implementation of this method can be used to compute the ground-state electronic structure of a 1000-atom bulk silicon system in less than 30 wall clock minutes and that this method scales beyond 8000 computational cores for a bulk silicon system containing about 4000 atoms. The efficiency of the present methodology in treating large systems enables us to investigate adsorption properties of water molecules on Ag-supported two-dimensional silicene. Our computational results show that water monomer, dimer, and trimer configurations exhibit distinct adsorption behaviors on silicene. In particular, the presence of additional water molecules in the dimer and trimer configurations induces a transition from physisorption to chemisorption, followed by dissociation on Ag-supported silicene. This is caused by the enhanced effect of hydrogen bonds on charge transfer and proton transfer processes. Lastly, such a hydrogen bond autocatalytic effect is expected to have broad applications for silicene as an efficient surface catalyst for oxygen reduction reactions and water dissociation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A method for infrared sensing based on oscillating zero power microelectromechanical photoswitches

This paper presents an interesting new method for measuring infrared (IR) radiation using a micromechanical photoswitch (MP). By leveraging the event-driven narrowband IR detection capability of an MP, electrostatic pull-in, and a novel integrated thermomechanical feedback mechanism, we show for the first time a zero-standby power IR sensor that can not only detect above-threshold IR power levels (>600 nW), but also generates an oscillating electromechanical pulse waveform whose frequency is a function of the incident IR power level. The device design, the theoretical model for the proposed idea, and the experimental demonstration of the mechanism are shown. The unique capability of zero-standby power IR detection and frequency-tunable AC waveform generation from a constant input signal (IR radiation) without the need for additional electronics promises to enable new functionalities for such remote wake-up sensors beyond simply detection, with potential uses in microrobotics and low-power computing.

Rajaram, Vageeswar (ORCID:0000000199546844)↗
DOE OSTI2013

Dose-shaping using targeted sparse optimization

Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot}{sup sparse} improves tradeoff between planning goals by 'sacrificing' voxels that have already been violated to improve PTV coverage, PTV homogeneity, and/or OAR-sparing. In doing so, overall plan quality is increased since these large violations only arise if a net reduction in E{sub tot}{sup sparse} occurs as a result. For example, large violations to dose prescription in the PTV in E{sub tot}{sup sparse}-optimized plans will naturally localize to voxels in and around PTV-OAR overlaps where OAR-sparing may be increased without compromising target coverage. The authors compared the results of our method and the corresponding clinical plans using analyses of DVH plots, dose maps, and two quantitative metrics that quantify PTV homogeneity and overdose. These metrics do not penalize underdose since E{sub tot}{sup sparse}-optimized plans were planned such that their target coverage was similar or better than that of the clinical plans. Finally, plan deliverability was assessed with the 2D modulation index.Results: The proposed method was implemented using IBM's CPLEX optimization package (ILOG CPLEX, Sunnyvale, CA) and required 1-4 min to solve with a 12-core Intel i7 processor. In the testing procedure, the authors optimized for several points on the Pareto surface of four 7-field 6MV prostate cases that were optimized for different levels of PTV homogeneity and OAR-sparing. The generated results were compared against each other and the clinical plan by analyzing their DVH plots and dose maps. After developing intuition by planning the four prostate cases, which had relatively few tradeoffs, the authors applied our method to a 7-field 6 MV pancreas case and a 9-field 6MV head-and-neck case to test the potential impact of our method on more challenging cases. The authors found that our formulation: (1) provided excellent flexibility for balancing OAR-sparing with PTV homogeneity; and (2) permitted the dose planner more control over the evolution of the PTV's spatial dose distribution than conventional objective functions. In particular, E{sub tot}{sup sparse}-optimized plans for the pancreas case and head-and-neck case exhibited substantially improved sparing of the spinal cord and parotid glands, respectively, while maintaining or improving sparing for other OARs and markedly improving PTV homogeneity. Plan deliverability for E{sub tot}{sup sparse}-optimized plans was shown to be better than their associated clinical plans, according to the two-dimensional modulation index.Conclusions: These results suggest that our formulation may be used to improve dose-shaping and OAR-sparing for complicated disease sites, such as the pancreas or head and neck. Furthermore, our objective function and constraints are linear and constitute a linear program, which converges to the global minimum quickly, and can be easily implemented in treatment planning software. Thus, the authors expect fast translation of our method to the clinic where it may have a positive impact on plan quality for challenging disease sites.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗