Small Dimensions Research Articles

Plastic Analysis with a Plasmonic Nano-Gold Sensor Coated with Plastic-Binding Peptides.

Contamination with plastics of small dimensions (<1 µm) represents a health concern for many terrestrial and aquatic organisms. This study examined the use of plastic-binding peptides as a coating probe to detect various types of plastic using a plasmon nano-gold sensor. Plastic-binding peptides were selected for polyethylene (PE), polyethylene terephthalate (PET), polypropylene (PP), and polystyrene (PS) based on the reported literature. Using nAu with each of these peptides to test the target plastics revealed high signal, at 525/630 nm, suggesting that the target plastic limited HCl-induced nAu aggregation. Testing with other plastics revealed some lack of specificity but the signal was always lower than that of the target plastic. This suggests that these peptides, although reacting mainly with their target plastic, show partial reactivity with the other target plastics. By using a multiple regression model, the relative levels of a given plastic could be corrected by the presence of other plastics. This approach was tested in freshwater mussels caged for 3 months at sites suspected to release plastic materials: in rainfall overflow discharges, downstream a largely populated city, and in a municipal effluent dispersion plume. The data revealed that the digestive glands of the mussels contained higher levels of PP, PE, and PET plastic particles at the rainfall overflow and downstream city sites compared to the treated municipal effluent site. This corroborated earlier findings that wastewater treatment could remove nanoparticles, at least in part. A quick and inexpensive screening test for plastic nanoparticles in biological samples with plasmonic nAu-peptides is proposed.

Optical and photocatalytic properties of sol-gel AuNPs@TiO2 ultrathin film

The optical and photocatalytic properties of ultrathin TiO2 layers were investigated in order to stress out the effect of nanoscale thickness on the film properties. The method relies on monitoring localized surface plasmon resonance (LSPR) through UV–visible spectroscopy and enhanced Raman spectroscopy (SERS). To achieve this, TiO2 thin films were prepared using the sol–gel method on high density gold nanoparticles arrays (AuNPs). TiO2 anatase phase was obtained by thermal annealing and confirmed by XRD, HRTEM, and SERS. Our results reveal that the thinnest TiO2 layers consist of compact TiO2NPs of small dimensions and lower porosity compared to the thicker TiO2NPs layers. Subsequently, these thin TiO2 layers functionalizing AuNPs were applied in plasmonic photocatalysis, specifically for the N-demethylation of methylene blue in the visible range. When comparing layers with the same thickness (a single deposition layer with layers prepared by stacking various thin layers), the stacked layers demonstrated enhanced photocatalytic activity. This novel, stable form of TiO2 has the potential to open numerous opportunities in the fields of photocatalysis and detection.

Studying quantum effects of fine scaling on the buckling behavior of CNTs under torsional loading using the density functional theory and molecular mechanics approach

In this study, we introduce a comprehensive investigation into the buckling behavior of carbon nanotubes (CNTs) using a combined approach of quantum mechanics and molecular mechanics methods. A novel aspect of our research lies in the exploration of the quantum effects of fine scaling on the buckling behavior of finite‐length nanotubes across various dimensions and chiralities. Specifically, we analyze the critical buckling strain variations in CNTs with distinct lengths, diameters, and chiralities, revealing pronounced differences influenced by atomic arrangement and the type of structure used in nanotube construction. Our findings elucidate that at smaller dimensions, nanotubes exhibit a higher critical buckling strain than other chiralities, while zigzag atomic arrangements demonstrate greater resistance to torsional loading at larger diameters. Additionally, we compare the buckling behavior of nanotubes obtained by wrapping armchair and zigzag nanosheets, highlighting differential resistance trends. This research not only underscores the critical role of quantum effects in determining nanotube buckling but also provides valuable insights into the nuanced influences of atomic arrangement and nanosheet type on the mechanical properties of CNTs. Thus, our work contributes a novel perspective to the field, bridging the gap between quantum mechanics and the mechanical behavior of nanostructures, which has significant implications for the design and application of nanoscale materials

Optimizing dimension selection for rain flow counting in fatigue assessment of large-scale lattice wind turbine support structures: A comprehensive study and design guidance

The selection of dimension (d) for the rain flow counting matrix significantly influences the reliable prediction of fatigue life in wind turbine support structures. However, there are limited public reports on the impact of dimensions on the fatigue assessment of wind turbine structures. This study explores the influence of dimensions on the fatigue assessment process and outcomes, focusing on a large-scale ultra-high lattice wind turbine support structure from an engineering project. Through integrated load simulation, fatigue load time series for different design load cases (DLCs) are obtained for the overall structure. The rain flow counting method is utilized to derive the overall rain flow counting matrix (Markov_n) with varying dimensions. Subsequently, employing a multi-scale fatigue assessment method, the damage matrix (Markov_D), cumulative fatigue damage (D), and fatigue life are computed. A detailed exploration examines the impact of rain flow counting matrix dimensions on Markov_n, Markov_D, D, fatigue life, and calculation time (t). Furthermore, guidance is provided for selecting the optimal dimension for engineering design. The findings indicate that selecting dimensions that are too small results in the loss and merging of smaller mean and amplitude load values, thereby failing to accurately represent the load history. Moreover, a small dimension yields an excessively cautious estimation of cumulative fatigue damage (D) and underestimates the fatigue life, consequently inflating construction expenses.

High-resolution dynamic thermal programming platform based on micro thermoelectric device assisted by laser integrated manufacturing

Thermoelectric devices (TEDs) exhibit much application potential in thermal camouflage and encrypted display recently, requiring that TEDs possess large responsivity, high resolution and rapid response with flexible configuration design, which are hardly realized by the traditional complex fabrication process. In this work, an innovative laser integrated manufacturing technology including double-side-printing selective laser melting (D-SLM) and selective laser ablation (SLA) is developed for the construction of the dynamic thermal platform based on micro TEDs. Through experimentally determining the laser process window assisted by external temperature field regulation, a flat p-type film can be directly transformed from n-type Bi2Te3 film by D-SLM. Thus, high-precision p-n patterns without metal joints are obtained from a single locally modified film, whose thermoelectric properties are further boosted by increasing energy density and introducing a post-annealing process. Then, a dynamic thermal platform with designable shapes and small dimensions can be fabricated rapidly whose working principle is also demonstrated. The thermal platform with 4*4 arrays exhibits imaging function with a pixel size of 2 mm×2 mm, a temperature difference of ∼3 K, and a fast response time of 0.143 s. This work offers an exciting yet effective approach to fabricating TEDs for dynamic thermal programmable information displays.

Rapid assessment of vanilla (Vanilla planifolia) quality parameters using portable near-infrared spectroscopy combined with random forest

The determination of moisture and vanillin content significantly influences the quality of vanilla. Currently, conventional chemical methods employed for assessing these parameters are time-consuming, involve complex sample preparation, are expensive, and environmentally unfriendly due to the use of chemical solutions. Portable Near-Infrared (NIR) spectroscopy emerges as a promising alternative, characterized by smaller dimensions and lower costs. This study investigates the performance of two portable NIR spectrometers with distinct wavelengths at 740–1070 nm and 1350–2550 nm, in conjunction with Random Forest (RF) and Partial Least Square (PLS) regression, and preprocessing techniques including min-max normalization, 1st derivative, standard normal variate (SNV), multiplicative scatter correction (MSC), 1st derivative + SNV, and 1st derivative + MSC for predicting moisture and vanillin content. At the wavelength range of 1350–2550 nm, RF coupled with 1st derivative produced the best moisture content prediction model with an R2 of 0.971, and RF paired with 1st derivative+SNV yielded the best vanillin content prediction with an R2 of 0.983. This work highlights that the integration of portable NIR and RF allows for rapid and non-destructive detection of moisture and vanillin content. This methodology provides a novel regression method for predicting vanilla qualities.

Partially explicit splitting scheme with explicit–implicit-null method for nonlinear multiscale flow problems

In this work, we present an efficient approach to solve nonlinear high-contrast multiscale diffusion problems. We incorporate the explicit–implicit-null (EIN) method to separate the nonlinear term into a linear term and a damping term, and then utilize the implicit and explicit time marching scheme for the two parts respectively. Due to the multiscale property of the linear part, we further introduce a temporal partially explicit splitting scheme and construct suitable multiscale subspaces to speed up the computation. The approximated solution is split into these subspaces associated with different physics. The temporal splitting scheme employs implicit discretization in the subspace with small dimension that representing the high-contrast property and uses explicit discretization for the other subspace. We exploit the stability of the proposed scheme and give the condition for the choice of the linear diffusion coefficient. The convergence of the proposed scheme is provided. Several numerical tests are performed to show the efficiency and accuracy of the proposed scheme.

Automatic and time-resolved determination of fracture characteristics from in situ experiments

The characterization of materials in ever smaller dimensions is crucial for the growing demand for miniaturized devices. Hence, in situ fracture experiments are frequently performed at the micron to sub-micron scale. To evaluate fracture process of these experiments, knowledge of the crack length or the crack tip opening displacement is required. Acquired in situ frames provide a direct measurement of the crack length, crack tip opening displacement and -angle. An algorithm was developed to extract these parameters from the in situ frame sequences automatically. To verify the performance of the algorithm, fracture characteristics were measured manually for several frames of the available in situ experiments. The fracture behavior of these samples ranged from brittle over semi-brittle to ductile. The comparison between algorithmic results and manual measurements demonstrated the applicability of the algorithm to different fracture behaviors. Additionally, the fracture characteristics determined by the algorithm are in accordance with the fracture toughness data reported in literature. The crack tip opening displacement measurement gives thorough insight into the plastic deformation during fracture. The automatic extraction of the fracture characteristics allows a more detailed analysis of small-scale fracture processes and enables a reproducible, continuous evaluation of the fracture characteristics of all frames.

The challenge of transseptal access for catheter ablation of left-sided arrhythmia substrate in infants and small children under 6 years of age

Abstract Background Young age and small cardiac dimensions are increased risk factors for catheter ablation (CA), therefore ablation below 15 kg should be recommended only in selected drug-refractory cases. The need for a transseptal puncture (TSP) may be an additional risk factor. Persistent foramen ovale (PFO) in infants can mitigate this risk and paradoxically, decrease the complication rate in the very young. Purpose This study aimed to compare the results of left-sided CA in infants under 1 year and in children between 1-6 years of age. Methods Between January 2010 and September 2023, 1703 pediatric CAs were performed, of which 17 left-sided ablations in children under 6 years without structural heart disease were retrospectively evaluated. CA results below 1 year and between 1-6 years of age were compared in terms of body size, procedural parameters, left atrial (LA) access, complication, and success rate. Results The patient group below 1 year (Group 1, n=5) has a mean age=0.13±0.03 years, mean body weight=3.6±1.1 kg, mean height=52.3±3.6 cm. Patients between 1-6 years (Group 2, n=12) have mean age=5.0±1.1 years, mean body weight=17.9±2.2 kg, mean height=111.2±7.4 cm. The arrhythmia substrate was an overt pathway in 3 pts (17.6%), concealed accessory pathway in 7 pts (41.2%), and focal LA tachycardia in 7 pts (41.2%). Foramen ovale was persistent in all 5 children in Group 1 and TSP was not required. In Group 2, only 2 pts (16.7%) had PFO, and, all other procedures required TSP. TSP was successful in 9/10 cases (90%). No complications related to LA access or other adverse events occurred in Group 1. In Group 2, there was one case of pericardial effusion that spontaneously regressed and one case of mechanical-induced advanced AV block that resolved after six days. There were no significant differences in procedure time, fluoroscopic time, and radiation dose between the two groups (Group 1: 126.4±47.0 min, 6.4±4.5 min, 4.0±5.3 cGycm2 vs. Group 2: 162.6±49.2 min, 7.9±9.4 min, 9.0±12.4 cGycm2, p&amp;gt;0.05). All CAs were performed with RF energy. The acute success rate of the procedures was 100%. Conclusion CA of left-sided arrhythmias in infants and small children may offer a safe and effective therapeutic option in selected cases. The high prevalence of PFO may explain the paradoxically less complication under 1 year of age.

Magnetic and Thermal Behavior of a Planar Toroidal Transformer

This paper presents a study on the magnetic and thermal behaviors of a planar toroidal transformer, comprising two planar toroidal coils. In our configuration, the primary coil consists of twenty turns, while the secondary coil consists of ten turns. This design combines the advantages of both toroidal and planar transformers: it employs flat coils, akin to those utilized in planar transformers, while retaining a toroidal shape for its magnetic core. This combination enables leveraging the distinctive characteristics of both transformer types. This study delves into electromagnetic and thermal behaviors. Electromagnetic behavior is elucidated through Maxwell’s equations, offering insights into the distribution of magnetic fields, potentials, and electric current densities. Fluid flow is modeled via the Navier–Stokes equations. By coupling these equation sets, a more comprehensive and accurate portrayal of the thermal phenomena surrounding electrical equipment is attained. Such research is invaluable in the design and optimization of electrical systems, empowering engineers to forecast and manage thermal effects more efficiently. Consequently, this aids in enhancing the reliability, durability, and performance optimization of electrical equipment. The mathematical model was solved using the finite element method integrated into the COMSOL Multiphysics software v. 6.0. The COMSOL Multiphysics simulation showed correct behavior of potential, electric field, current density, and uniformly distributed temperature. In addition, this planar toroidal coil transformer model offers many advantages, such as small dimensions, high resonance frequency, and high operating reliability. This study made it possible to identify the range of its optimal functioning.

Selected Nonorthogonal Configuration Interaction with Compressed Single and Double Excitations.

Addressing both dynamic and static correlations accurately is a primary goal in electronic structure theory. Nonorthogonal configuration interaction (NOCI) is a versatile tool for treating static correlation, offering chemical insights by combining diverse reference states. Nevertheless, achieving quantitative accuracy requires the inclusion of the missing dynamic correlation. This work introduces a framework for compressing orthogonal single and double excitations into a NOCI of a much smaller dimension. This compression is repeated with each Slater determinant in a reference NOCI, resulting in another NOCI that includes all of its single and double excitations (NOCISD), effectively recovering the missing dynamic correlations from the reference. This compressed NOCISD is further refined through a selection process using metric and energy tests (SNOCISD). We validate the effectiveness of SNOCISD through its application to the dissociation of the nitrogen molecule and the hole-doped two-dimensional Hubbard model at various interaction strengths.

Finite dimensional Frobenius–Perron algebras

Motivated by the Frobenius–Perron (FP) theory of endofunctors of a [Formula: see text]-linear category, we introduce the notion of a FP algebra. This notion can be seen as a generalization of a fusion algebra, and is related to the PP theory of endofunctors of the categories of finite dimensional representations of Taft algebras. Our main result is to classify such algebras with small dimensions according to their FP dimension vectors. Moreover, we introduce the notion of a FP Hopf algebra which can be used to categorify a FP algebra via the Green ring of the Hopf algebra.

End-effector with winding and scooping functions for folding and transporting various cloth parts after cutting

In this study, we propose a novel end-effector that combines the characteristics of winding and scooping fabrics to grasp and categorically place various cloth parts cut by a cutting machine. In addition, we introduce a method for folding the fabric front and back into smaller dimensions, thereby reducing the space required for categorizing, placing, and packaging various clothes, which, to the best of our knowledge, is unique. Subsequently, we develop a method that autonomously determines folding strategies based on the different dimensions of cloth parts, allowing targeted processing of various cloth parts. This approach reduces the height demands of the robot and improves its capability to simultaneously handle multiple types of clothes. Finally, we evaluate the proposed end-effector and folding method in a simulated factory environment using T-shirt parts made of different materials.

Transient Temperature at Tool-Chip Interface during Initial Period of Chip Formation in Orthogonal Cutting of Inconel 718.

Machining nickel-based super alloys such as Inconel 718 generates a high thermal load induced via friction and plastic deformation, causing these alloys to be among most difficult-to-cut materials. Localized heat generation occurring in machining induces high temperature gradients. Experimental techniques for determining cutting tool temperature are challenging due to the small dimensions of the heat source and the chips produced, making it difficult to observe the tool-chip interface. Therefore, theoretical analysis of cutting temperatures is crucial for understanding heat generation and temperature distribution during cutting operations. Periodic heating and cooling occurring during cutting and interruption, respectively, are modeled using a hybrid analytical and finite element (FE) transient thermal model. In addition to identifying a transition distance associated with initial period of chip formation (IPCF) from apparent coefficient of friction results using a sigmoid function, the transition temperature is also identified using the thermal model. The model is validated experimentally by measuring the tool-chip interface temperature using a two-color pyrometer at a specific cutting distance. Due to the cyclic behavior in interrupted cutting, where a steady-state condition may or may not be achieved, transient thermal modeling is required in this case. Input parameters required to identify the heat flux for the transient thermal model are obtained experimentally and the definitions of heat-flux-reducing factors along the cutting path are associated with interruptions and the repeating IPCF. The thermal model consists of two main parts: one is related to identifying the heat flux, and the other part involves the determination of the temperature field within the tool using a partial differential equation (PDE) solved numerically via a 2D finite element method.

Development of trench-shaped microstructure thermal neutron detector using α-Al2O3:C based on optically stimulated luminescence

Optical stimulated luminescence technique is increasingly used in neutron personal dosimetry, due to its capability of fast readout and potential for re-estimation of absorbed dose. The design configuration and performance of the microstructure optically stimulated luminescence neutron detector (MOSLND) using α-Al2O3:C was reported. To improve thermal neutron response, the MOSLND is structured with a matrix of microstructure trenches into the α-Al2O3:C substrate and backfilled with 6LiF. To obtain an optimum trench geometric parameter, several Monte Carlo simulations were performed using Geant4 code. The simulation results show that relatively high energy deposition can be realized for small cell dimensions with deep trenches, and is significantly increased compared with that of simple planar designs. Based on the results of calculation and practical limitation, the device was produced and tested using D2O-modrated 252Cf. The optimized minimal detectable dose (MDD) corresponding to signal integration time of 2 s is 7.2 μSv. The experimental results indicate that MOSLND can be a potential solution for personal neutron dosimetry.

MR-Neurography of the facial nerve in parotid tumors: intra-parotid nerve visualization and surgical correlation.

One of the most severe complications in surgery of parotid tumors is facial palsy. Imaging of the intra-parotid facial nerve is challenging due to small dimensions. Our aim was to assess, in patients with parotid tumors, the ability of high-resolution 3D double-echo steady-state sequence with water excitation (DE3D-WE) (1) to visualize the extracranial facial nerve and its tracts, (2) to evaluate their relationship to the parotid lesion and (3) to compare MRI and surgical findings. A retrospective study was conducted including all patients with parotid tumors, who underwent MRI from April 2022 to December 2023.Two radiologists independently reviewed DE3D-WE images, assessing quality of visualization of the facial nerve bilaterally and localizing the nerve's divisions in relation to the tumor. MRI data were compared with surgical findings. Forty consecutive patients were included (M:F = 22:18; mean age 56.3 ± 17.4years). DE3D-WE could excellently visualize the nerve main trunk and the temporofacial division in all cases. The cervicofacial branch was visible in 99% of cases and visibility was good. Distal divisions were displayed in 34% of cases with a higher visibility on the tumor side (p < 0.05). Interrater agreement was high (weighted kappa 0.94 ± 0.01 [95% CI 0.92-0.97]). Compared to surgery accuracy of MRI in localizing the nerve was 100% for the main trunk, 96% for the temporofacial and 89% for the cervicofacial branches. Facial nerve MR-neurography represents a reliable tool. DE3D-WE can play an important role in surgical planning of patients with parotid tumors, reducing the risk of nerve injury.

Revisiting the Pathophysiology of Intracranial Hemorrhage in Fetuses with Chiari II Malformation: Novel Imaging Biomarkers of Disease Severity?

Intracranial hemorrhage (ICH) has emerged as a notable concern in Chiari II malformation (CM II), yet its origins and clinical implications remain elusive. This study aims to validate the in utero prevalence of ICH in CM II and investigate contributing factors, and visualize the findings in a network format. A single-center retrospective review of fetal MRI scans obtained in fetuses with CM II (presenting January 2007 to December 2022) was performed for ICH utilizing EPI-T2* blood-sensitive sequence. Fetuses with aqueduct stenosis (AS) were included as a control group. The incidence of ICH and corresponding gestational ages were compared between CM II and AS cases, and morphometric measurements (inner/outer CSF spaces, posterior fossa, venous structure) were compared among the 4 1:1 age-matched groups: CM II+ICH, CM II-ICH, AS+ICH, and AS-ICH. Additionally, a co-occurrence network was constructed to visualize associations between phenotypic features in ICH cases. A total of 101 fetuses with CM II and 90 controls with AS at a median gestational age of 24.4 weeks and 22.8 weeks (P = .138) were included. Prevalence of ICH in fetuses with CM II was higher compared with the AS cases (28.7% versus 18.9%, P = .023), accompanied by congested veins (deep vein congestion mainly in young fetuses, and cortical veins may also be affected in older fetuses). ICH was notably correlated with specific anatomic features, essentially characterized by reduced outer CSF spaces and clivus-supraocciput angle. The co-occurrence network analysis reveals complex connections including bony defects, small posterior fossa dimensions, vermis ectopia, reduced CSF spaces, as well as venous congestion and venous sinus stenosis as pivotal components within the network. The high prevalence of ICH-detected by fetal MRI-among fetuses with CM emphasizes the pathophysiologic importance of venous congestion, ICH, and vasogenic edema. As indicators of disease severity, these features may serve as helpful additional imaging biomarkers for the identification of potential candidates for fetal surgery.

Failure assessment of corroded offshore pipelines using code-based approaches and a combination of numerical analysis and artificial neural network

The main purpose of the present paper is to investigate the failure pressure and the remaining life of the corroded offshore pipelines utilizing code-based methods such as ASME B31G, modified ASME B31G, DNV RP-F101 and FFS Level-1. Besides, the results of these approaches are compared with the responses of Finite Element Method (FEM) using Artificial Neural Network (ANN) model. To this purpose, the probability distribution of the corrosion defect length and depth as well as the corrosion rate values are obtained from an In-Line Inspection (ILI) survey of an offshore pipeline project in the Persian Gulf. In addition, a 3D verified numerical model of a corroded pipeline is constructed to conduct the numerical analyses. Using the numerical analysis data, a Multi-Layer Perceptron (MLP) model is created to estimate the failure pressure of the pipeline with arbitrary defect dimensions. Moreover, the remaining life of the corroded pipeline is quantified in order to prevent the catastrophic consequences of the pipeline failure. The results show that the MLP model is capable of estimating the failure pressure of the corroded offshore pipeline with quite acceptable accuracy compared with the mentioned code-based methods. Furthermore, the calculated failure pressure of the corroded pipeline can be sorted in ascending order as: (1) FFS-Level 1 (2) ASME modified B31G (3 & 4) ASME B31G & DNV RP-F101 (5) FEM + MLP. In fact, the failure pressure and the remaining life calculated by DNV RP-F101 are closer to the FEM + MLP results for the defects with small and medium dimensions. Diversely, the DNV RP-F101 method underestimates the failure pressure of the corroded pipeline when the defect dimensions become larger.

Nonlinear dynamics of dissipative water conveying SWCNT/MWCNT/Ferro nanofluid subject to radiation: Thermal analysis by linear slope regression

Carbon nanotubes have gained significant attention due to their unique properties like small dimensions, high thermal conductivity, and unique architecture. These nanotubes have enormous potential in various fields such as nanomedicine, mechanical compound materials, sensor devices, bio-sensors, and many other applications. The present study investigates the impact of adding nanoparticles such as iron oxide (Fe3O4), single-walled carbon nanotubes (SWCNT), and multi-walled carbon nanotubes (MWCNT) on magnetohydrodynamics (MHD) oscillatory water-based flow over a porous medium. The aim is to examine the effect of heat and mass transfer rate and radiative viscous dissipation that interacts with Fe3O4 nanoparticles and carbon nanotubes. The governing equations of the dynamic nanofluid systems are transformed into a set of coupled nonlinear partial differential equations through suitable dimensionless transformations and further converted into ordinary differential equations by taking appropriate solutions for oscillatory-type nanofluid flow. The homotopy perturbation method is applied to solve the governing equations with oscillatory boundary conditions and the solution is also compared with the numerical solver bvp4c. The rate of increase in the temperature and Heat Transfer are computed by the linear slope regression method and results are computed for nanoparticles SWCNT, MWCNT, and Ferro. Also, Skin friction and rate of heat transfer are computed and compared for the nanoparticles with varying Peclet and Eckert numbers. The velocity profile and temperature profile of SWCNT/MWCNT/Ferro nanofluids are being compared. The heat transfer rate is observed to be high for Ferro nanoparticles compared to SWCNT and MWCNT.

Accurate Description of Coulombic Interactions in Organic Field‐Effect Transistors Enabled by Efficient 3D Poisson's Equation Solver with Mixed Boundary Conditions

AbstractThe rational development of organic electronic devices can greatly benefit from a molecular‐level description, where an accurate description of the Coulombic interactions among charge carriers holds paramount importance. However, the molecular‐level organic field‐effect transistor (OFET) simulations do not fully include the short‐range charge‐carrier Coulombic interactions, thus limiting their accuracy. Here, an efficient solution is demonstrated to the 3D Poisson's equation with mixed boundary conditions, optimized for integration into the simulations of organic electronic devices. It leverages the finite difference method for discretization, the Krylov subspace iterative methods for solving the linear system, the algebraic multigrid algorithm for preconditioning, and OpenMP and CUDA parallelization for acceleration. For the organic field‐effect transistors of micrometer sizes or smaller dimensions, obtaining the electric potential within the device takes less than 0.1 s, which is sufficiently efficient for molecular‐level modeling. As a result, both short‐ and long‐range electrostatic interactions are successfully incorporated in the molecular‐level modeling of OFET devices. This integration significantly enhances the robustness of OFET modeling for future applications.