Experimental Structural Characterization Research Articles

Subdiffraction Limited Photonic Funneling of Light

AbstractEfficient optical coupling between nano‐ and macroscale areas is strongly suppressed by the diffraction limit. This work presents a possible solution to this fundamental problem via the experimental fabrication, characterization, and comprehensive theoretical analysis of structures referred to as “photonic funnels.” The funnels represent a novel composite material platform that combines hyperbolic dielectric response with geometry‐assisted optical confinement. Experimentally, funneling of mid‐infrared light through openings with diameters as small as 1/25th of the free space wavelength (λ0) is demonstrated. By analyzing the optical response of the funnels, as fabricated, both confinement of mid‐infrared radiation to the λ0/25 areas and efficient outcoupling of light from deep subwavelength areas are confirmed.

Microstructural and Mechanical Response of NiTi Lattice 3D Structure Produced by Selective Laser Melting

Nowadays, additive manufacturing (AM) permits to realize complex metallic structural parts, and the use of NiTi alloy, known as Nitinol, allows the integration of specific functions to the AM products. One of the most promising designs for AM is concerning the use of lattice structures that show lightweight, higher than bulk material deformability, improved damping properties, high exchange surface. Moreover, lattice structures can be realized with struts, having dimensions below 1 mm—this is very attractive for the realization of Nitinol components for biomedical devices. In this light, the present work regarded the experimental characterization of lattice structures, produced by selective laser melting (SLM), by using Ni-rich NiTi alloy. Differential scanning calorimetry (DSC), electron backscatter diffraction (EBSD), and compression testing were carried out for analyzing microstructure, martensitic transformation (MT) evolution, and superelasticity response of the SLMed lattice samples. The lattice microstructures were compared with those of the SLMed bulk material for highlighting differences. Localized martensite was detected in the nodes zones, where the rapid solidification tends to accumulate solidification stresses. An increase of martensitic transformation temperatures was also observed in lattice NiTi.

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization. The latter would allow for the rapid expansion of the known structural space for generating high quality template-based models. Our approach generalizes to other evolutionarily-related, short, cysteine-rich venoms of interest. Overall, we present and validate an approach for venom structure modeling and experimental guidance and employ it to produce a 290%-larger library of approximate conotoxin structures for HTS. We also provide a set of ranked conotoxin sequences for experimental structure determination to further expand this library.

Learning context-aware structural representations to predict antigen and antibody binding interfaces.

Understanding how antibodies specifically interact with their antigens can enable better drug and vaccine design, as well as provide insights into natural immunity. Experimental structural characterization can detail the 'ground truth' of antibody-antigen interactions, but computational methods are required to efficiently scale to large-scale studies. To increase prediction accuracy as well as to provide a means to gain new biological insights into these interactions, we have developed a unified deep learning-based framework to predict binding interfaces on both antibodies and antigens. Our framework leverages three key aspects of antibody-antigen interactions to learn predictive structural representations: (i) since interfaces are formed from multiple residues in spatial proximity, we employ graph convolutions to aggregate properties across local regions in a protein; (ii) since interactions are specific between antibody-antigen pairs, we employ an attention layer to explicitly encode the context of the partner; (iii) since more data are available for general protein-protein interactions, we employ transfer learning to leverage this data as a prior for the specific case of antibody-antigen interactions. We show that this single framework achieves state-of-the-art performance at predicting binding interfaces on both antibodies and antigens, and that each of its three aspects drives additional improvement in the performance. We further show that the attention layer not only improves performance, but also provides a biologically interpretable perspective into the mode of interaction. The source code is freely available on github at https://github.com/vamships/PECAN.git.

Biological vs. Crystallographic Protein Interfaces: An Overview of Computational Approaches for Their Classification

Complexes between proteins are at the basis of almost every process in cells. Their study, from a structural perspective, has a pivotal role in understanding biological functions and, importantly, in drug development. X-ray crystallography represents the broadest source for the experimental structural characterization of protein-protein complexes. Correctly identifying the biologically relevant interface from the crystallographic ones is, however, not trivial and can be prone to errors. Over the past two decades, computational methodologies have been developed to study the differences of those interfaces and automatically classify them as biological or crystallographic. Overall, protein-protein interfaces show differences in terms of composition, energetics and evolutionary conservation between biological and crystallographic ones. Based on those observations, a number of computational methods have been developed for this classification problem, which can be grouped into three main categories: Energy-, empirical knowledge- and machine learning-based approaches. In this review, we give a comprehensive overview of the training datasets and methods so far implemented, providing useful links and a brief description of each method.

Computational and experimental characterization of 3D-printed PCL structures toward the design of soft biological tissue scaffolds

Degradable porous polymeric structures are attractive candidates for biological tissue scaffolds, and adequate mechanical, transport, chemical and biological properties determine their functionality. Aside from the properties of polymer-based materials, the scaffold's meso-structure controls its elasticity at the organ length-scale. This study investigated the effect of the meso-structure on scaffolds' mechanical and transport properties using finite element analysis (FEA) and computational fluid dynamics (CFD). A number of poly (ε-caprolactone) (PCL) - based scaffolds were 3D printed, analyzed by microcomputed tomography (micro-CT) and mechanically tested. We found that the gradient (G) and gradient and staggered (GS) meso-structure designs led to a higher scaffold permeability, a more homogeneous flow inside the scaffold, and a lower wall shear stress (WSS) in comparison with the basic (B) meso-structure design. The GS design resulted in scaffold stiffness as low as 1.07/0.97 MPa under compression/tension, figures that are comparative with several soft tissues. Image processing of micro-CT data demonstrated that the imposed meso-structures could have been adequately realized through 3D printing, and experimental testing validated FEA analysis. Our results suggest that the properties of 3D-printed PCL-based scaffolds can be tuned via meso-structures toward soft tissue engineering applications. The biological function of designed scaffolds should be further explored in-situ studies.

Computational, Experimental Structural Characterization and Molecular Docking Studies of 5,7-Dihydroxy-4-methoxyflavone against Cytochrome P450 Enzymes

In this work, the geometry optimization and harmonic vibrational wavenumbers of kaempferide (5,7-dihydroxy-4-methoxyflavone) were computed by density functional theory (DFT) method. Theoretically computed vibrational wavenumbers were compared with experimental values and the interpretation of the vibrational spectra has been studied. Frontier molecular orbitals (FMO) and molecular electrostatic potential (MEP) analysis of the title compound have been carried out. The 1H & 13C NMR, UV visible and electronic properties of the compound were investigated theoretically and compared with the experimental values. Molecular docking study of the compound against cytochrome P450 family enzymes (CYPs 1A1, 1A2, 3A4, 2C8, 2C9 and 2D6) were also studied and the results revealed that the title compound interact with human CYP2C8 enzymes with minimum binding energy of -9.43 kcal/mol. The compound forms hydrogen bond with the residues of Thr302, Thr305, Leu361, Val362, Cys435, Gln356 and Ala297. Thus, these studies assist to understand the inhibitory mechanism of kaempferide with CYP450 enzymes and may facilitate significant clinical implications in the prevention and treatment of various therapeutic diseases.

Modeling Antibody-Antigen Complexes by Information-Driven Docking

Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.

Phase stability and electronic structure of iridium metal at the megabar range

The 5d transition metals have attracted specific interest for high-pressure studies due to their extraordinary stability and intriguing electronic properties. In particular, iridium metal has been proposed to exhibit a recently discovered pressure-induced electronic transition, the so-called core-level crossing transition at the lowest pressure among all the 5d transition metals. Here, we report an experimental structural characterization of iridium by x-ray probes sensitive to both long- and short-range order in matter. Synchrotron-based powder x-ray diffraction results highlight a large stability range (up to 1.4 Mbar) of the low-pressure phase. The compressibility behaviour was characterized by an accurate determination of the pressure-volume equation of state, with a bulk modulus of 339(3) GPa and its derivative of 5.3(1). X-ray absorption spectroscopy, which probes the local structure and the empty density of electronic states above the Fermi level, was also utilized. The remarkable agreement observed between experimental and calculated spectra validates the reliability of theoretical predictions of the pressure dependence of the electronic structure of iridium in the studied interval of compressions.

Identifying rhenium substitute candidate multiprincipal-element alloys from electronic structure and thermodynamic criteria

Abstract

Experimental and Theoretical Structural Characterization of Cu–Au Tripods for Photothermal Anticancer Therapy

Anisotropic metal nanostructures (e.g., Au–Ag, Au–Cu) are emerging for biomedical and catalytic applications in recent years. Herein, we report a modified synthesis of Cu–Au tripod nanocrystals thr...

Information-Driven Modelling of Antibody-Antigen Complexes

Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial to improve our ability of designing efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for those complexes. We investigate here how information about complementary determining regions and binding epitopes can be used to drive the modelling process and present a comparative study of four different docking software (ClusPro, LightDock, ZDOCK and HADDOCK) providing specific options for antibody-antigen modelling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models both in the presence and absence of information about the epitope on the antigen.

Experimental Characterization of SLM and EBM Cubic Lattice Structures for Lightweight Applications

This study carries out an experimental characterization of lattice structures that are based on cubic cells fabricated through selective laser melting (SLM) and electron beam melting (EBM). The lattice failure under compressive load is studied as a function of the process typology, material properties, and dimensional parameters of the unit cell. The bulk material is first characterized to evaluate the process stability. Three main failure modes of the lattice are identified, depending on the response of ductile/brittle material and the direction of crack propagation. The relationship between lattice geometrical parameters and mechanical strength is observed. The results of the modeling and experiments are suitable to validate the design of lightweight components built with AM processes. The structural performances related to geometrical features, material properties and technological constraints are well explained for further applications in structural design. The equivalent Young’s module of lattice samples with different cell size has been measured and compared with numerical simulations based on the homogenization method.

Structure and Mechanical Behavior of Additive Manufactured Fused Deposition Modeling ABS

One of the most important Additive Manufacturing (AM) technologies is the Fused Deposition Modeling (FDM) technology, suitable for various engineering applications which is currently used with many types of thermoplastic materials including ABS. AM-FDM printed ABS possesses an inherent capacity for property modifications as a function of printing parameters. The main goals of this study were to characterize experimentally the mechanical and structural properties of printed ABS specimens; as well as to reach an expression that will allow us to estimate the strength of the AM-FDM printed ABS for different printing parameters, prior to the printing process. In this experimental study, the mechanical and structural characterization of AM-FDM ABS material was performed by visual non-destructive testing inspection, mechanical testing, and light microscopy (LM) investigation. The three-point bend flexural test results revealed the mechanical properties as well as the fracture surface, according to build-on (coupon) specimens' dimensions and build-strategies. The results of this study provide preliminary quantitative estimates for the mechanical significant properties, as a function of some AM-FDM process variables for the ABS material. Parameter coefficients were defined to calculate the estimated strength of the printed ABS. They are chosen according to the desired printing parameters, and then multiplied by the highest average strength achieved for the X or Z direction bending tests specimens to achieve the estimated strength. The parameter coefficients were used to estimate the flexural strength of AM-FDM ABS specimens pertaining to a different RD a decent agreement between the experimental data and the calculated results was obtained.

Surveying the Energy Landscapes of Aβ Fibril Polymorphism.

Many unrelated proteins and peptides have been found spontaneously to form amyloid fibers above a critical concentration. Even for a single sequence, however, the amyloid fold is not a single well-defined structure. Although the cross-β hydrogen bonding pattern is common to all amyloids, all other aspects of amyloid fiber structures are sensitive to both the sequence of the aggregating peptides and the solvent conditions under which the aggregation occurs. Amyloid fibers are easy to identify and grossly characterize using microscopy, but their insolubility and aperiodicity along the dimensions transverse to the fiber axis have complicated detailed experimental structural characterization. In this paper, we explore the landscape of possibilities for amyloid protofilament structures that are made up of a single stack of peptides associated in a parallel in-register manner. We view this landscape as a two-dimensional version of the usual three-dimensional protein folding problem: the survey of the two-dimensional folds of protein ribbons. Adopting this view leads to a practical method of predicting stable protofilament structures of arbitrary sequences. We apply this scheme to variants of Aβ, the amyloid forming peptide that is characteristically associated with Alzheimer's disease. Consistent with what is known from experiment, we find that Aβ protofibrils are polymorphic. To our surprise, however, the ribbon-folding landscape of Aβ turned out to be strikingly simple. We confirm that, at the level of the monomeric protofilament, the landscape for the Aβ sequence is reasonably well funneled toward structures that are similar to those that have been determined by experiment. The landscape has more distinct minima than does a typical globular protein landscape but fewer and deeper minima than the landscape of a randomly shuffled sequence having the same overall composition. It is tempting to consider the possibility that the significant degree of funneling of Aβ's ribbon-folding landscape has arisen as a result of natural selection. More likely, however, the intermediate complexity of Aβ's ribbon-folding landscape has come from the post facto selection of the Aβ sequence as an object of study by researchers because only by having a landscape with some degree of funneling can ordered aggregation of such a peptide occur at in vivo concentrations. In addition to predicting polymorph structures, we show that predicted solubilities of polymorphs correlate with experiment and with their elongation free energies computed by coarse-grained molecular dynamics.

Focusing of Terahertz Radiation With Laser-Ablated Antireflective Structures

Numerical simulations and experimental characterization of laser-ablated focusing antireflective and phase-shifting structures for terahertz frequencies are presented. More than 10% shift of reflectance minimum to lower frequencies was predicted by simulations for relatively coarse structures with the period of 100 $\mu$ m in comparison with that of a substantially smaller period and with results of the model used for the design of antireflective surfaces in the terahertz range. Such a shift of the resonance frequency can be employed to optimize the thickness of antireflective layers simultaneously obtaining additional means of more precise control of layer properties due to ablation of larger structures. Nearly 90% transmittance of silicon wafers within 0.5–0.6 THz frequencies was confirmed experimentally. Optical path differences equivalent to a half period at 0.53 THz, suitable for applications in high-efficiency zone plates, were demonstrated with high transmittance simultaneously. Possibilities of delay adjustment up to one wavelength were illustrated by numerical simulations. A focusing binary zone plate for 0.6 THz was produced employing phase-shift differences of the dual-function antireflective layer. Its close to diffraction-limited focusing performance was evaluated, further confirming sufficient uniformity of the structured layer.

Controlling the Plasmonic Properties of Ultrathin TiN Films at the Atomic Level

By combining first-principles theoretical calculations and experimental optical and structural characterization such as spectroscopic ellipsometry, X-ray spectroscopy, and electron microscopy, we study the dielectric permittivity and plasmonic properties of ultrathin TiN films at an atomistic level. Our theoretical results indicate a remarkably persistent metallic character of ultrathin TiN films and a progressive red shift of the plasmon energy as the thickness of the film is reduced, which is consistent with previous experimental studies. The microscopic origin of this trend is interpreted in terms of the characteristic two-band electronic structure of the system. Surface oxidation and substrate strain are also investigated to explain the deviation of the optical properties from the ideal case. This paves the way to the realization of ultrathin TiN films with tailorable and tunable plasmonic properties in the visible range for applications in ultrathin metasurfaces and nonlinear optics.

Experimental Characterization of Circular Polarization Selective Structures Using Linearly Single-Polarized Antennas

We present a technique for performing high-accuracy measurements of the transmission and reflection properties in circular polarizations (CPs) of a test panel. Using linearly polarized antennas and measuring at four different antenna orientations, all with a relative rotation of 45°, an efficient normalization of each scattering component can be utilized. This method achieves a high signal-to-noise ratio in all normalized linear polarization components used to synthesize the CP scattering. Furthermore, a postprocessing scheme is introduced to compensate for measurement uncertainties due to antenna misalignments. The novel measurement and postprocessing techniques are utilized to characterize a manufactured wideband CP selective structure, both in transmission and reflection, and the measurement results are in excellent agreement with simulation results from commercial software. The repeatability of the measurement results is investigated, and the results are in the expected range in comparison with estimated measurement uncertainties.

The Least Stable Isomer of BN Naphthalene: Toward Predictive Trends for the Optoelectronic Properties of BN Acenes

The least stable isomer of the parental BN naphthalene series has been synthesized in a simple four-step sequence. Its experimental electronic structure characterization via UV-PES, cyclic voltammetry, and UV-vis spectroscopy in direct comparison with three other known BN naphthalene isomers has established two guiding principles for predicting the electronic structures of BN acene compounds: (1) Orientational BN isomers have similar HOMO-LUMO gaps. (2) For each pair of orientational BN isomers, the more thermodynamically stable compound has the lower HOMO energy. Furthermore, we demonstrate that BN/CC isosterism in the context of BN-9,1-Naph can impact crystal packing to favor a cofacial π-stack motif.

Experimental characterization of three-dimensional flow vortical structures in submerged hydraulic jumps

The characteristics of three-dimensional vortical flow structures in submerged hydraulic jumps (generated downstream of a sluice gate) are analyzed in this paper. Results of a careful experimental investigation of the mean flow as well as turbulence statistics obtained with the use of Acoustic Doppler Velocimetry (ADV) and Particle Tracking Velocimetry (PTV) are presented and discussed. Experiments encompass incident Froude numbers (Fr1) of 3, 4 and 5, and submergence factors (S) ranging from 0.18 to 1.04. First, distributions in three vertical planes of values of the stream-wise velocity component and turbulent kinetic energy (TKE) are shown. With this information, the influence of Fr1 and S on turbulence statistics is assessed. For the first time to the best of our knowledge, an approximately self-similar behavior of the profiles of TKE in the fully-developed region of the submerged jump is reported herein. A “climb effect” in the TKE is identified, very much in agreement with what occurs with the velocities. Then, the analysis focuses on the zone located near the gate, aiming at explaining the physical mechanisms which are responsible for the vorticity of vertical axis in that area. A relationship between the length scale of the roller of horizontal axis (Lrsj) and that of the vortices of vertical axis (Lv) is introduced, revealing that the dynamics of the two vortices are strongly linked. Compelling evidence sustaining that vorticity of vertical axis appears as a consequence of boundary-layer separation associated with the lateral walls is also provided. Finally, the anisotropy of turbulence in the outskirts of the vertical vortices is addressed, finding that such anisotropy is a consequence rather a cause of the presence of the vortices.