Unit Cell Edge Research Articles

A novel sandwich ELISA method for quantifying CHI3L1 in blood serum and cerebrospinal fluid multiple sclerosis patients using sustainable photo-irradiated zero-valence gold nanoparticles

The widespread occurrence of chronic demyelinating MS presents a significant challenge for ongoing research aimed at comprehending its progression, diagnosis, and treatment. In our research, we have devised a novel approach to quantify CHI3L1 (Chitinase-3-like protein 1), which has emerged as a valuable biomarker in MS because of its involvement in inflammation, tissue remodeling, and immune response—crucial factors in regulating damaged nerve cells and preventing their accumulation in the brain, utilizing sandwich ELISA technology. This innovative method primarily depends on gold nanoparticles synthesized through a novel process of photo-irradiation with ultraviolet light. The crystal structure and particle size of sustainable zero-valent gold nanoparticles were measured using X-ray diffraction (XRD), which proved the cubic shape, with a cubic unit cell edge length of 4.0095 Å. The transmission electron microscopy (TEM) and field emission scanning electron microscope (FE-SEM) demonstrated that the distribution of Au NPs is uniform, with an average diameter of 22 nm. The UV–Vis spectrum, displaying a pronounced absorbance peak at a wavelength of 548 nm, suggests the presence of Au NPs. The optimal conditions for the formation of the Au-biotinylated antibody-HRP complex were studied. The optimum pH was 7, the dilution ratio of AuNPs with biotinylated antibody-HRP was 1:3, and the concentration of nanogold was (1 × 10−3 mg/ml) to avoid increasing it. Then a standard curve was drawn for this method and compared to the traditional method, and it was found to be twice as sensitive as the traditional method, with a high accuracy of CV% (3–6 %) as well as a rapid color generation for measurement. This method, based on gold nanoparticles that are considered a carrier for biotinylated antibody-HRP, was applied for the first time to measure CHI3L1 in the sera and cerebrospinal fluid of patients with multiple sclerosis, and the results demonstrated the accuracy and sensitivity of the method. The method has the potential to be an excellent tool for evaluating CHI3L1 and may have applications in other diseases for rapid diagnosis and timely treatment.

Discreditation of Platarsite: A S-Rich Variety of Sperrylite

Abstract Platarsite is a relatively uncommon platinum-group mineral, reported from several world-wide localities, that has been defined as both Pt(As,S)2 and PtAsS in the literature. It was first described using material from the Onverwacht mine, eastern Bushveld Complex, Republic of South Africa, where it occurs with genkinite, geversite, and Pt-Fe alloy. Data from chemical analyses indicate (1) Pt is the dominant PGE, but with significant enrichments of both Rh and Ru; (2) ΣAs+S ∼ 2; (3) ΣPGE:ΣAs+S ∼ 1:2; and (4) As:S ratios of ∼1 (but with most data showing As > S), all of which suggest either PtAsS or Pt(As,S)2 as ideal compositions. Results from crystal-structure analyses conducted on both platarsite and sperrylite (Szymański 1979) demonstrate that the two are isostructural, both crystallizing in the cubic space group Pa3, with refined unit-cell edges of 5.788(1) and 5.9681(1) Å, respectively. They possess a pyrite-like crystal structure that includes a single metal site and a single anion site. The latter indicates that As and S, even if present in ratios of ∼1, must be disordered over a single site, rather than occupying two separate crystallographic sites. A re-evaluation of the available chemical data, along with the results from crystal-structure analyses, indicate that platarsite is a S-enriched variety of sperrylite and, as such, it has been discredited as a valid mineral species.

Physically informed deep homogenization neural network for unidirectional multiphase/multi-inclusion thermoconductive composites

Elements of the periodic homogenization framework and deep neural network were seamlessly connected for the first time to construct a new micromechanics theory for thermoconductive composites called physically informed Deep Homogenization Network (DHN). This method utilizes a two-scale expansion of the temperature field of spatially uniform composites in terms of macroscopic and fluctuating contributions. The latter is estimated using deep neural network layers. The DHN is trained on a set of collocation points to obtain the fluctuating temperature field over the unit cell domain by minimizing a cost function given in terms of residuals of strong form steady-state heat conduction governing differential equations. Novel use of a periodic layer with several independent periodic functions with adjustable training parameters ensures that periodic boundary conditions of temperature and temperature gradients at the unit cell edges are exactly satisfied. Automatic differentiation is utilized to correctly compute the fluctuating temperature gradients. Homogenized properties and local temperature and gradient distributions of unit cells reinforced by unidirectional fiber or weakened by a hole are compared with finite-element reference results, demonstrating remarkable correlation but without discontinuities associated with temperature gradient distributions in the finite-element simulations. We also illustrate that the DHN enhanced with transfer learning provides a substantially more efficient and accurate simulation of multiple random fiber distributions relative to training the network from scratch.

Deviation from the fcc structure in the vertically deposited opal layers

The discrepancy between the experimental and theoretical results of Bragg diffraction in vertically deposited opal layers occurred in the literature. They refer to diffraction extrema associated with planes other than parallel to the top surface. Analyzing the results of spectrogoniometric studies of the transmission coefficient the new “face-centered tetragonal” (“fct”) structure was proposed. Assuming that structure a satisfactory agreement of the theoretical and experimental dependencies was obtained. Based on the new structure, the diameter of nanospheres, filling factor, deformation coefficient, and thus the length of the opal unit cell edge were obtained for several samples.

Thermal-hydraulic performance of additively manufactured lattices for gas turbine blade trailing edge cooling

• Thermal-hydraulic performance of four lattice frame materials, namely, Octet, Tetrakaidecahedron, Face diagonal-cube, and Cube is studied for turbine edge cooling application. • Face diagonal-cube provided the highest heat transfer coefficient and pressure drop values amongst the investigated samples at similar porosity values and unit cell size. • Cube topology yielded the lowest flow losses and consequently highest thermal–hydraulic performance of ∼ 2.78 at the lowest investigated Reynolds number. Gas turbine blade trailing edge cooling is challenging because of the stringent geometrical constraints driven by aerodynamics and thermal stresses. The blade topology becomes significantly thin towards the trailing edge which leaves a narrow room for the construction of internal cooling channels and also makes this section susceptible to failure due to thermal stresses. Conventionally, pin-fins are employed in the internal cooling channels of the trailing edge because they provide high levels of heat transfer coefficient values and also structural integrity. Much of the past studies on pin fins have focused on their relative arrangements, heights, crossflow scheme, etc., with an aim to enhance the endwall heat transfer coefficient as well as leverage the conjugate heat dissipation capabilities of these “extended surfaces”. Lattices on the other hand, have been investigated to a lesser degree, and some studies can be found for blade mid-chord region, however, with their manufacturability challenges at that time, the concepts did not gain traction. Lattices are far more complex topologies with superior local heat transfer characteristics as well as high conjugate heat dissipation capabilities due to large wetted surface area. With the recent advancements in metal additive manufacturing, complex topologies such as lattices can be revisited due to high chances of their realization now. To this end, we are presenting our study on lattices additively manufactured in 420 Stainless Steel (thermal conductivity nearly twice of Inconel 718), where four different unit cell topologies, (a) Octet, (b) Tetrakaidecahedron, (c) Face diagonal-cube, and (d) Cube, were printed using Binder Jetting technology. The aim of this study is to characterize the conjugate heat transfer capabilities of these lattices manufactured in 420 Stainless Steel prior to conduct similar study with Inconel 718, due to relatively simpler additive manufacturing route of Binder jetting (420 stainless steel) compared to Direct Metal Laser Sintering (Inconel 718). The intended design porosity of the samples was 0.886 and the coupons had single unit cell (edge size of 10 mm) in the thickness. The steady-state experiments were conducted to evaluate the effective thermal conductivity and forced convective heat transfer performance. For forced convection, the experiments were conducted for a wide range of Reynolds numbers with air as the working fluid. Overall heat transfer coefficient, pressure drop, Nusselt number and friction factor enhancement level and pumping power requirements of these structures are presented. The implications of the porosity variation due to manufacturing process on the interpretation of relative performance trends is discussed. The effective thermal conductivity was independent of the topology for considered porosity value. Face diagonal-cube yielded the highest heat transfer and pressure drop for the investigated Reynolds number range. However, Cube provided the best overall thermal hydraulic performance value of 1.94 to 2.78 for the investigated range of Reynolds number. At fixed pumping power conditions, Cube was capable of providing the highest heat transfer coefficient.

Study on the Dynamic Performance of Locally Resonant Plates with Elastic Unit Cell Edges

A Floquet–Bloch approach is employed to demonstrate the stop bands for an infinite locally resonant plate. In addition, the effects of the connection stiffness of the unit cells on the band gap and dynamic performance of a locally resonant plate are analysed. The results show that the degree of inhibition of elastic waves in the band gaps increases rapidly when the connection stiffness of the unit cells increases within the scope of the transition stage stiffness. However, outside of the range of transition stage stiffness, the degree of inhibition of elastic waves in the band gaps basically remains unchanged. This discovery widens the application scope for vibration and noise control using locally resonant plates.

Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning.

Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials property prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average coefficient of determination (R2) of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due to the homogeneity of the structures. However, these models trained with small data sets are usually not applicable to generic lattice parameter prediction of materials with diverse compositions. Herein, we report MLatticeABC, a random forest machine learning model with a new descriptor set for lattice unit cell edge length (a, b, c) prediction which achieves an R2 score of 0.973 for lattice parameter a of cubic crystals with an average R2 score of 0.80 for a prediction of all crystal systems. The R2 scores are between 0.498 and 0.757 over lattice b and c prediction performance of the model, which could be used by just inputting the molecular formula of the crystal material to get the lattice constants. Our results also show significant performance improvement for lattice angle predictions. Source code and trained models can be freely accessed at https://github.com/usccolumbia/MLatticeABC.

Liquid Organic Frameworks: The Single-Network "Plumber's Nightmare" Bicontinuous Cubic Liquid Crystal.

Novel bolapolyphiles, built of a p-terphenyl or bistolane core with polar glycerol end-groups and two laterally attached n-alkyl or semiperfluoroalkyl chains, form the first "single plumber's nightmare network", the simplest soft-matter cubic phase (Pm3̅m). Its cage-like grid comprises bundles of aromatic rods lying along the cubic unit cell edges, connected by six-way hydrogen-bonded junctions. Side-chains fill the remaining volume of this unique noninterpenetrating liquid-crystalline organic framework.

IMAGINE: The neutron protein crystallography beamline at the high flux isotope reactor.

IMAGINE is a high intensity, quasi-Laue neutron crystallography beamline developed at the 85MW High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). This state-of-the-art facility for neutron-diffraction enables neutron protein structures to be determined at or near atomic resolutions from crystals with volumes of <1mm3 and unit cell edges of <150Å. The beamline features include elliptical focusing mirrors that deliver neutrons into a 2.0×3.2mm2 focal spot at the sample position, and variable short and long wavelength cutoff optics that provide automated exchange between multiple wavelength configurations. The beamline is equipped with a single-axis goniometer, neutron-sensitive cylindrical image plate detector and room temperature and cryogenic sample environments. This article describes the beamline components, the diffractometer and the data collection and data analysis protocols that are used, and outlines the protein deuteration, crystallization and conventional crystallography capabilities that are available to users at ORNL's neutron facilities. We also present examples of the scientific questions being addressed at this beamline and highlight important findings in enzyme chemistry that have been made possible by IMAGINE.

Computation of Thickness and Mechanical Properties of Interconnected Structures: Accuracy, Deviations, and Approaches for Correction

Identifying local thickness information of fibrous or highly porous structures is challenging. The analysis of tomography data calls for computationally fast, robust and accurate algorithms. This work systematically investigates systematic errors in the thickness computation and the impact of observed deviations on the predicted mechanical properties using a set of 16 model structures with varying ligament shape and solid fraction. Strongly concave, cylindrical, and convex shaped ligaments organized in a diamond structure are analyzed. The predicted macroscopic mechanical properties represent a highly sensitive measure for systematic errors in the computed geometry. Therefore, the quality of proposed correction methods is assessed via FEM beam models that can be automatically generated from the measured data and allow an efficient prediction of the mechanical properties. The results show that low voxel resolutions can lead to an overprediction of up to 30% in the Young’s modulus. A model scanned with a resolution of 200 voxels per unit cell edge (8M voxels) reaches an accuracy of a few percent. Analyzing models of this resolution with the Euclidean distance transformation showed an underprediction of up to 20% for highly concave shapes whereas cylindrical and slightly convex shapes are determined at high accuracy. For the Thickness algorithm, the Young’s modulus and yield strength are overpredicted by up to 100% for highly concave ligament shapes. A proposed Smallest Ellipse approach corrects the Thickness data and reduces this error to 20%. It can be used as input for a further robust correction of the Thickness data using an artificial neural network. This approach is highly accurate with remnant errors in the predicted mechanical properties of only a few percent. Furthermore, the data from the FEM beam models are compared to results from FEM solid models providing deeper insights towards further developments on nodal corrections for FEM beam models. As expected, the FEM beam models show an increasing overprediction of the compliance with increasing solid fraction. As an unexpected result, the mechanical strength can however be underpredicted or overpredicted, depending on the ligament shape. Therefore, a nodal correction is needed that solves contradicting tasks in terms of stiffness and strength.

Valleyite: A new magnetic mineral with the sodalite-type structure

Abstract Valleyite, Ca4(Fe,Al)6O13, is a new sodalite-type mineral discovered in late Pleistocene basaltic scoria from the Menan Volcanic Complex near Rexburg, Idaho, U.S.A. It is an oxidation product of basaltic glass during the early stage of the scoria formation and is associated with hematite (α-Fe2O3), maghemite (γ-Fe2O3), luogufengite (ε-Fe2O3), and quartz on the surface of vesicles. The measured crystal size of valleyite ranges from ~250 to ~500 nm. The empirical chemical formula of valleyite is (Ca3.61Mg0.39)(Fe3.97Al1.91Ti0.09)O13. The mineral has a space group of I43m. The (Fe,Al)-O bond distance and unit-cell edge are slightly larger than those reported for synthetic Ca4Al6O13, presumably due to the presence of the larger Fe3+ cations, compared with Al3+, in the structure. Density functional theory calculations predict that valleyite may be a metastable phase at low temperatures. Measured Curie temperatures for valleyite and luogufengite are 645 and 519 K, respectively. Their magnetization hysteresis loop indicates the magnetic exchange coupling between valleyite (soft magnet) and luogufengite (hard magnet) that aids in the understanding of magnetic properties and paleo-magnetism of basaltic rocks. This new mineral, valleyite, with the sodalite-type cage structure is potentially a functional magnetic material.

Membrane- and plate-type acoustic metamaterials with elastic unit cell edges

Membrane- and plate-type acoustic metamaterials are thin membranes or plates consisting of periodic unit cells with small added masses. It has been shown in numerous studies, that these metamaterials exhibit tunable anti-resonances with transmission loss values much higher than the corresponding mass-law. However, in most studies it is assumed that the unit cell edges (or grid) of the metamaterial are fixed. This idealised boundary condition is not applicable to real world applications in noise control. Therefore, the acoustic performance of these metamaterials under more realistic circumstances, where the grid structure cannot be perfectly rigid, can be expected to be different. In this contribution, the vibro-acoustic behavior of membrane- and plate-type acoustic metamaterials with a non-rigid grid is investigated. For this purpose, an efficient analytical model is developed to predict the eigenmodes and sound transmission loss of such metamaterials. In this model, elastic unit cell edges are modelled using a grid of Euler-Bernoulli beams and the sound transmission loss can be calculated for oblique incidence. A comparison to FEM simulations shows that the proposed model yields the same results but with a considerably reduced computational effort. The analytical model is then used to discuss the vibro-acoustic properties of the metamaterial, with particular focus on the influence of the mass and stiffness of the grid beams. It is shown that even when a non-rigid grid and diffuse incident sound fields are considered, the transmission loss of the metamaterial exhibits anti-resonances with remarkably high noise reduction values. These anti-resonances can be tuned by choosing appropriate values of the grid parameters. Furthermore, the formation of band gaps in the propagation of bending waves is discussed by investigating the dispersion curves of the metamaterial. The results in this contribution show that membrane- and plate-type acoustic metamaterials can still efficiently reduce low-frequency noise, even when the unit cell edges are not assumed to be fixed. This important finding and the proposed analytical modal can support the utilization of these metamaterials in practical noise control applications.

Interrogation of spline surfaces with application to isogeometric design and analysis of lattice-skin structures

A novel surface interrogation technique is proposed to compute the intersection of curves with spline surfaces in isogeometric analysis. The intersection points are determined in one-shot without resorting to a Newton–Raphson iteration or successive refinement. Surface-curve intersection is required in a wide range of applications, including contact, immersed boundary methods and lattice-skin structures, and requires usually the solution of a system of nonlinear equations. It is assumed that the surface is given in form of a spline, such as a NURBS, T-spline or Catmull–Clark subdivision surface, and is convertible into a collection of Bézier patches. First, a hierarchical bounding volume tree is used to efficiently identify the Bézier patches with a convex-hull intersecting the convex-hull of a given curve segment. For ease of implementation convex-hulls are approximated with k-dops (discrete orientation polytopes). Subsequently, the intersections of the identified Bézier patches with the curve segment are determined with a matrix-based implicit representation leading to the computation of a sequence of small singular value decompositions (SVDs). As an application of the developed interrogation technique the isogeometric design and analysis of lattice-skin structures is investigated. Although such structures have been common in large-scale civil engineering, current additive manufacturing, or 3d printing, technologies make it possible to produce up to metre size lattice-skin structures with designed geometric features reaching down to submillimetre scale. The skin is a spline surface that is usually created in a computer-aided design (CAD) system and the periodic lattice to be fitted consists of unit cells, each containing a small number of struts. The lattice-skin structure is generated by projecting selected lattice nodes onto the surface after determining the intersection of unit cell edges with the surface. For mechanical analysis, the skin is modelled as a Kirchhoff–Love thin-shell and the lattice as a pin-jointed truss. The two types of structures are coupled with a standard Lagrange multiplier approach.

The Neutron Macromolecular Crystallography Instruments at Oak Ridge National Laboratory: Advances, Challenges, and Opportunities

The IMAGINE and MaNDi instruments, located at Oak Ridge National Laboratory High Flux Isotope Reactor and Spallation Neutron Source, respectively, are powerful tools for determining the positions of hydrogen atoms in biological macromolecules and their ligands, orienting water molecules, and for differentiating chemical states in macromolecular structures. The possibility to model hydrogen and deuterium atoms in neutron structures arises from the strong interaction of neutrons with the nuclei of these isotopes. Positions can be unambiguously assigned from diffraction studies at the 1.5–2.5 Å resolutions, which are typical for protein crystals. Neutrons have the additional benefit for structural biology of not inducing radiation damage to protein crystals, which can be critical in the study of metalloproteins. Here we review the specifications of the IMAGINE and MaNDi beamlines and illustrate their complementarity. IMAGINE is suitable for crystals with unit cell edges up to 150 Å using a quasi-Laue technique, whereas MaNDi provides neutron crystallography resources for large unit cell samples with unit cell edges up to 300 Å using the time of flight (TOF) Laue technique. The microbial culture and crystal growth facilities which support the IMAGINE and MaNDi user programs are also described.

IMAGINE: neutrons reveal enzyme chemistry.

Neutron diffraction is exquisitely sensitive to the positions of H atoms in protein crystal structures. IMAGINE is a high-intensity, quasi-Laue neutron crystallography beamline developed at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. This state-of-the-art facility for neutron diffraction has enabled detailed structural analysis of macromolecules. IMAGINE is especially suited to resolve individual H atoms in protein structures, enabling neutron protein structures to be determined at or near atomic resolutions from crystals with volumes of less than 1 mm3 and unit-cell edges of less than 150 Å. Beamline features include elliptical focusing mirrors that deliver neutrons into a 2.0 × 3.2 mm focal spot at the sample position, and variable short- and long-wavelength cutoff optics that provide automated exchange between multiple wavelength configurations. This review gives an overview of the IMAGINE beamline at the HFIR, presents examples of the scientific questions being addressed at this beamline, and highlights important findings in enzyme chemistry that have been made using the neutron diffraction capabilities offered by IMAGINE.

Neutron macromolecular crystallography.

Neutron diffraction techniques permit direct determination of the hydrogen (H) and deuterium (D) positions in crystal structures of biological macromolecules at resolutions of ∼1.5 and 2.5 Å, respectively. In addition, neutron diffraction data can be collected from a single crystal at room temperature without radiation damage issues. By locating the positions of H/D-atoms, protonation states and water molecule orientations can be determined, leading to a more complete understanding of many biological processes and drug-binding. In the last ca. 5 years, new beamlines have come online at reactor neutron sources, such as BIODIFF at Heinz Maier-Leibnitz Zentrum and IMAGINE at Oak Ridge National Laboratory (ORNL), and at spallation neutron sources, such as MaNDi at ORNL and iBIX at the Japan Proton Accelerator Research Complex. In addition, significant improvements have been made to existing beamlines, such as LADI-III at the Institut Laue-Langevin. The new and improved instrumentations are allowing sub-mm3 crystals to be regularly used for data collection and permitting the study of larger systems (unit-cell edges >100 Å). Owing to this increase in capacity and capability, many more studies have been performed and for a wider range of macromolecules, including enzymes, signalling proteins, transport proteins, sugar-binding proteins, fluorescent proteins, hormones and oligonucleotides; of the 126 structures deposited in the Protein Data Bank, more than half have been released since 2013 (65/126, 52%). Although the overall number is still relatively small, there are a growing number of examples for which neutron macromolecular crystallography has provided the answers to questions that otherwise remained elusive.

Formation and characterization of ternary (Na, NH4, H3O)-jarosites produced from Acidithiobacillus ferrooxidans cultures

The purpose of this study was to characterize a series of (Na, NH4, H3O)-jarosites produced with various combinations of NH4+ + Na+ in cultures of Acidithiobacillus ferrooxidans that simulated acid solutions from bioleaching systems. The solution concentrations utilized were 6.1, 80, 160 and 320 mM for NH4+ and 0, 50, 100, 250 and 500 mM for Na+ as their respective sulfates. Media at pH 2.2 were inoculated with iron-oxidizing A. ferrooxidans and incubated in shake flasks at 22 ± 2 °C. As the bacteria oxidized ferrous sulfate, ferric iron hydrolyzed and precipitated as schwertmannite (idealized formula Fe8O8(OH)6(SO4).nH2O) and/or as solid solution jarosites [(Na, NH4, H3O)-Fe3(SO4)2(OH)6)] depending on the relative and absolute concentrations of NH4+ and Na+. The precipitates were characterized by elemental analysis, X-ray diffraction, specific surface area, and Munsell color. Schwertmannite was the dominant mineral product at low combinations of Na+ (≤50 mM) and NH4+ (≤80 mM) in the media after 2 weeks of aging. At higher single or combined concentrations and with aging for 6 and 11 weeks, the formation of yellowish, solid solution jarosites was enhanced. Precipitation of jarosite-group minerals was favored by NH4+ relative to Na+. Color (Munsell hue) was a useful tool for assessing sample mineralogy after extended aging, but the presence of abundant, poorly crystalline schwertmannite tended to mask the color of admixed jarosite-group minerals after only 2 weeks of contact with the culture media. The purest samples of jarosite-type minerals had specific surface areas <1.0 m2/g. Unit cell edge lengths and cell volume calculations from powder XRD data indicated that the jarositic phases produced were ternary (Na, NH4, H3O)-solid solutions. Most products also appeared to be deficient in structural Fe, especially at low NH4 contents. Thus, ferric iron precipitation from the simulated bioleaching systems yielded solid solutions of jarosites with chemical compositions that were dependent on the relative concentrations of Na+ and NH4+ in the synthesis media. No phase separations involving discrete, end-member Na-, NH4-, or H3O-jarosites were detected.

An efficient analytical model for baffled, multi-celled membrane-type acoustic metamaterial panels

A new analytical model for the oblique incidence sound transmission loss prediction of baffled panels with multiple subwavelength sized membrane-type acoustic metamaterial (MAM) unit cells is proposed. The model employs a novel approach via the concept of the effective surface mass density and approximates the unit cell vibrations in the form of piston-like displacements. This yields a coupled system of linear equations that can be solved efficiently using well-known solution procedures. A comparison with results from finite element model simulations for both normal and diffuse field incidence shows that the analytical model delivers accurate results as long as the edge length of the MAM unit cells is smaller than half the acoustic wavelength. The computation times for the analytical calculations are 100 times smaller than for the numerical simulations. In addition to that, the effect of flexible MAM unit cell edges compared to the fixed edges assumed in the analytical model is studied numerically. It is shown that the compliance of the edges has only a small impact on the transmission loss of the panel, except at very low frequencies in the stiffness-controlled regime. The proposed analytical model is applied to investigate the effect of variations of the membrane prestress, added mass, and mass eccentricity on the diffuse transmission loss of a MAM panel with 120 unit cells. Unlike most previous investigations of MAMs, these results provide a better understanding of the acoustic performance of MAMs under more realistic conditions. For example, it is shown that by varying these parameters deliberately in a checkerboard pattern, a new anti-resonance with large transmission loss values can be introduced. A random variation of these parameters, on the other hand, is shown to have only little influence on the diffuse transmission loss, as long as the standard deviation is not too large. For very large random variations, it is shown that the peak transmission loss value can be greatly diminished.

A microlattice material with negative or zero thermal expansion

Abstract This work presents a microlattice composite structure with a cubic unit cell that consists of twelve quarter-octahedra and describes an investigation of thermal expansion behavior of the proposed lattice material. It is assumed that all edge members of the octahedron have the same material properties and the members connecting the opposite vertices of the octahedron have different properties. Thermal expansions along the unit cell edge directions are determined by means of thermoelasticity. It is shown that the lattice material may undergo negative or zero thermal expansion with proper selection of the material and geometric properties of the microlattice members.

Preliminary neutron diffraction analysis of challenging human manganese superoxide dismutase crystals.

Superoxide dismutases (SODs) are enzymes that protect against oxidative stress by dismutation of superoxide into oxygen and hydrogen peroxide through cyclic reduction and oxidation of the active-site metal. The complete enzymatic mechanisms of SODs are unknown since data on the positions of hydrogen are limited. Here, methods are presented for large crystal growth and neutron data collection of human manganese SOD (MnSOD) using perdeuteration and the MaNDi beamline at Oak Ridge National Laboratory. The crystal from which the human MnSOD data set was obtained is the crystal with the largest unit-cell edge (240 Å) from which data have been collected via neutron diffraction to sufficient resolution (2.30 Å) where hydrogen positions can be observed.