Diffusive Motion Research Articles

Acupuncture Alleviates Chronic Ischemic White Matter Injury in SHR Rats via JNK-NMDAR Circuit.

To study the protective mechanism of acupuncture at "Jiangya Recipe" on chronic ischemic white matter injury in spontaneously hypertensive rats (SHR) and the regulation of Jun N-terminal kinase-N-methyl-D-aspartate receptor (JNK-NMDAR) loop. A hypertensive white matter injury model was established in 46 male SHR rats aged 11 weeks by bilateral common carotid artery tapering (SHR-2VGO). In the SHR sham operation group, only bilateral common carotid arteries were isolated and in the SHR-2VGO modeling group, 36 rats were used for microcoil spring clip implantation to narrow the common carotid arteries and then, after 2 weeks of modeling, rats with impaired motor function were removed, and SHR-2VGO rats with successful final models were randomly divided into the model group, JNK blocking group, and acupuncture group. The sham operation group, model group, and JNK blocking group underwent the same grasping fixation, and the acupuncture group received acupuncture at acupoints "Jiangya Fang" once daily. In the JNK blocker group, an injection cannula was implanted into the lateral ventricle and sp600125 was injected into the lateral ventricle at 4.5 ul/day for 4 weeks. One week after the end of the intervention, white matter lesions were detected by MRI DWI and T2 imaging, and the learning and memory ability of rats was tested by Y-Maze and Passive Avoidance. Myelin density was detected by luxol fast blue (LFB) staining, also axon arrangement, myelin integrity, and thickness of neurons were detected by electron microscopy; neuronal morphology and the number of Nissl bodies in the hippocampus were detected by Nissl staining, dendritic spine density changes were detected by Golgi staining, and JNK, NMDAR1, and N-methyl-D-receptor 2B (NMDAR2B) in DG, CA3 region of hippocampus were detected by immunohistochemistry, protein expression of p-JNK/JNK, p-NMDAR1/NMDAR1, NMDAR2B, GSK3β protein expression in the fimbria of hippocampus was detected by Western blot. The Y maze test of SHR-2VGO+Acu and SHR-2VGO+ sp600125 group showed that the spontaneous alternating reaction rate increased significantly. At the same time, the incubation period increased significantly and the number of errors decreased significantly in Passive Avoidance. MRI T2WI showed that the white matter high signal of the corpus callosum, internal capsule and hippocampal fimbria in the SHR-2VGO+ sp600125 and SHR-2VGO+Acu groups was significantly lower than that in the SHR-2VGO model group, and the striatum and anterior commissure were not obvious. DWI showed that the SHR-2VGO model group had scattered high signal and limited diffusion movement in both the internal capsule and striatum, but the difference between groups was not obvious. Compared with SHR-2VGO rats, LFB staining of SHR-2VGO + sp600125 and SHR-2VGO +Acu groups showed significant relaxation of myelin porosity in corpus callosum, striatum, inner capsule, anterior commissure and hippocampal fimbria, and electron microscopy showed improved axonal myelin integrity and thickness in corpus callosum region. Also, the number of blue patchy Nissl bodies increased, and the number and complexity of dendritic spines increased significantly in Golgi staining. Immunohistochemical detection showed that JNK levels in DG and CA3 region were increased and NMDAR1 and NMDAR2B levels were decreased in SHR-2VGO+Acu and SHR-2VGO+ sp600125 groups. Meanwhile, protein expressions of GSK3β, NMDAR1/p-NMDAR1 and NMDAR2B in fimbria of hippocampus were increased, and JNK/P-JNK protein expression decreased. Acupuncture can increase the density and thickness of myelin sheath in white matter areas of corpus callosum, anterior commissure and hippocampal fimbria, increase the number and length of hippocampal neuronal dendrites, and improve hypertensive white matter injury and cognitive decline through JNK-NMDAR pathway.

Quasielastic Neutron Scattering Study on Thermal Gelation in Aqueous Solution of Agarose.

The dynamics of water and agarose molecules in an agarose aqueous solution has been studied by means of quasielastic neutron scattering (QENS). The dynamic structure factor S (Q,E) of the agarose aqueous solution was fitted well to the sum of the Lorentz and delta function. The former is attributed to the diffusive motion of water molecules and the latter to the local vibrational motion of agarose molecules. The self-diffusion coefficient D of water molecules was obtained from the Q-dependence of the width of the Lorentz function, while the mean square displacement <u2> of agarose molecules was obtained from the Q-dependence of the intensity of the delta term. In the cooling direction, both D and <u2> decreased with decreasing temperature and showed discontinuous changes around the thermal gelation temperature (around 314 K). In the heating direction, however, D and <u2> did not show the obvious change below 343 K, indicating a large hysteresis effect. The present results of <u2> and D revealed that the thermal gelation suppresses the motion of the polymer and accelerates the diffusion of water molecules. The activation energy Ea of the diffusion of water in the sol state is the same as that of bulk water, but the Ea in the gel state is clearly smaller than that of bulk water.

Modelling of drifting object dispersion in linear wave-induced flow

The dispersal of drifting objects like plant propagule under wave action can provide important information for the restoration of the plant community in coastal areas. An improved motion equation of the drift under wave action is established by coordinate transformation under the premise that the buoyancy is always perpendicular to the free surface, considering the variation of submerged height and the pressure gradient. Its numerical solution obtained by the fourth order Runge-Kutta method was compared with the experimental results in the literature, and the rationality of the improved motion equation is then verified. Then the perturbation method and Lagrange tracking principle were used to obtain the average longitudinal drift velocity expressed by Stokes drift velocity. The effect of different forces in the motion equations to the longitudinal diffusive motion was analyzed. Finally, the hydrodynamic coefficients affecting the prediction were analyzed, and the results show that the effects of the added mass coefficient and the drag coefficient are mainly reflected in the region with higher wave heights. The findings may provide certain scientific guidance for the restoration of coastal vegetation ecology through natural colonization.

Replisome loading reduces chromatin motion independent of DNA synthesis

Chromatin has been shown to undergo diffusional motion, which is affected during gene transcription by RNA polymerase activity. However, the relationship between chromatin mobility and other genomic processes remains unclear. Hence, we set out to label the DNA directly in a sequence unbiased manner and followed labeled chromatin dynamics in interphase human cells expressing GFP-tagged proliferating cell nuclear antigen (PCNA), a cell cycle marker and core component of the DNA replication machinery. We detected decreased chromatin mobility during the S-phase compared to G1 and G2 phases in tumor as well as normal diploid cells using automated particle tracking. To gain insight into the dynamical organization of the genome during DNA replication, we determined labeled chromatin domain sizes and analyzed their motion in replicating cells. By correlating chromatin mobility proximal to the active sites of DNA synthesis, we showed that chromatin motion was locally constrained at the sites of DNA replication. Furthermore, inhibiting DNA synthesis led to increased loading of DNA polymerases. This was accompanied by accumulation of the single-stranded DNA binding protein on the chromatin and activation of DNA helicases further restricting local chromatin motion. We, therefore, propose that it is the loading of replisomes but not their catalytic activity that reduces the dynamics of replicating chromatin segments in the S-phase as well as their accessibility and probability of interactions with other genomic regions.

Replisome loading reduces chromatin motion independent of DNA synthesis.

Chromatin has been shown to undergo diffusional motion, which is affected during gene transcription by RNA polymerase activity. However, the relationship between chromatin mobility and other genomic processes remains unclear. Hence, we set out to label the DNA directly in a sequence unbiased manner and followed labeled chromatin dynamics in interphase human cells expressing GFP-tagged proliferating cell nuclear antigen (PCNA), a cell cycle marker and core component of the DNA replication machinery. We detected decreased chromatin mobility during the S-phase compared to G1 and G2 phases in tumor as well as normal diploid cells using automated particle tracking. To gain insight into the dynamical organization of the genome during DNA replication, we determined labeled chromatin domain sizes and analyzed their motion in replicating cells. By correlating chromatin mobility proximal to the active sites of DNA synthesis, we showed that chromatin motion was locally constrained at the sites of DNA replication. Furthermore, inhibiting DNA synthesis led to increased loading of DNA polymerases. This was accompanied by accumulation of the single-stranded DNA binding protein on the chromatin and activation of DNA helicases further restricting local chromatin motion. We, therefore, propose that it is the loading of replisomes but not their catalytic activity that reduces the dynamics of replicating chromatin segments in the S-phase as well as their accessibility and probability of interactions with other genomic regions.

Modeling the flexoelectric effect in semiconductors via a second-order collocation MFEM

In this paper, the flexoelectric effect in flexoelectric semiconductors (FSs) is studied via a second-order collocation mixed finite element method (MFEM) with the consideration of the strain gradient, electric field gradient, and drift-diffusion motion of carriers. In the present second-order collocation MFEM, the mechanical strain is assumed to be an independent quadratic polynomial function of local coordinates, and the kinematic constraint between the mechanical strain and displacement is approximately satisfied through a collocation method at 9 Gaussian quadrature points in each element. The setup for the electric field and electric potential also follows similar collocation strategy. Thus, except for the fundamental field variables, no additional DOFs are introduced. The accuracy of the proposed second-order collocation MFEM is verified by comparing numerical results with analytical solutions for a cantilever beam example. By performing the numerical experiments using the second-order collocation MFEM, the flexoelectric effect in FSs is simulated. Besides, we propose a novel mechanism for the converse flexoelectric effect in FSs which is induced by the diffusion motion of electrons. Numerical results indicate that by intensifying the diffusion motion of electrons, the converse flexoelectric effect, associated with the electric field gradient, could be enhanced.

Thermal enhancement, thermophoretic diffusion, and Brownian motion impacts on MHD micropolar nanofluid over an inclined surface: Numerical simulation

The majority of liquids are undesirable for engineering due to their low heat conductivity. Scientists and researchers are developing nanofluids, which are made of nanoparticles (NPs) scattered in a base fluid, to boost the capacity for heat transfer in a variety of industries, including molten metals, pharmaceuticals, and computers. In this study, the magneto-hydrodynamics (MHD) flow of a micropolar nanofluid model with particle microstructure and inertial properties is investigated. A micropolar nanofluid’s flow is examined concerning the effects of a magnetic field. Aspects of heat and mass transfer are investigated using thermal radiation, thermophoresis, Brownian motion, and double diffusion theory toward an inclined surface. With the right level of similarity, the process converts partial differential equations emerging in nanofluidic systems into nonlinear differential equation systems. The FDM finite difference approach (FDM) (Lobatto IIIA) is used for the nonlinear nanofluid issue with the precision of order 4–5 and is implemented using a variety of collocation locations. The strength of Lobatto IIIA is its effectiveness in handling coupled differential equations that are extremely nonlinear. The higher-order differential equations are converted into a first-order method utilizing the boundary value dilemma (bvp4c) solver, which is part of the MATLAB software package, to computationally analyze the simplified mathematical model. The data obtained demonstrated a high degree of accuracy and symmetry when measured against previously published studies. Numerous variables’ effects on fluid flow are examined and graphically displayed with obtained numerical data. The results show that the temperature profile behaves in a way that is consistent with increasing thermophoresis and Brownian motion forces. This work provides insights into practical applications such as nanofluidic, energy conservation, friction reduction, and power generation. However, the work makes a significant point that the flow of a micropolar nanofluid including NPs can be regulated by appropriately modifying the thermophoresis parameter and Brownian motion parameter.

Collective motion in hcp-Fe at Earth’s inner core conditions

Earth's inner core is predominantly composed of solid iron (Fe) and displays intriguing properties such as strong shear softening and an ultrahigh Poisson's ratio. Insofar, physical mechanisms to explain these features coherently remain highly debated. Here, we have studied longitudinal and shear wave velocities of hcp-Fe (hexagonal close-packed iron) at relevant pressure-temperature conditions of the inner core using in situ shock experiments and machine learning molecular dynamics (MLMD) simulations. Our results demonstrate that the shear wave velocity of hcp-Fe along the Hugoniot in the premelting condition, defined as T/Tm (Tm: melting temperature of iron) above 0.96, is significantly reduced by ~30%, while Poisson's ratio jumps to approximately 0.44. MLMD simulations at 230 to 330 GPa indicate that collective motion with fast diffusive atomic migration occurs in premelting hcp-Fe primarily along [100] or [010] crystallographic direction, contributing to its elastic softening and enhanced Poisson's ratio. Our study reveals that hcp-Fe atoms can diffusively migrate to neighboring positions, forming open-loop and close-loop clusters in the inner core conditions. Hcp-Fe with collective motion at the inner core conditions is thus not an ideal solid previously believed. The premelting hcp-Fe with collective motion behaves like an extremely soft solid with an ultralow shear modulus and an ultrahigh Poisson's ratio that are consistent with seismic observations of the region. Our findings indicate that premelting hcp-Fe with fast diffusive motion represents the underlying physical mechanism to help explain the unique seismic and geodynamic features of the inner core.

Stationary state of harmonic chains driven by boundary resetting

We study the nonequilibrium steady state of an ordered harmonic chain of N oscillators connected to two walls which undergo diffusive motion with stochastic resetting. The intermittent resetting of the walls effectively emulates two nonequilibrium reservoirs that exert temporally correlated forces on the boundary oscillators. These reservoirs are characterized by the diffusion constants and resetting rates of the walls. We find that, for any finite N, the velocity distribution of the bulk oscillators remains non-Gaussian, as evidenced by a non-zero bulk kurtosis that decays . We calculate the spatio-temporal correlation of the velocity of the oscillators both analytically as well as using numerical simulation. The signature of the boundary resetting is present at the bulk in terms of the two-time velocity correlation of a single oscillator and the equal-time spatial velocity correlation. For the resetting driven chain, the two-time velocity correlation decay as at the large time, and there exists a non-zero equal-time spatial velocity correlation when . A non-zero average energy current will flow through the system when the boundary walls reset to their initial positions at different rates. This average energy current can be computed exactly in the thermodynamic limit. Numerically we show that the distribution of the instantaneous energy current at the boundary is independent of the system size. However, the distribution of the instantaneous energy current in the bulk approaches a stationary distribution in the thermodynamic limit.

Sliding Dynamics of a Small Charged Ring Chain on the Diblock Polyelectrolyte in Poly[2]catenane in the Presence of Counterions.

In this study, we investigate the sliding dynamics of small charged ring chains along the rigid central cyclic diblock polyelectrolyte of AnBn in radial charged poly[2]catenane in the presence of counterions using molecular dynamics simulations and the Lifson-Jackson formula, and our aim is to study the effects of electrostatical interaction strength, the size of the charged small ring chain, and the rigid block length of the diblock polyelectrolyte on the sliding dynamics of a small ring chain threaded on the rigid diblock polyelectrolyte. The mean-square displacement g3(t) of a small ring chain sliding along the rigid diblock polyelectrolyte of A10B10 exhibits oscillating behavior at short time scales for the moderate electrostatical interaction strength, while for the weak or strong electrostatic interactions, it is normal subdiffusion at short time scales. For n = 1, the diffusion coefficient D of the small ring chain sliding along the rigid diblock polyelectrolyte of A1B1 decreases monotonically as the relative electrostatic interaction strength A increases from A = 0.25-4. However, for n ≠ 1, the diffusion coefficient D of the small ring chain sliding along the rigid diblock polyelectrolyte of AnBn first decreases and then increases with the increase of A, and the nonmonotonous relationship between D and A becomes more obvious for larger n. In view of the free energy potential, the sliding diffusion of a small ring chain is governed by both the width of the free energy potential well and the height of the free energy potential barrier. According to the potential of mean force (PMF) of the small ring chain sliding along the rigid diblock polyelectrolyte, we find that our results are in good agreement with the theoretical analysis using the Lifson-Jackson formula. These results may help us to understand the diffusion motion of a ring chain in radial poly[n]catenanes from a fundamental point of view and control the sliding dynamics in molecular designs.

Influence of physical interactions on spatiotemporal patterns.

Spatiotemporal patterns are often modeled using reaction-diffusion equations, which combine complex reactions between constituents with ideal diffusive motion. Such descriptions neglect physical interactions between constituents, which might affect resulting patterns. To overcome this, we study how physical interactions affect cyclic dominant reactions, like the seminal rock-paper-scissors game, which exhibits spiral waves for ideal diffusion. Generalizing diffusion to incorporate physical interactions, we find that weak interactions change the length- and time scales of spiral waves, consistent with a mapping to the complex Ginzburg-Landau equation. In contrast, strong repulsive interactions typically generate oscillating lattices, and strong attraction leads to an interplay of phase separation and chemical oscillations, like droplets co-locating with cores of spiral waves. Our work suggests that physical interactions are relevant for forming spatiotemporal patterns in nature, and it might shed light on how biodiversity is maintained in ecological settings.

Anion and cation dynamics in a carbon-substituted cesium closo-hydroborate CsCB11H12: 1H and 133Cs NMR studies

Cesium monocarba-hydroborate CsCB11H12 belongs to the family of alkali-metal closo- hydroborate salts which are considered as promising solid electrolytes for battery applications. To study the dynamical properties of this compound at the microscopic level, we have measured the 1H and 133Cs nuclear magnetic resonance (NMR) spectra and spin-lattice relaxation rates over the temperature range of 80–434 K. Our measurements have revealed a coexistence of two types of reorientational jump processes of the complex [CB11H12]− anions. For the faster of these processes characterized by the average activation energy of 310 meV, the anion reorientations are not “frozen” at the NMR frequency scale down to 120 K. The behavior of the 133Cs NMR line width in CsCB11H12 is consistent with the onset of long-range diffusive motion of Cs+ ions at the frequency scale of ∼104 s−1 above 340 K, and the distinct effects of the diffusive Cs+ jumps on both the 1H and 133Cs spin-lattice relaxation rates become observable above 380 K.

Enhanced thermally-activated skyrmion diffusion with tunable effective gyrotropic force

Magnetic skyrmions, topologically-stabilized spin textures that emerge in magnetic systems, have garnered considerable interest due to a variety of electromagnetic responses that are governed by the topology. The topology that creates a microscopic gyrotropic force also causes detrimental effects, such as the skyrmion Hall effect, which is a well-studied phenomenon highlighting the influence of topology on the deterministic dynamics and drift motion. Furthermore, the gyrotropic force is anticipated to have a substantial impact on stochastic diffusive motion; however, the predicted repercussions have yet to be demonstrated, even qualitatively. Here we demonstrate enhanced thermally-activated diffusive motion of skyrmions in a specifically designed synthetic antiferromagnet. Suppressing the effective gyrotropic force by tuning the angular momentum compensation leads to a more than 10 times enhanced diffusion coefficient compared to that of ferromagnetic skyrmions. Consequently, our findings not only demonstrate the gyro-force dependence of the diffusion coefficient but also enable ultimately energy-efficient unconventional stochastic computing.

Holstein polaron transport from numerically "exact" real-time quantum dynamics simulations.

Numerically "exact" methods addressing the dynamics of coupled electron-phonon systems have been intensively developed. Nevertheless, the corresponding results for the electron mobility μdc are scarce, even for the one-dimensional (1d) Holstein model. Building on our recent progress on single-particle properties, here we develop the momentum-space hierarchical equations of motion (HEOM) method to evaluate real-time two-particle correlation functions of the 1d Holstein model at a finite temperature. We compute numerically "exact" dynamics of the current-current correlation function up to real times sufficiently long to capture the electron's diffusive motion and provide reliable results for μdc in a wide range of model parameters. In contrast to the smooth ballistic-to-diffusive crossover in the weak-coupling regime, we observe a temporally limited slow-down of the electron on intermediate time scales already in the intermediate-coupling regime, which translates to a finite-frequency peak in the optical response. Our momentum-space formulation lowers the numerical effort with respect to existing HEOM-method implementations, while we remove the numerical instabilities inherent to the undamped-mode HEOM by devising an appropriate hierarchy closing scheme. Still, our HEOM remains unstable at too low temperatures, for too strong electron-phonon coupling, and for too fast phonons.

Evolution of transport under cumulative damage in metro systems

One dominant aspect of cities is transport and massive passenger mobilization which remains a challenge with the increasing demand on the public as cities grow. In addition, public transport infrastructure suffers from traffic congestion and deterioration, reducing its efficiency. In this paper, we study the capacity of transport in 33 worldwide metro systems under the accumulation of damage. We explore the gradual reduction of functionality in these systems associated with damage that occurs stochastically. The global transport of each network is modeled as the diffusive movement of Markovian random walkers on networks considering the capacity of transport of each link, where these links are susceptible to damage. Monte Carlo simulations of this process in metro networks show the evolution of the functionality of the system under damage considering all the complexity in the transportation structure. This information allows us to compare and classify the effect of damage in metro systems. Our findings provide a general framework for the characterization of the capacity to maintain the transport under failure in different systems described by networks.

Boron carbide with improved mechanical properties fabricated via rapid pressureless densification with electromagnetic induction assistance

Herein electromagnetic induction is used to densify one of the hardest-to-sinter non-oxide ceramics, boron carbide. Power on for less than 5 min allowed densification of boron carbide to a relative density of 95% without application of sintering additives and external mechanical pressure. No cracks were found in the densified samples despite fast heating and cooling rates; Vickers' hardness was 30 GPa, Young's modulus was 322∼415 GPa and fracture toughness was 3.38∼4.82 MPa·m1/2. A gradient of densification was observed, with a higher degree of densification observed closer to the surface. The obtained results suggest that very fast pressureless densification of boron carbide was achieved as a result of acceleration of atomic diffusion and dislocation motion under eddy currents induced in boron carbide under high-frequency magnetic field at high temperatures.

Dislocation density-mediated creep ageing behavior of an Al-Cu-Li alloy

Creep aging is well-known to be a time-dependent, coupled process of deformation and precipitation strengthening for age-hardening alloys. Its existing mechanisms are mainly attributed to those interactions between atomic diffusion and dislocation motion. However, an understanding of the relationship between dislocation density and a special multistage creep behavior, i.e., double steady creep feature, is still far limited. Here we investigate the effect of various dislocation density levels on such an abnormal multistage creep of an Al-Cu-Li alloy. We find that the increased dislocation densities enable an apparent time decrease (from 6.2 h to 0.8 h) of their first steady Ⅱ-stage. The yield strength of post-aged samples increases from 425.0 MPa to 580.0 MPa while the corresponding elongation decreases from 12.3% to 7.3% for the creep-aged samples #1 to #4. Microstructural results also reveal that a great difference in dislocation configuration, tailored by various density levels, results in varying creep processes of the Ⅱ-stage. This stage is closely related to the nucleation and early growth of T1 precipitates. Their number densities (maximum: 2.9 × 1019 m–3) and the average length (maximum: 21.3 nm) of T1 precipitates are much smaller than those of the stable peak-aged T1 phases, suggesting that creep Ⅱ-stage of all three creep-aged samples is dominant by the nucleation and initial growth of those T1 precipitates. This study provides valuable insights into the dislocation density-mediated creep deformation of an Al-Cu-Li alloy.

Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories.

Single-particle traces of the diffusive motion of molecules, cells, or animals are by now routinely measured, similar to stochastic records of stock prices or weather data. Deciphering the stochastic mechanism behind the recorded dynamics is vital in understanding the observed systems. Typically, the task is to decipher the exact type of diffusion and/or to determine the system parameters. The tools used in this endeavor are currently being revolutionized by modern machine-learning techniques. In this Perspective we provide an overview of recently introduced methods in machine-learning for diffusive time series, most notably, those successfully competing in the anomalous diffusion challenge. As such methods are often criticized for their lack of interpretability, we focus on means to include uncertainty estimates and feature-based approaches, both improving interpretability and providing concrete insight into the learning process of the machine. We expand the discussion by examining predictions on different out-of-distribution data. We also comment on expected future developments.

A Practical Nanoplasmonic SERS Substrate for Differential Diagnosis of Lung Normal and Cancer Cells through Multivariate Statistical Analysis

AbstractLung cancer ranks first for cancer‐related mortalities primarily due to late diagnosis. Though Surface‐Enhanced Raman spectroscopy (SERS) is a popular bioanalytical technique, its direct application to diagnosis is impeded by low data reproducibility. Colloidal nanoparticles suffer from SERS intensity fluctuations due to unavoidable aggregation, and Brownian and diffusion motions in biological samples. The processes for solid‐state SERS substrates are either sophisticated or difficult to reproduce. Herein, we revisit the well‐established thermal evaporation process for the easy and reproducible preparation of silver nanoparticles loaded SERS glass substrates. The static mode of thermal evaporation yielded closely packed and uniformly distributed silver nanoparticles. The properties of these nanoparticles are tuned for the best performance by controlling the thermal evaporation process. And SERS substrate exhibited a reasonably good enhancement factor of ~105 with uniformity and reproducibility &lt;6 % RSD over a large area. It was utilized for label‐free SERS fingerprinting of lung adenocarcinoma cells A549 and normal lung fibroblast cells, WI‐38. The obtained data shows a slight distinction of Raman fingerprints in terms of certain biomolecules like nucleic acids, proteins, and lipids. Further multivariate statistical tools have been utilized which ensures a clear divergence between the cancerous cells and normal cells.

Effect of amino-modified SiO2 nanoparticles on micro-water diffusion behaviour in soybean oil-based natural ester oil-paper insulation system

Nanoparticles can significantly improve the insulation property of oil-paper insulation systems. In this paper, amino-modified SiO2 nanoparticles were used as nano-additives to establish a soybean oil-cellulose paper oil-paper insulation model, and the effect of amino-modified SiO2 nanoparticles on micro-water diffusion in oil-paper insulation systems was systematically studied. Simulation experiments show that amino-modified SiO2 nanoparticles can effectively delay the diffusion of water molecules in oil-paper insulation. As the temperature rises, compared with unmodified SiO2 nanoparticles, the diffusion motion of water molecules in amino-modified SiO2 nanoparticles oil–water model is slower. When the temperature is 383 K, the water molecule diffusion coefficient of the unmodified model is 1.22 times that of the modified model, and amino-modified SiO2 nanoparticles can form special hydrogen bonds with water molecules, preventing water molecules from further diffusing into cellulose paper, breaking the cellulose chain leads to a decrease in mechanical property, and further generating small molecules such as water and acid, which accelerate the aging of oil-paper insulation systems. Indirectly improve the electrical performance and aging performance of oil-paper insulation.