Physical Mechanism Research Articles

Emergence of cellular nematic order is a conserved feature of gastrulation in animal embryos.

Cells undergo dramatic changes in morphology during embryogenesis, yet how these changes affect the formation of ordered tissues remains elusive. Here we find that the emergence of a nematic liquid crystal phase occurs in cells during gastrulation in the development of embryos of fish, frogs, and fruit flies. Moreover, the spatial correlations in all three organisms are long-ranged and follow a similar power-law decay with less than unity for the nematic order parameter, suggesting a common underlying physical mechanism unifies events in these distantly related species. All three species exhibit similar propagation of the nematic phase, reminiscent of nucleation and growth phenomena. Finally, we use a theoretical model along with disruptions of cell adhesion and cell specification to characterize the minimal features required for formation of the nematic phase. Our results provide a framework for understanding a potentially universal features of metazoan embryogenesis and shed light on the advent of ordered structures during animal development.

Learning Model Based on Electrochemical Metallization Memristor with Cluster Residual Effect

Although a memristor model, subjected to electrochemical metallization mechanism, has been proposed based on the spontaneous decay of clusters in the previous work, it does not agree with the human forgetting accurately. Therefore, an improved model is meaningfully presented for the memristor with the cluster spontaneous decay by adding the residual effect. The former is due to the inward contraction of atoms driven by surface energy, while the latter is because of the balance of attractive and repulsive forces between atoms. The model fits well with the actual device. The forgetting is caused by the spontaneous decay. Memory retention is generated due to the added effect, which is also the internal cause of good agreement with the actual forgetting. Additionally, short‐term plasticity is converted to long‐term plasticity through the repeated learning. The efficiency of experiential learning using this model is much higher than that using the previous. It is shown that the physical mechanism of spontaneous decay in the cluster‐based channel is different from that in vacancy‐based or atom‐based channel. The model working under a non‐ideal condition with the temperature influence is discussed. Potential applications based on the model are stated.

Extended electronegative-difference-ratio effect on the enhanced out-of-plane piezoelectricity in MXenes monolayers

2D MXenes materials with out-of-plane piezoelectricity are competitive in numerous cutting-edge applications. However, it is still challenging to find MXenes materials with high-performance out-of-plane piezoelectricity and further reveal the piezoelectric mechanism. Here, via first-principles calculations, six stable ScYCTT' (T, T' = F, Cl or Br; T ≠ T') semiconductors are identified from 24 kinds of MXenes compounds. These semiconductors exhibit excellent out-of-plane piezoelectricity, surpassing many reported MXenes piezoelectric materials. The functional-group-modification-model and extended electronegative-difference-ratio (redScYCTT′) in the five-atom-layer ScYCTT' monolayers are defined for the first time to understand the piezoelectric physical mechanism. We find that the larger redScYCTT′corresponds to the larger out-of-plane piezoelectricity within the same group, which is defined as the electronegative-difference-ratio effect. This effect is also proved by data from 17 kinds of materials in other works. This work provides new perspectives for understanding the out-of-plane piezoelectric mechanism and offers promising candidates for touch screens and biomimetic skin.

Modeling and self-supporting printing simulation of fuse filament fabrication

This study presented a comprehensive computational fluid dynamics-based model for fused filament fabrication (FFF) three-dimensional (3D) printing multiphase and multiphysics coupling. A model based on the framework of computational fluid dynamics was built, utilizing the front-tracking method for high precision of multiphase material interfaces, a fully resolved simulation at the mesoscale explores the underlying physical mechanism of the self-supported horizontal printing. The study investigated the influence of printing temperature and velocity on the FFF process, exhibiting a certain self-supporting forming ability over a specific range. The results indicated that during the printing of large-span horizontal extension structures, the bridge deck material transitions from initial straight extension to sagging deformation, ultimately adopting a curved shape. The straight extension distance is inversely proportional to the depth of the sagging deformation. Additionally, the study revealed that printing temperature primarily affected the curing time of the molten material, while printing velocity fundamentally affected the relaxation time of both thermal and dynamic characteristics of the material.

Elucidating the transfer dynamics of high-viscosity silver paste for laser-induced forward transfer of continuous line

Laser-induced forward transfer (LIFT), as an innovative 3D direct-write method, has been increasingly applied for various material printing in many applications. Elucidating the transfer process of paste is crucial to manipulate the printing quality. In this work, the transfer dynamics of high-viscosity silver paste in LIFT of continuous line was systematically investigated based on the cumulative effect from images obtained over hundreds of laser pulses. The influences of process parameters, including the laser energy input (single pulse energy, repetition frequency, and scanning speed) and the thickness of paste film, on the bump height and expansion velocity of bump front were analyzed. With increasing the single pulse energy or repetition frequency, or decreasing the scanning speed or film thickness, the evolution of bump morphology and sputtering varies from just a tiny bump with no sputtering, to a moderate-sized bump with a small amount of sputtering and rebounding, and further to a large bump with intense sputtering and rebounding. A non-dimensional group in terms of Reynolds and Weber numbers was proposed to categorize different evolution regimes and claim the physical mechanism on LIFT of continuous line. When the Reynolds number is greater than 0.01 and the Weber number is greater than 0.1, the inertial effect is sufficient to resist the viscous and capillary effects, inducing the paste to bulge and transfer downwards. A moderate-sized bump with no visibly fragmented sputtering is desirable for the transfer of continuous grid lines. The forming status of grid lines can be predicted according to the behavior of paste transfer, and the predicted grid line state agrees well with the actual state. This can provide process and theoretical references for printing continuous grid lines with LIFT.

Dual-phase competitive behavior in N-type Sn–Bi–Te thermoelectric films achieving high thermoelectric performance

The dual-phase competitive behavior is introduced as an effective strategy to optimize the physical and chemical properties of N-type Bi2Te3 thermoelectric (TE) materials. Controllable SnTe-embedded Bi2Te3 nanocomposites can be synthesized with the addition of excessive Sn into Bi2Te3 by tuning the crystallization behavior under proper thermal heating temperature. Notably, the precipitation temperature of Bi2Te3 increases from 473 ​K for Sn20.9(Bi2Te3)79.1 to 573 ​K for Sn34.4(Bi2Te3)65.6, expanding the controllable temperature span for the presence of SnTe phase. The second-phase nanoprecipitate SnTe can improve electrical conductivity by competing with the Bi2Te3 phase, achieving an increase of four orders of magnitude at the critical temperature of ∼500 ​K. Simultaneously, it increases the interfacial energy filtration effect between nanocrystalline grains, decoupling electrical parameters between conductivity and Seebeck coefficient. Consequently, the high power factor of ∼147 ​μW/mK2 at 650 ​K for optimized Sn26.6(Bi2Te3)73.4 films can be obtained, which is more than twice that of the pure Bi2Te3 material. Our work demonstrates a new physical mechanism to unravel the complicated structure-property relationship by dual-phase competitive behavior during phase transition. This study fills the gap in knowledge on the effects of the SnTe phase regarding the Bi2Te3 system and provides guidance for the innovative design of high-performing inorganic thermoelectrics.

Numerical study of mid-infrared broadband perfect absorber based on dielectric/aluminium doped zinc oxide multilayer films

We propose a lithography-free wide-angle polarization-insensitive ultra-broadband absorber by using multilayer films consist of five pairs of aluminium doped zinc oxide (AZO) and a dielectric film which is supposed to be fabricated on glass substrate. The absorption spectrum of the proposed model is calculated by using transfer matrix method. The analytic results show that the absorptivity is larger than 95% with normal incidence light in the wavelength range from 7.5μm to 20μm and having high transmittance at the visible wavelength range from 0.4μm to 0.8μm range. Further, the effect of incident angle and polarization on the absorption spectrum are also investigated. The absorption spectrum of the proposed design is highly tunable on changing the damping constant of the AZO film. The electric field and magnetic distributions at different wavelengths show that the absorption is mainly originated due to the constructive interference of electromagnetic waves in the multilayer films. Such physical mechanism of broadening bandwidth based on increasing the carrier concentration of the highly visible transparent conducting films have pave a new direction for the design of tunable broadband absorber in different frequency band. Meanwhile, this broadband absorber is a good candidate for the potential applications in daytime radiation cooling system in the mid-infrared frequency band and also used as transparent conducting electrode in solar cell applications.

A transient formulation of entropy and heat transfer coefficients of Newton's cooling law with the unifying entropy potential difference in compressible flows

The original Newton's law of cooling is considered an ideal convection model of a point source ignoring conduction, but its unknown convection conductance and inconsistent thermal potential difference make it difficult to further elucidate the transient heat transfer mechanism of convection because of the no-slip condition at the interface between a body and a fluid. For this purpose, both the convective entropy transfer theory and the hypothesis of the isothermal velocity sublayer are developed to recast Newton's law of cooling into a standard Ohm's law form via the unified entropy driving force and the unambiguous entropy transfer coefficient. An explicit expression for the transient heat transfer coefficient is presented theoretically and experimentally in compressible flows by virtue of the product of the free-stream velocity, the volumetric thermal capacity of the fluid, and the near-wall velocity constant. The unified thermal potential difference is established between the body temperature and the total temperature (reduced to the ambient temperature for incompressible fluids). The physical mechanism of convection mode in the original Newton's cooling law is reasonably explained by the entropy transfer theory and entropy transfer efficiency, and the formulae for the entropy flux vector driven by the standard entropy potential difference and the rate of entropy generation are obtained. The analytical heat transfer coefficients as well as the standard thermal driving forces are validated by comparison with the forced convection experiment with a maximum error of 4.6 % in incompressible flows and the previous Newton's benchmark cooling experiments with the maximum error of 6.7 % in compressible flows. The effects of radiation on the total heat transfer coefficient are also analyzed quantitatively.

Hydrophobic terahertz metamaterial absorber sensor for renal cancer detection application

In this paper, a hydrophobic terahertz (THz) metamaterial absorber sensor aiming to detect renal cancer cells is proposed. The absorption properties, physical mechanism, structural parameters, sensing properties, and wettability of the sensor are theoretically investigated using the full-vector finite element method. The results indicate that the sensitivity (S), quality factor (Q) and figure of merit (FOM) for A-mode and B-mode are 180.46 GHz/RIU, 1128.23, 226.59 and 211.33 GHz/RIU, 1103.54, 246.59, respectively. The Q-factor and FOM are higher than those of the current sensors. The device can accurately differentiate between cancerous and normal cells in renal tissue. Additionally, the sensor possesses self-cleaning and self-protection capabilities due to the hydrophobic layer of polytetrafluoroethylene (PTFE). This provides a solid foundation for the repeated use and cost reduction of the sensor. Given these advantages, the proposed sensor has potential application value in the field of bio-detection and sensing.

Chirality-Induced Magnet-Free Spin Generation in a Semiconductor.

Electrical generation and transduction of polarized electron spins in semiconductors (SCs) are of central interest in spintronics and quantum information science. While spin generation in SCs is frequently realized via electrical injection from a ferromagnet (FM), there are significant advantages in nonmagnetic pathways of creating spin polarization. One such pathway exploits the interplay of electron spin with chirality in electronic structures or real space. Here, utilizing chirality-induced spin selectivity (CISS), the efficient creation of spin accumulation in n-doped GaAs via electric current injection from a normal metal (Au) electrode through a self-assembled monolayer (SAM) of chiral molecules (α-helix l-polyalanine, AHPA-L), is demonstrated. The resulting spin polarization is detected as a Hanle effect in the n-GaAs, which is found to obey a distinct universal scaling with temperature and bias current consistent with chirality-induced spin accumulation. The experiment constitutes a definitive observation of CISS in a fully nonmagnetic device structure and demonstration of its ability to generate spin accumulation in a conventional SC. The results thus place key constraints on the physical mechanism of CISS and present a new scheme for magnet-free SC spintronics.

The impact of non-frozen turbulence on the modelling of the noise from serrated trailing edges

Serrations are commonly employed to mitigate the turbulent boundary layer trailing-edge noise. However, significant discrepancies persist between model predictions and experimental observations. In this paper, we show that this results from the frozen turbulence assumption. A fully developed turbulent boundary layer over a flat plate is first simulated using the large-eddy simulation method, with the turbulence at the inlet generated using the digital filter method. The space–time correlations and spectral characteristics of wall pressure fluctuations are examined. The simulation results demonstrate that the coherence function decays in the streamwise direction, deviating from the constant value of unity assumed in the frozen turbulence assumption. By considering an exponential decay function, we relax the frozen turbulence assumption and develop a prediction model that accounts for the intrinsic non-frozen nature of turbulent boundary layers. To facilitate a direct comparison with frozen models, a correction coefficient is introduced to account for the influence of non-frozen turbulence. The comparison between the new and original models demonstrates that the new model predicts lower noise reductions, aligning more closely with the experimental observations. The physical mechanism underlying the overprediction of the noise model assuming frozen turbulence is discussed. The overprediction is due to the decoherence of the phase variation along the serrated trailing edge. Consequently, the ratio of the serration amplitude to the streamwise frequency-dependent correlation length is identified as a crucial parameter in determining the correct prediction of far-field noise.

Predictive Power of a Bayesian Effective Action for Fully Connected One Hidden Layer Neural Networks in the Proportional Limit.

We perform accurate numerical experiments with fully connected one hidden layer neural networks trained with a discretized Langevin dynamics on the MNIST and CIFAR10 datasets. Our goal is to empirically determine the regimes of validity of a recently derived Bayesian effective action for shallow architectures in the proportional limit. We explore the predictive power of the theory as a function of the parameters (the temperature T, the magnitude of the Gaussian priors λ_{1}, λ_{0}, the size of the hidden layer N_{1}, and the size of the training set P) by comparing the experimental and predicted generalization error. The very good agreement between the effective theory and the experiments represents an indication that global rescaling of the infinite-width kernel is a main physical mechanism for kernel renormalization in fully connected Bayesian standard-scaled shallow networks.

Numerical simulation of residual oil distribution characteristic of carbonate reservoir after water flooding

Carbonate reservoirs are characterized by abundant reserves and are currently focal points for development in oil and gas producing regions such as the Ahdab oilfield, Tarim Basin, Sichuan Basin, and Ordos Basin. The primary method for exploiting carbonate reservoirs is waterflooding. However, due to the complex pore structure and pronounced heterogeneity of carbonate rocks, the waterflooding process often leads to an unclear distribution of remaining oil and low waterflooding recovery efficiency, significantly impacting the stable and high production of carbonate reservoirs. This paper presents a two-phase flow model of oil and water in distinct pore structures by integrating fluid flow equations and interface tracking equations. It visually represents the waterflooding process at the pore scale, elucidates the distribution and formation mechanism of remaining oil, and discusses the mechanism of microscopic displacement efficiency change. The study reveals that: 1) After waterflooding, the distribution patterns of remaining oil can be categorized into dead-end remaining oil, pressure balance remaining oil, wall-bound remaining oil, Jamin effect remaining oil, and water-encapsulating remaining oil, which are governed by microscopic pore structure, wettability, and preferential flow paths; 2) From the perspective of actual reservoir displacement efficiency, intergranular pores > intergranular dissolved pores > visceral foramen > mould pore, with this trend being more pronounced under hydrophilic wetting conditions; 3) Given the oil-wet to strong oil-wet wettability characteristics of these carbonate rocks, capillary forces pose significant resistance during waterflooding. The conclusion underscores the importance of leveraging the reservoir’s microscopic pore structure and wettability characteristics for actual oil wells, elucidating the evolutionary law of the mechanical mechanism of oil-water interface advancement, clarifying oil-water percolation characteristics at the pore scale, and understanding the microscopic displacement physical mechanism, all of which are crucial for guiding the design of schemes aimed at enhancing reservoir recovery efficiency.

Intelligent RCS Extrapolation Technology of Target Inspired by Physical Mechanism Based on Scattering Center Model

In this paper, a technology named SCM−ANN combining physical scattering mechanisms and artificial intelligence is proposed to realize radar cross-section (RCS) extrapolation of non-cooperative conductor targets with higher efficiency. Firstly, an adaptive scattering center (SC) extraction algorithm is used to construct the scattering center model (SCM) for non-cooperative targets from radar echoes in the low-frequency band (LFB). Secondly, an artificial neural network (ANN) is constructed to capture the nonlinear relationship between the real LFB echoes and those reconstructed from the SCM. Finally, the SCM is used to reconstruct echoes in the high-frequency band (HFB), and these reconstructions, together with the trained ANN, optimize the extrapolated HFB RCS. For the SCM−ANN technology, physical mechanistic modes are used for trend prediction, and artificial intelligence is used for regression optimization based on trend prediction. Simulation results show that the proposed method can achieve a 50% frequency extrapolation range, with an average prediction error reduction of up to 40% compared with the traditional scheme. By incorporating physical mechanisms, this proposed approach offers improved accuracy and an extended extrapolation range compared with the RCS extrapolation techniques relying solely on numerical prediction.

An improved meteorological variables-based aerosol optical depth estimation method by combining a physical mechanism model with a two-stage model

A two-stage model integrating a spatiotemporal linear mixed effect (STLME) and a geographic weight regression (GWR) model is proposed to improve the meteorological variables-based aerosol optical depth (AOD) retrieval method (Elterman retrieval model-ERM). The proposed model is referred to as the STG-ERM model. The STG-ERM model is applied over the Beijing-Tianjin-Hebei (BTH) region in China for the years 2019 and 2020. The results show that data coverage increased by 39.0% in 2019 and 40.5% in 2020. Cross-validation of the retrieval results versus multi-angle implementation of atmospheric correction (MAIAC) AOD shows the substantial improvement of the STG-ERM model over earlier meteorological models for AOD estimation, with a determination coefficient (R2) of daily AOD of 0.86, root mean squared prediction error (RMSE) and the relative prediction error (RPE) of 0.10 and 36.14% in 2019 and R2 of 0.86, RMSE of 0.12 and RPE of 37.86% in 2020. The fused annual mean AOD indicates strong spatial variation with high value in south plain and low value in northwestern mountainous areas of the BTH region. The overall spatial seasonal mean AOD ranges from 0.441 to 0.586, demonstrating strongly seasonal variation. The coverage of STG-ERM retrieved AOD, as determined in this exercise by leaving out part of the meteorological data, affects the accuracy of fused AOD. The coverage of the meteorological data has smaller impact on the fused AOD in the districts with low annual mean AOD of less than 0.35 than that in the districts with high annual mean AOD of greater than 0.6. If available, continuous daily meteorological data with high spatiotemporal resolution can improve the model performance and the accuracy of fused AOD. The STG-ERM model may serve as a valuable approach to provide data to fill gaps in satellite-retrieved AOD products.

Genetically-Based Active Flow Control And PIV Measurements Of A Circular Cylinder Wake

In the field of flow manipulation, considerable attention is devoted to controlling the wake of bluff bodies, which are characterized by the phenomenon of vortex shedding. Specifically, the control of the wake behind a single circular cylinder has garnered substantial research interest due to its engineering applications, such as reducing aerodynamic drag in the automotive and aerospace industries. Therefore, in the current work, through the application of the planar PIV technique, the fluid dynamic behavior of a circular cylinder wake controlled via synthetic jets (SJ) and Machine Learning (ML) methods is analyzed and discussed. ML algorithms are used to determine the optimal voltage signal for the loudspeaker, which effectively minimizes the aerodynamic drag of the cylinder. This approach overcomes the limitations associated with the a priori assumption of a parametric waveshape. In particular, the gradient-enriched machine learning control (gMLC) algorithm is chosen as optimization tool to search the best open-loop control policy for aerodynamic drag reduction. The cost function for this problem has been defined considering both the drag reduction contribution and the electrical power spent for the actuation. Initial optimization tests are performed by minimizing a cost function considering only the reduction in aerodynamic drag. Subsequently, a term related to the electrical power consumption for actuation is incorporated into the cost function. Once obtained the optimal control policies for these cases (hereinafter renamed CC1 and CC2, respectively), the physical mechanism responsible for reducing the aerodynamic drag is investigated more closely by analyzing the effect of the control laws on the turbulent flow statistics. Figure 1 reports a comparative assessment of the CC1 and CC2 with the baseline configuration and the configuration controlled by a sinusoidal law (CCS). The baseline configuration is characterized by an extended region of localized turbulent fluctuations in the far wake, where the time-averaged signature of von Kármán vortices is found. In contrast, all the controlled configurations show a global reduction in wake turbulence, with a peak of turbulent energy at the rear stagnation point due to the momentum injection from the SJ actuator. Notably, the CCS and CC2 configurations share similar flow field morphologies, while the CC1 configuration shows a greater reduction in turbulent fluctuations compared to the other controlled cases. This control law also achieves the largest drag reduction among all configurations studied reporting a 9.7% of drag reduction, compared to CCS and CC2, which exhibit similar reductions of 8.4% and 8.5%, respectively. Therefore, the optimization procedure has proven the capability of finding control policies able to outperform the traditional sinusoidal control widely studied in literature.

A semi-cellular Z-type Gate SOI-LDMOS with Improved Gate Control Capability

A Semi-cellular Z-type Gate SOI-LDMOS (ZG LDMOS) with Improved Gate Control Capability is proposed, and its physical mechanism is studied by SENTAURUS. It is a semi-cellular structure similar to "Z" consisting of a Trench Gate (TG) and a Planar Gate (PG). At the on-state, the inversion layer of the conductive channel is not only formed at the top of the P-well region, but also formed along the side wall of the Z Gate, expanding the width of the channel, improving the electron injection ability and reducing the specific on-resistance (Ron,sp). In addition, the Z Gate can also form a uniform current distribution from the drift region to the bottom, which is helpful to reduce the Ron,sp, improve the transconductance and enhance the current control ability. The 3D simulation results show that BV, Ron,sp are 187.3 V and 4.45 mΩ cm2, respectively. The FOM reached 7.91 MW/cm2. Compared with the conventional LDMOS, the FOM value of ZG LDMOS increased by 58.8 %, which breaks through the silicon limit of RESURF.

Unified properties of supermassive black hole winds in radio-quiet and radio-loud AGN

ABSTRACT Powerful supermassive black hole (SMBH) winds in the form of ultra-fast outflows (UFOs) are detected in the X-ray spectra of several active galactic nuclei (AGNs) seemingly independently of their radio classification between radio quiet (RQ) and radio loud (RL). In this work, we explore the physical parameters of SMBH winds through a uniform analysis of a sample of X-ray bright RQ and RL AGN. We explored several correlations between different wind parameters and with respect to the AGN bolometric and Eddington luminosities. Our analysis shows that SMBH winds are not only a common trait of both AGN classes but also that they are most likely produced by the same physical mechanism. Consequently, we find that SMBH winds do not follow the radio-loudness dichotomy seen in jets. On average, a comparable amount of material accreted by the SMBH is ejected through such winds. The average wind power corresponds to about 3 per cent of the Eddington luminosity, confirming that they can drive AGN feedback. Moreover, the most energetic outflows are found in the most luminous sources. We find a possible positive correlation of the wind energetics, renormalized to the Eddington limit, with respect to $\lambda _{\mathrm{ Edd}}$, consistent with the correlation found with bolometric luminosity. We also observe a possible positive correlation between the energetics of the outflow and the X-ray radio-loudness parameter. In general, these results suggest an underlying relation between the acceleration mechanisms of accretion disc winds and jets.

A Novel Terahertz Metamaterial Microfluidic Sensing Chip for Ultra-Sensitive Detection.

A terahertz metamaterial microfluidic sensing chip for ultrasensitive detection is proposed to investigate the response of substances to terahertz radiation in liquid environments and enhance the molecular fingerprinting of trace substances. The structure consists of a cover layer, a metal microstructure, a microfluidic channel, a metal reflective layer, and a buffer layer from top to bottom, respectively. The simulation results show that there are three obvious resonance absorption peaks in the range of 1.5-3.0 THz and the absorption intensities are all above 90%. Among them, the absorption intensity at M1 = 1.971 THz is 99.99%, which is close to the perfect absorption, and its refractive index sensitivity and Q-factor are 859 GHz/RIU and 23, respectively, showing excellent sensing characteristics. In addition, impedance matching and equivalent circuit theory are introduced in this paper to further analyze the physical mechanism of the sensor. Finally, we perform numerical simulations using refractive index data of normal and cancer cells, and the results show that the sensor can distinguish different types of cells well. The chip can reduce the sample pretreatment time as well as enhance the interaction between terahertz waves and matter, which can be used for early disease screening and food quality and safety detection in the future.

Clothing color effect as a target of the smallest scale climate change adaptation.

The purpose of this study is to understand a physical mechanism to determine the surface temperature of clothes in calm and fine conditions of outdoors. We observed surface temperatures of polo shirts of the same material and design but different colors. The shirts were placed in unshaded and well-ventilated outdoor, open spaces on sunny summer days. The maximum difference between dark green or black and white was more than 15°C during calm, fine weather and was greatest when the solar radiation was strong. If the transmission of solar radiation energy through a shirt is ignored to calculate the absorption by the shirt, the difference in solar radiation absorption due to different colors is as much as 24% in the maximum, and if considered, we concluded that an absorption difference of 34% led to a temperature difference of 15℃. When we compared the brightness of the colors, we found that the albedo of both the visible and NIR bands explained why the red and green colors were so different with respect to the surface temperatures we observed. The reflection in the NIR bands was also an important determinant of the surface temperature. An additional experiment using masks showed that the temperature difference between white and black was almost eliminated at a wind speed of ~ 3m/s. The color of clothing is therefore a target for small-scale adaptation to climate change.