To optimize the heating properties of magnetic nanoparticles (MNPs) in magnetic hyperthermia applications, it is necessary to calculate the area of their hysteresis loops in an alternating magnetic field. The separation between “relaxation losses” and “hysteresis losses” presented in several articles is artificial and criticized here. The three types of theories suitable for describing hysteresis loops of MNPs are presented and compared to numerical simulations: equilibrium functions, Stoner–Wohlfarth model based theories (SWMBTs), and a linear response theory (LRT) using the Neel–Brown relaxation time. The configuration where the easy axis of the MNPs is aligned with respect to the magnetic field and the configuration of a random orientation of the easy axis are both studied. Suitable formulas to calculate the hysteresis areas of major cycles are deduced from SWMBTs and from numerical simulations; the domain of validity of the analytical formula is explicitly studied. In the case of minor cycles, the hysteresis area calculations are based on the LRT. A perfect agreement between the LRT and numerical simulations of hysteresis loops is obtained. The domain of validity of the LRT is explicitly studied. Formulas are proposed to calculate the hysteresis area at low field that are valid for any anisotropy of the MNP. The magnetic field dependence of the area is studied using numerical simulations: it follows power laws with a large range of exponents. Then analytical expressions derived from the LRT and SWMBTs are used in their domains of validity for a theoretical study of magnetic hyperthermia. It is shown that LRT is only pertinent for MNPs with strong anisotropy and that SWMBTs should be used for weakly anisotropic MNPs. The optimum volume of MNPs for magnetic hyperthermia is derived as a function of material and experimental parameters. Formulas are proposed to allow to the calculation of the optimum volume for any anisotropy. The maximum achievable specific absorption rate (SAR) is calculated as a function of the MNP anisotropy. It is shown that an optimum anisotropy increases the SAR and reduces the detrimental effects of the size distribution of the MNPs. The optimum anisotropy is simple to calculate; it depends only on the magnetic field used in the hyperthermia experiments and the MNP magnetization. The theoretical optimum parameters are compared to those of several magnetic materials. A brief review of experimental results as well as a method to analyze them is proposed. This study helps in the determination of suitable and unsuitable materials for magnetic hyperthermia and provides accurate formulas to analyze experimental data. It is also aimed at providing a better understanding of magnetic hyperthermia to researchers working on this subject.

/pdf/simple-models-for-dynamic-hysteresis-loop-calculations-of-2c72rhikay.pdf

Simple models for dynamic hysteresis loop calculations of magnetic single-domain nanoparticles: Application to magnetic hyperthermia optimization

To optimize the heating properties of magnetic nanoparticles (MNPs) in magnetic hyperthermia applications, it is necessary to calculate the area of their hysteresis loops in an alternating magnetic field. The three types of theories suitable for describing the hysteresis loops of MNPs are presented and compared to numerical simulations: equilibrium functions, Stoner-Wohlfarth model based theories (SWMBTs) and linear response theory (LRT). Suitable formulas to calculate the hysteresis area of major cycles are deduced from SWMBTs and from numerical simulations; the domain of validity of the analytical formula is explicitly studied. In the case of minor cycles, the hysteresis area calculations are based on the LRT. A perfect agreement between LRT and numerical simulations of hysteresis loops is obtained. The domain of validity of the LRT is explicitly studied. Formulas to calculate the hysteresis area at low field valid for any anisotropy of the MNP are proposed. Numerical simulations of the magnetic field dependence of the area show it follows power-laws with a large range of exponents. Then, analytical expressions derived from LRT and SWMBTs are used for a theoretical study of magnetic hyperthermia. It is shown that LRT is only pertinent for MNPs with strong anisotropy and that SWMBTs should be used for weak anisotropy MNPs. The optimum volume of MNPs for magnetic hyperthermia as function of material and experimental parameters is derived. The maximum specific absorption rate (SAR) achievable is calculated versus the MNP anisotropy. It is shown that an optimum anisotropy increases the SAR and reduces the detrimental effects of size distribution. The optimum anisotropy is simple to calculate and depends on the magnetic field used in the hyperthermia experiments and on the MNP magnetization only. The theoretical optimum parameters are compared to the one of several magnetic materials.

/pdf/simple-models-for-dynamic-hysteresis-loops-calculation-45i5rokoof.pdf

Simple models for dynamic hysteresis loops calculation: Application to hyperthermia optimization

Heating efficiency in magnetic nanoparticle hyperthermia

Stimulus responsive nanogels are polymeric nanoparticles which are capable of responding to external stimuli by changing their physico-chemical properties, such as volume, water content, refractive index, permeability, and hydrophilicity–hydrophobicity. Compared with other polymer nanoparticles used for drug delivery, stimulus responsive nanogels are noted for their ability to encapsulate bioactive drugs, their high stability for prolonged circulation in the blood stream, and their controlled release and site-specific targeting of loaded drugs modulated by environment stimuli. Particularly, the application of stimulus responsive nanogels provides an interesting opportunity for drug delivery in which the delivery system becomes an active participant, rather than a passive carrier, in the optimization of disease therapy. In this article, the authors review the recent developments in the preparation and application in drug delivery of stimulus responsive nanogels which can respond to small temperature and pH changes, light, magnetic field, biomolecule recognition (specifically glucose responsive nanogels for insulin delivery), and multi-responsive nanogels. The limitations and future improvements of stimulus responsive nanogels are also discussed.

Stimulus responsive nanogels for drug delivery

Maghemite and cobalt ferrite anionic magnetic nanoparticles enter tumor cells and can be used as heat sources when exposed to a high-frequency magnetic field. Comparative studies of the two particles enable to unravel the magnetic heating mechanisms (Neel relaxation vs. Brown relaxation) responsible for the cellular temperature rise, and also to establish a simple model, adjusted to the experimental results, allowing to predict the intracellular heating efficiency of iron oxide nanoparticles. Hence, we are able to derive the best nanoparticle design for a given material with a view to intracellular hyperthermia-based applications.

Intracellular heating of living cells through Néel relaxation of magnetic nanoparticles

http://magneticliquid.narod.ru/autority/389.pdf

The heating effect of magnetic fluids in an alternating magnetic field

In this simulation, the nanoparticle distribution and entropy generation were studied using the Buongiorno ’ s developed two-phase model and magnetic ﬁ eld inside a porous semiannulus cavity. The in ﬂ uence of three terms was considered in the Buongiorno ’ s developed two-phase model such as Brownian motion, thermophoresis, and magnetophoresis e ﬀ ects. In addition, the entropy generation was assessed due to temperature and velocity gradient. The evidence showed that the e ﬀ ects of the magnetic ﬁ eld in high porosities and volume fraction of nanoparticles were remarkable on the Nusselt number and entropy generation. Also, irreversibility due to heat transfer is much greater than ﬂ uid friction.

Cooling a Hot Semiannulus with Constant Heat Flux by Using Fe 3 O 4 -Water Nanofluid and a Magnetic Field: Natural Convection Mechanism

In this simulation, the nanoparticle distribution and entropy generation were studied using the Buongiorno’s developed two-phase model and magnetic field inside a porous semiannulus cavity. The influence of three terms was considered in the Buongiorno’s developed two-phase model such as Brownian motion, thermophoresis, and magnetophoresis effects. In addition, the entropy generation was assessed due to temperature and velocity gradient. The evidence showed that the effects of the magnetic field in high porosities and volume fraction of nanoparticles were remarkable on the Nusselt number and entropy generation. Also, irreversibility due to heat transfer is much greater than fluid friction.

Cooling a Hot Semiannulus with Constant Heat Flux by Using <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1">
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In recent years, underwater shield tunnels are being developed according to large-scale sections. The problems of large buried depth and high water pressure have posed major challenges to the safety of segmented structures. The load-bearing capacity and damage of segmented structures under high water pressure features have always attracted attention. Based on a machine learning approach to smart grid energy management, this paper proposes a design method for high voltage tunnels in a balanced groundwater environment and tests the capacity of the high voltage tunnels. Based on the high water pressure failure test phenomenon of the large-section shield tunnel of the GIL project, this paper analyzes the failure characteristics and laws of the segment structure under high water pressure conditions. On this basis, an evaluation index for the load-bearing performance of the segment structure is proposed, and control suggestions are given based on the research results. According to the fault characteristics and the section structure law, the section performance evaluation index is proposed, and the control parameter recommendations are given based on the test results. Valuable discoveries and breakthroughs have been made in the failure of the prototype segment structure and the difference in the mechanical properties of the segment structure in the form of the high water pressure tunnel assembly. The research results show that under the condition of staggered assembly of high-voltage tunnels, the maximum dislocation amount of the high-voltage tunnel structure during instability failure is 10 mm, and the bolt strength is improved. The more important aspect is the existence of concave and tenon between the rings. In structure, the maximum stress of the bolts between the rings is only 38.6% of the yield stress at the time of instability failure. This indicates that the distributed concave-convex tenon between the segments not only can control the dislocation of the segments but also can ensure that the longitudinal bolts are well protected. It is safe to ensure the pressure resistance of the high water pressure tunnel.

New Method for High Water Pressure Tunnel Design Based on Machine Learning for Smart Grid Energy Management and Groundwater Environmental Balance

In recent years, with the rapid development of tunnel construction in China, the length of tunnels has continued to increase, and the consequent tunnel disease detection has attracted more and more attention from maintenance departments. Among many diseases, lining cracks are the most common, which directly reflect the stress of the lining, which is very important for the study of tunnel diseases. In view of the current detection status and detection requirements, this article has carried out research work on a vehicle-mounted tunnel lining crack detection system based on image processing. Due to the grayscale difference between the cracks on the lining surface and the lining background, these differences lead to significant crack edge features and relatively stable detection. Therefore, this article designs an intelligent edge algorithm system for cracks on the lining surface to detect the edges of the image, extract the edges of cracks, and remove useless interference information in the lining background. The experiment proves that the paired sample t-test can find that after the experiment is over, the 
 
 P
 
 value of different edge detection operators for global threshold segmentation is less than 0.05, which has a significant difference. The Canny, Deriche, and Lanser filters are relatively strong, and the extracted crack edge noise is relatively small. Finally, the parameter values of the crack image are calculated, and the calculated values of the crack parameters provide a scientific and reliable basis for tunnel safety evaluation.

/pdf/intelligent-edge-computing-detection-vehicle-and-detection-171ckg4m.pdf

Zhengqiang Yang

Papers

The heating effect of magnetic fluids in an alternating magnetic field

Cooling a Hot Semiannulus with Constant Heat Flux by Using Fe 3 O 4 -Water Nanofluid and a Magnetic Field: Natural Convection Mechanism

Cooling a Hot Semiannulus with Constant Heat Flux by Using <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <msub> <mrow> <mtext>Fe</mtext> </mrow> <mrow>

New Method for High Water Pressure Tunnel Design Based on Machine Learning for Smart Grid Energy Management and Groundwater Environmental Balance

Intelligent Edge Computing Detection Vehicle and Detection Method Based on Tunnel Lining Concrete