Strong Relaxation Research Articles

A Hybrid Perovskite-Based Electromagnetic Wave Absorber with Enhanced Conduction Loss and Interfacial Polarization through Carbon Sphere Embedding.

Electronic equipment brings great convenience to daily life but also causes a lot of electromagnetic radiation pollution. Therefore, there is an urgent demand for electromagnetic wave-absorbing materials with a low thickness, wide bandwidth, and strong absorption. This work obtained a high-performance electromagnetic wave absorption system by adding conductive carbon spheres (CSs) to the CH3NH3PbI3 (MAPbI3) absorber. In this system, MAPbI3, with strong dipole and relaxation polarization, acts dominant to the wave absorber. The carbon spheres provide a free electron transport channel between MAPbI3 lattices and constructs interfacial polarization loss in MAPbI3/CS. By regulating the content of CSs, we speculate that this increased effective absorption bandwidth and reflection loss intensity are attributed to the conductive channel of the carbon sphere and the interfacial polarization. As a result, when the mass ratio of the carbon sphere is 7.7%, the reflection loss intensity of MAPbI3/CS reaches -54 dB at 12 GHz, the corresponding effective absorption bandwidth is 4 GHz (10.24-14.24 GHz), and the absorber thickness is 2.96 mm. This work proves that enhancing conduction loss and interfacial polarization loss is an effective strategy for regulating the properties of dielectric loss-type absorbing materials. It also indicates that organic-inorganic hybrid perovskites have great potential in the field of electromagnetic wave absorption.

New Insights in Luminescence and Quenching Mechanisms of Ag2S Nanocrystals through Temperature-Dependent Spectroscopy.

Bright near-infrared-emitting Ag2S nanocrystals (NCs) are used for in vivo temperature sensing relying on a reversible variation in intensity and photoluminescence lifetime within the physiological temperature range. Here, to gain insights into the luminescence and quenching mechanisms, we investigated the temperature-dependent luminescence of Ag2S NCs from 300 to 10 K. Interestingly, both emission and lifetime measurements reveal similar and strong thermal quenching from 200 to 300 K, indicating an intrinsic quenching process that limits the photoluminescence quantum yield at room temperature, even for perfectly passivated NCs. The low thermal quenching temperature, broadband emission, and multiexponential microsecond decay behavior suggest the optical transition involves strong lattice relaxation, which is consistent with the recombination of a Ag+-trapped hole with a delocalized conduction band electron. Our findings offer valuable insights for understanding the optical properties of Ag2S NCs and the thermal quenching mechanism underlying their temperature-sensing capabilities.

Strong Optimal Classification Trees

Decision trees are among the most interpretable and popular machine learning models that are used routinely in applications ranging from revenue management to medicine. Traditional heuristic methods, although fast, lack modeling flexibility for incorporating constraints such as fairness and do not guarantee optimality. Recent efforts aim to overcome these limitations using mixed-integer optimization (MIO) for better modeling flexibility and optimality, but speed remains an issue. In “Strong Optimal Classification Trees,” Aghaei, Gómez, and Vayanos use integer optimization and polyhedral theory to create an MIO-based formulation with a strong LO relaxation resulting in a 29% speed-up in training time compared with state-of-the-art MIO-based formulations, as well as up to an 8% improvement in out-of-sample accuracy.

A Branch-and-Cut-and-Price Algorithm for Cutting Stock and Related Problems

In this project, we introduce a branch-and-cut-and-price framework to solve the Cutting Stock Problems with strong relaxations using the Set Covering (Packing) Formulations, which are solved through column generation. We propose an extended Ryan-Foster branching scheme tailored to non-binary models, a pricing algorithm that produces convergence in a few iterations, and a variable selection technique based on branching history. These strategies are combined with subset-row cuts and custom primal heuristics to create a framework that overcomes the current state-of-the-art of Cutting Stock Problem, Skiving Stock Problem, and other related problems, being at least twice faster in the first problem and at least 60% faster in the second one.

Hydrodynamics for Asymmetric Simple Exclusion on a Finite Segment with Glauber-Type Source

We consider an open interacting particle system on a finite lattice. The particles perform asymmetric simple exclusion and are randomly created or destroyed at all sites, with rates that grow rapidly near the boundaries. We study the hydrodynamic limit for the particle density at the hyperbolic space-time scale and obtain the entropy solution to a boundary-driven quasilinear conservation law with a source term. Different from the usual boundary conditions introduced in Bardos et al (Commun Partial Differ Equ 4(9):1017–1034, https://doi.org/10.1080/03605307908820117, 1979) and Otto (C R Acad Sci Paris 322(1):729–734, 1996), discontinuity (boundary layer) does not formulate at the boundaries due to the strong relaxation scheme.

The Effect of Ájuga Turkestánica on the Rat Aortic Smooth Muscle Ion Channels

According to the literature, Ájuga turkestánica extract has an effective impact on diseases of the cardiovascular system. Aortic smooth muscle ion transport systems play an important role in the development of these diseases1. This study investigated the effects of Ájuga turkestánica extract on ion transport systems in rat aortic smooth muscle preparations under isometric conditions in vitro, and it was found that this extract exerts a strong dose-dependent relaxant effect on the contraction induced by KCl (50 mM) From the obtained results, the effect of this extract on potential-dependent Ca2+ channels was estimated, and in order to confirm the assumption, it was compared with verapamil, a specific blocker of this channel, and the effect of Ájuga turkestánica extract on potential-dependent Ca2+ channels was determined. In the course of the studies, it was assumed that the investigated extract affects not only the potential-dependent Ca2+ channels, but also the receptor-dependent Ca2+ channels, the Ca2+ transport system in the sarcoplasmic reticulum, and the endothelium-dependent relaxation mechanisms. According to the results of the study, it was found that Ájuga turkestánica extract has an effective effect on these ion transport systems (the results obtained are described in detail in the article below).

Sparse dynamic discretization discovery via arc-dependent time discretizations

While many time-dependent network design problems can be formulated as time-indexed formulations with strong relaxations, the size of these formulations depends on the discretization of the time horizon and can become prohibitively large. The recently-developed dynamic discretization discovery (DDD) method allows many time-dependent problems to become more tractable by iteratively solving instances of the problem on smaller networks where each node has its own discrete set of departure times. However, in the current implementation of DDD, all arcs departing a common node share the same set of departure times. This causes DDD to be ineffective for solving problems where all near-optimal solutions require many distinct departure times at the majority of the high-degree nodes in the network. Region-based networks are one such structure that often leads to many high-degree nodes, and their increasing popularity underscores the importance of tailoring solution methods for these networks.To improve methods for solving problems that require many departure times at nodes, we develop a DDD framework where the set of departure times is determined on the arc level rather than the node level. We apply this arc-based DDD method to a temporal variant of the service network design problem (SND). We show that an arc-based approach is particularly advantageous when instances arise from region-based networks, and when candidate paths are fixed in the base graph for each commodity. Moreover, our algorithm builds upon the existing DDD framework and achieves these improvements with only benign modifications to the original implementation.

A Strong Combinatorial Relaxation for the Problem of Min-Time Coverage in Constricted Environments

A Strong Combinatorial Relaxation for the Problem of Min-Time Coverage in Constricted Environments

Dislocations in twistronic heterostructures

Long-period moiré superlattices at the twisted interface of van der Waals heterostructures relax into preferential stacking domains separated by dislocation networks. Here, we develop a mesoscale theory for dislocations in networks formed in twistronic bilayers with parallel (P) and antiparallel (AP) alignment of unit cells across the twisted interface. For P bilayers we find an exact analytical displacement field across partial dislocations and determine analytic dependences of energy per unit length and width on the orientation and microscopic model parameters. For AP bilayers we formulate a semi-analytical approximation for displacement fields across perfect dislocations, establishing parametric dependences for their widths and energies per unit length. In addition, we find regions in the parametric space of crystal thicknesses and Moiré periods for strong and weak relaxation of the Moiré pattern in multilayered twistronic heterostructures.

Frontiers in Operations: Equitable Data-Driven Facility Location and Resource Allocation to Fight the Opioid Epidemic

Problem definition: The opioid epidemic is a crisis that has plagued the United States for decades. One central issue of the epidemic is inequitable access to treatment for opioid use disorder (OUD), which puts certain populations at a higher risk of opioid overdose. Methodology/results: We integrate a predictive dynamical model and a prescriptive optimization problem to compute high-quality opioid treatment facility and treatment budget allocations for each U.S. state. Our predictive model is a differential equation-based epidemiological model that captures the dynamics of the opioid epidemic. We use a process inspired by neural ordinary differential equations to fit this model to opioid epidemic data for each state and obtain estimates for unknown parameters in the model. We then incorporate this epidemiological model into a corresponding mixed-integer optimization problem (MIP) that aims to minimize the number of opioid overdose deaths and the number of people with OUD. We develop strong relaxations based on McCormick envelopes to efficiently compute approximate solutions to our MIPs that have a mean optimality gap of 3.99%. Our method provides socioeconomically equitable solutions, as it incentivizes investments in areas with higher social vulnerability (from the U.S. Centers for Disease Control’s Social Vulnerability Index) and opioid prescribing rates. On average, when allowing for overbudget solutions, our approach decreases the number of people with OUD by [Formula: see text], increases the number of people in treatment by [Formula: see text], and decreases the number of opioid-related deaths by [Formula: see text] after 2 years compared with the baseline epidemiological model’s predictions. Managerial implications: Our solutions show that policymakers should target adding treatment facilities to counties that have significantly fewer facilities than their population share and are more socially vulnerable. Furthermore, we demonstrate that our optimization approach, guided by epidemiological and socioeconomic factors, should help inform these strategic decisions, as it yields population health benefits in comparison with benchmarks based solely on population and social vulnerability. History: This paper has been accepted in the Manufacturing & Service Operations Management Frontiers in Operations Initiative. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0042 .

Interface Engineering of Titanium Nitride Nanotube Composites for Excellent Microwave Absorption at Elevated Temperature

HighlightsThe boosted heterogeneous interfaces in titanium nitride (TiN) nanotube/polydimethylsiloxane (PDMS) composite contributed to strong polarization loss relaxation ability.The TiN nanotubes/PDMS composite possessed both good impedance matching behavior and strong dielectric loss ability in wide temperature spectrum.The TiN nanotubes/PDMS composite exhibited excellent EMWA performances (effective absorption bandwidth value of 3.23 GHz and minimum reflection loss value of − 44.15 dB) at the varied temperature from 298 to 573 K.

Finding triangle‐free 2‐factors in general graphs

AbstractA 2‐factor in a graph is a subset of edges such that every node of is incident with exactly two edges of . Many results are known concerning 2‐factors including a polynomial‐time algorithm for finding 2‐factors and a characterization of those graphs that have a 2‐factor. The problem of finding a 2‐factor in a graph is a relaxation of the NP‐hard problem of finding a Hamilton cycle. A stronger relaxation is the problem of finding a triangle‐free 2‐factor, that is, a 2‐factor whose edges induce no cycle of length 3. In this paper, we present a polynomial‐time algorithm for the problem of finding a triangle‐free 2‐factor as well as a characterization of the graphs that have such a 2‐factor and related min–max and augmenting path theorems.

Numerical Analysis of Residual Stresses Effect in Multi-materials

Background: In this study, the effect of mechanical and physical properties of the metal and temperature is highlighted. The purpose of this study is to analyze the effect of these stresses on multi-materials. This work aimed to conduct a three-dimensional numerical study by the finite element method on the levels and distributions of the stresses in the Al2O3/NI/HAYNES multi-materials. These stresses of thermal and mechanical origin are generally detrimental to the service life of multi-material. Methods: The use of numerical resolution by finite element method is the most suitable for complex mechanical problems. It allows a more in-depth analysis of all points of the structure. In this study, a fundamental tool was constructed to resolve the mechanical behavior of materials subjected to complex solicitations. Therefore, the ABAQUS calculation code version 6.14 was used to analyze the residual stresses. Results: By interpreting the results in terms of stress variation, we identified the areas at risk; in particular, the nature of a joint effect plays a decisive role in the assembly of the right material in its mechanical resistance. This nature is defined in terms of stiffness (Young's modulus) and differential expansion (coefficient of thermal expansion). Conclusion: The presence of strong residual stresses can constitute a risk of damage to several materials. The difference between the coefficients of thermal expansion of the two materials (metal and ceramic) linked together induces, in these two constituents, normal internal stresses. This difference determines the level and distribution of these constraints. Moreover, the sign of this difference determines the state of the normal stresses.

Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR

We use hindcasts from a state-of-the-art decadal climate prediction system initialized between 1979 and 2017 to explore the predictability of the Antarctic dipole—that is, the seesaw between sea ice cover in the Weddell and Ross Seas, and discuss its implications for Antarctic sea ice predictability. Our results indicate low forecast skills for the Antarctic dipole in the first hindcast year, with a strong relaxation of March values toward the climatology contrasting with an overestimation of anomalies in September, which we interpret as being linked to a predominance of local drift processes over initialized large-scale dynamics. Forecast skills for the Antarctic dipole and total Antarctic sea ice extent are uncorrelated. Limited predictability of the Antarctic dipole is also found under preconditioning around strong warm and strong cold events of the El Niño-Southern Oscillation. Initialization timing and model drift are reported as potential explanations for the poor predictive skills identified.

Multisignal Biosensors Based on Mn Paramagnetic Relaxation and Nanocatalysis for Norovirus Detection.

A multisignal method for the sensitive detection of norovirus based on Mn paramagnetic relaxation and nanocatalysis was developed. This dual-modality sensing platform was based on the strong relaxation generated by cracked Au@MnO2 nanoparticles (NPs) and their intrinsic enzyme-like activity. Ascorbic acid rapidly cracked the MnO2 layer of Au@MnO2 NPs to release Mn(II), resulting in the relaxation modality being in a "switch-on" state. Under the optimal conditions, the relaxation modality exhibited a wide working range (6.02 × 103-3.01 × 107 copies/μL) and a limit of detection (LOD) of 2.29 × 103 copies/μL. Using 4,4',4″,4″'-(porphine-5,10,15,20-tetrayl) tetrakis (benzenesulfonic acid) (tpps)-β-cyclodextrin (tpps-β-CD) as a T1 relaxation signal amplification reagent, a lower LOD was obtained. The colorimetric modality exploited the "peroxidase/oxidase-like" activity of Au@MnO2 NPs, which catalyzed the oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue oxidized TMB, which exhibited a working range (6.02 × 104-6.02 × 106 copies/μL) and an LOD of 2.6 × 104 copies/μL. In addition, the rapid amplification reaction of recombinase polymerase enabled the detection of low norovirus levels in food samples and obtained a working range of 101-106 copies/mL and LOD of 101 copies/mL (relaxation modality). The accuracy of the sensor in the analysis of spiked samples was consistent with that of the real-time quantitative reverse transcription polymerase chain reaction, demonstrating the high accuracy and practical utility of the sensor.

Exploring the efficacy and future potential of polypyrrole/metal oxide nanocomposites for electromagnetic interference shielding: a review.

With recent advancements in technology, the emission of electromagnetic radiation has emerged as a significant issue due to electromagnetic interferences. These interferences include various undesirable emissions that can degrade the performance of equipment and structures. If left unresolved, these complications can create extra damage to the security operations and communication systems of numerous electronic devices. Various studies have been conducted to address these issues. In recent years, electrically conductive polypyrrole has gained a unique position because of its many advantageous properties. The absorption of microwaves and the electromagnetic interference (EMI) shielding characteristics of electrically conductive polypyrrole can be described in relation to its great electrical conductivity with strong relaxation and polarization effects due to the existence of strong bonds or localized charges. In the present review, advancements in electromagnetic interference shielding with conjugated polypyrrole and its nanocomposites with metal oxides are discussed and correlated with various properties such as dielectric properties, magnetic properties, electrical conductivity, and microwave adsorption properties. This review also focuses on identifying the most suitable polypyrrole-based metal oxide nanocomposites for electromagnetic interference shielding applications.

Dielectric behavior and impedance spectroscopy of Niobium substituted Lanthanum based orthovanadates at high temperatures

We present the detailed study of the temperature dependent dielectric properties, impedance spectroscopy and electrical conductivity of LaV1−xNbxO4 (x=0–1) samples prepared by the solid-state reaction method. The dielectric constant (ϵr′) increases (decreases) with increase in the temperature (frequency); while, the magnitude of ϵr′ remains almost invariant (order of 104 at 100 Hz and 600 °C) with x. The single phase x=0 (monoclinic-monazite, P21/n) and x=1 (monoclinic fergusonite, I2/a) samples show the lower values of loss factor [tanδ= (4–8)] as compared to the x=0–0.8 samples [tanδ= (12–18)] having mixed tetragonal and monoclinic phases, which indicates the strong correlation between the crystal structure and the dielectric properties. The real part of impedance (Z′) decreases with both temperature and frequency, and the observed weak relaxation remains almost unaltered with x. The imaginary part of impedance (Z′′) shows strong relaxation peaks shifting towards higher temperatures with frequency, which is attributed to the effect of grains, grain boundaries, and electrodes in the samples. The activation energy of the relaxation process is estimated to be 0.8–1.0 eV for the x=0–0.6 samples, and ≈1.4 eV for the x=0.8; whereas the x=1 sample shows two values (≈0.5 eV and ≈1.0 eV) in the higher and lower temperature range, respectively. Further, the change in total conductivity with the angular frequency, which found to be in the range of 10−3 to 10−5 S/m, is fitted using the Jonsher power law. The analysis suggests the overlapping large polaron tunneling (OLPT) model for all the samples, whereas the x = 1 sample exhibit a transition near 480 °C and at higher temperatures it shows non-overlapping small polaron tunneling (NSPT) and quantum mechanical tunneling (QMT). This transition is corroborated by the tangent loss curves and may be associated with the change in structure.

Fabrication of recyclable and biodegradable PBAT vitrimer via construction of highly dynamic cross-linked network

The emergence of biodegradable materials has not satisfactorily addressed the issue of plastic waste management, owing to their high cost and poor mechanical performance and durability that impair their potential to replace traditional plastics. In this study, a dynamic cross-linked network with robust remoldability was fabricated in PBAT. Transesterification catalysts were employed to catalyze the reaction of β-hydroxyl groups produced from the branching reaction of polyester end groups and epoxy branching agents with the abundant ester groups of PBAT to produce biodegradable PBAT vitrimers. Swelling experiments, DMA tests and stress relaxation experiments confirmed the presence of the dynamic cross-linking structure, while rheological analysis demonstrated that the highly catalyst-loaded PBAT vitrimer dynamic cross-linked network could achieve chain relaxation by exchanging bonds quickly at physical entanglement and chemical cross-linking points. Multiple recycling experiments further demonstrated that the robust dynamic cross-linked network of PBAT vitrimers possessed both strong stress relaxation ability and remoldability, thus conferring excellent recyclability to PBAT. Upon recycling 4 times, the elongation at break of the PBAT vitrimer remained at 93.46 % (with a tensile strength retention of 85.99 %), whereas the raw PBAT could only maintain an elongation at break of 28.01 % (with a tensile strength retention of 56.09 %). TGA and hydrolysis experiments revealed that PBAT vitrimers exhibited better degradation performance relative to raw PBAT. PBAT vitrimers, featuring excellent mechanical performance and durability, can be recycled several times in easily recyclable settings, thus reducing production costs, and finally biodegrade after disposal, thereby serving as a viable replacement for traditional plastics. This straightforward and practicable approach provides a solution for plastic waste management.

The column generation approach to the mean-risk model for the portfolio selection problem with spillover risk aversion

In this article, we propose extensions of the general mean-risk portfolio selection models to limit the spillover effect of risk. We use the conditional value at risk (CoVaR) as a measure to identify the spillover risk contribution of securities. The goal is to find a portfolio that minimizes general risk measures while the spillover risk contribution is limited. Based on the frameworks of the general mean-risk models, we additionally guarantee that a portfolio has limited spillover risk contributions. To solve these problems efficiently, we propose a Dantzig-Wolfe decomposition reformulation that yields a strong continuous relaxation bound by introducing a set of feasible investment patterns. We develop an algorithm that incorporates a column generation procedure to reduce the spillover effect of tail risk in subproblems. Finally, we present the performance of the portfolios using real historical data. The results show that our model can provide better portfolios than the general mean-risk models.

Comprehensive energy-storage performance enhancement in relaxor anti-ferroelectrics via strengthening local polarization

Lead-free dielectric capacitors with excellent energy-storage performance have gained much attention for their remarkable potential applications in pulsed power electronic systems and devices. However, the large recoverable energy-storage density Wrec is usually accompanied with low efficiency η, hindering their practical applications. Such performance deterioration occurs because the large polarization is generally linked with strong reversal hysteresis, making the synergetic optimization of energy-storage density and efficiency a great challenge. Here we develop a strategy of constructing strengthened local polarization in the lead-free relaxor anti-ferroelectric ceramics 0.9NaNbO3-0.1Bi(Ni2/3Nb1/3)O3 by carefully manipulating the microstructures, the ultrahigh Wrec ∼ 11.2 J/cm3 and large η ∼ 90.5 % have been simultaneously achieved. Moreover, superior charge/discharge performances (power density PD ∼ 548 WM/cm3, discharge speed t0.9 ∼ 27 ns) and outstanding temperature (up to 160 °C) and cycling (up to 106) stabilities are also ensured. The excellent overall properties are mainly attributed to the stabilized antiferroelectric phase, the strong relaxation characteristic, as well as the enhanced local polarization in the polar nano-regions (PNRs) caused by the introduction of Bi(Ni2/3Nb1/3)O3. This work not only provides a lead-free system with remarkable energy-storage performance that demonstrates great potential in the application field of high-power pulse electronic devices, but also proposes a convenient and efficient strategy to design new dielectric materials with excellent energy-storage performance.