Time-dependent Approach Research Articles

Modelling Sea-Surface Wave Motion and Ship Response Using Smoothed Particle Hydrodynamics and Finite Element Analysis

The response of a ship or other vessel to surface sea waves, including extreme waves, may compromise crew and vessel safety and long-term operational capability. Herein, a novel high-fidelity numerical time-dependent simulation approach is presented using Smoothed Particle Hydrodynamics (SPH) for modelling sea waves coupled with Finite Element Analysis for modelling vessel structural response under wave loading conditions. The results are compared with physical scale model wave tank test results. Good agreement was obtained for heave and pitch motions and vertical bending moments for various forward (head) speeds in regular head waves, heave and pitch motions, and vertical bending moments. High computational demands can be met by the increasing availability of computation power. Ongoing research is outlined. The implications for the design of vessels such as ships and for through-life assessment are discussed.

Role of Near-IR Sensitive Asymmetric A-DA′D–π–A-type Non-Fullerene Acceptors for Efficient Organic Solar Cells: A Theoretical Insight

Non-fullerene acceptor (NFA) molecules attracted huge attention from the photovoltaic community for their potential use in organic solar cells (OSCs). Herein, we designed a series of NFA materials (AR1–AR9) for OSCs by altering end-capped moieties. We employed various advanced density functional theory (DFT) and time-dependent (TD-DFT) approaches to characterize this designed AR1–AR9 series. Compared to the synthetic reference molecule ([Formula: see text], designed molecules AR1–AR9 revealed a smaller bandgap (1.85 eV), and improved absorption spectra ([Formula: see text] 741 nm) in comparison to [Formula: see text] ([Formula: see text] 668 nm), indicating the better potential for the tailored molecules. Furthermore, the designed series (AR1–AR9) shows lower reorganization energy values (for holes and electrons) and lower binding energies (0.323 eV), whereas, improved charge mobilities, showing them better candidates for OSCs. Moreover, frontier molecular orbitals (FMO), open-circuit voltages ([Formula: see text] and improved charge-transfer characteristics have also been investigated. These findings revealed that all developed NFAs exhibited a wide range of exciton dissociation constants and enhanced absorption efficiency with a relatively lower LUMO energy level. Therefore, we believe that these materials will be beneficial in boosting the power conversion efficiency (PCE) of OSC devices by improving their optoelectronic and photophysical properties.

A multi-layer multi-configurational time-dependent Hartree approach to lattice models beyond one dimension.

The multi-layer multi-configurational time-dependent Hartree (MCTDH) approach is an efficient method to study quantum dynamics in real and imaginary time. The present work explores its potential to describe quantum fluids. The multi-layer MCTDH approach in second quantization representation is used to study lattice models beyond one dimension at finite temperatures. A scheme to map the lattice sites onto the MCTDH tree representation for multi-dimensional lattice models is proposed. A statistical sampling scheme previously used in MCTDH calculations is adapted to facilitate an efficient description of the thermal ensemble. As example, a two-dimensional hard-core Bose-Hubbard model is studied considering up to 64 × 64 lattice sites. The single particle function basis set size required to obtain converged results is found to not increase with the lattice size. The numerical results properly simulate the finite temperature Berezinskii-Kosterlitz-Thouless phase transition.

Crystal Growth, Structural Elucidation, Chemical Reactivity, Topology Exploration (ELF, LOL, AIM, RDG) and NLO Activity of 4-Cumyl Phenol Crystal Using Quantum Chemical Calculation

The main objective of the study is to analyze the structural behavior and NLO activity of 4-cumyl phenol by experimental and theoretical spectroscopic techniques. Its computational result is compared with the cumene compound. The optimized structural parameters of the title compound were computationally obtained at the B3LYP/6-31G (d, p) basis set. The fundamental modes of vibration were examined by experimental FT-IR, and FT-Raman techniques. The distribution of the vibrational bands was carried out with the help of normal coordinate analysis (NCA). The resulting harmonic wavenumbers were scaled by using NCA method. Topological analysis, such as Electron localization function (ELF), natural bond orbital analysis (NBO), reduced density gradient (RDG) and atoms in molecule (AIM) analysis, molecular electrostatic potential (MEP) have been used to evaluate the intermolecular interaction, especially the hydrogen bonds. UV-visible spectrum of the compound was recorded in the region 200–900 nm and the electronic properties and HOMO-LUMO energies were calculated by time dependent density functional theory approach.

Simulating temperature and tautomeric effects for vibrationally resolved XPS of biomolecules: Combining time-dependent and time-independent approaches to fingerprint carbonyl groups.

Carbonyl groups (C=O) play crucial roles in the photophysics and photochemistry of biological systems. O1s x-ray photoelectron spectroscopy allows for targeted investigation of the C=O group, and the coupling between C=O vibration and O1s ionization is reflected in the fine structures. To elucidate its characteristic vibronic features, systematic Franck-Condon simulations were conducted for six common biomolecules, including three purines (xanthine, caffeine, and hypoxanthine) and three pyrimidines (thymine, 5F-uracil, and uracil). The complexity of simulation for these biomolecules lies in accounting for temperature effects and potential tautomeric variations. We combined the time-dependent and time-independent methods to efficiently account for the temperature effects and to provide explicit assignments, respectively. For hypoxanthine, the tautomeric effect was considered by incorporating the Boltzmann population ratios of two tautomers. The simulations demonstrated good agreement with experimental spectra, enabling differentiation of two types of carbonyl oxygens with subtle local structural differences, positioned between two nitrogens (O1) or between one carbon and one nitrogen (O2). The analysis provided insights into the coupling between C=O vibration and O1s ionization, consistently showing an elongation of the C=O bond length (by 0.08-0.09Å) upon O1s ionization.

The effects of processing parameters on the shape of particle size distribution and grinding rate in a stirred mill

The study of particle size distribution (PSD) of materials is a crucial aspect of mineral processing. It not only determines the appropriate beneficiation process and equipment but also has a significant impact on the grade and recovery of concentrate. This study utilizes a pin-stirred mill for the wet fine grinding of limonite to examine four different widths of PSD functions and compares their quantitative descriptions of the PSD. Skewness is a parameter introduced to quantitatively describe the asymmetry of the PSD. This study aims to investigate the effect of the stirrer speed, the density and the size of the grinding media on the shape of the PSD and on the grinding rate. The results show that a lower stirrer speed and a lower density of the grinding media result in a narrower and a more symmetrical PSD of the grinding products. Moreover, the time-dependent approach succeeds in simulating and proving the evolution behavior of the median particle size. It was found that the optimum mixing ratio of the grinding media can effectively adjust the shape of the PSD and improve the grinding efficiency.

Dynamic characteristics and performance analysis of a double-stage energy storage heat transformer with a large temperature lift

Intermittence and low grade are significant barriers for the widespread application of renewable/waste energy. An absorption energy storage heat transformer with adequate energy storage and temperature lift characteristics effectively addresses this challenge. An advancement in this technology is the double-stage energy storage heat transformer (DESHT), which further enhances the range of temperature upgrade through twice temperature lifts. This paper proposes a time-dependent approach for a comprehensive study of the DESHT cycle with a working pair of LiBr/H2O. Firstly, the dynamic characteristics of the DESHT cycle are shown. Subsequently, the effects of discharging temperatures, charging temperatures, and solution mass ratio on cycle performance are analyzed. Results show that the DESHT cycle can achieve a temperature lift from 35 °C to 55 °C. 90 % of the total storage capacity can be reached in 60–70 % of the total charging time. The maximum discharging time per unit of charging time is achieved at a temperature lift of 45 °C. Besides, compared to the conventional double-stage absorption energy storage cycle, the DESHT cycle shows a higher exergy efficiency. Optimizing the solution mass ratio can enhance the cycle performance. These findings can serve as a valuable reference in exploring the DESHT cycle.

Theoretical Study on Vibrationally Resolved Electronic Spectra of Chiral Nanographenes.

Nanographenes are of increasing importance owing to their potential applications in the photoelectronic field. Meanwhile, recent studies have primarily focused on the pure electronic spectra of nanographenes, which have been found to be inadequate for describing the experimental spectra that contain vibronic progressions. In this study, we focused on the vibronic effect on the electronic transition of a range of chiral nanographenes, especially in the low-energy regions with distinct vibronic progressions, using theoretical calculations. All the calculations were performed at the PBE0-D3(BJ)/def2-TZVP level of theory, adopting both time-dependent and time-independent approaches with Franck-Condon approximation. The resulting calculated curves exhibited good alignment with the experimental data. Notably, for the nanographenes incorporating helicene units, owing to the increasing π-extension, the major vibronic modes in the vibrationally resolved spectra differed significantly from those of the primitive helicenes. This investigation suggests that calculations that account for the vibronic effect could have better reproducibility compared with calculations based solely on pure electronic transitions. We anticipate that this study could pave the way for further investigations into optical and chiroptical properties, with a deeper understanding of the vibronic effect, thereby providing theoretical explanations with higher precision on more sophisticated nanographenes.

Tensor-Train Format Hierarchical Equations of Motion Formalism: Charge Transfer in Organic Semiconductors via Dissipative Holstein Models.

Hierarchical Equations of Motion (HEOM) in the Tensor-Train (TT) representation is applied to study the charge-transfer dynamics in organic semiconductors (OSCs). The theoretical formulation as well as the basic computational aspects of HEOM-TT are discussed in detail. Charge transfer in OSCs is modeled using dissipative polaronic models that incorporate the effects of both high- and low-frequency molecular vibrations, and it is simulated in a fully quantum and nonperturbative manner, which has not been studied intensively. The capability of treating complex electron-vibrational systems is examined by analyzing and comparing the numerical behavior of the time-dependent variational approach and the time-Alternating Minimal Energy methods and by calculating the current autocorrelation function and diffusivity across various models. Our results indicate that the HEOM-TT framework offers a robust tool for the detailed analysis of complex polaronic systems, suggesting its potential for broader applications.

Improved switching condition for reachable set estimation of discrete-time switched delayed neural networks

This research delves into the reachable set estimation (RSE) problem for general switched delayed neural networks (SDNNs) in the discrete-time context. Note that existing relevant research on SDNNs predominantly relies on either time-dependent or state-dependent switching approaches. The time-dependent versions necessitate the stability of each subnetwork beforehand, whereas the state-dependent switching strategies solely depend on the current state, thus disregarding the historical information of the neuron states. For fully harnessing the historical information pertaining to neuron states, a delicate combined switching strategy (CSS) is formulated with the explicit goal of furnishing a relaxed and less conservative design framework tailored for discrete-time SDNNs, where all subnetworks can also be unstable. By resorting to the established time-dependent multiple Lyapunov–Krasovskii functional (TDMLF) technique, the improved criteria are subsequently presented, ensuring that the reachable set encompassing all potential states of SDNNs is confined to an anticipated bounded set. Ultimately, the practicality and superiority of the presented RSE approach are thoroughly validated by two illustrative simulation examples.

Good Rates From Bad Coordinates: The Exponential Average Time-dependent Rate Approach.

Our ability to calculate rate constants of biochemical processes using molecular dynamics simulations is severely limited by the fact that the time scales for reactions, or changes in conformational state, scale exponentially with the relevant free-energy barrier heights. In this work, we improve upon a recently proposed rate estimator that allows us to predict transition times with molecular dynamics simulations biased to rapidly explore one or several collective variables (CVs). This approach relies on the idea that not all bias goes into promoting transitions, and along with the rate, it estimates a concomitant scale factor for the bias termed the "CV biasing efficiency" γ. First, we demonstrate mathematically that our new formulation allows us to derive the commonly used Infrequent Metadynamics (iMetaD) estimator when using a perfect CV, where γ = 1. After testing it on a model potential, we then study the unfolding behavior of a previously well characterized coarse-grained protein, which is sufficiently complex that we can choose many different CVs to bias, but which is sufficiently simple that we are able to compute the unbiased rate directly. For this system, we demonstrate that predictions from our new Exponential Average Time-Dependent Rate (EATR) estimator converge to the true rate constant more rapidly as a function of bias deposition time than does the previous iMetaD approach, even for bias deposition times that are short. We also show that the γ parameter can serve as a good metric for assessing the quality of the biasing coordinate. We demonstrate that these results hold when applying the methods to an atomistic protein folding example. Finally, we demonstrate that our approach works when combining multiple less-than-optimal bias coordinates, and adapt our method to the related "OPES flooding" approach. Overall, our time-dependent rate approach offers a powerful framework for predicting rate constants from biased simulations.

Rise and Fall of Anderson Localization by Lattice Vibrations: A Time-Dependent Machine Learning Approach.

The intricate relationship between electrons and the crystal lattice is a linchpin in condensed matter, traditionally described by the Fröhlich model encompassing the lowest-order lattice-electron coupling. Recently developed quantum acoustics, emphasizing the wave nature of lattice vibrations, has enabled the exploration of previously uncharted territories of electron-lattice interaction not accessible with conventional tools such as perturbation theory. In this context, our agenda here is two-fold. First, we showcase the application of machine learning methods to categorize various interaction regimes within the subtle interplay of electrons and the dynamical lattice landscape. Second, we shed light on a nebulous region of electron dynamics identified by the machine learning approach and then attribute it to transient localization, where strong lattice vibrations result in a momentary Anderson prison for electronic wavepackets, which are later released by the evolution of the lattice. Overall, our research illuminates the spectrum of dynamics within the Fröhlich model, such as transient localization, which has been suggested as a pivotal factor contributing to the mysteries surrounding strange metals. Furthermore, this paves the way for utilizing time-dependent perspectives in machine learning techniques for designing materials with tailored electron-lattice properties.

New conjugated copolymer MEH-PPV-P3HT with donor-acceptor system for organic optoelectronics applications: Experimental and theoretical study

Donor-acceptor architecture was designed of new diblocks copolymer MEH-PPV-P3HT synthesis. The new copolymer was elaborated through oxidative pathway. The correlation structure-properties and their potential photophysical characteristics of the obtained material were reported utilizing several characterization analyses (InfraRed, Raman, TGA, UV visible spectroscopy, as well as PL and TRPL). To define the model's geometric structure, vibrational, and optoelectronic properties of the studied copolymer, Density Functional Theory DFT and Time-dependent Density Functional Theory TD-DFT approach were carried out. The obtained copolymer exhibits great thermal stability and substantial absorption in the visible range. An energy gap lower than the original materials by the amount of 1.74 eV which proves the presence of the charge transfer process. In addition, due to Forster energy transfer from the MEH-PPV to the P3HT an enhancement of the exciton average lifetime was detected. The obtained results from the copolymer characterization suggest a potential for application in organic optoelectronic devices. A good accordance between experimental and theoretical results based DFT calculations is obtained.

Systematic Modeling of N-Type D–A–D Conjugated Small Molecule-Based Nonfullerene Acceptors for Organic Photovoltaics

This study investigates the impact of six novel (SPZ1–SPZ6) small molecular conjugated nonfullerene acceptors (NFAs), for organic solar cells (OSCs). The designed NFAs are characterized by various advanced quantum chemical simulations of density functional theory (DFT) and time-dependent (TD-DFT) approaches. We revealed in-depth information regarding molecules’ structural-property relationship charge transfer and optical absorption characteristics of designed molecules and compared them with synthetic reference molecules (R). The designed SPZ1–SPZ6 molecules exhibit red-shifted absorption, reduced bandgaps and increased extinction coefficients, indicating improved molecular phase separation during thin-film deposition during device fabrication. Moreover, the modeled SPZ1–SPZ6 molecules significantly enhance photophysical, optoelectronic and photovoltaic parameters compared to R. Among these, the designed small molecule SPZ2 exhibits superior UV–Vis absorption of 730.44 nm, surpassing R and others. SPZ2 features the smallest bandgap (2.00 eV) and has a substantial improvement over R’s 2.37 eV, and this is due to our efficient molecular modeling strategy. Further investigation revealed efficient charge transfer between the SPZ2 acceptor molecule and PTB7-Th donor molecule complex, making this design capable of producing efficient OSCs in the future.

A non-hierarchical multi-layer multi-configurational time-dependent Hartree approach for quantum dynamics on general potential energy surfaces.

The correlation discrete variable representation (CDVR) enables multi-layer multi-configurational time-dependent Hartree (MCTDH) quantum dynamics simulations on general potential energy surfaces. In a recent study [R. Ellerbrock and U. Manthe, J. Chem. Phys. 156, 134107 (2022)], an improved CDVR that can account for the symmetry properties of a tree-shaped wavefunction representation has been introduced. This non-hierarchical CDVR drastically reduces the number of grid points required in the time-dependent quadrature used to evaluate all potential energy matrix elements. While the first studies on the non-hierarchical CDVR approach have been restricted to single-layer calculations, here the complete theory required for the implementation of the non-hierarchical CDVR approach in the multi-layer MCTDH context will be presented. Detailed equations facilitating the efficient recursive computation of all matrix elements are derived, and a new notation adapted to the symmetry properties of the tree-shaped representation is introduced. Calculations studying the non-adiabatic quantum dynamics of photoexcited pyrazine in 24 dimensions illustrate the properties of the non-hierarchical multi-layer CDVR.

Modeling the electroluminescence of atomic wires from quantum dynamics simulations.

Static and time-dependent quantum-mechanical approaches have been employed in the literature to characterize the physics of light-emitting molecules and nanostructures. However, the electromagnetic emission induced by an input current has remained beyond the realm of molecular simulations. This is the challenge addressed here with the help of an equation of motion for the density matrix coupled to a photon bath based on a Redfield formulation. This equation is evolved within the framework of the driven-Liouville von Neumann approach, which incorporates open boundaries by introducing an applied bias and a circulating current. The dissipated electromagnetic power can be computed in this context from the time derivative of the energy. This scheme is applied in combination with a self-consistent tight-binding Hamiltonian to investigate the effects of bias and molecular size on the electroluminescence of metallic and semiconducting chains. For the latter, a complex interplay between bias and molecular length is observed: there is an optimal number of atoms that maximizes the emitted power at high voltages but not at low ones. This unanticipated behavior can be understood in terms of the band bending produced along the semiconducting chain, a phenomenon that is captured by the self-consistency of the method. A simple analytical model is proposed that explains the main features revealed by the simulations. The methodology, applied here at a self-consistent tight-binding level but extendable to more sophisticated Hamiltonians such as density functional tight binding and time dependent density functional theory, promises to be helpful for quantifying the power and quantum efficiency of nanoscale electroluminescent devices.

Designing efficient materials for high-performance of non-fullerene organic solar cells through side-chain engineering on DBT-4F derivatives by non-fused-ring electron acceptors.

For the advancement in fields of organic and perovskite solar cells, various techniques of structural alterations are being employed on previously reported chromophores. In this study, the end-capped engineering is carried out on DBT-4F (R) by modifying terminal acceptors to improve optoelectronic and photovoltaic attributes. Seven molecules (AD1-AD7) are modeled using different push-pull acceptors. DFT/B3LYP/6-31G along with its time-dependent approach (TD-DFT) are on a payroll to investigate ground state geometries, absorption maxima (λmax), energy gap (Eg), excitation energy (Ex), internal reorganization energy, light harvesting efficiency (LHE), dielectric constant, open circuit voltage (VOC), fill factor (FF), etc. of OSCs. AD1 displayed the lowest band gap (1.76eV), highest λmax (876nm), lowest Ex (1.41eV), and lowest binding energy (0.21eV). Among various calculated parameters, all of the sketched molecules demonstrated greater dielectric constant when compared to R. The highest dielectric constant was exhibited by AD3 (56.26). AD5 exhibited maximum LHE (0.9980). Lower reorganization energies demonstrated improved charge mobility. AD5 and AD7 (1.63 and 1.68eV) have higher values of VOC than R (1.51eV). All novel molecules having outperforming attributes will be better candidates to enhance the efficacy of OSCs for future use. Precisely, a DFT and TD-DFT analysis on all of the proposed organic molecules were conducted, using the functional MPW1PW91 at 6-31G (d,p) basis set to examine their optoelectronic aspects, additionally the solvent-state computations were studied with a TD-SCF simulation. For all these simulations, Guassian 09 and GuassView 5.0 were employed. Moreover, the Origin 6.0, Multiwfn 3.8, and PyMOlyze 1.1 software were utilized for the visual depiction of the graphs of absorption, TDM, and DOS, respectively of the studied molecules. A number of crucial aspects such as FMOs, bandgaps, light-harvesting efficiency, electrostatic potential, dipole moment, ionization potential, open-circuit voltage, fill factor, binding energy, interaction coefficient, chemical hardness-softness, and electrophilicity index were also investigated for the studied molecules.

Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression.

Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disorder of the central nervous system, leading to progressive functional impairments. Predicting disease progression with a probabilistic and time-dependent approach might help suggest interventions for a better management of the disease. Recently, there has been increasing focus on the impact of air pollutants as environmental factors influencing disease progression. This study employs a Continuous-Time Markov Model (CMM) to explore the impact of air pollution measurements on MS progression using longitudinal data from MS patients in Italy between 2013 and 2022. Preliminary findings indicate a relationship between air pollution and MS progression, with pollutants like Particulate Matter with a diameter of 10 micrometers (PM10) or 2.5 micrometers (PM2.5), Nitrogen Dioxide (NO2), and Carbon Monoxide (CO) showing potential effects on disease activity.

A comparative study on the parametrization of a time-variable geopotential model from GRACE monthly solutions

The gravity field of the Earth is time-dependent due to several types of mass variations which take place on different time scales. Usually, the time-variability of the gravitational potential of the Earth is expressed by the monthly determination of a static geopotential model based on data from gravity field missions. In this paper, the variability of the potential is parameterized by a functional approach which contains a polynomial trend and periodic contributions. The respective parameters are estimated based on the monthly solutions derived from the GRACE and GRACE-FO gravity field mission up to a maximum degree of expansion nmax=96\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n_\ ext {max}=96$$\\end{document}. As a preliminary data analysis, a Fourier analysis is performed on selected potential coefficients from the available monthly solutions of the GFZ. The indicated frequency components are then used to formulate a time-dependent analytical approach to describe each Stokes coefficient’s temporal behaviour. Different approaches are presented that include both polynomial and periodic components. The respective parameters for modelling the temporal variability of the coefficients are estimated in a Gauss-Markov model and tested for significance by statistical methods. Extensive comparative numerical studies are carried out between the newly generated model variants and the existing monthly GRACE, GRACE-FO and the existing time dependent EIGEN-6S4 solutions. The numerical comparisons make it clear that estimated models based on all available monthly solutions describe the essential periods very well, but such monthly events that deviate strongly from the mean behaviour of the signal show less precision in the space domain. Models that are estimated based on fourteen consecutive monthly solutions, covering one selected year, represent the amplitudes much more precise. The statements made apply to four initial data used, which are filtered to varying degrees. In particular, DDK2, DDK5 and DDK8, as well as unfiltered coefficients were used. For all the model approaches used, it can be seen that the potential coefficients contain up to about n≈40\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n\\approx 40$$\\end{document} in case of DDK5 periodically signals with annual, semi-annual or quarterly, as well as Luna nodal periods and do not vary significantly beyond that degree. Only an offset can be estimated significantly for all Stokes coefficients.

Implications and late outcomes of type II endoleaks after endovascular aneurysm repair

ObjectiveType II endoleaks (T2ELs) are the most common cause of reintervention after endovascular aneurysm repair (EVAR). Although most resolve spontaneously, the long-term implications of T2ELs remain elusive. We aim to evaluate the impact of persistent and late T2ELs on clinical outcomes after EVAR. MethodsThis was a single-institution retrospective review of patients who underwent EVAR for degenerative infrarenal abdominal aortic aneurysm between January 2010 and June 2022 with no type I (T1EL) or III (T3EL) endoleak seen at EVAR completion. Patients were categorized based on T2EL status. Group 1 included patients with never detected or transient T2ELs (detected at EVAR completion but not after). Group 2 encompassed persistent T2ELs (seen at EVAR completion and again during follow-up) and late T2ELs (detected for the first time at any point during follow-up). Time-to-event analysis was conducted using a time-dependent approach to T2EL status. Primary outcomes included freedom from sac enlargement (SE), aneurysm-related reinterventions, and overall survival. ResultsA total of 803 patients met inclusion criteria. Group 1 included 418 patients (52%), of which 85% had no T2ELs and 15% had transient T2ELs. Group 2 had 385 patients; 23% had persistent T2ELs, and 77% developed a new T2EL. Patients in group 1 had a higher prevalence of smoking (88% vs 83%; P < .001), chronic obstructive pulmonary disease (33% vs 25%; P = .008), chronic kidney disease (13% vs 8%; P = .021), and a higher mean Society for Vascular Surgery score (7 vs 6 points; P = .049). No differences were found in aneurysm diameter or morphology. Mean follow-up was 5 years for the entire cohort. In Group 2, 58 patients (15%) underwent T2EL treatment, most commonly transarterial embolization. At 10 years after EVAR, Group 2 was associated with lower freedom from SE (P < .001) and abdominal aortic aneurysm-related reinterventions (P < .001) and comparable overall survival (P = .42). More T1ELs were detected during follow-up in Group 2 (6 [1%] vs 20 [5%]; P = .004), with 15 (75%) of these detected at a median of 3 years after the T2EL. No difference between groups was observed in explant (0.7% vs 2.1%; P = .130) or aneurysm rupture (0.5% vs 1.3%; P = .269) rates. ConclusionsOne-half of patients treated with infrarenal EVAR developed persistent/late T2ELs, which are associated with a higher risk of SE and reinterventions. No difference in overall survival or aneurysm rupture risk was seen at 10 years, based on T2EL status or T2EL intervention. A conservative approach to T2ELs may be appropriate for most patients with absent T1ELs or T3ELs.