SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Abstract Not Provided
The national airspace has evolved over many years to accommodate increased traffic demand [1] while simultaneously maintaining one of the safest forms of transportation [2], [3]. One of the reasons for this success is the ability of the system and the operators to adapt and accommodate to situations that routinely disrupt optimal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators ability to control. These factors can lead to states where automation is unable to properly handle these issues and therefore air traffic controllers and pilots have to intervene, ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions this can be viewed as an increase in complexity. The reasoning for this is because humans are now required to make tactical decisions in response to external factors, resulting in a departure from the strategic plan where operations would be more efficiently managed. Human operators control airspace complexity under rigid regulations that are constantly changing. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. There has been past work that devised airspace complexity metrics in commercial aviation and related these metrics to controller workload (e.g., [4],[5]). The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic, including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly [6]. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to our proposed effort that identifies such contributing factors or precursor patterns. To define the scope we are proposing to measure complexity from the viewpoint of the Terminal Radar Approach Control Facilities (TRACON) controller’s perspective. In particular we are analyzing arrivals into KSFO. With safety as the top concern for airspace operators, it is important to recognize that as density and heterogeneity grow, the focus of the system will change. Times of the day when the airspace has low density and heterogeneity, the flights will follow more efficient paths where the aircraft move on established routes that are more or less directly to the destination. However, when density and heterogeneity increases, the system will begin changing focus to avoiding conflicts and collisions and route the flights in a more flexible way. Higher flexibility requires more communication and coordination between controllers and pilots which the current automation is unable to handle. This paper proposes a novel approach that monitors airspace complexity at multiple scales, uses a Machine Learning-based tool that predicts when operations will transition to a regime of greater complexity, and identifies actions that can reduce the complexity while still maintaining efficient and safe operations. We demonstrate our proposed approach using data from multiple complementary sources. This includes, but is not limited to: historical aircraft surveillance data from NASA’s Sherlock Data Warehouse [7], METAR weather data, and airport configuration data from Aviation System Performance Metrics (ASPM). The surveillance data flight paths are sampled at a variable sample rate — increasing as the aircraft approaches the airport. This is due to how Sherlock manages flight track stitching between different radar facilities which have different sampling rates. The weather and performance data are logged at defined intervals throughout the day at a courser refresh rate. In addition to the logged data and metrics, we leverage pre-defined Standard Terminal Arrival Routes (STARs) procedures to characterize the path of each flight. Each flight files for one of these routes in the flight plan well before entering the terminal airspace, and approximately follows the route until it leaves the STAR, typically on the final fix of a runway transition. However, most flights do not always fly the full STAR procedure to completion [8], but the majority do adhere to the fixes within the common route of the procedure. Our approach leverages fixes in the common route of each of the STARs to build a reference path to the airport. This allows us to characterize the flight paths in what we are defining as the “maneuvering area” (the airspace between the STAR and before the flight is lined up on the runway’s final approach) to determine how off nominal the flights are to calculate its complexity score. Determining airspace complexity is a concept that does not have a concrete answer. In designing this metric, we consider what increases the workload for the air traffic controllers. Consequently more specialized vectoring maneuvers results in higher workload. Accordingly, we start with a theory: each flight has a direct path it takes from the STAR’s common route to the final approach’s outer marker fix for the flight’s landing runway. It is important to note that the direct path is only used as a reference. If the majority of the flights have a large consistent offset as compared to other routes it does not necessarily mean that those flights have higher complexity. We are merely building a distribution based on this direct path for that particular STAR and runway pair to determine the normal mode of operations for that route. Flights that are in the upper tail of these distributions will result in higher complexity scores and flights that fly in the median will represent the normal mode of operations and therefore will have lower complexity scores. Since flights following each STAR route take different paths to the airport, we have a different distribution for each STAR route and therefore can model these distributions to compute a complexity score from their respective normalized distributions. To evaluate the effectiveness of our proposed airspace complexity metric we will compare against an established approach based on trajectory clustering [9]. This unsupervised learning technique consists of the following steps: (1) identify the general maneuvering areas (waypoints) by performing $\kappa$-means or DBSCAN clustering on locations where aircraft frequently turn based on the surveillance radar track data, (2) map flight trajectories onto sequences of waypoints, and (3) cluster the sequences based on their common subsequences. From a high-level perspective, this baseline model learns nominal operations in the airspace through the sequence of waypoints that are representative of where aircraft change direction and defines deviations from the nominal operations as “complex.” Therefore, more deviations from the nominal operations correspond to higher complexity values. For our validation, we re-implemented this technique and tune model hyper-parameters to correctly detect waypoints for the arrival traffic into the San Francisco bay area. We will compute the complexity measure over a one-year period using our proposed technique as well as the baseline. Our validation will be based on each technique’s ability to detect a set of undesirable outcomes (e.g., go-arounds, holding patterns, average time in the airspace, etc.). Since our current complexity metric is derived from the offset from the direct reference path, it’s important to understand what causes these offsets. In many of the flights with high offset distance, flights performing holding patterns and S turns can be observed. These maneuvering tactics are utilized to add distance between the aircraft and the destination runway to prevent multiple flights from having conflicting arrival times. In order to predict a rise in complexity (or the precursor to complexity), it’s necessary to be able to identify these potential conflicts (which in turn, result in higher offsets). To do this, we define a “representative flight” for each STAR route and runway pair. This flight is approximately the path the flight would take if there was a clear path with no other flights in the airspace — including the time remaining to the airport. We first identify the flights for a given STAR runway pair using the offset to the reference path distributions that fall between the 44-55 percentiles. This yields the flights that conform to the most normal mode of operation. Each of these flights is partitioned based on the percent complete from the entry point into the maneuvering areas from 0\% – 100\% complete. Then for each percent “bin”, we take the median value of the flight’s latitude/longitude coordinates, airspeed, and (non causal) time remaining to the airport to construct a lookup table for each percent complete bin on a given route. As a flight enters the maneuvering area, we can find the estimated arrival time of a flight to the airport by finding the closest point to the representative path’s percent complete bin (relative to the flight’s current position at any snapshot in the airspace) and therefore retrieve the corresponding remaining time left on the “representative path”. We assume that the flight will follow the representative path to completion when deriving these estimates. We can then compare these estimated arrival times against other flights for the same snapshot in time to identify potential conflicts. If more flights are estimated to arrive within a tolerance window than there are runways available, then we have a potential conflict. We can use this derived measure along with other factors expected to add disruption to the operation such as weather and runway configuration changes as an input to machine learning tools to detect precursors that increases in our complexity measure. This novel method will assist in uncovering insights into the contributing factors that lead to increased complexity that may allow for in-time responses to avoid reaching a high complexity state in the airspace.
ABSTRACT NADH:quinone oxidoreductase (complex I) is a bioenergetic enzyme that transfers electrons from NADH to quinone, conserving the energy of this reaction by contributing to the proton motive force. While the importance of NADH oxidation to mitochondrial aerobic respiration is well documented, the contribution of complex I to bacterial electron transport chains has been tested in only a few species. Here, we analyze the function of two phylogenetically distinct complex I isozymes in Rhodobacter sphaeroides , an alphaproteobacterium that contains well-characterized electron transport chains. We found that R. sphaeroides complex I activity is important for aerobic respiration and required for anaerobic dimethyl sulfoxide (DMSO) respiration (in the absence of light), photoautotrophic growth, and photoheterotrophic growth (in the absence of an external electron acceptor). Our data also provide insight into the functions of the phylogenetically distinct R. sphaeroides complex I enzymes (complex I A and complex I E ) in maintaining a cellular redox state during photoheterotrophic growth. We propose that the function of each isozyme during photoheterotrophic growth is either NADH synthesis (complex I A ) or NADH oxidation (complex I E ). The canonical alphaproteobacterial complex I isozyme (complex I A ) was also shown to be important for routing electrons to nitrogenase-mediated H 2 production, while the horizontally acquired enzyme (complex I E ) was dispensable in this process. Unlike the singular role of complex I in mitochondria, we predict that the phylogenetically distinct complex I enzymes found across bacterial species have evolved to enhance the functions of their respective electron transport chains. IMPORTANCE Cells use a proton motive force (PMF), NADH, and ATP to support numerous processes. In mitochondria, complex I uses NADH oxidation to generate a PMF, which can drive ATP synthesis. This study analyzed the function of complex I in bacteria, which contain more-diverse and more-flexible electron transport chains than mitochondria. We tested complex I function in Rhodobacter sphaeroides , a bacterium predicted to encode two phylogenetically distinct complex I isozymes. R. sphaeroides cells lacking both isozymes had growth defects during all tested modes of growth, illustrating the important function of this enzyme under diverse conditions. We conclude that the two isozymes are not functionally redundant and predict that phylogenetically distinct complex I enzymes have evolved to support the diverse lifestyles of bacteria.
Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached in finding the optimal or 'best balance' of the system functions and interrelationships. This is achievable following von Bertalanffy's approach of describing systems as a set of equations representing both the system functions and the system interrelationships. Reduction is found based on an objective function defining the system output given variations in the system inputs and the system operating environment. By minimizing the objective function with respect to these inputs and environments, a reduced system can be found. Thus, a reduction of the system complexity is feasible.
Mercury (Hg) is a major global pollutant arising from both natural and anthropogenic sources. Its widespread use in medicinal and industrial applications makes it a common chemical exposure and environmental pollutant. It can exist in several forms which include: Metallic mercury (Hg{sup 0}), mercurous (Hg{sub 2}{sup 2+}), mercuric salts (Hg{sup 2+}), and organic mercury (e.g. CH{sub 3}Hg{sup +}), with the latter being the most toxic of all the species. Due to mercury's high toxicity, new approaches towards its detection has received significant attention in the scientific community. Mercury exposure at the Savannah River Site (SRS) has been a recent concern especially with increasing amounts of organic mercury in the saltstone. It originates mainly from its use as an acidic dissolution catalyst of aluminum cladding from target fuels within the uranium and plutonium processing operations [1]. It is present to an amount of about 60 metric tons in the high-level waste (HLW) tanks. Organic Mercury species have been found in low activity waste (LAW) at the site that eventually ends up in the saltstone. Therefore, there is a need for: i) Converting organic mercury to other less toxic forms and ii) Complexation and removal of Hg prior of disposal of LAW in saltstone. Various methods have been developed for selective sensing of mercury in the presence of other toxic metals. These methods include using ligands that can form organo-soluble metal complexes with different optical and spectroscopic properties that can be used for toxic metal sensing. In 2005, our group pioneered an ion-exchange extraction method, in which o-phenylenediamine-derived disulfonamides were used to complex and selectively extract and sense Pb{sup 2+} from aqueous solutions into an organic phase [2,3]. Herein, a disulfonamide and a bis-dansylamide have been shown to extract, complex and sense Hg(II). Ligand 1: The crystal structure of the disulfonamide-Hg complex confirms the complexation of Hg(II) with the ligand. Complexation was corroborated by the {sup 1}H-NMR spectra obtained after contacting solutions of various concentrations of Hg{sup 2+} with 2 mM ligand in chloroform. Distinct resonances are observed at Hg/L ratio of 0.5 that are also observed for the isolated 1:2 complex. In the presence of excess mercury, new resonances, as well as the movement of Et{sub 3}N resonances indicate the formation of a different Hg-sulfonamide-triethylamine complex, presumably having 1:1 Hg:L stoichiometry. The electronic spectra of aqueous phases after extraction show that there was no free ligand absorption at 0.5 eq of Hg, indicating a complete complexation. Complexation was also confirmed by the UV-visible titrations with Hg{sup 2+} at constant ligand concentration. pH-dependent extraction carried out shows that extraction of Hg(II) by ligand 1 was over 90% for most alkaline pHs. Ligand 2: The crystal structure of the Ligand 2 complex formed with Hg(OAc){sub 2} shows a remarkable coordination pattern with 4:2 metal:ligand stoichiometry. The fluorescent bis-dansyl disulfonamide derivative was found to complex and sense HgCl{sub 2} and Hg(OAc){sub 2} by demonstrating fluorescence quenching upon Hg(II) addition in comparison with other metals (Zn(II), Cd(II), Pb(II)). No were observed for Cu(II), Ag(I) and Co(II). We have shown the complexation of Hg(II) by a disulfonamide and a bis-dansyl disulfonamide ligand using several spectroscopic methods. Ligand 1 was able to extract mercury into chloroform and form a complex in the presence of excess mercury by synergistic complexation with triethylamine acting as a co-ligand. X-ray and NMR both confirm a 1:2 HgL{sub 2} stoichiometry. Ligand 2 can be used for sensing of Hg(II) as fluorescence quenching was observed after addition of Hg(II)
Purpose: Complexity metrics have been suggested as a complement to measurement-based quality assurance for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). However, these metrics have not yet been sufficiently validated. This study develops and evaluates new aperture-based complexity metrics in the context of static multileaf collimator (MLC) openings and compares them to previously published metrics. Methods: This study develops the converted aperture metric and the edge area metric. The converted aperture metric is based on small and irregular parts within the MLC opening that are quantified as measured distances between MLC leaves. The edge area metric is based on the relative size of the region around the edges defined by the MLC. Another metric suggested in this study is the circumference/area ratio. Earlier defined aperture-based complexity metrics—the modulation complexity score, the edge metric, the ratio monitor units (MU)/Gy, the aperture area, and the aperture irregularity—are compared to the newly proposed metrics. A set of small and irregular static MLC openings are created which simulate individual IMRT/VMAT control points of various complexities. These are measured with both an amorphous silicon electronic portal imaging device and EBT3 film. The differences between calculated and measured dose distributions are evaluated using a pixel-by-pixel comparison with two global dose difference criteria of 3% and 5%. The extent of the dose differences, expressed in terms of pass rate, is used as a measure of the complexity of the MLC openings and used for the evaluation of the metrics compared in this study. The different complexity scores are calculated for each created static MLC opening. The correlation between the calculated complexity scores and the extent of the dose differences (pass rate) are analyzed in scatter plots and using Pearson’s r-values. Results: The complexity scores calculated by the edge area metric, converted aperture metric, circumference/area ratio, edge metric, and MU/Gy ratio show good linear correlation to the complexity of the MLC openings, expressed as the 5% dose difference pass rate, with Pearson’s r-values of −0.94, −0.88, −0.84, −0.89, and −0.82, respectively. The overall trends for the 3% and 5% dose difference evaluations are similar. Conclusions: New complexity metrics are developed. The calculated scores correlate to the complexity of the created static MLC openings. The complexity of the MLC opening is dependent on the penumbra region relative to the area of the opening. The aperture-based complexity metrics that combined either the distances between the MLC leaves or the MLC opening circumference with the aperture area show the best correlation with the complexity of the static MLC openings.
Purpose: To develop a system that analyses and reports the complexity of Volumetric Modulated Arc Therapy (VMAT) plans to aid in the decision making for streamlining patient specific dosimetric quality assurance (QA) tests. Methods: A software system, Delcheck, was developed in-house to calculate VMAT plan and delivery complexity using the treatment delivery file. Delcheck has the functionality to calculate multiple plan complexity metrics including the Li-Xing Modulation Index (LI-MI), multiplicative combination of Leaf Travel and Modulation Complexity Score (LTMCSv), Monitor Units per prescribed dose (MU/D) and the delivery complexity index (MIt) that incorporates the modulation of dose rate, leaf speed and gantry speed. Delcheck includes database functionality to store and compare plan metrics for a specified treatment site. The overall plan and delivery complexity is assessed based on the 95% conformance limit of the complexity metrics as Similar, More or Less complex. The functionality of the software was tested using 42 prostate conventional, 10 prostate SBRT and 15 prostate bed VMAT plans generated for an Elekta linear accelerator. Results: The mean(σ) of LI-MI for conventional, SBRT and prostate bed plans were 1690(486), 3215.4(1294) and 3258(982) respectively. The LTMCSv of the studied categories were 0.334(0.05), 0.325(0.07) and 0.3112(0.09). The MU/D of the studied categories were 2.4(0.4), 2.7(0.7) and 2.5(0.5). The MIt of the studied categories were 21.6(3.4), 18.2(3.0) and 35.9(6.6). The values of the complexity metrics show that LI-MI appeared to resolve the plan complexity better than LTMCSv and MU/D. The MIt value increased as the delivery complexity increased. Conclusion: The developed software was shown to be working as expected. In studied treatment categories Prostate bed plans are more complex in both plan and delivery and SBRT is more complex in plan and less complex in delivery as demonstrated by LI-MI and MIt. This project was funded through a Cancer Council NSW Project Grant (RG14-11)
A user's guide for the Air Traffic Complexity Measurement Environment (ACME) software is presented. The ACME consists of two major components, a complexity analysis tool and user interface. The Complexity Analysis Tool (CAT) analyzes complexity off-line, producing data files which may be examined interactively via the Complexity Data Analysis Tool (CDAT). The Complexity Analysis Tool is composed of three independently executing processes that communicate via PVM (Parallel Virtual Machine) and Unix sockets. The Runtime Data Management and Control process (RUNDMC) extracts flight plan and track information from a SAR input file, and sends the information to GARP (Generate Aircraft Routes Process) and CAT (Complexity Analysis Task). GARP in turn generates aircraft trajectories, which are utilized by CAT to calculate sector complexity. CAT writes flight plan, track and complexity data to an output file, which can be examined interactively. The Complexity Data Analysis Tool (CDAT) provides an interactive graphic environment for examining the complexity data produced by the Complexity Analysis Tool (CAT). CDAT can also play back track data extracted from System Analysis Recording (SAR) tapes. The CDAT user interface consists of a primary window, a controls window, and miscellaneous pop-ups. Aircraft track and position data is displayed in the main viewing area of the primary window. The controls window contains miscellaneous control and display items. Complexity data is displayed in pop-up windows. CDAT plays back sector complexity and aircraft track and position data as a function of time. Controls are provided to start and stop playback, adjust the playback rate, and reposition the display to a specified time.
The complexities of chemical composition and crystal structure are fundamental characteristics of minerals that have high relevance to the understanding of their stability, occurrence and evolution. This review summarises recent developments in the field of mineral complexity and outlines possible directions for its future elaboration. The database of structural and chemical complexity parameters of minerals is updated by H-correction of structures with unknown H positions and the inclusion of new data. The revised average complexity values (arithmetic means) for all minerals are 3.54(2) bits/atom and 345(10) bits/cell (based upon 4443 structure reports). The distributions of atomic information amounts, chemIG and strIG, versus the number of mineral species fit the normal modes, whereas the distributions of total complexities, chemIG,total and strIG,total, along with numbers of atoms per formula and per unit cell are log normal. The three most complex mineral species known today are ewingite, morrisonite and ilmajokite, all either discovered or structurally characterised within the last five years. The most important complexity-generating mechanisms in minerals are: (1) the presence of isolated large clusters; (2) the presence of large clusters linked together to form three-dimensional frameworks; (3) formation of complex three-dimensional modular frameworks; (4) formation of complex modular layers; (5) high hydration state in salts with complex heteropolyhedral units; and (6) formation of ordered superstructures of relatively simple structure types. The relations between symmetry and complexity are considered. The analysis of temporal dynamics of mineralogical discoveries since 1875 with the step of 25 years show the increasing chemical and structural complexities of human knowledge of the mineral kingdom in the history of mineralogy. In the Earth’s history, both diversity and complexity of minerals experience dramatic increases associated with the formation of Earth’s continental crust, initiation of plate tectonics and the Great Oxidation event.
Additions of two equivalents of (CF 3 ) 3 COH (R F9 OH) or (CF 3 ) 2 MeCOH (R F6 OH) to W(NAr) 2 R 2 complexes (Ar = 2,6-diisopropylphenyl, R = n-propyl or i-propyl) offer the opportunity to synthesize propylene or isopropylidene olefin metathesis-active complexes in the absence of free propylene. Propylene and isopropylidene complexes (W(NAr)(ArNH 2 )(OR F9 ) 2 (propylene) and W(NAr)(ArNH 2 )(OR F9 ) 2 (CMe 2 )) are formed at room temperature from both W(NAr) 2 (i-propyl) 2 and W(NAr) 2 (n-propyl) 2 complexes upon addition of two equivalents of R F9 OH; no W = CHCH 2 Me complexes are observed. Similar results are found for W(NAd) 2 (propyl) 2 complexes (Ad = 1-adamantyl). Both RNH 2 and RNH 2 B(C 6 F 5 ) 3 (R = Ar or Ad) catalyze the interconversion of propylene and isopropylidene complexes. Addition of R F6 OH to W(NAr) 2 R 2 or W(NAd) 2 R 2 complexes leads to mixtures that contain largely propylene complexes. Addition of (CF 3 )Me 2 COH (R F3 OH) to W(NAr) 2 (i-Pr) 2 yields only propylene complexes. One propylene complex, W(NAd)(OR F9 ) 2 (CH 2 ═CHMe)(dme), was isolated, structurally characterized, and found to react with AdNH 2 to reform W(NAd)(OR F9 ) 2 (CMe 2 )(AdNH 2 ). Furthermore, it is proposed that propylene and isopropylidene complexes interconvert through the formation of an intermediate isopropyl complex.
Five heteroleptic cationic iridium complexes with a π-expansive cyclometalating 2,3-diphenylbenzo[g] quinoxaline (dpbq) ligand (C^N ligand) and different diimine ligands (N^N ligands) (i.e. 2,2’-bipyridine (bpy, 1), phenanthroline (phen, 2), 2-(2-pyridinyl)quinoline (pqu, 3), 2,2’-bisquinoline (bqu, 4), and 2-(quinolin-2-yl)quinoxaline (quqo, 5)) were synthesized and characterized. The lowest-energy singlet electronic transitions (S1 states) were mainly dpbq ligand-centred 1ILCT (intraligand charge transfer)/1MLCT (metal to ligand charge transfer) transitions mixed with some 1π,π* transitions for complexes 1–4 with increased contributions from 1LLCT (ligand to ligand charge transfer) in 3 and 4. For complex 5, the S1 state was switched to the 1LLCT/1MLCT transitions. All five complexes displayed weak near-infrared (NIR) phosphorescence, with maximal emission output spanning 700–1400 nm and quantum yields being on the order of 10-3. The triplet state absorptions of 1–4 all resembled that of the [Ir(dpbq)2Cl]2 dimer with lifetimes of ca. 400 ns, while the TA spectrum of 5 possessed the characteristics of both the quqo ligand and the [Ir(dpbq)2Cl]2 dimer with a bi-exponential decay of ca. 5 μs and 400 ns. While the photophysics of these complexes differ slightly, their theranostic photodynamic therapy (PDT) effects varied drastically. All of the complexes were biologically active toward melanoma cells. Complexes 2 and 3 were the most cytotoxic, with 230–340 nM activity and selectivity factors for melanoma cells over normal skin fibroblasts of 34 to 40 fold. Complexes 2, 3, and 5 became very potent cytotoxins with light activation, with EC50 values as low as 12–18 nM. This potent nanomolar light-triggered activity combined with a lower dark toxicity resulted in 5 having a phototherapeutic index (PI) margin of almost 275. The bpy coligand led to the least amount of dark toxicity of 1, while phen and pqu produced cytotoxic but selective complexes 2 and 3. The quqo coligand produced the most potent complex 5 for in vitro PDT, both in terms of photocytotoxicity and PI. All Ir(III) complexes exhibited very bright NIR phosphorescence in melanoma cells. The wide range of cytotoxicity and photocytotoxicity effects within a relatively small class of complexes highlights the importance of the identity of the coligand in the biological activity of the π-expansive biscyclometalated Ir(III) complexes, and their bright NIR emission in live cells demonstrates their potential as theranostic PDT agents.
Complex systems have characteristics that challenge traditional systems engineering processes and methods. These characteristics have been defined in various ways. INCOSE has previously identified characteristics of complex systems and potential methods to deal with complexity in system development. The purpose of this paper is to provide definitions and describe distinguishing characteristics of complexity using example systems to illustrate approaches to assessing the extent of complexity. The paper applies Appreciative Inquiry to identify and assess complex system characteristics. The characteristics are used to examine several different examples of systems to illuminate areas of complexity. These examples range from seemingly simple systems to complicated systems to complex systems. Different tiers of complexity are identified as a result of the assessment. The paper also identified and introduces topics on managing complexity and the integrating system perspective that represent new directions for the engineering of complex systems. The Appreciative Inquiry approach provides a method for systems engineering practitioners to more readily identify complexity when they encounter it, and to deal more effectively with this complexity once it has been identified.
Bitterness often associated with whole wheat products may be related to phenolics in the bran. Cyclodextrins (CDs) are known to form inclusion complexes. The objective was to form inclusion complexes between β-CD and wheat phenolics. Pure phenolic acids (trans-ferulic acid (FA), caffeic acid (CA), and p-coumaric acid (CO)) and phenolic acids from wheat bran were used to investigate complex formation potential. Complexes were characterized by spectroscopy techniques, and a computational and molecular modeling study was carried out. The relative amount of complex formation between β-CD and wheat bran extract was CA > CO > FA. The phenolic compounds formed inclusion complexes with β-CDs by non-covalent bonds. The quantum-mechanical calculations supported the experimental results. The most stable complex was CO/β-CD complex. The ΔH value for CO/β-CD complex was -11.72 kcal/mol and was about 3 kcal/mol more stable than the other complexes. The QSPR model showed good correlation between binding energy and 1H NMR shift for the H5 signal. This research shows that phenolics and β-CD inclusion complexes could be utilized to improve the perception of whole meal food products since inclusion complexes have the potential to mask the bitter flavor and enhance the stability of the phenolics in wheat bran.
Impact of f-element complexation on the radiolytic robustness of separations ligands Gregory P. Horne, Makayla R. Baxter, Corey D. Pilgrim, Travis S. Grimes, Center for Radiation Chemistry Research, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID, 83415, USA Cristian Celis Barros, Department of Chemistry and Biochemistry, Florida State University, Tallahassee, FL 32306, USA. E-mail: ccelisbarros@fsu.edu Andrew R. Cook, Department of Chemistry, Brookhaven National Laboratory, Upton, New York, 11973, USA Stephen P. Mezyk, Department of Chemistry and Biochemistry, California State University Long Beach, 1250 Bellflower Boulevard, Long Beach, California, 90840-9507, USA The effects of ionizing radiation are ubiquitous throughout all aspects of a nuclear fuel cycle. However, the complexity and intensity of these effects are greatest during the management of used nuclear fuel, owing to the presence of a wide spectrum of radionuclides from neutron capture and fission processes. With regards to used nuclear fuel (UNF) reprocessing, radiation-induced processes typically promote the destruction of active compounds (e.g., complexants and additives) with the concomitant formation of potentially detrimental degradation products and corresponding changes in physical and chemical properties, which ultimately impact the effectiveness and longevity of a given reprocessing system. Concerning UNF complexants, radiation chemistry studies have historically focused on their radiation robustness in the absence of the metal ions they were designed to selectively complex. This knowledge gap is worrisome as previous studies on aqueous phase complexants have demonstrated significant changes in radiolytic behavior upon metal ion complexation.1-4 More recently, the rate of reaction of the n-dodecane radical cation—believed to be the major organic phase radiation-induced transient species responsible for complexant radiolysis in n-dodecane based solvent systems—with hexa-n-octylnitrilo-triacetamide (HONTA) was shown to increase by an order-of-magnitude upon complexation of europium or americium.5 These findings have significant implications on the projected longevity of complexants in UNF reprocessing solvent systems. Consequently, a thorough understanding of metal ion complexation effects on the radiolytic integrity of UNF complexants is essential to evaluate their potential for process application. Presented here are two recent studies from the Idaho National Laboratory Center for Radiation Chemistry Research group that demonstrate the various impacts of f-element complexation (uranium, americium, and lanthanides) on the radiolytic integrity (gamma and electron pulse) of tributyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), N,N-di-2-ethylhexylisobutryamide (DEHiBA), and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester (HEH[EHP]) under UNF reprocessing conditions. References 1) Bhattacharyya and Kundu, Int. J. Radiat. Phys. Chem., 1971, 3, 1. 2) Kundu and Matuura, Int. J. Radiat. Phys. Chem., 1975, 7, 565. 3) Ilan and Czapski, Biochimica et Biophysica Acta, 1977, 498, 386. 4) Buettner, Doherty, and Patterson, Fed. Euro. Biochem. Soc., 1983, 158 (1), 143. 5) Toigawa, Peterman, Meeker, Grimes, Zalupski, Mezyk, Cook, Yamashita, Kumagai, Matsumura, Horne, PCCP, 2021, 23, 1343.
Highlights: •Cross-linked complexes of ferredoxin (Fd) and Fd–NADP{sup +} reductase form oligomers. •In the crystal structures, Fd- and FNR moieties swap across the molecules. •The complexes exhibit concentration-dependent oligomerization at sub-milimolar order. -- Abstract: Ferredoxin–NADP{sup +} reductase (FNR) forms a 1:1 complex with ferredoxin (Fd), and catalyzes the electron transfer between Fd and NADP{sup +}. In our previous study, we prepared a series of site-specifically cross-linked complexes of Fd and FNR, which showed diverse electron transfer properties. Here, we show that X-ray crystal structures of the two different Fd–FNR cross-linked complexes form oligomers by swapping Fd and FNR moieties across the molecules; one complex is a dimer from, and the other is a successive multimeric form. In order to verify whether these oligomeric structures are formed only in crystal, we investigated the possibility of the oligomerization of these complexes in solution. The mean values of the particle size of these cross-linked complexes were shown to increase with the rise of protein concentration at sub-milimolar order, whereas the size of dissociable wild-type Fd:FNR complex was unchanged as analyzed by dynamic light scattering measurement. The oligomerization products were detected by SDS–PAGE after chemical cross-linking of these complexes at the sub-milimolar concentrations. The extent and concentration-dependent profile of the oligomerizaion were differentiated between the two cross-linked complexes. These results show that these Fd–FNR cross-linked complexes exhibit concentration-dependent oligomerization, possibly through swapping of Fd and FNR moieties also in solution. These findings lead to the possibility that some native multi-domain proteins may present similar phenomenon in vivo.
Six new Co{sup II} complexes [Co(L{sup 1}){sub 4}(OH){sub 2}] (1), {[Co(L"1)(H_2O)_4]·2ClO_4}{sub ∞} (2), {[Co(L"1)(H_2O)_4]·SiF_6}{sub ∞} (3), {[Co(L"1)_3]·2ClO_4}{sub ∞} (4), [Co(L{sup 2})Cl{sub 2}]{sub ∞} (5) and {[Co(L"2)_2]·SiF_6}{sub ∞} (6) [L{sup 1}=3,6-bis(N-imidazolyl) pyridazine, L{sup 2}=3,6-bis (N-benzimidazolyl) pyridazine] have been synthesized and characterized by elemental analysis, IR spectra and single crystal X-ray diffraction. Complex 1 has a mononuclear structure, while complexes 2 and 3 have 1-D chain structures. Considering the Co{sup II} centers were linked by the L{sup 1} ligands, the 3-D framework of complex 4 can be rationalized to be a {4^12.6^3} 6-c topological net with the stoichiometry uninodal net. 5 reveals a coordination 1-D zigzag chain structure consisting of a neutral chain [Co(L{sup 2})Cl{sub 2}]{sub n} with the Co{sup II} centers. Complex 6 has a rhombohedral grid with a (4, 4) topology. The TGA property, fluorescent property and photocatalytic activity of complexes 1–6 have been investigated and discussed. - Graphical abstract: Six Co{sup II} complexes of bis(N-imidazolyl/benzimidazolyl)pyridazine were synthesized and structurally characterized. The fluorescence properties and photocatalytic activity for dye degradation under UV light of all complexes have been investigated and discussed. Display Omitted - Highlights: • Six new Co{sup II} complexes with bis(N-imidazolyl/benzimidazolyl) pyridazine. • Structural analysis of all complexes. • Fluorescent property of all complexes. • Photocatalytic activity for dye degradation under UV light of all complexes.
The structure of unconventional complex coacervates, such as polymer-nonpolymer complex coacervates, remains less investigated than that of the conventional coacervates formed between oppositely charged polyelectrolytes with symmetric charge species. Yet, their microscopic structural organization is important to further elucidate the mechanism of liquid-liquid-phase separation processes upon complexation. In this work, we characterize the microstructural organization of complex coacervates formed between inorganic polyoxometalate (POM) and polyzwitterion by small-angle X-ray scattering (SAXS) with in situ temperature and shear control. Furthermore, despite the apparent transparent and homogeneous morphology of dense coacervates as observed by optical microscopy, our previous results (Macromolecules 2018, 51, 22, 9405-9411) suggest that dense polyzwitterion-POM coacervates exhibit critical-gel-like networks containing both complex-poor region (mesh pore) and complex-rich region (connective network). SAXS results as reported in this work support that the complex-rich region is actually in the form of loosely packed POM aggregates linked by polyzwitterion, designated as complex particles. The structure of aggregating complex particles is further examined against varied composition and salt concentrations, temperature, and shear, thanks to the high X-ray scattering contrast of POMs from that of other components in the coacervates. The complex particles in the dense coacervates appear to grow with more tightly packed POM aggregates with increasing POM-to-polyzwitterion concentration ratio, in contrast to more loosely packed POM aggregates with decreasing salt concentration. Conversely, increasing temperature could result in smaller complex particles containing more loosely packed POM aggregates, consistent with temperature-dependent viscoelasticity of dense coacervates. Furthermore, such POM-based hybrid dense coacervates exhibit intriguing strain-hardening behavior, resulting from shear-enhanced POM packing inside the complex particles. Distinct from the shear-thinning behavior of most conventional crosslinked polymeric networks, the strain-hardening property combined with thermal- and salt-responsive characteristics of polyzwitterion-POM coacervates could broaden the applications of hybrid organic-inorganic macroion coacervates as smart functional materials working under extreme environmental conditions.
Proton-responsive half-sandwich Cp*Ir(III) complexes possessing a bipyridine ligand with two hydroxy groups at the 3,3'-, 4,4'-, 5,5'- or 6,6'-positions (3DHBP, 4DHBP, 5DHBP, or 6DHBP) were systematically investigated. UV-vis titration data provided average pK a values of the hydroxy groups on the ligands. Both hydroxy groups were found to deprotonate in the pH 4.6–5.6 range for the 4–6DHBP complexes. One of the hydroxy groups of the 3DHBP complex exhibited the low pK a value of < 0.4 because the deprotonation is facilitated by the strong intramolecular hydrogen bond formed between the generated oxyanion and the remaining hydroxy group, which in turn leads to an elevated pK a value of ~13.6 for the second deprotonation step. The crystal structures of the 4– and 6DHBP complexes obtained from basic aqueous solutions revealed their deprotonated forms. The intramolecular hydrogen bond in the 3DHBP complex was also observed in the crystal structures. The catalytic activities of these complexes in aqueous phase reactions, at appropriate pH, for hydrogenation of carbon dioxide (pH 8.5), dehydrogenation of formic acid (pH 1.8), transfer hydrogenation reactions using formic acid/formate as a hydrogen source (pH 7.2 and 2.6) were investigated to compare the positional effects of the hydroxy groups. The 4– and 6DHBP complexes exhibited remarkably enhanced catalytic activities under basic conditions because of the resonance effect of the strong electrondonating oxyanions, whereas the 5DHBP complex exhibited negligible activity despite the presence of electron-donating groups. The 3DHBP complex exhibited relatively high catalytic activity at low pH owing to the one strong electron-donating oxyanion group stabilized by the intramolecular hydrogen bond. DFT calculations were employed to study the mechanism of CO₂ hydrogenation by the 4DHBP and 6DHBP complexes, and comparison of the activation free energies of the H₂ heterolysis and CO₂ insertion steps indicated that H₂ heterolysis is the rate-determining step for both complexes. The presence of a pendent base in the 6DHBP complex was found to facilitate the rate-determining step, and renders 6DHBP a more effective catalyst for formate production.