Minimal Dispersion Research Articles

Impact of double diffusion on solid particle dispersion in rotated cylinders with nano-enhanced phase change materials

This study introduces an innovative approach that combines the Incompressible Smoothed Particle Hydrodynamics method with Artificial Neural Networks to examine the dispersion of solid particles within rotated circular cylinders filled with nano-enhanced phase change materials. This method addresses the limitations of traditional numerical techniques by improving accuracy in complex geometries and dynamic boundary conditions. The various parameters are examined, including the lengths of low sources in boundary walls Lb, dimensionless time τ, Hartmann number (Ha), Darcy number (Da), thermal radiation parameter (Rd), and Rayleigh number (Ra). The solid particles are initially situated at the center gate between the two circular cylinders, maintained at elevated temperature Th and concentration Ch. Due to the upward direction of convection flow, the solid particles are consistently dispersed into the top circular cylinder. The findings offer valuable insights into the system's behavior. The dispersion of solid particles within the NEPCM is influenced by both τ and Lb, showcasing minimal dispersion for τ≤0.1 and intensified dispersion for τ≥0.2, particularly augmented by larger Lb. The heat capacity ratio (Cr) exhibits a decrease with increasing Lb at multiple time points. A decrease in the Darcy number significantly slows down the dispersion of solid particles because of the substantial resistance posed by the porous medium. As the Rayleigh number increases, there is an enhanced dispersion of solid particles into the upper circular cylinder and heightened temperature distributions. Additionally, the average Nusselt number Nu¯ and Sherwood number Sh¯ decrease with the increase in Lb due to the expansion of low-temperature and concentration source. When the length Lb was increased from 0.25 to 1, Nu¯ and Sh¯ decreased by approximately 76% and 67%, respectively, underscoring the impact of geometric configuration on heat and mass transfer efficiency. The study highlights the effectiveness of the MLP model in predicting Nu¯ and Sh¯ values through graphical analysis, showing significant agreement with the target values. The results demonstrated notable improvements in managing particle dispersion and heat/mass transfer, emphasizing the potential of this integrated approach for applications in thermal management and energy optimization.

Physics-based natural gradient boosting probabilistic prediction model for seismic failure modes of reinforced concrete columns

A novel physics-based natural gradient boosting (PNGB) probabilistic prediction model for flexure failure (FF), flexure-shear failure (FSF) and shear failure (SF) of reinforced concrete (RC) columns under strong earthquakes has been developed to address the limitations of empirical and machine learning (ML) models, which often fail to learn physical laws, insufficiently consider uncertainties, and exhibit poor generalization performance. Firstly, an improved natural gradient boosting (NGB) probabilistic model of seismic failure modes was created by using natural gradient boosting and gradient boosting regressor algorithms. Then a new hyperparameter optimization method for the improved NGB probabilistic model was proposed based on the ML algorithms and the physical laws. Finally, the predictive performance and engineering practicability of the PNGB probabilistic model were verified compared to empirical and ML models. According to the analysis results, the PNGB model can effectively improve the predictive recall of FF, FSF and SF by about 19–65 %, 20–67 % and 20–56 % respectively compared with empirical models, and by about 1–7 %, 7–43 % and 6–32 % respectively compared with ML models. Moreover, the PNGB model exhibits satisfactory generalization performance and minimal dispersion, which can be used to calibrate the ML models based on the confidence intervals. Furthermore, the result predicted by the PNGB model satisfies the physical laws relating to the seismic failure modes and design parameters, which can further represent the competitive relationships of various seismic failure modes.

Phenotypic Characterization of the Martina Franca Donkey: An Endangered Italian Donkey Breed.

The Martina Franca (MF) donkey breed (Equus asinus) primarily inhabits the rural areas surrounding the homonymous municipality, as well as neighboring municipalities in the provinces of Bari and Brindisi, all located in the Apulia region of Italy. The objective of this study was to assess the current phenotype through the evaluation of 27 morphologic measurements. The study was conducted on 73 female and 18 male breeding animals from eight different herds located in central and southern Italy. Statistical analysis was performed in order to demonstrate statistical differences between males and females, as well as sexual dimorphism and uniformity of all measurements in both genders. The results demonstrated that the mean of three parameters used for the evaluation of an MF donkey (height at withers, circumference of thorax, and shin circumference) are highly representative of the population, with minimal dispersion Cv^ = 0.05-0.06 up to a maximum of 10%, as evidenced by relatively low standard deviations across observed measurements in both genders. Regarding sexual dimorphism, a statistically significant difference was found between males and females. This dimorphism is linked to reproductive activity and is useful during gestation. Overall, our findings suggest that the MF donkey phenotype has been largely preserved over time with high uniformity in males, slight inhomogeneity in the female population, and less variability in both genders.

Experimental studies on controlling dispersion and fluid flow in paper membranes/assays using hydrogel

Paper membranes find applications in various fields, including Point-of-Care (POC) diagnostics, separation, filtration, and fluid transport. Still, they are frequently plagued by dispersion-related issues that lead to uneven flow, further affecting sensitivity and specificity, especially in detection assays. Hence, flow control in paper membranes becomes essential to achieving an effective paper-based platform. The present work develops a novel methodology based on adaptive flow regulation to optimize dispersion and flow control. This approach leverages real-time data to measure the controlled flow rates and prevent dispersion using hydrogel across paper-based membranes. Effects of three major parameters, namely mixing speed (100 rpm – 400 rpm), hydrogel concentration (6.45 mg/ml–12.9 mg/ml) for preparing hydrogel, and types of filter paper membranes are investigated in detail. Imaging techniques are applied to capture high-resolution images of fluid behavior on the paper strip surface at various time intervals, and the results are demonstrated in terms of mean intensity as a quantifiable indicator (0−255). It was found that the hydrogel prepared using 400 rpm mixing speed at a specific concentration exhibited significant resistance to the fluid flow with minimal dispersion. Furthermore, the Filter-paper 441 membrane is compared with other filter-paper membranes used in this experiment. Notably, a 43 %-79 % reduction in dispersion was observed for the hydrogel-laden paper membranes. Additionally, the dispersion was largely minimized even when lower concentrations of sodium hydroxide were detected on hydrogel-based paper assays, enhancing its sensitivity. Overall, this research offers a multifaceted solution to reduce dispersion and optimize flow control in paper-based membranes using hydrogel to improve the performance of the paper assays.

Minimal dispersion on the cube and the torus

We improve some upper bounds for minimal dispersion on the cube and torus. Our new ingredient is an improvement of a probabilistic lemma used to obtain upper bounds for dispersion in several previous works. Our new lemma combines a random and non-random choice of points in the cube. This leads to better upper bounds for the minimal dispersion.

Quasi-BICs enhanced second harmonic generation from WSe2 monolayer.

Quasi-bound states in the continuum (quasi-BICs) offer unique advantages in enhancing nonlinear optical processes and advancing the development of active optical devices. Here, the tunable robust quasi-BICs resonances are experimentally achieved through the engineering of multiple-hole Si-metasurface. Notably, the quasi-BICs mode exhibits flat bands with minimal dispersion at a wide range of incident angles, as demonstrated by the angle-resolved spectroscopy measurements. Furthermore, we demonstrate a giant second-harmonic generation (SHG) enhancement by coupling a WSe2 monolayer to the quasi-BICs hosted in the metasurface. Leveraging the strong local electric field and high state density of the observed quasi-BICs, the SHG from the WSe2 monolayer can be enhanced by more than two orders of magnitude. Our work paves the way for effectively enhancing nonlinear optical processes in two dimensional (2D) materials within the framework of silicon photonics and is expected to be applied in nonlinear optical devices.

Spinel ferrites having conductive grains, resistive interfacial boundaries and relaxation mechanism for possible supercapacitor applications

Linear increase in crystallite size (16–24 nm) of MnxZn1−xFe2O4 nanostructures and mixed behavior of lattice constant (8.429–8.462 Å) is reported. The system exhibits considerable promise for microwave applications due to its elevated dielectric constants and minimal dispersion losses from 20 Hz to 20 MHz. With x = 0.75, sample is good for energy storage devices like supercapacitors due to large specific surface area (53 m2/g) and dielectric constant. These samples exhibit maximum relaxation times ranging from 1.97 × 10−7 s to 2.43 × 10−4 s, with corresponding relaxation energy values spanning from 159.22 meV to 341 meV for x = 0 and x = 1 samples. The Cole-Cole plots reveal that grains exhibit conductive behavior at lower frequencies, while grain boundaries contribute significantly to the resistive behavior. Additionally, we have introduced Bode diagrams and equivalent electronic circuit models for the first time, offering valuable insights into the electrical behavior of the nanomaterial samples.

МОДЕЛЮВАННЯ ВПЛИВУ НА СТРУКТУРУ ТА ВЛАСТИВОСТІ ЗМІНИ РЕЖИМІВ ОБРОБКИ НИЗЬКОВУГЛЕЦЕВОЇ СТАЛІ

Round bar sections made from the low-carbon SAE 1008 steel grades require a continuously increase of the improvements of the reliable quality assurance of the system. The grain size, leading to changes in mechanical properties, is the most important microstructure parameter. Influence of the parameters of the deformation and heat treatment on the structure of the investigated steel, which is ferrite with small areas of lamellar pearlite, was determined due to metallographic examinations. Established, based on the conducted computational and analytical investigations, that after high-speed hot deformation, exactly the temperature of the end of the cooling affected the average conditional diameter of the grain. Cooling to temperatures ~ А1 + 150ºС after hot deformation, followed by slow cooling, during which forms a more uniform grain, which ensures minimal dispersion of the mechanical properties, is rational for rolled steels of the SAE 1008 grades.

DFT study of optoelectronics and transport properties of double perovskites Cs2YCuX6 (X = Cl, Br, I) for energy conversion devices

Double perovskite halides (DPHs) hold great promise for applications in energy conversion. This article provides a comprehensive exploration of the elastic, thermoelectric and optoelectronic characteristics of Cs2YCuX6 (X = Cl, Br, I) DPHs. The elastic constants and phonon dispersion curves reveal ductile nature and mechanical and thermodynamic stability of the examined materials. The Born stability criteria ensures structural stability, while the formation energy ranging from −2.28 to −1.68 eV signifies thermodynamic viability. Furthermore, the thermodynamic stability of investigated double perovskites Cu2YCuX6 (X = Cl, Br, I) have been verified by performing ab-initio finite temperature molecular dynamics (MD) simulation. The examination of mechanical characteristics affirms the ductile nature of the material, and its substantial anisotropic factor enhance its significance for device fabrication. The band gaps calculated at 2.65 eV, 2.55 eV, and 2.45 eV from band structures, highlight the significance of the studied double perovskites (DPs) for optoelectronic applications. Optical parameters yield information on minimal dispersion and expansive absorption band. Additionally, transport characteristics are analyzed through parameters such as Seebeck coefficient, thermal conductivity, electrical conductivity, and the Figure of merit (ZT).

A tight lower bound on the minimal dispersion

We give a new lower bound for the minimal dispersion of a point set in the unit cube and its inverse function in the high dimension regime. This is done by considering only a very small class of test boxes, which allows us to reduce bounding the dispersion to a problem in extremal set theory. Specifically, we translate a lower bound on the size of r-cover-free families to a lower bound on the inverse of the minimal dispersion of a point set. The lower bound we obtain matches the recently obtained upper bound on the minimal dispersion up to logarithmic terms.

Transport, dispersion, and degradation of nonpoint source contaminants during flood‐managed aquifer recharge

AbstractIn water‐stressed regions of the world, the inundation of working landscapes to replenish aquifers—known as flood‐managed aquifer recharge (flood‐MAR)—has become a valuable tool for sustainable groundwater management. Due to their diverse land use histories, however, many potential recharge sites host nonpoint source contaminants (such as salts, pesticides, and fertilizers) within the vadose zone that may flush to groundwater during recharge operations. To identify the controls on contaminant migration, we perform stochastic simulations of flood‐MAR through a heterogeneous alluvial aquifer and apply transient particle tracking to evaluate conservative and reactive contaminant transport over 80 years of recharge operations. With semi‐annual recharge events, the water table begins to rise 0.13–1.84 years after the first inundation event while solutes take much longer (11 to 80 years) to transit the 45‐m thick unsaturated zone. We derive a parametric expression for the ratio of celerity (or rate of pressure transmission) to velocity of the flood‐MAR wetting front and show that this simplified expression agrees with values calculated from heterogeneous model simulations. Slow solute velocities (0.25–1.75 m year−1) allow for significant contaminant removal through denitrification, but the contaminant plume experiences minimal dispersion or dilution over this time, reaching the water table as a sharp front. Our results suggest that minimizing groundwater velocity and maximizing groundwater celerity during flood‐MAR should optimize increases in water supply while limiting water quality degradation.

The Sonopet iQ® Ultrasonic Bone Aspirator in Craniofacial Surgery: A Scoping Review and Qualitative Analysis

Background: The Sonopet iQ® Ultrasonic Aspirator is a surgical tool used for the fragmentation and emulsification of bone and soft tissue. Ultrasonic vibrations emulsify bone with cited benefits of decreased damage to surrounding soft tissue and minimal heat dispersion. Despite these potential benefits, there is a paucity of published articles on the safety and efficacy of the Sonopet® in the setting of craniofacial surgery. Methods: In accordance with PRISMA guidelines, MEDLINE and Pubmed were searched for articles that studied use of the Sonopet® for osteotomies in the craniofacial setting. Studies exclusively investigating soft tissue aspiration were excluded. Results: Out of 61 articles discovered, 22 met inclusion criteria and discussed a total of 816 patients. Of the 22 articles, there were 8 retrospective chart reviews, 7 case series, 5 cadaver models, and 2 case reports. Studies spanned multiple disciplines including otolaryngology, ophthalmology, craniofacial surgery, neurosurgery, and oral and maxillofacial surgery. Despite its frequent use in orthognathic and cranial vault remodeling surgery, only 4 studies described its use in these fields. The most commonly cited benefits of the Sonopet® were enhanced ergonomics and safety, discussed in 20 of the included studies. Eighteen studies claimed the Sonopet® was safer to use in surgically tight spaces compared to traditional drills. Four studies found decreased bone dust generation by the Sonopet® compared to conventional cutting devices. No studies reported an increase in postoperative complications due to the device. The most commonly cited disadvantage was the cost of the device, however, the majority of authors believed the benefits of the device outweighed the increase in cost. Conclusions: There is a dearth of research investigating the use of the Sonopet® in craniofacial surgery. Available studies emphasize the ergonomic and safety benefits of the Sonopet® and encourage expanded use of the device despite its cost.

The Minimal Spherical Dispersion

We prove upper and lower bounds on the minimal spherical dispersion, improving upon previous estimates obtained by Rote and Tichy in (Anz Österreich Akad Wiss Math Nat Kl 132:3–10, 1995). In particular, we see that the inverse N(ε,d)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N(\\varepsilon ,d)$$\\end{document} of the minimal spherical dispersion is, for fixed ε>0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varepsilon >0$$\\end{document}, linear in the dimension d of the ambient space. We also derive upper and lower bounds on the expected dispersion for points chosen independently and uniformly at random from the Euclidean unit sphere. In terms of the corresponding inverse N~(ε,d)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widetilde{N}(\\varepsilon ,d)$$\\end{document}, our bounds are optimal with respect to the dependence on ε\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varepsilon $$\\end{document}.

CFD Analysis of Microplastic Transport over the Slopes

Microplastics, ubiquitous in our environment, are significantly impacted by the hydrodynamic conditions around them. This study utilizes CFD to explore how various breaker types influence the dispersion and accumulation of microplastics in nearshore areas. A special focus is given to the impact of wave dynamics and particle size, particularly on buoyant microplastics in spilling breakers. It was discovered that spilling breakers, common on gently sloping seabeds, encourage broad dispersion of microplastics, notably for smaller-sized particles. Plunging breakers exhibit a similar pattern but with less dispersion and an initial forward movement of neutral and heavy particles. Surging breakers feature minimal dispersion and a distinct oscillatory motion. It has been observed that medium-sized particles with a 1 mm diameter in this work exhibit the most substantial forward movement, likely due to an optimal balance between inertia and viscosity, enabling an effective response to wave momentum. Larger particles, influenced mainly by inertia, tend to show less dispersion and advection. Meanwhile, smaller particles, more affected by viscosity, demonstrate greater dispersion, interacting extensively with wave-induced turbulence. This study reveals the significance of inertia in the behavior of microplastics over slopes, emphasizing the importance of considering inertial effects for precise modeling of microplastic movement in nearshore areas.

Highly efficient and aberration-free off-plane grating spectrometer and monochromator for EUV—soft X-ray applications

We demonstrate a novel flat-field, dual-optic imaging EUV—soft X-ray spectrometer and monochromator that attains an unprecedented throughput efficiency exceeding 60% by design, along with a superb spectral resolution of λ/Δλ > 200 accomplished without employing variable line spacing gratings. Exploiting the benefits of the conical diffraction geometry, the optical system is globally optimized in multidimensional parameter space to guarantee optimal imaging performance over a broad spectral range while maintaining circular and elliptical polarization states at the first, second, and third diffraction orders. Moreover, our analysis indicates minimal temporal dispersion, with pulse broadening confined within 80 fs tail-to-tail and an FWHM value of 29 fs, which enables ultrafast spectroscopic and pump-probe studies with femtosecond accuracy. Furthermore, the spectrometer can be effortlessly transformed into a monochromator spanning the EUV—soft X-ray spectral region using a single grating with an aberration-free spatial profile. Such capability allows coherent diffractive imaging applications to be conducted with highly monochromatic light in a broad spectral range and extended to the soft X-ray region with minimal photon loss, thus facilitating state-of-the-art imaging of intricate nano- and bio-systems, with a significantly enhanced spatiotemporal resolution, down to the nanometer–femtosecond level.

Scalable kernel balancing weights in a nationwide observational study of hospital profit status and heart attack outcomes.

Weighting is a general and often-used method for statistical adjustment. Weighting has two objectives: first, to balance covariate distributions, and second, to ensure that the weights have minimal dispersion and thus produce a more stable estimator. A recent, increasingly common approach directly optimizes the weights toward these two objectives. However, this approach has not yet been feasible in large-scale datasets when investigators wish to flexibly balance general basis functions in an extended feature space. To address this practical problem, we describe a scalable and flexible approach to weighting that integrates a basis expansion in a reproducing kernel Hilbert space with state-of-the-art convex optimization techniques. Specifically, we use the rank-restricted Nyström method to efficiently compute a kernel basis for balancing in nearly linear time and space, and then use the specialized first-order alternating direction method of multipliers to rapidly find the optimal weights. In an extensive simulation study, we provide new insights into the performance of weighting estimators in large datasets, showing that the proposed approach substantially outperforms others in terms of accuracy and speed. Finally, we use this weighting approach to conduct a national study of the relationship between hospital profit status and heart attack outcomes in a comprehensive dataset of 1.27 million patients. We find that for-profit hospitals use interventional cardiology to treat heart attacks at similar rates as other hospitals but have higher mortality and readmission rates.

Numerical Investigation of Flow Hydrodynamics in a Flow Field and Porous Substrate Configuration for Redox Flow Battery Application

In the recent past, most of the literature reported that the electrolyte circulations in parallel flow field configurations exhibit severe non-uniformity with higher Pressure Drop (Δp). The present work proposes a three-dimensional computational design of flow field configurations to achieve a single-phase uniform flow with minimal pump power and flow dispersion over an active cell area of 131cm2 for All Iron Redox Flow Battery (AIRFB). Computational investigation of the Pressure Drop (Δp), electrolyte flow velocity and uniform flow distribution in the channels and through the graphite felt electrode under various flow conditions was conducted using the Computational Fluid Dynamics (CFD) tool. It is observed from the results that the Multi-Channel Serpentine Flow Field (MCSFF) has the least pressure drop among the other flow fields. However, the Cross-Split Serpentine Flow Field (CSSFF) resulted in better flow circulation and dispersion over the entire active cell area with a high uniformity index, operating at a wide range of flow rates with a reasonable Pressure Drop (Δp). The porous media permeability and a strong function of Compression Ratio (CR) were numerically validated from the well-known correlation existing in the literature. At CR 50% it was observed that the volume uniformity index of the felt was 69%, which would correspondingly enhance the rate of mass transfer and electro-kinetics at electrode felt and ion conductivity across the membrane. The CSSFF configuration is predominant in terms of uniform flow distribution and wettability at the defined operating conditions resulting in enhanced cell performance.

Synergizing a Large Ordinary Nernst Effect and Axis-Dependent Conduction Polarity in Flat Band KMgBi Crystals.

The exploration of quantum materials in which an applied thermo/electrical/magnetic field along one crystallographic direction produces an anisotropic response has led to unique functionalities. Along these lines, KMgBi is a layered, narrow gap semiconductor near a critical state between multiple Dirac phases due to the presence of a flat band near the Fermi level. The valence band is highly anisotropic with minimal cross-plane dispersion, which, in combination with an isotropic conduction band, enables axis-dependent conduction polarity. Thermopower and Hall measurements indicate dominant p-type conduction along the cross-plane direction, and n-type conduction along the in-plane direction, leading to a significant zero-field transverse thermoelectric response when the heat flux is at an angle to the principal crystallographic directions. Additionally, a large Ordinary Nernst effect (ONE) is observed with an applied field. It arises from the ambipolar term in the Nernst effect, whereby the Lorentz force on electrons and holes makes them drift in opposite directions so that the resulting Nernst voltage becomes a function of the difference between their partial thermopowers, greatly enhancing the ONE. It is proven that axis-dependent polaritycan synergistically enhance the ONE, in addition to leading to a zero-field transverse thermoelectric performance.

Understanding Mold Wear Mechanisms and Optimizing Performance through Nico Coating: An In-Depth Analysis

This research investigates the wear mechanism of molds and examines the worn areas using high power microscopes and SEM (Scanning Electron Microscopy). In addition, EDS (Energy Dispersive Spectroscopy) and XRF (X-ray fluorescence) techniques are used to compare the worn areas with the normal areas. The results indicate that the wear mechanism of the molds is similar to adhesive wear. To address the issue of die wear, the application of Nico coating to the copper substrate surface is investigated. Two sample preparation methods, namely DC power supply and dual pulse power supply, are employed. SEM analysis shows that the sample group prepared using the dual pulse power supply has a relatively dense surface coating. The samples with a 60:40 weight ratio of Nico exhibit the highest average hardness and thickness, with minimal dispersion as indicated by the low standard deviation. The samples also show minimal roughness. Repeat tests under the same conditions confirm that the coating surface remains dense and uniform with a hardness of 467.628 hv, a thickness of 43.0665 μm and a roughness of 4.331 nm. The nanoindenter test results show that the coating has improved wear resistance (−28.7 nm) compared to the original mold (−142.4 nm), an increase of 80%.

Is Drug Delivery System a Deterministic or Probabilistic Approach? A Theoretical Model Based on the Sequence: Electrodynamics–Diffusion–Bayes

Commonly, it is accepted that oncology treatment would yield outcomes with a certain determinism without any quantitative support or mathematical model that establishes such determinations. Nowadays, with the advent of nanomedicine, the targeting drug delivery scheme has emerged, whose central objective is the uptake of nanoparticles by tumors. Once they are injected into the bloodstream, it is unclear as to which process governs the directing of nanoparticles towards the desired target, deterministic or stochastic. In any scenario, an optimal outcome, small toxicity and minimal dispersion of drugs is expected. Commonly, it is expected that an important fraction of them can be internalized into tumor. In this manner, due to the fraction of nanoparticles that have failed to uptake, the success of the drug delivery scheme might be at risk. In this paper, a theory based on the sequence electrodynamics–diffusion–Bayes theorem is presented. The Bayesian probability that emerges at the end of the sequence might be telling us that dynamical processes based on the injection of electrically charged nanoparticles might be dictated by stochastic formalism. Thus, rather than expecting a deterministic process, the chain of events would convert the drug delivery scheme to be dependent on a sequence of conditional probabilities.