Semi-empirical Research Articles

Understanding the interactions between PMMA polymer and common industrial gasses: a computational xTB, DFT, SAPT and MD study

In this paper, extended tight binding (xTB), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT) and molecular dynamics (MD) simulations were used to understand the interaction between PMMA polymer and industrial gases (H2, O2, N2 and H2O). Geometrical pre-optimizations of all structures have been performed using different methods, starting with GFN2-xTB method, followed by re-optimisation with the B3LYP-D3, M06-2X and r2SCAN-3c methods. Binding energies were calculated using a semiempirical GFN2-xTB method, density functional methods B3LYP-D3 and M06-2X and composite methods r2SCAN-3c. These calculations revealed that the binding of H2O molecules to the PMMA chain is undoubtedly the strongest compared to the other investigated gases in this paper. The strengths of noncovalent interactions explained the obtained trends in binding energies. The SAPT2 calculations have provided insights into the interaction energy and charge transfer components. The PMMA and H2O systems show the strongest attractive interaction and H2 and N2 molecules show much less charge transfer, which leads to weaker interactions. O2 shows little charge transfer, leading to a moderate interaction strength with PMMA. Using MD simulations, we investigated the behaviour of gas molecules in the presence of the examined polymer, which is important for studying adsorption and solubility within the polymer matrix.

Enhancing biotextile applications with nanocomposite fibers: Molecular dynamics and interferometric analysis of the structural and mechanical properties of treated polypropylene

AbstractThis study explores the enhancement of polypropylene (PP) fibers through the incorporation of titanium oxide nanoparticles (TiO2), with a comprehensive characterization of their molecular, optical, mechanical, and antimicrobial properties. Density functional theory (DFT) and the PM6 semiempirical method were used to investigate the electronic properties and structure–activity relationships of the fibers. Experimental analyses, including FTIR, mechanical testing, and interferometric measurements using a Mach–Zehnder interferometer, were conducted to assess the impact of TiO2 nanoparticles on the fibers' performance. The antimicrobial efficacy was evaluated using the shake flask method. Results indicate that the addition of TiO2 nanoparticles significantly improved the material's polarity, mechanical strength, and antimicrobial properties. Specifically, the total dipole moment (TDM) increased from 0.0706 Debye in neat PP to 3.7180 Debye in PP‐TiO2, and the band gap energy decreased from 10.58 to 1.14 eV, indicating a transition to semiconducting behavior. The mechanical properties of PP‐TiO2 demonstrated a yield strength of 206.83 MPa and an elastic shear modulus of 439.58 MPa, a notable improvement over neat PP. Moreover, PP‐TiO2 fibers exhibited enhanced birefringence and strong antimicrobial activity against Escherichia coli, Staphylococcus aureus, and Candida species, underlining their potential for advanced applications in medical and hygiene‐related fields.Highlights Structural and optical properties of PP and PP‐TiO2 have been analyzed. Advanced characterization with Mach–Zehnder interferometry and modeling has been used. Opto‐mechanical behavior was studied via stress–strain and refractive index. Antimicrobial efficacy was evaluated using the shake flask method. PP‐TiO2 shows potential for biomedical applications like suture and dressings.

Methods for Analyzing Avionics Reliability Reflecting Atmospheric Radiation in the Preliminary Development Phase: An Integrated Failure Rate Analysis

Abstract: Advances in deep submicron semiconductor technology have increased the significance of studying soft errors caused by atmospheric radiation in avionics systems. Atmospheric radiation particles, such as protons and neutrons, can induce Single Event Upsets (SEUs) in sensitive electronic components, leading to system malfunctions and data corruption. Traditional reliability analysis based on older IC or LSI components may fail to account for radiation-induced effects. However, modern avionics systems equipped with state-of-the-art VLSI components are increasingly susceptible to Single Event Upsets (SEUs), potentially leading to underestimated failure rates in these advanced systems. This study introduces an integrated failure rate analysis that incorporates both the physics of failure rates resulting from aging and wear-out and soft error rates induced by atmospheric radiation. The proposed failure rate analysis of the reliability of avionics operating at altitudes of up to 18 km by combining the physics of failure rates with radiation-induced failure rates was derived using a semi-empirical SEU estimation method. Case studies using the Zynq 7000 board, sourced from AMD (San Jose, USA), confirmed that the integrated failure rate analysis provides more accurate reliability predictions compared to conventional analysis. This approach is expected to improve the accuracy of safety assessments during the preliminary development stages, leading to a shortened development timeline and enhanced design quality.

Quantum chemical studies of carbon-based graphene-like nanostructures: from benzene to coronene.

This study presents quantum chemical analysis of 14 distinct carbon-based nanostructures (CBN), ranging from simple molecules, like benzene, to more complex structures, such as coronene, which serves as an exemplary graphene-like model. The investigation focuses on elucidating the relationships between molecular orbital (MO) energies, the energy band gaps, electron occupation numbers (eON), electronic conduction, and the compound topologies, seeking to find the one that approaches most of a graphene-like structure for in silico studies. Through detailed examination of molecular properties including chemical hardness and chemical potential, we demonstrate that the electronic exchange between orbitals is directly influenced by the structural topology of the carbon-based nanostructures, as the electron occupation numbers and the molecular orbital energies. Raman theoretical analysis was performed, ensuring the approximation to a graphene structure by its experimental fingerprint comparison. The correlations presented here offer an approach for anticipating electronic conductivity in graphene-like materials, as well as the confirmation of coronene as a graphene nanostructure for theoretical analyses. The models were designed at Ghemical software optimized at Tripos5.2 force field and properly protonated on the peripheral carbons. The models were then optimized by PM7 semiempirical method using MOPAC2016 to minimize the gradient energy before applying the DFT calculations. After that, the model's geometry was finally optimized at ab initio B3LYP hybrid functional and 6-31G* basis, using ORCA5.0.4. The eON, the MO energies and the Raman spectrum were obtained with the same methods, making possible the spectrum extraction without the interference of H atoms, approaching the analyses to graphene-like topologies.

Dynamic Heat Transfer Modeling and Validation of Super-Long Flexible Thermosyphons for Shallow Geothermal Applications

In comparison to borehole heat exchangers that rely on forced convection, super-long thermosyphons offer a more efficient approach to extracting shallow geothermal energy. This work conducted field tests on a super-long flexible thermosyphon (SFTS) to evaluate its heat transfer characteristics. The tests investigated the effects of cooling water temperature and the inclination angle of the condenser on the start-up characteristics and steady-state heat transfer performance. Based on the field test results, the study proposed a dynamic heat transfer modeling method for SFTSs using the equivalent thermal conductivity (ETC) model. Furthermore, a full-scale 3D CFD model for geothermal extraction via SFTS was developed, taking into account weather conditions and groundwater advection. The modeling validation showed that the simulation results aligned well with the temperature and heat transfer power variations observed in the field tests when the empirical coefficient in the ETC model was specified as 2. This work offers a semi-empirical dynamic heat transfer modeling method for geothermal thermosyphons, which can be readily incorporated into the overall simulation of a geothermal system that integrates thermosyphons.

Conversion of 10 min Rain Rate Time Series into 1 min Time Series: Theory, Experimental Results, and Application in Satellite Communications

We propose a semi-empirical method—based on a filtered Markov process—to convert 10 min rain rate time series into 1 min time series, i.e., quasi-instantaneous rainfall—the latter to be used as input to the synthetic storm technique, which is a very reliable tool for calculating rain attenuation time series in satellite communication systems or for estimating runoff, erosion, pollutant transport, and other applications in hydrology. To develop the method, we used a very large data bank of 1 min rain rate time series collected in several sites with different climatic conditions. The experimental and simulated 1 min rain rate time series agree very well. Afterward, we used them to simulate rain attenuation time series at 20.7 GHz, in 35.5° slant paths to geostationary satellites. The two simulated annual rain attenuation probability distributions show very small differences. We conclude that the rain rate conversion method is very reliable.

Advances and Challenges in Speciation Measurement and Microkinetic Modeling for Gas-Solid Heterogeneous Catalysis.

Microkinetic modeling of heterogeneous catalysis serves as an efficient tool bridging atom-scale first-principles calculations and macroscale industrial reactor simulations. Fundamental understanding of the microkinetic mechanism relies on a combination of experimental and theoretical studies. This Perspective presents an overview of the latest progress of experimental and microkinetic modeling approaches applied to gas-solid catalytic kinetics. Then, opportunities and challenges are presented based on recent research progress in gas-solid catalysis and combustion chemistry. For experimental approaches, the importance of ideal catalytic reactors, structured catalysts, and precise elementary rate measurements is emphasized. Additionally, integrating spatiotemporally resolved operando gas-phase diagnostics with surface-adsorbed species characterization methods offers new opportunities for gaining deeper insights into gas-surface reactions. In microkinetic modeling, a hybrid rate parameter evaluation approach that combines first-principles calculations with semiempirical methods, followed by automated mechanism generation and data-driven optimization, opens new avenues for efficiently constructing surface mechanisms. Furthermore, extending microkinetic modeling beyond mean-field approximations allows simulations under realistic catalyst operating conditions. Finally, the critical role of gas-phase mechanisms and comprehensive microkinetic modeling analyses in advancing our fundamental understanding of gas-solid catalytic processes is highlighted.

Quick-and-Easy Validation of Protein-Ligand Binding Models Using Fragment-Based Semiempirical Quantum Chemistry.

Electronic structure calculations in enzymes converge very slowly with respect to the size of the model region that is described using quantum mechanics (QM), requiring hundreds of atoms to obtain converged results and exhibiting substantial sensitivity (at least in smaller models) to which amino acids are included in the QM region. As such, there is considerable interest in developing automated procedures to construct a QM model region based on well-defined criteria. However, testing such procedures is burdensome due to the cost of large-scale electronic structure calculations. Here, we show that semiempirical methods can be used as alternatives to density functional theory (DFT) to assess convergence in sequences of models generated by various automated protocols. The cost of these convergence tests is reduced even further by means of a many-body expansion. We use this approach to examine convergence (with respect to model size) of protein-ligand binding energies. Fragment-based semiempirical calculations afford well-converged interaction energies in a tiny fraction of the cost required for DFT calculations. Two-body interactions between the ligand and single-residue amino acid fragments afford a low-cost way to construct a "QM-informed" enzyme model of reduced size, furnishing an automatable active-site model-building procedure. This provides a streamlined, user-friendly approach for constructing ligand binding-site models that requires neither a priori information nor manual adjustments. Extension to model-building for thermochemical calculations should be straightforward.

Convergent Protocols for Computing Protein-Ligand Interaction Energies Using Fragment-Based Quantum Chemistry.

Fragment-based quantum chemistry methods offer a means to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation to compute protein-ligand interaction energies in systems with several thousand atoms, using a new software platform for managing fragment-based calculations that implements a screened many-body expansion. Convergence tests using a minimal-basis semiempirical method (HF-3c) indicate that two-body calculations, with single-residue fragments and simple hydrogen caps, are sufficient to reproduce interaction energies obtained using conventional supramolecular electronic structure calculations, to within 1 kcal/mol at about 1% of the computational cost. We also demonstrate that the HF-3c results are illustrative of trends obtained with density functional theory in basis sets up to augmented quadruple-ζ quality. Strategic deployment of fragmentation facilitates the use of converged biomolecular model systems alongside high-quality electronic structure methods and basis sets, bringing ab initio quantum chemistry to systems of hitherto unimaginable size. This will be useful for generation of high-quality training data for machine learning applications.

ADSORPTION PROCESS OF PESTICIDE ON SWCNT FUNCTIONALIZED AND CROSSLINKED WITH CHITOSAN USING PM3 SEMI-EMPIRICAL METHOD AND MONTE CARLO SIMULATION

In this work, using the PM3 semi-empirical method, the oxidation of the single-walled carbon nanotube (SWCNT) was studied by sulfuric and nitric acid for the incorporation of carbonyl (C=O), phenol (OH) and carboxylic (COOH) groups in the C=C bonds present on the surface of the nanotube. Subsequently, the crosslinking of the oxidized SWCNT (SWCNTox) and chitosan (Q) was observed through hydrogen bonds of the C=O and OH bonds with 2.34 Å, the process was endothermic and soluble in polar solvents due to the presence of OH and NH groups in the structure of SWCNTox/Q. The Monte Carlo modeling allowed to study the adsorption of pesticides in the SWCNTox/Q at different temperatures, where the QSAR (quantitative structure activity relationship) properties allowed predicting the behavior of the pesticides, that is, the degree of hydrophobicity (log P) and accessible surface area (ASA) were important parameters in the evaluation of SWCNTox/Q as an adsorbent and surface interacting with pesticides respectively. Finally, the adsorption was a physisorption process due to the electronegativity of the CO, OH, NH2, NH and C=O bonds.

Ribosome engineering of Myxococcus xanthus for enhancing the heterologous production of epothilones

BackgroundRibosome engineering is a semi-empirical technique used to select antibiotic-resistant mutants that exhibit altered secondary metabolism. This method has been demonstrated to effectively select mutants with enhanced synthesis of natural products in many bacterial species, including actinomycetes. Myxobacteria are recognized as fascinating producers of natural active products. However, it remains uncertain whether this technique is similarly effective in myxobacteria, especially for the heterologous production of epothilones in Myxococcus xanthus.ResultsAntibiotics that target the ribosome and RNA polymerase (RNAP) were evaluated for ribosome engineering of the epothilone-producing strain M. xanthus ZE9. The production of epothilone was dramatically altered in different resistant mutants. We screened the mutants resistant to neomycin and rifampicin and found that the yield of epothilones in the resistant mutant ZE9N-R22 was improved by sixfold compared to that of ZE9. Our findings indicate that the improved growth of the mutants, the upregulation of epothilone biosynthetic genes, and specific mutations identified through genome re-sequencing may collectively contribute to the yield improvement. Ultimately, the total titer of epothilones achieved in a 10 L bioreactor reached 93.4 mg/L.ConclusionsRibosome engineering is an efficient approach to obtain M. xanthus strains with enhanced production of epothilones through various interference mechanisms. Here, we discuss the potential mechanisms of the semi-empirical method.

Photoisomerization Dynamics of Azo-Escitalopram Using Surface Hopping and a Semiempirical Method.

The photoisomerization dynamics of azo-escitalopram, a synthetic photoswitchable inhibitor of the human serotonin transporter, is investigated in both gas-phase and water. We use the trajectory surface hopping method─as implemented in SHARC─interfaced with the floating occupation molecular orbital-configuration interaction semiempirical method to calculate on-the-fly energies, forces, and couplings. The inclusion of explicit water molecules is enabled using an electrostatic quantum mechanics/molecular mechanics framework. We find that the photoisomerization quantum yield of trans-azo-escitalopram is wavelength- and environment-dependent, with n → π* excitation yielding higher quantum yields than π → π* excitation. Additionally, we observe the formation of two distinct cis-isomers in the photoisomerization from the most thermodynamically stable trans-isomer, with formation rates influenced by both the excitation window and the surrounding environment. We predict longer excited-state lifetimes than those reported for azobenzene, suggesting that the escitalopram moiety contributes to prolonged lifetimes and slower torsional motions.

A fast and responsive turn-on fluorescent probe based on a quinone conjugated alkoxy derivative for biothiols and a cellular imaging study.

The detection of intracellular biothiols (cysteine, N-acetyl cysteine, and glutathione) with high selectivity and sensitivity is important to reveal biological functions. In this study, a 2-(2-methoxy-4-methylphenoxy)-3-chloro-5,8-dihydroxynaphthalene-1,4-dione (DDN-O) compound (3) was newly synthesized and used as a fluorogenic probe (detector molecule) in the fluorometric method for the rapid, highly selective, and sensitive determination of biothiols. The intensity values (λex = 260 nm, λem = 620 nm) of the product were measured by adding biothiols to the reaction medium at varying concentrations and the glutathione equivalent thiol content values of each biothiol were calculated. Using compound 3, glutathione as the reference biothiol was detected in the linear concentration range of 10-70 μM and the LOD value was found to be 0.11 μM. Biothiol detection with structurally simple compound 3 was performed at the cellular level within 1 min and the probe was also successfully used in bioimaging with low cytotoxicity. It was concluded that this probe can serve as an alternative to existing fluorescence-based biothiol probes with applications in rapid biothiol detection at the cellular level for biological functions. To evaluate the molecular structure of 3, conformational analysis was performed using the PM3 semiempirical method. The most stable obtained molecular geometry was then optimized at the DFT/wb97xd/6-311++G(d,p) level of theory. Frontier molecular orbitals (HOMO and LUMO) and molecular electrostatic potential map analyses were performed for the optimized structure. Molecular docking studies demonstrated the interactions of 3 with HAS (1AO6) and FhGST (2FHE) target proteins.

Semi-empirical method of studying the D-layer aeronomy. II. Evidence-based calibration of the method

This paper presents the results of evidence-based calibration of a new semi-empirical method for studying the D-layer aeronomy. We use simultaneous measurements of altitude profiles of electron density Ne(h) and ionization rate q(h) under disturbed conditions (case 1) and mean <Ne> under various heliogeophysical conditions at low (LSA) and high (HSA) solar activity (case 2). The experimental data and methods are described in detail. It is shown that it is necessary to include temperature dependences of rate constants T(h) for all heliogeophysical conditions. Care should be taken when choosing the T(h) distribution with due regard to most of known factors having an effect on it, wherever possible. We draw a conclusion on the practicability of the use of new photodetachment rates that depend on the solar zenith angle and h. The unknown dissociative recombination rate for cluster positive ions and the photodetachment rate can be reasonably considered as free parameters, of course within due limits. Under disturbed ionospheric conditions, the evidence shows a fall in Ne at all altitudes h when q≈(1.3÷2)⋅10² cm⁻³ s⁻¹ with further increase in the parameters with q, which is confirmed by calculations using the semi-empirical model, yet for a wider range of q variations. The theoretical model that explains the aforementioned effect is the subject of future study. The results for dayside <Ne> coincide qualitatively with our knowledge on the behavior of aeronomy parameters in the D layer. The studies suggest that the presented method allows qualitative estimations under all heliogeophysical conditions and even wholly satisfactory quantitative estimations under disturbed ionospheric conditions.

Geometry-Corrected Quadratic Optimization Algorithm for NDDO-Descendant Semiempirical Models.

The long-held assumption that the optimization of parameters for NDDO-descendant semiempirical methods may be performed without precise geometry optimization is assessed in detail; the relevant equations for the analytical evaluation of the geometry-corrected derivatives of molecular properties that account for changes in the optimum geometry are then presented. The first and second derivatives calculated from our implementation of MNDO are used for a limited reparameterization of 1,113 CHNO molecules taken from the PM7 training set, demonstrating an improvement over the PARAM program used in the optimization of parameters for the PMx methods.

Полуэмпирический приближенный метод исследования некоторых вопросов аэрономии области D-ионосферы. II. Отработка (калибровка) метода по экспериментальным данным

This paper presents the results of evidence-based calibration of a new semi-empirical method for studying the D-layer aeronomy. We use simultaneous measurements of altitude profiles of electron density Ne(h) and ionization rate q(h) under disturbed conditions (case 1) and mean <Ne> under various heliogeophysical conditions at low (LSA) and high (HSA) solar activity (case 2). The experimental data and methods are described in detail. It is shown that it is necessary to include temperature dependences of rate constants T(h) for all heliogeophysical conditions. Care should be taken when choosing the T(h) distribution with due regard to most of known factors having an effect on it, wherever possible. We draw a conclusion on the practicability of the use of new photodetachment rates that depend on the solar zenith angle and h. The unknown dissociative recombination rate for cluster positive ions and the photodetachment rate can be reasonably considered as free parameters, of course within due limits. Under disturbed ionospheric conditions, the evidence shows a fall in Ne at all altitudes h when q≈(1.3÷2)⋅10² cm⁻³ s⁻¹ with further increase in the parameters with q, which is confirmed by calculations using the semi-empirical model, yet for a wider range of q variations. The theoretical model that explains the aforementioned effect is the subject of future study. The results for dayside <Ne> coincide qualitatively with our knowledge on the behavior of aeronomy parameters in the D layer. The studies suggest that the presented method allows qualitative estimations under all heliogeophysical conditions and even wholly satisfactory quantitative estimations under disturbed ionospheric conditions.

Self-assembly of cationic surfactant in choline chloride-based deep eutectic solvents: structural solvation and dynamics.

Deep eutectic solvents (DESs) have gained popularity in various applications due to their improved environmental sustainability and biodegradability. For the present study, several polyhydric alcohols, including ethylene glycol (EG), diethylene glycol (DEG), triethylene glycol (TEG), and glycerol (Gly), have been used as hydrogen bond donors (HBDs) and choline chloride (ChCl) as a hydrogen bond acceptor (HBA) in a fixed molar ratio to form a homogenous and stable DES. Controlled water mixing into such neat DESs has always been thought to be a quick and efficient method to tune the chemical and thermodynamic properties of DESs. The structural solvation and dynamics of the prepared DESs with the inclusion of water vary from low to high water concentrations that have been examined employing Fourier transform infrared (FT-IR), and proton nuclear magnetic resonance (1H-NMR) spectroscopy. Herein, the micellization behavior of a cationic surfactant, dodecyltrimethylammonium bromide (DTAB), in neat DESs and DES-water mixtures has been demonstrated by using tensiometry, dynamic light scattering (DLS), and small-angle X-ray scattering (SAXS) techniques. Furthermore, it has been observed that DESs exhibit an ample thermodynamic driving force for creating micelles, since they contain an H-bonded nanostructure. However, such self-assembly appears to be very much dependent on DESs, the amount of water, and the surfactant used. A computational simulation approach using a semiempirical method is put forth employing the Gaussian 09 W calculation window in the Gauss View 5.0.9 software package. In addition, this study includes the determination of several optimized descriptors that intend to offer an in-depth examination of the surfactant-DES interactions.

Sensitivity Analysis in Photodynamics: How Does the Electronic Structure Control cis-Stilbene Photodynamics?

The techniques of computational photodynamics are increasingly employed to unravel reaction mechanisms and interpret experiments. However, misinterpretations in nonadiabatic dynamics caused by inaccurate underlying potentials are often difficult to foresee. This work focuses on revealing the systematic errors in the nonadiabatic simulations due to the underlying potentials and suggests a thrifty approach to evaluate the sensitivity of the simulations to the potential. This issue is exemplified in the photochemistry of cis-stilbene, where similar experimental outcomes have been differently interpreted based on the electronic structure methods supporting nonadiabatic dynamics. We examine the predictions of cis-stilbene photochemistry using trajectory surface hopping methods coupled with various electronic structure methods (OM3-MRCISD, SA2-CASSCF, XMS-SA2-CASPT2, and XMS-SA3-CASPT2) and assess their ability to interpret experimental observations. While the excited-state lifetimes and calculated photoelectron spectra show consistency with experiments, the reaction quantum yields vary significantly: either completely suppressing cyclization or isomerization. Intriguingly, analyzing stationary points on the potential energy surface does not hint at any major discrepancy, making the electronic structure methods seemingly reliable when treated separately. We show that performing an ensemble of simulations with different potentials provides an estimate of the electronic structure sensitivity. However, this ensemble approach is costly. Thus, we propose running nonadiabatic simulations with an external bias at a resource-efficient underlying potential (semiempirical or machine-learned) for the sensitivity analysis. We demonstrate this approach using a semiempirical OM3-MRCISD method with a harmonic bias toward cyclization.

Semi-empirical calculations of transition probabilities for atomic aluminium

Abstract We discuss the use of a semi-empirical method to obtain the energy values of 391 energy levels and dipolar-electric radiative transition probabilities in neutral aluminium. A relativistic Hartree-Fock atomic structure code allowing superposition of configurations coupled with a least-square fit procedure has been used for this purpose. Einstein coefficients for spontaneous emission not yet tabulated by the NIST atomic spectra database are reported for several transitions.

An investigation on the collapse pressure prediction of subsea pipelines with realistic corrosion defects

Subsea pipelines are widely used for oil and gas transportation, but they are susceptible to failure due to corrosion. Corrosion in pipelines typically results in defects of varying depths and complex shapes. The computational simulation through the finite element (FE) method is one of the most efficient and accurate tools for assessing the integrity of corroded subsea pipes by allowing the simulation of the nonlinear behavior and assessing the hydrostatic collapse. This paper evaluates the collapse response of subsea pipelines with realistic corrosion defects. The study uses the PIPEFLAW system - developed by the PADMEC (High-Performance Processing on Computational Mechanics) research group from UFPE - which integrates reliable tools for automatic FE model generation and performs nonlinear analyses. After validation based on the experimental tests available in the literature, the effect of realistic corrosion defects on the collapse pressure of subsea pipelines is analyzed in detail. The results are compared to results obtained using a semi-empirical method and numerical results obtained considering idealized FE models, i.e., constant-depth and elliptical-shaped corrosion defects. It is observed that the non-uniformity of defects is an important factor affecting the collapse response of pipes. In addition, the idealized geometry of the corrosion defects, especially when considering constant depth, leads to an excessively conservative prediction of the hydrostatic collapse.