Manifestation of structural Higgs and Goldstone modes in the hexagonal manganites
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75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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Results for “Structural order parameter”
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Fouling behavior of zwitterionic membranes compared to polyamide membranes
Membrane fouling remains a critical bottleneck for reverse osmosis (RO) desalination, driving energy consumption and reducing membrane lifetime. Here, we employ all-atom molecular dynamics simulations to investigate the antifouling behavior of random zwitterionic amphiphilic copolymer (r-ZAC) membranes composed of sulfobetaine methacrylate (SBMA) and allyl methacrylate (AMA), benchmarked against conventional polyamide (PA) RO membranes. Structural and dynamical analyses—including radial distribution functions, coordination numbers, tetrahedral order parameters, vector orientation, and residence-time correlation functions—reveal that r-ZAC surfaces sustain tightly bound, long-lived hydration layers with preserved tetrahedrality and anisotropic water orientation, in sharp contrast to the weak and disordered hydration of PA. Steered molecular dynamics simulations demonstrate that r-ZAC membranes impose substantial free-energy barriers to foulant approach (alginate ≈ 90 kcal/mol, sucrose ≈ 35 kcal/mol, humic acid ≈ 15 kcal/mol), whereas PA membranes exhibit negligible barriers (< 1 kcal/mol) and thermodynamically favorable adsorption. Detailed foulant–surface interaction analyses show that zwitterionic hydration and electrostatic heterogeneity in r-ZAC suppress adhesion, except in the case of amphiphilic humic acid, which exploits multiple binding modes. Together, these results establish molecular-level design principles for antifouling membranes: the combination of zwitterionic hydration, structured interfacial water, and controlled amphiphilic balance in r-ZAC membranes provides superior resistance to organic fouling relative to PA.
Cross-linked polyamide↗
Bandgap analysis and carrier localization in cation-disordered ZnGeN 2
The bandgap of ZnGeN 2 changes with the degree of cation site disorder and is sought in light emitting diodes for emission at green to amber wavelengths. By combining the perspectives of carrier localization and defect states, we analyze the impact of different degrees of disorder on electronic properties in ZnGeN 2 , addressing a gap in current studies, which largely focus on dilute or fully disordered systems. The present study demonstrates changes in the density of states and localization of carriers in ZnGeN 2 calculated using bandgap-corrected density functional theory and hybrid calculations on partially disordered supercells generated using the Monte Carlo method. We use localization and density of states to discuss the ill-defined nature of a bandgap in a disordered material and identify site disorder and its impact on the structure as a mechanism controlling electronic properties and potential device performance. Decreasing the order parameter results in a large reduction of the bandgap. The reduction in bandgap is due, in part, to isolated, localized states that form above the valence band continuum associated with nitrogen coordinated by more zinc than germanium. The prevalence of defect states in all but the perfectly ordered structure creates challenges for incorporating disordered ZnGeN 2 into optical devices, but the localization associated with these defects provides insight into the mechanisms of electron/hole recombination in the material.
36 MATERIALS SCIENCE↗
Graph identification of proteins in tomograms ( GRIP‐Tomo )
Abstract In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three‐dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo‐multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single‐domain protein native topologies as well as distinct single‐domain proteins from multimeric complexes within noisy volumes.
59 BASIC BIOLOGICAL SCIENCES↗
State-space formulation of multi-shaker modal analysis
As modal testing techniques have improved in recent years, the demands placed on the accuracy of modal test results have increased. This paper describes a new multi-input, multi-output modal parameter estimation algorithm suitable for the identification of reduced-order models of structures. The method described is a frequency-domain method based on excitation and response spectra. The principal features of the algorithm are: (1) applicability to general linear, time-invariant systems, (2) direct use of multiple input and multiple response data, (3) identification of reduced-order models with minimum user interaction through the use of two automatic model-reduction techniques, (4) identification of a consistent set of modal parameters through the use of numerically stable least-squares techniques, and (5) complete user documentation.
Craig, Roy R., Jr.↗
Dynamic analysis of Space Shuttle/RMS configuration using continuum approach
The initial assembly of Space Station Freedom involves the Space Shuttle, its Remote Manipulation System (RMS) and the evolving Space Station Freedom. The dynamics of this coupled system involves both the structural and the control system dynamics of each of these components. The modeling and analysis of such an assembly is made even more formidable by kinematic and joint nonlinearities. The current practice of modeling such flexible structures is to use finite element modeling in which the mass and interior dynamics is ignored between thousands of nodes, for each major component. The model characteristics of only tens of modes are kept out of thousands which are calculated. The components are then connected by approximating the boundary conditions and inserting the control system dynamics. In this paper continuum models are used instead of finite element models because of the improved accuracy, reduced number of model parameters, the avoidance of model order reduction, and the ability to represent the structural and control system dynamics in the same system of equations. Dynamic analysis of linear versions of the model is performed and compared with finite element model results. Additionally, the transfer matrix to continuum modeling is presented.
Ramakrishnan, Jayant↗
A sequential linear optimization approach for controller design
A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.
Horta, L. G.↗
Magnetic and electronic structures of antiferromagnetic topological material candidate EuMg 2 Bi 2
In this work, EuMg 2 Bi 2 has been investigated to understand the electronic and magnetic behaviors as an antiferromagnetic (AFM) topological semimetal candidate. High-quality single crystals of EuMg 2 Bi 2 were grown via a Bi flux and, subsequently, characterized to be consistent with the previously reported bulk magnetic and resistivity properties. A ferromagnetic interaction is indicated by the positive Curie–Weiss temperature obtained through fitting the bulk magnetic susceptibility data. The bulk resistivity measurements reveal an interesting electronic behavior that is potentially influenced by a competing antiferromagnetic and ferromagnetic interaction in and out of the ab plane. From the resulting refinement of the neutron diffraction data, EuMg 2 Bi 2 was found to exhibit an A-type magnetic structure with Eu 2+ moments ferromagnetically aligned in the plane and antiferromagnetically stacked between neighbor ferromagnetic Eu layers. The power law fitting magnetic ordering parameter below TN~8 K agrees with the 2D Heisenberg model, indicating a weak interlayer antiferromagnetic interaction. Considering the magnetic structure determined by neutron diffraction, the surface state calculation suggests that EuMg 2 Bi 2 is an AFM topological insulator candidate. Linearly dispersed Dirac surface states were also observed in our angle-resolved photoemission spectroscopy measurements, consistent with the calculation.
36 MATERIALS SCIENCE↗
A crystallographic approach to the short-range ordering problem in V[subscript 1;#8722;x]Mo[subscript x]O[subscript 2] (0.50 ;#8804; x ;#8804; 0.60)
Abstract not provided
Davenport, Matthew A.↗
Multiband superconductivity in strongly hybridized 1 T ' - WTe 2 / NbSe 2 heterostructures
The interplay of topology and superconductivity has become a subject of intense research in condensed-matter physics for the pursuit of topologically nontrivial forms of superconducting pairing. An intrinsically normal-conducting material can inherit superconductivity via electrical contact to a parent superconductor via the proximity effect, usually understood as Andreev reflection at the interface between the distinct electronic structures of two separate conductors. However, at high interface transparency, strong coupling inevitably leads to changes in the band structure, locally, owing to hybridization of electronic states. Here, we investigate such strongly proximity-coupled heterostructures of monolayer $1T$' - $\mathrm{WTe_2}$ grown on NbSe 2 by van der Waals epitaxy. The superconducting local density of states, resolved in scanning tunneling spectroscopy down to 500 mK, reflects a hybrid electronic structure well described by a multiband framework based on the McMillan equations which captures the multiband superconductivity inherent to the NbSe 2 substrate and that is induced by proximity to $\mathrm{WTe_2}$ self-consistently. Our material-specific tight-binding model captures the hybridized heterostructure quantitatively and confirms that strong interlayer hopping gives rise to a semimetallic density of states in the two-dimensional $\mathrm{WTe_2}$ bulk, even for nominally band-insulating crystals. The model further accurately predicts the measured order parameter Δ ≅ 0.6 meV induced in the $\mathrm{WTe_2}$ monolayer bulk, stable beyond a 2 T magnetic field. So we believe that our detailed multiband analysis of the hybrid electronic structure provides a useful tool for sensitive spatial mapping of induced order parameters in proximitized atomically thin topological materials.
36 MATERIALS SCIENCE↗
A first-order Lyapunov robustness method for linear systems with uncertain parameters
A method for stability-robustness analysis based on a quadratic Liapunov function that varies linearly with uncertainty parameters is derived. Linear time-invariant systems with structured uncertainties are discussed. The Liapunov function is optimized numerically to maximize the robustness region in parameter space. Numerical results are given for four examples in which the first-order method is compared to previous Liapunov methods. While the zero-order method is slightly better than the first-order method for one example, the first-order method is clearly superior in the other three (more realistic) examples. The first-order method is especially superior for the active control of flexible structures, where robustness with respect to (1) unmodeled coupling between modeled modes and (2) unmodeled modes is important. For such applications, the first-order method is much better at detecting the increased robustness associated with increased separation between frequencies.
Leal, M. A.↗
Critical structural parameter determining magnetic phases in the Fe 2 Mo 3 O 8 altermagnet system
A systematic structural investigation of Fe 2 Mo 3 O 8 as a function of pressure, temperature, and magnetic field reveals that the 𝑃6 3 𝑚𝑐 space group remains robust over a wide range of conditions. No changes in the long-range crystal structure are observed for pressures up to 10 GPa, temperatures between 11 K and 300 K, and magnetic fields up to 9 T. The magnetostructural response, quantified by Δ𝑐/𝑐, is determined for magnetic fields applied transverse to the crystallographic 𝑐 axis, demonstrating strong magnetoelastic coupling. The well-known magnetic-field-induced transition is confirmed to be first order and isostructural, occurring between two distinct altermagnetic states. Importantly, this transition can also be accessed using magnetic fields applied within the 𝑎𝑏 plane. When expressed in terms of the 𝑐/𝑎 ratio, the structural evolution under pressure (0–10 GPa) maps continuously onto that observed across the full Zn substitution range in (Fe 1−𝑦 Zn 𝑦 )2 Mo 3 O 8 (0 ≤ 𝑦 ≤ 1), indicating a common underlying structural control parameter. Furthermore, these results demonstrate that the 𝑐-axis lattice parameter is the primary structural degree of freedom governing magnetic behavior under external tuning parameters. More broadly, they indicate that magnetic order in this family of complex oxides (𝐴 2 Mo 3 O 8 , 𝐴 = Co,Mn,Ni) can be systematically tuned via pressure. This tunability highlights these materials as promising platforms for controllable magnetic switching, particularly in thin films integrated with piezoelectric substrates.
36 MATERIALS SCIENCE↗
Superconducting properties of MoTe 2 from ab initio anisotropic Migdal-Eliashberg theory
Molybdenum ditelluride (MoTe 2 ) is attracting considerable interest since it is the archetypal type-II Weyl semimetal and a candidate for topological superconductivity. In this work, we investigate the superconducting phase diagram of two MoTe 2 polymorphs using the ab initio anisotropic Migdal-Eliashberg theory, and we show that the superconducting dome originates from the synergistic contribution of the density of states at the Fermi level and the transverse acoustic Te modes in the 1$\textit{T}’$ phase. We find that the electron and hole pockets carry trivial $\textit{s}$-wave order parameters of slightly different magnitude, reminiscent of a two-gap structure as suggested by recent experiments. We suggest that a possible route for enhancing the superconducting critical temperature, and realizing $s_{+ –}$ pairing, in the $T_d$ phase is to exploit its nontrivial band topology via electron doping.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Some experiences with the Eigensystem Realization Algorithm
The Eigensystem Realization Algorithm (ERA) is a multiinput/multioutput time-domain algorithm for minimum-order system realization and modal parameter identification. It has been used for structural dynamics data analysis at the Langley Research Center for several years. Some of the practical experiences encountered in these projects are discussed in this paper. Three examples are used: the Galileo spacecraft, the Solar Array Flight Experiment, and a laboratory space-truss model. Several techniques for assessing identification accuracy are illustrated.
Pappa, Richard S.↗
A physics-constrained neural network for multiphase flows
The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.
Mechanics↗
Modeling of the Site Preference in Ternary B2-Ordered Ni-Al-Fe Alloys
The underlying equilibrium structure, site substitution behavior, and lattice parameter of ternary Ni-Fe-Al alloys are determined via Monte Carlo-Metropolis computer simulations and analytical calculations using the BFS method for alloys for the energetics. As a result of the theoretical calculations presented, a simple approach based on the energetics of small atomic clusters is introduced to explain the observed site preference schemes.
Bozzolo, Guillermo H.↗
Robustness of quantum correlation in quantum energy teleportation
In this article, we explore a feedback-control protocol in different quantum field theories (QFTs) to study the quantum correlation in nonunitary evolution of quantum systems. Traditional studies on QFTs focus on quantum entanglement of pure states under the unitary evolution, however, we examine quantum correlation in mixed states using quantum energy teleportation (QET), which is an energy transfer protocol by utilizing ground state entanglement, and introduce quantum discord as a measure. QET involves a midcircuit measurement, which disrupts pure state entanglement. Despite this, our analysis demonstrates that quantum discord maintains the correlation throughout the QET process. We conducted numerical analyses with benchmark models including the Nambu-Jona-Lasinio (NJL) model, revealing that quantum discord consistently acts as an order parameter for phase transitions. The model is extended in a way that it has both the chiral chemical potential and the chemical potential, which are useful to study the phase structures mimicking the chiral imbalance between left- and right- quarks coupled to the chirality density operator. In all cases we studied, the quantum discord behaved as an order parameter of the phase transition. Published by the American Physical Society 2024
Ikeda, Kazuki (ORCID:0000000338212669)↗
Effects of model deficiencies on parameter estimation
Reliable structural dynamic models will be required as a basis for deriving the reduced-order plant models used in control systems for large space structures. Ground vibration testing and model verification will play an important role in the development of these models; however, fundamental differences between the space environment and earth environment, as well as variations in structural properties due to as-built conditions, will make on-orbit identification essential. The efficiency, and perhaps even the success, of on-orbit identification will depend on having a valid model of the structure. It is envisioned that the identification process will primarily involve parametric methods. Given a correct model, a variety of estimation algorithms may be used to estimate parameter values. This paper explores the effects of modeling errors and model deficiencies on parameter estimation by reviewing previous case histories. The effects depend at least to some extent on the estimation algorithm being used. Bayesian estimation was used in the case histories presented here. It is therefore conceivable that the behavior of an estimation algorithm might be useful in detecting and possibly even diagnosing deficiencies. In practice, the task is complicated by the presence of systematic errors in experimental procedures and data processing and in the use of the estimation procedures themselves.
Hasselman, T. K.↗