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At least 19 records

Heterometallic UO 2 2+ /Ag + Complexes: Structural Design and Luminescence Properties

Reported here are the synthesis, structural characterization, and luminescence properties of 11 novel UO 2 2+ /Ag + heterometallic complexes. Halogenated benzoic acids (2,6-dihalobenzoic acid (halo = F, Br), 3,5-dichlorobenzoic acid, and 3-halobenzoic acid (halo = Br, I)) and N-donor polycyclic ligands (2,2′-bipyridine, 2,2’;6′,2″-terpyridine, 1,10-phenanthroline, 2,2′-bipyrimidine) were employed to synthesize a set of compounds and induce structural diversity. The primary mode of coordination with the uranyl cation is hexagonal bipyramidal monomeric units with three halobenzoate ligands in the equatorial plane, though 1-D chains with pentagonal bipyramidal uranyl centers also form. The Ag + cations coordinate preferentially to the N-donor ligands and serve as counter-cations for the anionic uranyl motifs. The soft ligand character of the N-donor molecules is found to be a requirement for the inclusion of the Ag + cation into the structures. Anionic uranyl units and cationic silver units assemble via noncovalent interactions between π systems on adjacent rings and between halogens (when Br and I are present). Solid-state emission spectra display the usual uranyl band with superimposed vibronic fine structure, except for that of compound 1 , which shows emission from the 2,2′-bipyridine center. This family of compounds represents a substantial contribution to the already rich library of UO 2 2+ /Ag + compounds, and the synthetic parameters discussed within reveal a platform for the design of new heterometallic uranyl-containing materials.

anions↗

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high-biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height-normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Jonathan A. Walter↗

Structural complexity of γ-Al 2 O 3 : The nature of vacancy ordering and the structure of complex antiphase boundaries

The structure of γ-Al2O3 remains largely undetermined despite decades of research. This is due to the high degree of disorder, which poses significant challenges for structural analysis using conventional crystallographic approaches. Herein, we study the structure of γ-Al2O3 with Scanning Transmission Electron Microscopy (STEM) and ab-initio calculations to provide a complete structural description. We show that the microstructure can be understood in terms of two key structural features of nanoscale spinel domains and finite thickness segments termed as complex antiphase boundaries (cAPB) that provide the domain interconnectivity. The spinel domains have a distinctive preference for vacancy ordering, which can be rationalized in terms of a structure with a stacking disorder. Tetragonal P4 1 2 1 2 or monoclinic P2 1 models, all based on the identical motif, can be considered as representative ordered forms. Individual spinel domains are interconnected via cAPBs, which adopt a distinct non-spinel bonding environment of δ-Al 2 O 3 . The most common cAPB consists of a single delta motif with thickness of just 0.6 nm on (001), with the resulting displacement a/4 [101]. Remarkably, the cAPBs are shown to energetically stabilize the spinel domains of γ-Al 2 O 3 explaining their high abundance. We demonstrate how the tetragonal distortions naturally arise in this intricate microstructure and place the proposed model in the context of phase transformations to high temperature transition aluminas.

36 MATERIALS SCIENCE↗

Geometrically frustrated interactions drive structural complexity in amorphous calcium carbonate

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca∙∙∙Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca 2+ -ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca 2+ ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep Learning Prediction of Protein Complex Structures

Proteins interact to form protein complex to carry out biological functions such as catalytic chemical reaction. Therefore, it is important to develop computational methods to predict protein-protein interaction and the structures of protein complexes to study and enhance protein function. In this project, we successfully developed several deep learning methods to predict inter-protein contacts and the reinforcement learning and optimization methods to reconstruct protein complex structures from predicted inter-chain contacts. The methods were integrated with the MULTICOM protein complex structure prediction system and applied to predict the complex structures of biomass production-related proteins of green algae. During the two and a half years of research and development, all the specific milestones of the project were achieved successfully. 16 publications/manuscripts were produced. 10 software tools were developed. A patent application was submitted. Our MULTICOM predictors leveraging some tools developed in this project were ranked among the top predictors in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022.

59 BASIC BIOLOGICAL SCIENCES↗

Active impedance matching of complex structural systems

Viewgraphs on active impedance matching of complex structural systems are presented. Topics covered include: traveling wave model; dereverberated mobility model; computation of dereverberated mobility; control problem: optimal impedance matching; H2 optimal solution; statistical energy analysis (SEA) solution; experimental transfer functions; interferometer actuator and sensor locations; active strut configurations; power dual variables; dereverberation of complex structure; dereverberated transfer function; compensators; and relative power flow.

Macmartin, Douglas G.↗

Structural complexity and primary production resistance are coupled in a temperate forest

The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.

lidar—remote sensing↗

A nanobody suite for yeast scaffold nucleoporins provides details of the nuclear pore complex structure

Nuclear pore complexes (NPCs) are the main conduits for molecular exchange across the nuclear envelope. The NPC is a modular assembly of ~500 individual proteins, called nucleoporins or nups. Most scaffolding nups are organized in two multimeric subcomplexes, the Nup84 or Y complex and the Nic96 or inner ring complex. Working in S. cerevisiae, and to study the assembly of these two essential subcomplexes, we here develop a set of twelve nanobodies that recognize seven constituent nucleoporins of the Y and Nic96 complexes. These nanobodies all bind specifically and with high affinity. We present structures of several nup-nanobody complexes, revealing their binding sites. Additionally, constitutive expression of the nanobody suite in S. cerevisiae detect accessible and obstructed surfaces of the Y complex and Nic96 within the NPC. Overall, this suite of nanobodies provides a unique and versatile toolkit for the study of the NPC.

59 BASIC BIOLOGICAL SCIENCES↗

Application of ultrasonic signature analysis for fatigue detection in complex structures

Ultrasonic signature analysis shows promise of being a singularly well-suited method for detecting fatigue in structures as complex as aircraft. The method employs instrumentation centered about a Fourier analyzer system, which features analog-to-digital conversion, digital data processing, and digital display of cross-correlation functions and cross-spectra. These features are essential to the analysis of ultrasonic signatures according to the procedure described here. In order to establish the feasibility of the method, the initial experiments were confined to simple plates with simulated and fatigue-induced defects respectively. In the first test the signature proved sensitive to the size of a small hole drilled into the plate. In the second test, performed on a series of fatigue-loaded plates, the signature proved capable of indicating both the initial appearance and subsequent growth of a fatigue crack. In view of these encouraging results it is concluded that the method has reached a sufficiently advanced stage of development to warrant application to small-scale structures or even actual aircraft.

Zuckerwar, A. J.↗

Structural complexity biases vegetation greenness measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. In conclusion, our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

60 APPLIED LIFE SCIENCES↗

Electronic structure complexity and extremely large magnetoresistance in antiferromagnetic semimetal SmAgSb 2

SmAgSb 2 , a layered magnetic semimetal in the tetragonal 𝑅⁢𝑇⁢ Sb 2 family (𝑅 = Y, Sc, rare earth; 𝑇 = transition metal), is known to exhibit extremely large magnetoresistance (XMR) below its antiferromagnetic (AFM) transition temperature. Here, in this work, we present a comprehensive investigation combining magnetotransport measurements, density functional theory calculations accounting for electron correlation, and angle-resolved photoemission spectroscopy. Our results reveal a complex electronic structure characterized by a multiband Fermi surface and intricate magnetic ground states. We demonstrate that simple two-band models, previously employed in the literature, fail to consistently describe the observed transport phenomena. Notably, we report an XMR of approximately 25200% at 2 K under a 14 T magnetic field, significantly exceeding earlier reports for this material family and rivaling the performance of prominent nonmagnetic XMR systems. This pronounced enhancement below 𝑇 𝑁 suggests that the XMR originates from a combination of multiband electron-hole compensation and enhanced magnetic scattering in this correlated AFM semimetal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗

Developing a framework for qualitative engineering: Research in design and analysis of complex structural systems

The research is focused on automating the evaluation of complex structural systems, whether for the design of a new system or the analysis of an existing one, by developing new structural analysis techniques based on qualitative reasoning. The problem is to identify and better understand: (1) the requirements for the automation of design, and (2) the qualitative reasoning associated with the conceptual development of a complex system. The long-term objective is to develop an integrated design-risk assessment environment for the evaluation of complex structural systems. The scope of this short presentation is to describe the design and cognition components of the research. Design has received special attention in cognitive science because it is now identified as a problem solving activity that is different from other information processing tasks (1). Before an attempt can be made to automate design, a thorough understanding of the underlying design theory and methodology is needed, since the design process is, in many cases, multi-disciplinary, complex in size and motivation, and uses various reasoning processes involving different kinds of knowledge in ways which vary from one context to another. The objective is to unify all the various types of knowledge under one framework of cognition. This presentation focuses on the cognitive science framework that we are using to represent the knowledge aspects associated with the human mind's abstraction abilities and how we apply it to the engineering knowledge and engineering reasoning in design.

Franck, Bruno M.↗

Structural Complexity and Tuned Thermoelectric Properties of a Polymorph of the Zintl Phase Ca 2 CdSb 2 with a Non-centrosymmetric Monoclinic Structure

The Zintl phase Ca 2 CdSb 2 was found to be dimorphic. Besides the orthorhombic Ca 2 CdSb 2 (-o), here we report on the synthesis, the structural characterization, and the thermoelectric transport properties of its monoclinic form, Ca 2 CdSb 2 (-m), and its Lu-doped variant Ca 2–x Lu x CdSb 2 (x ≈ 0.02). The monoclinic structure exhibits complex structural characteristics and constitutes a new structure type with the non-centrosymmetric space group Cm (Z = 30). The electrical resistivity ρ(T) measured on single crystals of both phases portrays a transition from a semiconductor to a degenerate p-type semiconductor upon doping with Lu and with an attendant change in the Hall carrier concentration nH from 7.15 × 10 18 to 2.30 × 10 19 cm –3 at 300 K. The Seebeck coefficient S(T) of both phases are comparable and indicate a hole-dominated carrier transport mechanism with magnitudes of 133 and 116 μV/K at 600 K for Ca 2 CdSb 2 (-m) and Ca 2–x Lu x CdSb 2 , respectively. The convoluted atomic bonding with an attendant large unit cell volume of ~4365 Å 3 drives a putative low thermal conductivity in these materials resulting in a power factor PF of 1.63 μW/cm K 2 and an estimated thermoelectric figure of merit zT of ~0.5 for Ca 2–x Lu x CdSb 2 at 600 K. Furthermore, differential scanning calorimetry results reveal the stability of these phases up to about 960 K, making them candidates for moderate temperature thermoelectric materials.

36 MATERIALS SCIENCE↗

A gated graph transformer for protein complex structure quality assessment and its performance in CASP15

Abstract Motivation Proteins interact to form complexes to carry out essential biological functions. Computational methods such as AlphaFold-multimer have been developed to predict the quaternary structures of protein complexes. An important yet largely unsolved challenge in protein complex structure prediction is to accurately estimate the quality of predicted protein complex structures without any knowledge of the corresponding native structures. Such estimations can then be used to select high-quality predicted complex structures to facilitate biomedical research such as protein function analysis and drug discovery. Results In this work, we introduce a new gated neighborhood-modulating graph transformer to predict the quality of 3D protein complex structures. It incorporates node and edge gates within a graph transformer framework to control information flow during graph message passing. We trained, evaluated and tested the method (called DProQA) on newly-curated protein complex datasets before the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) and then blindly tested it in the 2022 CASP15 experiment. The method was ranked 3rd among the single-model quality assessment methods in CASP15 in terms of the ranking loss of TM-score on 36 complex targets. The rigorous internal and external experiments demonstrate that DProQA is effective in ranking protein complex structures. Availability and implementation The source code, data, and pre-trained models are available at https://github.com/jianlin-cheng/DProQA.

59 BASIC BIOLOGICAL SCIENCES↗