Superelastic Tellurium Thermoelectric Coatings for Advanced Trimodal Microsensing

Domain: physics
Published: 2026-01-13
Editorial outcome: major_revision

Abstract
Tactile endoscopes can provide physicians with rich sensory information, enabling fast and accurate medical diagnoses. However, existing tactile endoscopy sensors do not consider temperature perception, which is a very important diagnostic indicator in medicine. Here, we report for the first time a tellurium-based superelastic thermoelectric visual-tactile sensor. This platform achieves a breakthrough by combining tellurium thermocouples designed based on crystal structures with viscoelastic silicone encapsulation, enabling simultaneous microscale visual, thermal, and force measurements in a single device. By employing a morphologically optimized tellurium-polymer heterointerface and advanced deep neural network algorithms, we address the inherent trade-off between transparency and responsiveness, achieving artifact-free imaging, real-time thermal mapping, and microstructure force feedback. We conduct clinical endoscopic palpation experiments on liver rabbits and successfully achieve tactile diagnosis of inflamed tissue including temperature distribution, especially in cases where visual distinction is difficult, pointing out possible development directions for intelligent endoscopy systems.

Introduction
Tactile endoscopes can significantly enhance the richness of sensory information in tactile diagnosis and minimally invasive surgery, thereby improving doctors’ efficiency and accuracy1,2. In the past decades, tactile endoscope systems have achieved force measurement while maintaining basic visual observation capabilities3–6. This marks progress in enhancing the safety and accuracy of endoscopic procedures by enabling surgeons to obtain both visual insights into the surgical site and quantitative force feedback2,7,8. However, a notable limitation of current tactile endoscope systems lies in their general lack of temperature-sensing functionality, which is a critical capability for endoscopic surgeries. The involvement of temperature modalities can achieve necessary thermal monitoring9,10 (real-time target tissue temperature measurement to avoid thermal damage) and play a key role in the accurate diagnosis of abnormal tissues11–13 (such as identifying inflammation and tumor lesions through local temperature changes). Therefore, how to seamlessly integrate temperature sensing technology into tactile endoscope systems to achieve high-precision 3D force measurement and high-definition visual imaging without compromising the system’s existing compact structure remains a significant challenge in this field.

Among the mainstream temperature measurement methods, non-contact temperature sensing represented by infrared temperature sensors is favored because it avoids contact damage, but the measurement accuracy is limited14–16. In contrast, contact-based temperature sensors are relatively mature in development and application, primarily categorized into thermistors and thermocouples. Thermistor made from precious metals like Pt and Cu offer exceptional signal stability17–19. However, their minimal signal variation and complex calibration circuits make them difficult to integrate onto flexible micro-probes for visual-tactile sensing, rendering them more suitable for temperature drift calibration in micro-nanoelectronic devices20–23. Thermocouples based on the Seebeck effect show a strong correlation between their signal and contact position and have excellent spatial resolution24–26. Leveraging the high band degeneracy and unique lattice arrangements of tellurium materials, a series of outstanding thermoelectric materials have been developed around tellurium and its compounds27–31. However, due to thermoelectric mechanisms, thermocouple systems represented by tellurium-based compounds typically require larger longitudinal or lateral dimensions to achieve greater temperature differentials. This inevitably impacts signal acquisition and reconstruction in tactile sensing. Therefore, the construction of 3-dimensional, small-size, high-sensitivity temperature sensor devices remains an extremely significant challenge.

Here, we develop a paradigm-shifting Te endoscope architecture (T-scope) that achieves unprecedented tri-functional integration of vision, 3D tactile force sensing and sensitive thermal analysis within an ultra-compact 4.8 mm probe. To prevent the temperature sensor from interfering with the visual and tactile information, we employ the high Seebeck coefficient and weak thermal conductivity of Te polycrystalline thin film to construct a 3-dimensional, small-size temperature sensor on the surface of silica gel. The thickness of the temperature-sensing film is approximately 200 nm, with a lateral size of less than 1 mm² and a detection accuracy of 647 μV/K. The AI-driven visual-tactile deep neural network enables accurate three-dimensional contact force estimation for tissues with different hardness. It also integrates visual restoration observation integrated with spatiotemporal context information, by performing pixel-level segmentation and tracking of the artificially marked deformations naturally provided by Te devices32–34. The real tactile endoscopy experiments conducted in living rabbits verify its leading clinical advantages: it successfully distinguishes abnormal inflammatory tissue from normal tissue from aspects such as visual observation, pressure mechanical properties and temperature distribution.

Results
Principles and design of the T-scope sensor
The core innovation of our study lies in integrating cutting-edge flexible thermoelectric materials with visual AI technology to realize a visual-tactile-thermal tri-modal sensing system within compact endoscopic devices (Fig. 1a, Supplementary Movie S1). Our first contribution is the design of a tactile probe that can seamlessly integrate into existing endoscopic systems. The probe is made of a transparent elastomer with specially designed textured patterns, as illustrated in Fig. 1b. This design enables the camera to detect tiny deformations in the sensor caused by physical contact, achieving temperature and force modeling while maintaining clear visual observation (Fig. 1c).

The probe is integrated at the front end of a traditional endoscope. In this study, an over-molding process is employed to construct a soft-rigid hybrid structure. This structure consists of two components: a flexible elastomer (Supplementary Fig. S1) for high sensitivity contacts detection and a rigid skeleton for structural support. The transparent silicone substrate of the probe is precisely molded onto the prefabricated skeleton using advanced casting technology, with texture layers and protective layers subsequently applied. The final sensor combines the advantages of both components—it maintains structural stability to ensure sufficient strength under large contact forces, while exhibiting high sensitivity in detecting and responding to minimal interaction forces.

A critical breakthrough involves using tellurium polycrystalline films based on the Seebeck effect to embed temperature-sensing functionality into textured patterns. This flexible material seamlessly integrates with elastomers, enabling precise temperature measurement while preserving tactile imprint detection and image quality (Fig. 1d). The T-scope system translates tactile information into identifiable pattern variations through regularly arranged tellurium polycrystalline patterns on its elastomer surface. The process of transferring its 3D microstructure enables adhesion to micro-level curved surfaces, with each thermoelectric imprint maintaining 200 μm diameter. To ensure durability in complex biofluid environments, a protective layer is added via secondary injection molding (detailed manufacturing steps in Methods section, Supplementary Fig. S2).

In addition, we propose advanced deep neural network methods for visual observation inpainting and accurate 3D force estimation (Fig. 1e). Specifically, we propose the EndoForce network, which performs 3D force estimation based on the thermoelectric imprint changes in various contact states, and a transformer-based video inpainting algorithm, which provides imaging quality comparable to endoscopic systems without a tactile layer and high-sensitivity.

Structure of Te-based thermoelectric subsystem
The thermoelectric component based on polycrystalline tellurium thin films is developed for temperature sensing in the T-scope system (Fig. 2a). In the subsystem design, highly transparent ITO electrodes are employed as external leads to effectively reduce optical interference with the T-scope vision system. By precisely controlling the total device thickness at the 10 μm level, interference effects on the deformation processes of posterior organic materials are significantly minimized. The innovative selection of polycrystalline tellurium as the sensitive functional layer features a crystalline structure composed of parallel-aligned ternary helical chains (Fig. 2b). Intra-chain Te atoms are bonded through intermolecular interactions, while inter-chain ordering is maintained using van der Waals force-driven stacking. This unique crystal structure exhibits significant lattice scattering, effectively suppressing lattice heat conduction and promoting the establishment of a significant temperature gradient (Fig. 2c). This enables efficient thermoelectric conversion and reduces the trade-off between thickness and responsivity.

The fabrication process flow comprises the following key steps (Fig. 2d, Further details in the Methods section and Supplementary Fig. S3): Initial surface cleaning and PDMS composite treatment of 10 μm PET substrates; Magnetron sputtering deposition of gold electrodes on half-area substrates followed by full-substrate tellurium thin film deposition; Laser direct writing processing of AuTe-Te interfaces into 1 mm-diameter temperature-sensitive unit (Fig. 2e). When placed on a 42 °C hot plate, the temperature-sensitive unit demonstrates clear temperature field distribution characteristics on its surfaces, confirming temperature detection capabilities. Furthermore, an ITO polycrystalline thin film is fabricated and patterned as an external electrode. Optical photography reveals the excellent light transmittance of the ITO layer (Fig. 2f). Finally, the temperature-sensitive unit is integrated with the ITO electrode through microassembly, completing the fabrication of a Te-based polycrystalline temperature sensor (Fig. 2d).

Simulation and Evaluation of Te-based Thermoelectric Performance
For assessing the device’s operational viability, finite element analysis (FEM) through COMSOL Multiphysics is implemented to characterize thermal-to-electrical conversion performance in simulated application scenarios (Fig. 2g). The model incorporates a PET substrate to mimic surface encapsulation and an Ecoflex layer to replicate integration with visual sensors, while considering natural convection effects. By applying thermal gradients (20-40 °C) at contact interfaces, simulations reveal significant temperature field redistribution and corresponding thermal potential variations (Fig. 2h, Supplementary Fig. S4). At a contact temperature of 30 °C, a 4 °C temperature gradient across the Te domain produces a 4 mV output, demonstrating its robust thermal detection capabilities (Fig. 2i). The difference in thermal behavior between the Te and AuTe alloys is evident: AuTe maintains a uniform temperature distribution due to its high thermal and electrical conductivity, while Te’s lower lattice thermal conductivity results in a 10 °C temperature gradient at a 40 °C contact temperature. This contrast amplifies carrier accumulation on the Te surface, generating a 9 mV potential difference (Fig. 2h), confirming the mechanism of temperature-dependent signal generation.

Subsequently, the thermoelectric performance is evaluated under controlled contact heat sources (20–42 °C). The Te-based thermoelectric sensor exhibits stable output potential at identical contact temperatures, demonstrating its stability (Fig. 2j). Further analysis reveals a linear relationship between voltage and contact temperature variation, with a sensitivity of 0.323 mV/K (Supplementary Fig. S5). Remarkably, when heated to 39 °C (close to mammalian body temperature), the output is 5.5 mV (Fig. 2k). Measurements reveal a temperature difference between the upper and lower surfaces, and analysis reveals the film’s Seebeck coefficient to be 0.647 mV/K, 2.6 times higher than that of bulk tellurium (Supplementary Fig. S6). These results highlight the dual advantages of this sensor: Te’s low thermal conductivity facilitates the formation of steep thermal gradients, while its enhanced Seebeck response ensures high-resolution temperature detection, confirming its suitability for environmental monitoring and in-vivo biomedical applications. Detailed thermoelectric effect analysis can be found in Supplementary Note S1.

Visual-tactile deep neural networks
Because the proposed thermoelectric devices provide natural landmarks in the endoscopic field of view, our endoscopic vision system can capture their position and overall shape changes, thereby creating an accurate map of the 3D contact forces acting on the probe35,36. We first designate a tactile data acquisition system (Fig. 3a(i)): two T-scope tactile endoscopic probes with different marker patterns (Fig. 3a(ii)) are fixed on a commercial multi-dimensional force sensor. Contact tests with varying directions and magnitudes are conducted using a variety of soft materials that fully cover the hardness range of human tissues (elastic modulus from 0 to 100 kPa) (Fig. 3a(iii), Supplementary Fig. S7). The six-axis force/torque sensor provides ground-truth forces acting on the surface of the tactile probe. Subsequently, we adopt a data-driven approach and propose the EndoForce 3D force estimation network to directly estimate 3D forces from raw visual observation inputs.

The proposed EndoForce network (Fig. 3b) first extracts thermoelectric imprint information through an image segmentation network (Efficient-SAM37). By calculating the difference between real-time imprint segmentation results and non-contact reference values, positional displacement differences are isolated. Binary XOR processing highlights the movement of markers, and the processed images are then fed into the force estimation network. This network is based on the ResNet architecture, with detailed information provided in Supplementary Fig. S8, Note S2, and Table S1. This method effectively reduces interference from diverse endoscopic backgrounds, allowing the network to focus on learning pattern features at the thermal-electrical imprint level (Supplementary Table S2).

Experimental results demonstrate that the system achieves excellent performance under varying contact magnitudes and directions (Supplementary Table S3 and S4). The average full-scale error percentage of the contact force is about 6% FS, with the average errors of the tangential force and normal force components being 0.02 N (6.50% FS) and 0.06 N (5.96% FS), respectively. Error distribution analysis reveals consistent prediction accuracy across different force magnitudes, with no error escalation observed when contact forces increase (Fig. 3c(i)). Directional error analysis (Supplementary Fig. S9) indicates comparable performance across different orientations, though slightly higher errors occur in the central and downward directions. This phenomenon may be attributed to the contact habits of operators. Further validation through randomized finger contact trials (Fig. 3c(ii)) shows stable 3D force estimation with consistently low errors, confirming the generalization capability of the network. The testing process of perceived 3D force versus ground-truth 3D force when randomly pressing the sensor probe with a human finger is available in Supplementary Movie S2.

Thermoelectrical imprints cause visual occlusion in endoscopic images (Fig. 3a(ii)), which may compromise the clarity of the diagnostic field of view. To address this issue, we adopt ProPainter38 for AI-driven visual inpainting. We first prepare a dataset suitable for real in-vivo tissue scenarios (Fig. 3d(i), Supplementary Note S3). Specifically, we use a T-scope probe without thermal-electrical markers to capture videos of the respiratory tract and gastric tissues of live rabbits. Visual inpainting synthetic datasets are then generated by manually adding various markers, including different dot arrays and dot-line patterns (Supplementary Fig. S10).

We first retrain the ProPainter network using the synthetic dataset with ground-truth labels. In real in-vivo experiments, the visual inpainting network with the trained weights is directly used for real-time visual observation (Fig. 3d(ii)). Results from the in-vivo experiments show that the cross-domain trained model successfully reconstructs visual information occluded by different thermoelectrical imprints (Fig. 3e(ii)). More inpainting examples can be found in Supplementary Fig. S11 and S12. The model achieves an average peak signal-to-noise ratio (PSNR) of 37.35 decibels (dB) across various contact scenarios. Meanwhile, it maintains a complete diagnostic field of view and remains unaffected by variations in the position and size of marker occlusions (Fig. 3e(i), (ii), Supplementary Table S5).

In vitro simulated visual-tactile diagnostic experiment
To verify the practical efficacy of the T-scope system in clinical endoscopic environments, we conduct visual-tactile diagnostic experiments using full-scale biosimulation phantoms. During the experiments, the T-scope sensing device is mounted at the distal end of a standard endoscopic system. Operators perform multiple contact detection tests by manually manipulating the endoscope within the simulated models of the human bronchus, stomach, and large intestine (Fig. 4a(i), Fig. 4b(i), Fig. 4c(i)). This study specifically records the 3D force detection data from the sensor’s interaction with physiological and pathological tissues in these anatomical structures, and conducts comparative analyses on the dual-modal sensing capabilities (three-dimensional contact force and vision) of the T-scope system when it contacts normal tissues and simulated tumor tissues.

Biomechanical test data from the bronchial and gastric models (Fig. 4a(ii), b(ii)) shows that due to the higher biomechanical stiffness of tumor tissue, the fluctuation of its normal force value is more significant than that of healthy tissue when maintaining a stable contact state. Visual inpainting results (Fig. 4a(iii), b(iii)) indicate that the inpainting algorithm in this study can effectively eliminate the occlusion of normal and abnormal tissues caused by thermoelectric devices, enabling the normal visual observation function of the endoscope. In addition, in the human intestinal model (Fig. 4c(i)), we also conduct fast and slow contact tests on normal tissues: Fig. 4c(ii) and (iii) respectively show the comparison of normal force and tangential force sensed by the T-scope probe during fast contact and slow contact. Experimental results show that the increase rate of normal force (-1.4 vs -0.17) and the vibration amplitude of lateral force (-58 mN vs 21 mN) during fast contact are significantly greater than those during slow contact, which indirectly proves the sensitivity and accuracy of the 3D force sensing deep neural network in this study. For more detailed three-dimensional force sensing data, please refer to Supplementary Fig. S13 and S14, Movies S3, S4, and S5.

In-vivo animal visual-tactile diagnosis verification experiment
To verify the efficacy of the T-scope system in real in-vivo scenarios, visual-tactile-temperature diagnostic experiments are conducted in the gastric cavity of anesthetized rabbits (Supplementary Movie S6). Prior to the experiments, a precise inflammation model of rabbit gastric tissue is established through inflammation modeling over a 4-day period. The T-scope probe is encapsulated at the front end of a handheld endoscope, which is then delivered into the rabbit’s body through its oral cavity to perform visual-tactile endoscopic diagnosis (Fig. 5a). At the initial stage of the experiment, researchers navigate the probe delivery process using conventional endoscopic observation. Fig. 5b illustrates the visual observation sequence, which tracks the probe’s path from the exterior of the rabbit’s oral cavity, through the esophagus and cardia, and finally to the inflamed gastric tissue. This sequence not only demonstrates the system’s excellent visual observation performance but also confirms the effectiveness and stability of the proposed AI visual restoration algorithm in real in-vivo scenarios (Supplementary Fig. S15).

During the pressing process on normal and abnormal tissues inside the living rabbit, the T-scope system is observed to achieve accurate visual reconstruction while exhibiting highly sensitive force estimation capabilities (Fig. 5c(i)). When researchers apply similar pressing forces to different types of tissues, it is found that the inflamed tissue—due to its higher hardness—exhibits significantly larger absolute values of normal force and a faster force increase rate compared to normal tissue (Fig. 5c(ii): rate, -0.016 vs -0.009; maximum absolute value of normal force, 516 mN vs 328 mN).

Furthermore, intensive contact sampling is performed in the vicinity of the inflamed tissue to obtain the temperature distribution of the inflamed tissue and its boundary regions (Fig. 5d(i)). The results reveal that the temperature of the inflamed tissue is significantly higher than that of normal tissue, with a maximum temperature difference of approximately 4 °C. A sliding temperature measurement experiment is also conducted at the boundary of the inflamed tissue, where the probe slides from the normal tissue to the inflamed tissue. The corresponding visual observations and temperature change curves are recorded (Fig. 5d(ii)). The results indicate that at the boundary of the inflamed tissue, a noticeable temperature rise occurs even when no obvious visual changes are observed. This finding confirms the significance of integrating temperature sensing into endoscopic systems, particularly for advancing precision medicine applications.

Methods
Mechanical structure overview of the T-scope probe
The miniaturized imaging module has a diameter of 3 mm (Supplementary Movie S1). This ultra-compact design enhances operational flexibility within confined anatomical spaces, enabling rapid navigation through complex tissue networks. To support this technology, the T-scope instrument maintains the critical dimensions of a 5 mm outer diameter and a 7.5 mm functional length, achieving an optimal balance between mechanical rigidity and space economy for endoscope compatibility. Supplementary Movies S3, S4, and S5, and S6 capture the system in action, demonstrating its ability to simultaneously acquire multimodal data during complex surgical procedures requiring millimeter-level precision.

Thin-film processing of polycrystalline tellurium composites
As shown in Supplementary Fig. S3, the 10 μm polyethylene terephthalate substrate underwent sequential solvent purification: primary degreasing in ethanol via 30-minute ultrasonic bath followed by equivalent duration deionized water rinsing. To mitigate substrate deformation, the plasma-treated PET was electrostatically laminated onto polydimethylsiloxane backing. Selective metallization was achieved through removable adhesive masking, enabling magnetron-sputtered deposition of 50 nm Au films on 50% substrate area. Subsequent mask removal permitted full-surface tellurium encapsulation (50 nm thickness), establishing a bifunctional surface architecture with Au-Te heterojunction and pristine Te zones. Laser ablation (λ=1064 nm) defined circular thermal transduction elements (1 mm diameter) at Au-Te/Te interfacial boundaries.

Precision electrode fabrication involved: (1) sputter-coating indium tin oxide through stepwise masked alignment, generating electrically isolated conductive traces; (2) laser-assisted micro-patterning to form peripheral interconnects. Final device integration coupled the thermal transducer with ITO electrode discontinuities through photolithographic alignment, completing assembly of the polycrystalline tellurium thermosensitive platform.

Electrical Characterization of Te-based thermoelectric subsystem
We use a semiconductor analyzer (Keithley B1500A) to record the thermoelectric potential output of the sensing unit. We use a Peltier element as a single-side heat source, acquiring different temperature values through voltage control and calibrating with a thermocouple (UNI-T, UT325). To maintain the target contact temperature, we connect a thermocouple probe to the Peltier element and place a thermistor above the probe (Supplementary Note S4, Table S6). After applying a bias voltage to the Peltier element for 3 minutes, the corresponding temperature is recorded as the contact temperature. The opposite-side temperature is obtained by placing a Te-based thermistor between the thermocouple probe and the Peltier element. After applying a bias voltage to the Peltier element for 3 minutes, the corresponding temperature is recorded as the opposite-side temperature. To facilitate temperature calibration and enhance controllability, a commercially available temperature-controlled hot plate is subsequently used as the heat source to calibrate the temperature sensing subsystem within the integrated device.

Elastomeric structural system with visuotactile encoding
The probe’s load-bearing framework is constructed via additive manufacturing (layer resolution: 25 μm), achieving structural integrity within a 10 mm³ volumetric footprint. A transparent elastomeric dome (diameter: 5 mm, Shore 10A compliance) is precision-molded using optical-grade silicone, engineered to simultaneously enable contact-induced strain visualization and maintain >92% light transmittance for endoscopic imaging. Tactile fiducial markers (+=200 μm, carbon-particle enhanced) are strategically patterned to maximize tactile signal discrimination while maintaining <5% surface coverage for minimal optical obstruction.

Surface topology control is implemented through CNC-machined aerospace-grade aluminum molds (R <0.8 μm), ensuring sub-micrometer surface roughness on the elastomer. The marker integration protocol involve: (1) micro-needle indentation (+=100 μm) using vacuum-assisted mold transfer. This hierarchical fabrication methodology guarantees marker durability under cyclic contact stresses exceeding 50 kPa. Complete process schematics are provided in Supplementary Fig. S3.

EndoForce dataset collection
To construct a reliable dataset for training the EndoForce network, researchers design a 3D force acquisition system (Supplementary Fig. S7). The endoscopic probe is fixed to an ATI Gamma force-torque transducer, with their coordinate systems precisely aligned. Initial calibration measurements show that the sensor exhibits baseline drift in the non-contact state. By controlling the interaction between the instrument tip and various soft tissues, researchers obtain synchronized recordings of triaxial force vectors and corresponding endoscopic images, which form the foundational training corpus for the machine learning framework.

The data acquisition protocol captures tissue deformation patterns in real time via the probe’s imaging system, while simultaneously performing precise force measurements (the latter serving as reference values). The study employs 11 soft objects (with elastic modulus ranging from 0 to 100 kPa), covering the hardness range of real biological tissues, to verify mechanical performance in complex luminal environments.

Operators systematically apply contact forces at three levels (high, medium, and low) from 9 directions, ensuring coverage of a wide range of contact scenarios and force variations. To enhance the heterogeneity of the dataset, we fabricate 2 probes with different imprints under different operating environments. This methodology constructs a comprehensive 3D force database containing 121,800 experimental samples, of which 24,000 samples are used for network evaluation.

EndoForce network
As depicted in Fig. 3b, our methodology initiates with acquiring spatial marker distribution data through an Efficient-SAM semantic segmentation model applied to tactile imagery. Subsequently, the system calculates the disparity between current segmented markers and their baseline positions (recorded during non-interaction periods) to capture positional displacements.

Furthermore, an automated tracking system monitors centroid coordinates of the nine-marker array in real time. The system interprets stationary centroid coordinates as indicative of non-contact conditions, triggering a suspension of EndoForce network parameter updates until subsequent positional variations are detected. This design ensures computational efficiency during inactive phases while maintaining readiness for dynamic interaction analysis.

Image inpainting dataset
To establish a comprehensive image inpainting dataset, we first design a modified T-scope sensor—this sensor removes the textured surface layer and enables the acquisition of clean tactile images without interference from physical markers. We use the T-scope to collect real tissue contact sequences in in-vivo animal experiments. Subsequently, we systematically superimpose artificial patterns that simulate real marker characteristics (including positional variation, dimensional diversity, and angular rotation) onto these baseline images. This method generates precisely aligned input-target image pairs, providing effective training conditions for the reconstruction algorithms used to remove patterns.

Through computational augmentation techniques detailed in Supplementary Fig. S10, we generate multiple synthetic variants of each original image that match the distribution of ground-truth labels, enabling image expansion. This process ultimately constructs a large-scale dataset containing 17,500 samples, of which 900 samples are reserved for the final evaluation of the network.

Visual inpainting network
The raw input undergoes feature extraction through the segmentation framework, which precisely localizes the geometric distribution of marker patterns. To enhance reconstruction integrity, the algorithm expands the initial segmentation boundaries by 20% of the original dimensions, generating an enhanced mask that incorporates potential interference regions. This mask serves as a critical parameter to guide subsequent inpainting operations, effectively eliminating visual artifacts induced by markers. The trained inpainting network processes both the tactile image and augmented mask in parallel, ultimately producing a high-fidelity tissue surface representation devoid of marker interference.

Computational latency profiling
The current prototype prioritizes functional validation over runtime optimization. The image acquisition subsystem employs a Raspberry Pi 4B microcomputer executing Python-based capture routines, transmitting 224×224 pixel data at 30 fps through Gigabit Ethernet to a host workstation equipped with a GeForce RTX 4080 GPU (16GB VRAM). Deep learning models for 3D force field prediction and image restoration achieve respective throughputs of 30 fps and 17.8 fps, meeting real-time interactive requirements.

In vivo experimental protocol
All experimental procedures comply with the ethical guidelines are approved by the Wuhan Laboratory Animal Administration Office (Protocol ID: HZAURAB-2025-0017). Please refer to Supplementary Note S5 for the specific implementation process.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript \"Superelastic Tellurium Thermoelectric Coating for Advanced Trimodal Microsensing\" is meaningful because it simultaneously implements visual, tactile, and temperature sensing in a single endoscopic probe. However, compared to several previously published studies on the visuo-tactile endoscope, there are still many shortcomings, and the temperature measurement does not significantly impact in its performance. It is an example of applying the additional benefits of the material's properties to the endoscope.\nEven in the existing published literature - for example, the Vision-based Tactile Sensor for Endoscopy reported by Takashima et al.( DOI: 10.1007/978-4-431-30962-8_2 ) attempts have been made to provide contact information along with visual images by integrating tactile sensors at the end of the endoscope. This work has shown the potential to provide real-time tactile feedback with minimal degradation in the quality of optical images. One of the author’s basic ideas for measuring tactile force in your paper seems to originate here, which is surprising that it is not a reference.\nOne of the biggest issues with the proposed study was the study of endoscopes, which were only verified at a level that seemed significantly less likely to be used, and even if they were clinically verified, the performance suggested is still limited. The effectiveness of the study is minimal because the tumor simulation used in the study is only a simplified material, and the experiments on rabbit and pig stomach tissues do not reflect the various pathological complexities that appear in the actual patient environment.\nAI models are also lacking. EndoForce and ProPainter networks have been utilized for 3D force estimation and image correction (impainting), respectively, but the dataset is gathered in a very limited environment, resulting in insufficient generalization to real external environments.\nOverall, it seems to be nothing more than a study that finds application cases of special sensor materials, and the research results are comprehensively insufficient to be published in Nature Communications, so rejection of publication seems appropriate.\nAdditional review contents have been added to the following.\n1. The main text requires descriptions for Figures 2c, 2e, 3c, 4e, 4f, and 4g. These figures are present, but their corresponding explanations are missing from the body of the paper.\n2. In lines 223-225, Figures 2i and 2j are explained together. However, it would be better to provide a separate and more detailed explanation for Figure 2i. Based on the current sentence, it is difficult to understand what Figure 2i represents.\n3. In line 274, the statement, \"The marker layer enabling tactile perception introduces visual occlusion in endoscopic images (Fig. 3f),\" does not align well with the content of Figure 3f. A more appropriate description or a more suitable figure is needed.\n4. Overall, the figures in the \"Results\" section are not well described. The figures themselves are difficult to understand and should be replaced with more effective ones. Additionally, the descriptions for all figures need to be thoroughly reviewed and revised.", "reviewer_2": "This manuscript presents a novel multimodal endoscopic sensing platform, the T-scope, which integrates visual, tactile, and thermal sensing into a single functioning device. The work addresses a longstanding technological limitation of conventional endoscopes, namely their inability to provide tactile and temperature perception alongside visual imaging. The authors report a technically innovative solution using tellurium thermocouples and viscoelastic silicone encapsulation, further enhanced by optimized heterointerfaces and deep neural network algorithms. As a result, the device is capable of allowing high-quality imaging, precise thermal mapping, and force feedback at microscale resolution. Moreover, the T-scope is compatible with standard and commercial endoscopes, and clinical verification has been performed through in vivo and in vitro experiments. The manuscript is well-structured and technically rigorous; however, a few minor revisions would further enhance its overall clarity and readability.\n1) The introduction would benefit from a clearer comparison with existing benchmarks and state-of-the-art approaches. In particular, an explicit discussion of tellurium relative to alternative materials would strengthen the rationale for selecting this material.\n2) Further discussion on the stability, biocompatibility, and cost estimation of the proposed system would be valuable to assess its translational potential.\n3) A more detailed description of the experimental setup for temperature measurements would enhance transparency and reproducibility. Have the authors employed a thermocouple as a reference instrument to acquire the temperature?\n4)The readability of Figures 2 and 3 is limited; incorporating a legend and clearer annotations would substantially improve their interpretability.\n5) The authors are encouraged to discuss whether, in addition to visual feedback, the integration of alternative modalities—such as advanced haptic feedback systems—could further strengthen the closed-loop performance of the instrument. Including such considerations in the discussion section would highlight opportunities for future development.", "reviewer_3": "This work proposes a tellurium-based thermoelectric visual-tactile endoscope that integrates imaging, temperature sensing, and force feedback into a single platform. While the system is promising for multifunctional endoscopic applications, some questions remain to be addressed.\n1. The definitions of 'contact beginning,' 'stable contact,' 'fast contact,' and 'slow contact' are ambiguous. This makes it difficult to interpret the results of the in vitro contact experiment. Please clearly define these terms, for example, by specifying them along the time axis, to improve the clarity of the analysis.\n2. Some figures included in the main manuscript are not cited in the text. Please check all figure references to ensure every figure is properly called out and discussed.\n3. A significant number of figures contain a variety of typographical and display errors. For instance, in Figure 4i, the label \"contact beginning\" is improperly positioned and overlaps with other text. It is highly recommended that the authors perform a comprehensive and meticulous review of all figures, including the supplementary figures, to correct these issues. Ensuring the accuracy of all values, labels, and legends is crucial for the credibility of the presented data."}, "author_response": "Author Response to Reviews of\nSuperelastic Tellurium Thermoelectric Coatings for\nAdvanced Trimodal Microsensing (NCOMMS-25-\n66562)\nShaoweiCui,LinlinLi,Zi-xinHuang,YanzheYu,MingxueCai,XiangyinBao,ChaofanZhang,Tiandong\nZhang,LongCheng,WenxuanZhang,ZhengLou,ShuoWang,WenGong,Chao-fengWu,LiliWang,Yu\nWang\nNatureCommunications\nRC:ReviewerComment, AR:AuthorResponse\nReviewer#1\nGeneralComment\nRC: Themanuscript\"SuperelasticTelluriumThermoelectricCoatingforAdvancedTrimodalMicrosensing\"\nismeaningfulbecauseitsimultaneouslyimplementsvisual,tactile,andtemperaturesensinginasingle\nendoscopicprobe.However,comparedtoseveralpreviouslypublishedstudiesonthevisuo-tactileendoscope,\nthere are still many shortcomings, and the temperature measurement does not significantly impact in\nitsperformance. Itisanexampleofapplyingtheadditionalbenefitsofthematerial’spropertiestothe\nendoscope.\nAR: Manythanksforyourprofessionalcomments. Comparedwithprevioustactileendoscopestudies,ourstudy\nfocusonintroducingtemperaturesensingintoavisual-tactileendoscopysystem,achievingsimultaneous\nmultimodalsensing(visual,forceandtermperature)onacommonendoscopyprobeforthefirsttime.\nFirstly, we confirmed the significance of the temperature modality through consultations with practicing\nphysicians. Additionally, during our review of existing research, temperature is a crucial monitoring\nindicatorinendoscopicsurgery[1,2]. Kozenetal. mentionedthat\"Althoughthetheoreticalriskofelevated\ntemperaturesduringendoscopicearsurgeryhasbeenreportedpreviously,neithertemperaturechangenor\nheatdistributionassociatedwiththeendoscopehasbeenquantified[2].\"Meanwhile,temperatureisalso\nimportantforprecisionmedicaldiagnosisoflesionaltissues[3,4]. Kimetal. mentionedthat\"Inoptical\nimagingofsolidtumors, signalcontrastsderivedfrominherenttissuetemperaturedifferenceshavebeen\nemployedtodistinguishtumormassesfromsurroundingtissue[3].\"\nReferences:\n[1]MadhvapathySR,BuryMI,WangLW,etal. Miniaturizedimplantabletemperaturesensorsforthe\nlong-term monitoring of chronic intestinal inflammation[J]. Nature Biomedical Engineering, 2024, 8(8):\n1040-1052.\n[2]KozinED,LehmannA,CarterM,etal. Thermaleffectsofendoscopyinahumantemporalbonemodel:\nimplicationsforendoscopicearsurgery[J].TheLaryngoscope,2014,124(8): E332-E339.\n[3]KimS,OhG,KimYR,etal. Infraredthermalmodulationendoscopyforlabel-freetumordetection[J].\n[4]CalvareseM,CorbettaE,ContrerasJ,etal. EndomicroscopicAI-drivenmorphochemicalimagingand\nfs-laserablationforselectivetumoridentificationandselectivetissueremoval[J].ScienceAdvances,2024,\n10(50): eado9721.\nHowever, while the aforementioned studies have demonstrated the significance of temperature in tissue\ndiagnosis, most existing studies have used independent channel temperature sensing systems and\nhave not yet integrated these technologies into endoscopy systems. To the best of our knowledge,\nthe T-scope system proposed by us is the first trimodal endoscopic sensing system that enables direct\ntemperaturemeasurementatthecontacttipwhileprovidingreal-timefeedbackonbothforceandoriginal\nvisualobservation.\nIn our revision, the results of endoscopic diagnosis experiments on living animals indicate that at\ntheboundaryofinflamedtissue,eventhoughthevisualmodalitydidnotobserveabnormalchanges\ncomparedwithnormaltissue,thetemperatureshowedasignificantincrease. Thisfindingconfirmsthe\nsignificanceofintegratingtemperaturesensingintoendoscopicsystems,particularlyforadvancingprecision\nmedicineapplications. Thankyouagainforyourprofessionalcomments,whichhavegreatlyimprovedthe\nqualityofourmanuscript.\nIntherevisedmanuscript,wehavecomprehensivelyrevisedtheabstract,introduction,AImodel,andanimal\nstudies. Wehaveselectedsomekeyrevisionsasfollows:\nRevision:\nINTRODUCTION:\"However,anotablelimitationofcurrenttactileendoscopesystemsliesintheir\ngenerallackoftemperature-sensingfunctionality,whichisacriticalcapabilityforendoscopicsurgeries.\nTheinvolvementoftemperaturemodalitiescanachievenecessarythermalmonitoring10,11(real-timetarget\ntissuetemperaturemeasurementtoavoidthermaldamage)andplayakeyroleintheaccuratediagnosisof\nabnormaltissues12-14(suchasidentifyinginflammationandtumorlesionsthroughlocaltemperaturechanges).\nRESULTS (2.6): \"To verify the efficacy of the T-scope system in real in-vivo scenarios, visual-tactile-\ntemperaturediagnosticexperimentsareconductedinthegastriccavityofanesthetizedrabbits(Supplementary\nMovieS6). Priortotheexperiments,apreciseinflammationmodelofrabbitgastrictissueisestablished\nthroughinflammationmodelingovera4-dayperiod.\"\n\"Aslidingtemperaturemeasurementexperimentisalsoconductedattheboundaryoftheinflamedtissue,\nwheretheprobeslidesfromthenormaltissuetotheinflamedtissue. Thecorrespondingvisualobservations\nandtemperaturechangecurvesarerecorded(Fig. 5d(ii)). Theresultsindicatethatattheboundaryof\nthe inflamed tissue, a noticeable temperature rise occurs even when no obvious visual changes are\nobserved. Thisfindingconfirmsthesignificanceofintegratingtemperaturesensingintoendoscopic\nsystems,particularlyforadvancingprecisionmedicineapplications.\" \nMajorComment#1\nRC: Evenintheexistingpublishedliterature-forexample,theVision-basedTactileSensorforEndoscopy\nreportedbyTakashimaetal.(DOI:10.1007/978-4-431-30962-8_2)attemptshavebeenmadetoprovide\ncontactinformationalongwithvisualimagesbyintegratingtactilesensorsattheendoftheendoscope.\nThisworkhasshownthepotentialtoprovidereal-timetactilefeedbackwithminimaldegradationinthe\nqualityofopticalimages. Oneoftheauthor’sbasicideasformeasuringtactileforceinyourpaperseems\ntooriginatehere,whichissurprisingthatitisnotareference.\ninitialversionofourmanuscript. Wesincerelyapologizeforfailingtoproperlycitethesignificantworkby\nTakashimaetal. (DOI:10.1007/978-4-431-30962-8_2)onthe\"Vision-basedTactileSensorforEndoscopy\"\ninthefirstdraft.\nIntherevisedmanuscript,wehavemadetargetedsupplementsandimprovements:\n1) WehaveformallycitedTakashimaetal.’sworkinthecorrespondingsection,andhaveaddedadetailed\ndiscussiontoclarifytheconnectionanddistinctionbetweenourresearchandthisstudy;\n2) Wehavefurthersortedoutandsummarizedthelatestresearchprogressinthefieldoftactileendoscopy,\nand added a comparative analysis with multiple representative studies (including this work) to more\nsystematicallypresentthepositioningandinnovationofourresearchintheexistingacademiccontext.\nOnceagain,weappreciateyourcarefulreviewandcriticalfeedback,whichhassignificantlyhelpedimprove\nthecompletenessandrigorofourmanuscript.\nRevision:\nABSTRACT:\"Tactileendoscopescanprovidephysicianswithrichsensoryinformation,enablingfastand\naccuratemedicaldiagnoses. However,existingtactileendoscopysensorsdonotconsidertemperature\nperception,whichisaveryimportantdiagnosticindicatorinmedicine.\"\nINTRODUCTION:\"Inthepastdecades,tactileendoscopesystemshaveachievedforcemeasurement\nwhile maintaining basic visual observation capabilities3-6. This marks progress in enhancing the\nsafetyandaccuracyofendoscopicproceduresbyenablingsurgeonstoobtainbothvisualinsightsinto\nthesurgicalsiteandquantitativeforcefeedback7-9. However,anotablelimitationofcurrenttactile\nendoscopesystemsliesintheirgenerallackoftemperature-sensingfunctionality,whichisacritical\ncapabilityforendoscopicsurgeries. Theinvolvementoftemperaturemodalitiescanachievenecessary\nthermalmonitoring10,11(real-timetargettissuetemperaturemeasurementtoavoidthermaldamage)andplaya\nkeyroleintheaccuratediagnosisofabnormaltissues12-14(suchasidentifyinginflammationandtumorlesions\nthroughlocaltemperaturechanges). Therefore,howtoseamlesslyintegratetemperaturesensingtechnology\nintotactileendoscopysystemtoachievehigh-precision3Dforcemeasurementandhigh-definitionvisual\nimagingwithoutcompromisingthesystem’sexistingcompactstructureremainsasignificantchallengeinthis\nfield. \"\nREFERENCE:\"3. Takashima,K.,Yoshinaka,K.,Ikeuchi,K.: Vision-basedtactilesensorforendoscopy.\nIn: ComplexMedicalEngineering. SpringerJapan,Tokyo,pp. 13–23(2007)\"\nMajorComment#2\nRC: Oneofthebiggestissueswiththeproposedstudywasthestudyofendoscopes,whichwereonlyverified\nat a level that seemed significantly less likely to be used, and even if they were clinically verified, the\nperformance suggested is still limited. The effectiveness of the study is minimal because the tumor\nsimulationusedinthestudyisonlyasimplifiedmaterial,andtheexperimentsonrabbitandpigstomach\ntissuesdonotreflectthevariouspathologicalcomplexitiesthatappearintheactualpatientenvironment.\nAR: Thank you very much for your valuable comments and constructive suggestions, which have provided\nimportantguidanceforimprovingourstudy. OurultimategoalisundoubtedlytoapplytheT-scopesystem\ntohumanendoscopydiagnosis,butduetothereviewrestrictionsofhumanexperimentsandtheresearch\n3\nstage,weareunabletoconductrealhumanexperimentsatthisstage. Fortunately,wecanrefertoexisting\nexperimentalmethodsofexistingendoscopicdiagnosticliterature,whichusemammalssuchaspigs,\nrabbits,dogs,andmouse[1,2,3,4,5,6]tosimulatecomplexhumanlesions.\nReferences:\n[1]KongW,SunB,WangZ,etal. Physiologicallybasedpharmacokinetic–pharmacodynamicmodeling\nforpredictionofvonoprazanpharmacokineticsanditsinhibitionongastricacidsecretionfollowingintra-\nvenous/oraladministrationtorats,dogsandhumans[J].ActaPharmacologicaSinica,2020,41(6): 852-865.\n[2]LongY,LinA,KwokDHC,etal. Surgicalembodiedintelligenceforgeneralizedtaskautonomyin\nlaparoscopicrobot-assistedsurgery[J].ScienceRobotics,2025,10(104): eadt3093.\n[3]ShademanA,DeckerRS,OpfermannJD,etal. Supervisedautonomousroboticsofttissuesurgery[J].\nSciencetranslationalmedicine,2016,8(337): 337ra64-337ra64.\n[4] Saeidi H, Opfermann J D, Kam M, et al. Autonomous robotic laparoscopic surgery for intestinal\nanastomosis[J].Sciencerobotics,2022,7(62): eabj2908.\n[5]GarrickT,MulvihillS,BuackS,etal. Intracerebroventricularpressureinhibitsgastricantralandduodenal\ncontractilitybutnotacidsecretioninconsciousrabbits[J].Gastroenterology,1988,95(1): 26-31.\n[6]GoG,JeongSG,YooA,etal.Humanadipose–derivedmesenchymalstemcell–basedmedicalmicrorobot\nsystemforkneecartilageregenerationin-vivo[J].ScienceRobotics,2020,5(38): eaay6626.\nWefoundthatpigsandrabbitsarethemostcommonlyusedlaboratoryanimals. Forinstance, pigswere\nemployedasexperimentalsubjectsforautonomousroboticsurgeryin[3], whilemagneticallycontrolled\nsurgerywasperformedonrabbitsin[6]. Wefinallychoselivedomesticrabbits—amorespace-challenging\noption—asthelaboratoryanimalsforconductingin-vivoexperimentsintherevisedmanuscript.\nTaking full account of the pathological complexity of human lesion tissues, we ultimately chose to\ninduceinflammationtoestablishamodelofthegastrictissueinexperimentalrabbitsovera4-day\nperiodtosimulatetheactualpatientenvironment.\nSpecifically,weestablishedaninflammationmodelinthestomachofliverabbitsandconductedacomplete\nvisual-tactileendoscopicpalpationexperimentusingtheproposedT-scopehapticendoscopesystem. These\nexperimentscoveredthreecompleteprocesses: visualnavigation,visualobservation,temperatureandforce\nsensingofinflamedtissues. Inadditiontotheoriginalendoscopicvisualobservationfunction,weachieved\naccuratetactilediagnosisandobtainedinformationonthetemperaturedistributionandmechanicalresponse\ncharacteristicsoftheentireinflamedtissue. Theexperimentalresultsshowthatevenwhennoobvious\nvisualchangesareobserved,asignificanttemperatureincreaseoccursattheboundaryofinflamed\ntissues. This finding confirms the importance of integrating temperature sensing technology into\nendoscopicsystems,whichisparticularlycrucialforadvancingprecisionmedicineapplications.\nRevision:\nRESULTS (2.6): To verify the efficacy of the T-scope system in real in-vivo scenarios, visual-tactile-\ntemperaturediagnosticexperimentsareconductedinthegastriccavityofanesthetizedrabbits(Supplementary\nMovieS6). Priortotheexperiments, apreciseinflammationmodelofrabbitgastrictissueisestablished\nthroughinflammationmodelingovera4-dayperiod. TheT-scopeprobeisencapsulatedatthefrontend\nofahandheldendoscope,whichisthendeliveredintotherabbit’sbodythroughitsoralcavitytoperform\nvisual-tactileendoscopicdiagnosis(Fig. 5a). Attheinitialstageoftheexperiment,researchersnavigatethe\nusingamanuallyoperatedT-scopeprobe. bEndoscopicvisualnavigationeffectoftheT-scopeendoscopic\nsystem, starting from the oral cavity, passing through the esophagus and cardia, and finally reaching the\ninflamedtissueinthestomach.c(i)Comparisonofnormalforcechangesandvisualobservationresultsduring\nthepressingprocessonnormalgastrictissueandinflamedlesiontissue. (ii)Comparisonchartofnormalforce\nchangecurvesduringtworegularpressingprocessesonnormalandinflamedtissues;theinflamedtissueis\nstiffer,resultingingreaterspeedchangerateandpressurevalue. d(i)Temperaturedistributionmapobtained\nbymultipletemperaturemeasurementsintheboundaryareaaroundtheinflamedtissue. (ii)Temperature\nchangecurveandkeyframeimagesduringtheprocessofslidingtheprobefromthenormaltissuetothe\ninflamedtissue.\nprobedeliveryprocessusingconventionalendoscopicobservation. Fig. 5billustratesthevisualobservation\nsequence,whichtrackstheprobe’spathfromtheexterioroftherabbit’soralcavity,throughtheesophagus\nand cardia, and finally to the inflamed gastric tissue. This sequence not only demonstrates the system’s\nexcellentvisualobservationperformancebutalsoconfirmstheeffectivenessandstabilityoftheproposedAI\nvisualrestorationalgorithminrealin-vivoscenarios(SupplementaryFig. S15).\nDuringthepressingprocessonnormalandabnormaltissuesinsidethelivingrabbit, theT-scopesystem\n5\nis observed to achieve accurate visual reconstruction while exhibiting highly sensitive force estimation\ncapabilities(Fig. 5c(i)). Whenresearchersapplysimilarpressingforcestodifferenttypesoftissues,itis\nfoundthattheinflamedtissue—duetoitshigherhardness—exhibitssignificantlylargerabsolutevaluesof\nnormalforceandafasterforceincreaseratecomparedtonormaltissue(Fig. 5c(ii): rate,-0.016vs-0.009;\nmaximumabsolutevalueofnormalforce,516mNvs328mN).\nFurthermore, intensive contact sampling is performed in the vicinity of the inflamed tissue to obtain the\ntemperaturedistributionoftheinflamedtissueanditsboundaryregions(Fig. 5d(i)). Theresultsrevealthat\nthetemperatureoftheinflamedtissueissignificantlyhigherthanthatofnormaltissue,withamaximum\ntemperature difference of approximately 4 °C. A sliding temperature measurement experiment is also\nconducted at the boundary of the inflamed tissue, where the probe slides from the normal tissue to the\ninflamedtissue. Thecorrespondingvisualobservationsandtemperaturechangecurvesarerecorded(Fig. 5d\n(ii)). Theresultsindicatethatattheboundaryoftheinflamedtissue,anoticeabletemperatureriseoccurs\nevenwhennoobviousvisualchangesareobserved. Thisfindingconfirmsthesignificanceofintegrating\ntemperaturesensingintoendoscopicsystems,particularlyforadvancingprecisionmedicineapplications.\nMajorComment#3\nRC: AImodelsarealsolacking. EndoForceandProPainternetworkshavebeenutilizedfor3Dforceestimation\nandimagecorrection(impainting),respectively,butthedatasetisgatheredinaverylimitedenvironment,\nresulting in insufficient generalization to real external environments. Overall, it seems to be nothing\nmorethanastudythatfindsapplicationcasesofspecialsensormaterials,andtheresearchresultsare\ncomprehensivelyinsufficienttobepublishedinNatureCommunications,sorejectionofpublicationseems\nappropriate.\nAR: Thankyouverymuchforyourprofessionalcomments. RegardingtheProPainternetwork,inourrevised\nmanuscript,wehavecomprehensivelyreplacedtheprevioussimulatedtissueacquisitionprotocolwith\nmarker-freevisualimageacquisitionconductedonthelaryngealandgastrotrachealregionsoflive\nanimals. Theentiredatasetcomprisesapproximately65kdatasamples,andweperformedageneralization\ntest in real live animal experiments, which involved visual observation of various types of normal and\npathologicaltissues(includinginflammationandwounds). TheresultscanbefoundinSupplementaryFig.\nS15ofourrevisedmanuscript.\nIntermsofthetactileAImodel,theproposedEndoForcemodelextractsTeimprintmasksdirectlyfromraw\nimagesfordeformationtracking. Theforceestimationnetworkisindependentofthevisualbackground\nofrealvisceraltissues,buthighlycorrelatedwiththehardnessofthecontactedmaterial. Therefore,\nwehavesignificantlyexpandedthedatacollectionscenariosforthetactilenetwork,nolongerlimitingit\ntosimulatedorrealorgans. Intheoriginalmanuscript, weusedasimulatedhumanstomachmodel\nforforcedatacollection. Intherevisedmanuscript,weinsteadcollecteddataonrealanimaltissues,\nincluding11materialscoveringawiderangeofstiffness(includingrealpigstomach, pigliver, pig\nviscera,pigtongue,humanskinandotherrealanimalorgantissues),coveringthehardnessrangeof\ncommonhumansofttissues(spanning0–100kPa[1]). Forreference,thehardnessofhumangastrictissue\ntypicallyrangesfromapproximately0.5to5kPa[2].\nReferences:\n[1] Hai P, Zhou Y, Gong L, et al. Quantitative photoacoustic elastography of Young’s modulus in hu-\nmans[C]//PhotonsPlusUltrasound: ImagingandSensing2017. SPIE,2017,10064: 34-41.\n[2]JangM,AnJ,OhSW,etal. Matrixstiffnessepigeneticallyregulatestheoncogenicactivationofthe\nMeanwhile,inourin-vivoexperiments,weusedtheT-scopetomakerepeatedcontactwithvarioustypesof\nrealgastrictissuesandabnormaltissues,withthenumberofcontactinstancesexceeding50. Thesetissues\ntypicallyexhibitdistincthardnessdistributions,whichresultinawiderangeofforce-sensingcharacteristics—\nasillustratedinFig. 5oftherevisedmanuscript. TheresultsdemonstratetheeffectivenessofourEndoForce\ninforceestimationfordifferentrealtissues.\nRevision:\nRESULTS(2.4): \"Becausetheproposedthermoelectricdevicesprovidenaturallandmarksintheendoscopic\nfieldofview,ourendoscopicvisionsystemcancapturetheirpositionandoverallshapechanges,thereby\ncreating an accurate map of the 3D contact forces acting on the probe36,37. We first design a tactile data\nacquisitionsystem(Fig. 3a(i)): twoT-scopetactileendoscopicprobeswithdifferentmarkerpatterns(Fig.\n3a(ii))arefixedonacommercialmulti-dimensionalforcesensor. Contacttestswithvaryingdirectionsand\nmagnitudes are conducted using a variety of soft materials that fully cover the hardness range of human\ntissues(elasticmodulusfrom0to100kPa)(Fig. 3a(iii),SupplementaryFig. S7). Thesix-axisforce/torque\nsensorprovidestheground-truth3Dforcesactingonthesurfaceofthetactileprobe. Subsequently,weadopt\\adata-drivenapproachandproposetheEndoForce3Dforceestimationnetworktodirectlyestimate3Dforces\nfromrawvisualobservationinputs.\"\na b c\n3D force dataset\nmapping\nmarkers distribution\nnetwork\nIn Out\n4\n3\n1: Handheld pig stomach tissue 2: T-scopesensor 3: Connector 4: Force sensor 5: Platform\nSupplementaryFig. S7|The3Dforcedatasetcollectionpipeline. aTheT-scopesensorisfixedonan\nstandardATIsix-axisforce/torquesensor,andarealpieceofpigstomachtissueiscontactedwiththesensor\nsurfacemanually. bAdozenobjectscoveringthehardnessrangeof0-100KPaareusedfordatacollection. c\nThe3Dforcedatasetcontainsabundanttactileimage-forcepairs,andeachsampleprovidesaground-truth\n3Dforcelabelundervariouscontactscenes.\nRESULTS(2.4): \"Thermoelectricalimprintscausevisualocclusioninendoscopicimages(Fig. 3a(ii)),which\nmaycompromisetheclarityofthediagnosticfieldofview. Toaddressthisissue, weadoptProPainter39\nfor AI-driven visual inpainting. We first prepare a dataset suitable for real in-vivo tissue scenarios (Fig.\n3d(i),SupplementaryNoteS3). Specifically,weuseaT-scopeprobewithoutthermal-electricalmarkersto\ncapturevideosoftherespiratorytractandgastrictissuesofliverabbits. Visualinpaintingsyntheticdatasets\narethengeneratedbymanuallyaddingvariousmarkers,includingdifferentdotarraysanddot-linepatterns\n(SupplementaryFig. S10).\"\nRESULTS (2.4): \"We first retrain the ProPainter network using the synthetic dataset with ground-truth\nlabels. Inrealin-vivoexperiments,thevisualinpaintingnetworkwiththetrainedweightsisdirectlyusedfor\nreal-timevisualobservation(Fig. 3d(ii)). Resultsfromthein-vivoexperimentsshowthatthecross-domain\ntrainedmodelsuccessfullyreconstructsvisualinformationoccludedbydifferentthermoelectricalimprints\n(Fig. 3e(ii)). MoreinpaintingexamplescanbefoundinSupplementaryFig. S11andS12.\"\nRaw\nMask\nRestored\nRaw\nMask\nRestored\nSupplementaryFig. S12|Visualizationofanimagerestorationexample. Weplaceaprobewitha\ndot-linearrayimprintontheoralcavity,esophagus,andstomachofalivingrabbit,generatingvisual\nimagesandtherestorationresults.\nMinorComment#1\nRC: ThemaintextrequiresdescriptionsforFigures2c,2e,3c,4e,4f,and4g. Thesefiguresarepresent,but\ntheircorrespondingexplanationsaremissingfromthebodyofthepaper.\nAR: Thankyousincerelyforyourmeticulousreviewandvaluablefeedback, whichhashelpedusidentifyan\nimportantoversightinthemanuscript. Intherevisedmanuscript,wehavesupplementeddetaileddescriptive\ncontentforeachofthesesixsubfiguresattheirrespectivecorrespondingpositionsinthemaintext.\n4b(iii),and4c(i)intherevisedmanuscript.\nRevision:\nRESULTS(2.2): \"Thisuniquecrystalstructureexhibitssignificantlatticescattering,effectivelysuppressing\nlatticeheatconductionandpromotingtheestablishmentofasignificanttemperaturegradient(Fig. 2c). This\nenablesefficientthermoelectricconversionandreducesthetrade-offbetweenthicknessandresponsivity.\nThe fabrication process flow comprises the following key steps (Fig. 2d, Further details in the Methods\nsection and Supplementary Fig. S3): Initial surface cleaning and PDMS composite treatment of 10 um\nPET substrates; Magnetron sputtering deposition of gold electrodes on half-area substrates followed by\nfull-substratetelluriumthinfilmdeposition;LaserdirectwritingprocessingofAuTe-Teinterfacesinto1mm-\ndiametertemperature-sensitiveunit(Fig. 2e). Whenplacedona42◦Chotplate,thetemperature-sensitive\nunitdemonstratescleartemperaturefielddistributioncharacteristicsonitssurfaces,confirmingtemperature\ndetectioncapabilities.\"\nRESULTS(2.4): \"Experimentalresultsdemonstratethatthesystemachievesexcellentperformanceunder\nvarying contact magnitudes and directions (Supplementary Table S3 and S4). The average errors of the\ncontact tangential and normal force components are 0.02 N and 0.06 N, respectively. Error distribution\nanalysisrevealsconsistentpredictionaccuracyacrossdifferentforcemagnitudes,withnoerrorescalation\nobserved when contact forces increase (Fig 3c(i)). Directional error analysis (Supplementary Fig. S9)\nindicatescomparableperformanceacrossdifferentorientations,thoughslightlyhighererrorsoccurinthe\ncentralanddownwarddirections. Thisphenomenonmaybeattributedtothecontacthabitsofoperators.\nFurthervalidationthroughrandomizedfingercontacttrials(Fig. 3c(ii))showsstable3Dforceestimation\nwithconsistentlylowerrors,confirmingthegeneralizationcapabilityofthenetwork.\"\nRESULTS(2.5): \"Biomechanicaltestdatafromthebronchialandgastricmodels(Fig. 4a(ii),b(ii))shows\nthatduetothehigherbiomechanicalstiffnessoftumortissue,thefluctuationofitsnormalforcevalueis\nmoresignificantthanthatofhealthytissuewhenmaintainingastablecontactstate. Visualinpaintingresults\n(Fig. 4a(iii),b(iii))indicatethattheinpaintingalgorithminthisstudycaneffectivelyeliminatetheocclusion\nofnormalandabnormaltissuescausedbythermoelectricdevices,enablingthenormalvisualobservation\nfunctionoftheendoscope. Inaddition,inthehumanintestinalmodel(Fig. 4c(i)),wealsoconductfastand\nslowcontacttestsonnormaltissues: Fig. 4c(ii)and(iii)respectivelyshowthecomparisonofnormalforce\nandtangentialforcesensedbytheT-scopeprobeduringfastcontactandslowcontact. Experimentalresults\nshowthattheincreaserateofnormalforce(-1.4vs-0.17)andthevibrationamplitudeoflateralforce(-58\nmNvs21mN)duringfastcontactaresignificantlygreaterthanthoseduringslowcontact,whichindirectly\nprovesthesensitivityandaccuracyofthe3Dforcesensingdeepneuralnetworkinthisstudy.\"\nMinorComment#2\nRC: Inlines223-225,Figures2iand2jareexplainedtogether. However,itwouldbebettertoprovideaseparate\nandmoredetailedexplanationforFigure2i. Basedonthecurrentsentence,itisdifficulttounderstand\nwhatFigure2irepresents.\nAR: Thank you for your constructive suggestions. We deeply apologize for the confusing description in the\noriginalmanuscript. Fig. 2ipresentsasimulationresultatacontacttemperatureof30◦C.Theimagedepicts\nthetemperaturemeasuredontheoppositesideofthesensorwhenitisexposedtoa30◦Cheatsource. This\nfigureaimstoillustratethethermalconductivitydifferencesbetweenTeandAuTemoreintuitivelythrough\nnumericalcurves. WehaverevisedthelegendanddescriptionforFigure2iintherevisiontobetterconvey\nthecontentandlogicofthemanuscript.\na b c\nITO/PET ITO/PET 41.4 °C\nTe\nAuTe2 PET Interchain Intrachain Te AuTe 27.7 °C\ne Top Bottom\nd\nPatterning\nPolycrystalline\nTe film Te/PET\nThermoelectric sensor\nAssembly\nf\nPatterningITO ITO\nTransparent electrodes Temperature sensor With ITO Without ITO\ng h 293.15 K Contact Temperature 313.15 K\nEcoflex\n8 mV\nTe AuTe2\nPET\nContact surfaces Thermoelectric potential -1 mV\ni j k\nFig. 2|Mechanismandevaluationofthethermoelectricsubsystem. aThestructureoftheTe-based\nthermoelectricsubsystem. bThelatticestructurediagramofTe. cThermalgradientunder42°Cthermal\nloading(Upper: Macroscopicobservation;Lower: Infraredthermographicmapping). dFabricationprocess\nflowforpolycrystallineTetemperaturedetector(Magnetronsputteringthin-filmdepositioncombinedwith\nlaser-assistedmicro-patterning). eAshotofthefinishedTe-basedthermoelectricsensor. fOpticalimageof\nmagnetron-sputteredITOfilmsdepositedonflexiblePETsubstrates,demonstratinghighopticalclarityand\nvisible-lighttransmittance. gComputationalsimulationillustratingtheworkingprincipleofthermoelectric\nsensingelements,incorporatinganelastomericcontactlayeratthetop(tosimulatethethermelectricsubsystem\nimmobilizedonthetactileinterface)andathermallyregulatedboundaryatthebottom(tosimulatedifferent\ncontacttemperatures),withcolormapvisualizationofthethermaldistribution. Thefigureutilizesacontact\ntemperatureof30◦Candanambienttemperatureof25◦C.hTheseebeck-inducedvoltagemappingwithin\nthefunctionallayers,quantitativelycorrelatedwithinterfacialtemperaturemodulationattheactivecontact\nregion,20-40◦C.iDistributionofthermalandelectricalpotentialsunder30◦Ccontacttemperaturealongthe\nupperendofthesubsystem. jTime-dependentvoltageresponsecharacteristicsofthedeviceundervarying\nthermaldifferentials,definedasthedifferencebetweenthecontacttemperatureandtheambienttemperature.\nkQuantitativedependenceofgeneratedelectricalpotentialonappliedtemperature.\nRESULTS(2.3):\"Byapplyingthermalgradients(20-40°C)atcontactinterfaces,simulationsrevealsignificant\ntemperaturefieldredistributionandcorrespondingthermalpotentialvariations(Fig. 2h,SupplementaryFig.\nS4). Atacontacttemperatureof30°C,a4°CtemperaturegradientacrosstheTedomainproducesa4mV\n10\noutput,demonstratingitsrobustthermaldetectioncapabilities(Fig. 2i). Thedifferenceinthermalbehavior\nbetweentheTeandAuTealloysisevident: AuTemaintainsauniformtemperaturedistributionduetoitshigh\nthermalandelectricalconductivity,whileTe’slowerlatticethermalconductivityresultsina10°Ctemperature\ngradient at a 40 °C contact temperature. This contrast amplifies carrier accumulation on the Te surface,\ngeneratinga9mVpotentialdifference(Fig. 2h),confirmingthemechanismoftemperature-dependentsignal\ngeneration.\nSubsequently, the thermoelectric performance is evaluated under controlled contact heat sources (20–42\n°C).TheTe-basedthermoelectricsensorexhibitsstableoutputpotentialatidenticalcontacttemperatures,\ndemonstratingitsstability(Fig. 2j).\"\nMinorComment#3\nRC: In line 274, the statement, \"The marker layer enabling tactile perception introduces visual occlusion\ninendoscopicimages(Fig. 3f),\"doesnotalignwellwiththecontentofFigure3f. Amoreappropriate\ndescriptionoramoresuitablefigureisneeded.\nAR: Thankyouforyourmeticulousreviewandvaluablefeedback. WehavecomprehensivelyrevisedbothFigure\n3fandthecorrespondingtextdescription. PleasenotethatFigure3finouroriginalmanuscripthavebeen\nmodifiedtoFigure3a(ii)intherevisedmanuscript.\nRevision:\nRESULTS(2.4): \"Thermoelectricalimprintscausevisualocclusioninendoscopicimages(Fig. 3a(ii)),which\nmaycompromisetheclarityofthediagnosticfieldofview.\"\nMinorComment#4\nRC: Overall,thefiguresinthe\"Results\"sectionarenotwelldescribed. Thefiguresthemselvesaredifficultto\nunderstandandshouldbereplacedwithmoreeffectiveones. Additionally,thedescriptionsforallfigures\nneedtobethoroughlyreviewedandrevised.\nAR: Thankyousincerelyforyourcriticalandconstructivecomment,whichdirectlypointsoutakeyweaknessin\nthe\"Results\"sectionofourmanuscript. Toaddresstheseproblemscomprehensively,wehaveimplemented\ntwocorerevisions: First,wesystematicallyevaluatedandupdatedallfiguresinthe\"Results\"section,\nidentifiedthosewithpoorreadabilityorineffectivedatapresentation,andreplacedthemwithmoreintuitive,\ninformation-richversions—theseupdatedfiguresprioritizeclearlabeling(e.g.,axes,legends,samplegroups),\nlogicaldataorganization(e.g.,groupedbarchartsforcomparativedata,linechartsfortrendanalysis),and\ndirectalignmentwiththekeypointstheyaimtoillustrate. Second,wehavethoroughlyreviewedandrevised\nthedescriptivetextforallfiguresinthesection: wesupplementedkeydetails(e.g.,experimentalcontext,\nsamplesizes,statisticalindicators)foreachfigure,clarifiedthemeaningofcoredatapointsortrends,and\nexplicitlylinkedthefigurecontenttothecorrespondingresearchconclusions—ensuringthatreaderscan\neasilyfollowhowthevisualdatasupportsourarguments.\nAllrevisedfiguresandtablesinthe\"Results\"section,alongwiththeirupdateddescriptivetext,canbefound\ninourrevisedversion. Wereviewedeachfigureanditsdescriptionmultipletimestoensureconsistency,\nclarity,andvalidityoftheofpresentation.\nGeneralcomment\nRC: Thismanuscriptpresentsanovelmultimodalendoscopicsensingplatform,theT-scope,whichintegrates\nvisual,tactile,andthermalsensingintoasinglefunctioningdevice. Theworkaddressesalongstanding\ntechnologicallimitationofconventionalendoscopes,namelytheirinabilitytoprovidetactileandtemper-\natureperceptionalongsidevisualimaging. Theauthorsreportatechnicallyinnovativesolutionusing\ntelluriumthermocouplesandviscoelasticsiliconeencapsulation,furtherenhancedbyoptimizedheteroint-\nerfacesanddeepneuralnetworkalgorithms. Asaresult,thedeviceiscapableofallowinghigh-quality\nimaging,precisethermalmapping,andforcefeedbackatmicroscaleresolution. Moreover,theT-scope\niscompatiblewithstandardandcommercialendoscopes,andclinicalverificationhasbeenperformed\nthroughin-vivoandinvitroexperiments. Themanuscriptiswell-structuredandtechnicallyrigorous;\nhowever,afewminorrevisionswouldfurtherenhanceitsoverallclarityandreadability.\nAR: Thankyousincerelyforyourpositiverecognitionofourwork—wegreatlyappreciateyouracknowledgment\noftheT-scope’snoveltyasamultimodalendoscopicsensingplatform,itstechnicalinnovations(e.g.,tellurium\nthermocouples,viscoelasticsiliconeencapsulation),anditsvalueinaddressingconventionalendoscopes’\nlimitations. Wefullyagreethatminorrevisionswillenhancethemanuscript’sclarityandreadability,\nandthushaveconductedacomprehensiverevisionoftheentiretext,focusingonthreekeyaspects:\nenrichingthetelluriumthermocouplespatterndesign,optimizingtheAIendoscopictactileperception\nalgorithm,andperformingrealanimalendoscopicpalpationexperiments. Alltheserevisions,along\nwith overall polishing for clarity, can be found in our revision, and we hope they further strengthen the\nmanuscript’squality.\nComment#1\nRC: Theintroductionwouldbenefitfromaclearercomparisonwithexistingbenchmarksandstate-of-the-art\napproaches. In particular, an explicit discussion of tellurium relative to alternative materials would\nstrengthentherationaleforselectingthismaterial.\nAR: Thanks to the reviewers for their valuable suggestions. Mainstream temperature detectors are broadly\ncategorizedintocontactandnon-contacttypes. Whileinfraredtemperaturesensorscouldcircumventdirect\ncontactwiththelesion,theirownaccuracyhasbeenthesubjectofcriticism. Incomparison,thedevelopment\nandapplicationofcontacttemperaturesensorshavereachedarelativelyadvancedstageofmaturity. Among\nthese,thePt,Cu,andotherpreciousmetalsrepresentthethermistor-typetemperaturesensors,exhibitingan\nexceptionallyhighsignalstability. However,thesignalitselfisrelativelylessvariable,andthehigh-precision\nmeans of detection are more complex. Furthermore, achieving high-precision signal detection requires\ncomplex bridge circuit calibration, which necessitates multiple lead wires—making implementation on\nflexible micro-probes impractical. Additionally, ensuring spatial measurement accuracy and minimizing\nexternal circuit variations demands constructing high-resistance sensitive units within a 1 mm diameter\ncircle,withmultiplewiresextendingoutward. Thisnecessitatestheintroductionofmicro/nanofabrication\ntechniques,significantlyincreasingprocesscomplexity. Incontrast,thermocouplesensorsinherentlybind\ntemperaturetocontactdepthduetotheirmechanism. Consequently,thermocouplesensorseliminatetheneed\nforintricatepatternedwiringdesignsandcanbecustomizedforvisual-tactilesensingrequirements,aligning\nwithourneeds.\nExistingresearchindicatesthattelluriumanditscompoundsexhibitoutstandingthermoelectricproperties.\nNotably,recentstudiesdemonstratethattelluriumnanomaterialshaveextremelylowthermalconductivity\n12\n(facilitatingpronouncedtemperaturegradients)andexceptionalSeebeckcoefficients(yieldinghighersignal\noutputsforthesametemperaturedifference),makingthemhighlysuitableforthermoelectricsensingunit\nfabrication. This is the rationale behind selecting Te thin films for device construction and optimization\ninthiswork. Forafullexplanationofthesystemandmaterialselection,wehavethoroughlyrevisedthe\nintroductionsectionandprovidedtablesinthesupportinginformationformaterialcomparisonsalongwith\nrelevantexplanations(SupplementaryNoteS4,TableS6).\nRevision:\nINTRODUCTION:\"Amongthemainstreamtemperaturemeasurementmethods,non-contacttemperature\nsensingrepresentedbyinfraredtemperaturesensorsisfavoredbecauseitavoidscontactdamage,butthe\nmeasurementaccuracyislimited15-17. Incontrast,contact-basedtemperaturesensorsarerelativelymaturein\ndevelopmentandapplication,primarilycategorizedintothermistorsandthermocouples. Thermistormade\nfrompreciousmetalslikePtandCuofferexceptionalsignalstability18-20. However,theirminimalsignal\nvariationandcomplexcalibrationcircuitsmakethemdifficulttointegrateontoflexiblemicro-probesfor\nvisual-tactilesensing,renderingthemmoresuitablefortemperaturedriftcalibrationinmicro-nanoelectronic\ndevices21-24. Thermocouples based on the Seebeck effect show a strong correlation between their signal\nandcontactpositionandhaveexcellentspatialresolution25-27. Leveragingthehighbanddegeneracyand\nunique lattice arrangements of tellurium materials, a series of outstanding thermoelectric materials have\nbeen developed around tellurium and its compounds28-32. However, due to thermoelectric mechanisms,\nthermocouplesystemsrepresentedbytellurium-basedcompoundstypicallyrequirelargerlongitudinalor\nlateraldimensionstoachievegreatertemperaturedifferentials. Thisinevitablyimpactssignalacquisitionand\nreconstructionintactilesensing. Therefore,theconstructionof3-dimensional,small-size,high-sensitivity\ntemperaturesensordevicesremainsanextremelysignificantchallenge.\"\nSupplementaryNoteS4: Thermoelectriceffect. Temperaturesensorsareprimarilycategorizedintonon-\ncontact and contact types. Non-contact sensors are susceptible to external interference and significant\ndetectionerrorsduetovariationsintheemissivityofthetargetobject. Therefore,contact-typetemperature\nsensorsarepreferred.\nContact-type temperature sensors mainly include thermistors and thermocouples. Thermistors primarily\nutilizepreciousmetalsandsemiconductorsassensitivematerials,measuringtemperaturebydetectingchanges\nintheirinternalresistanceunderthermalinfluence. Thesesensorstypicallyexhibitminimalinternalresistance\nchanges,resultinginrelativelysmallvariationsinthegeneratedelectricalsignal. Furthermore,achieving\nhigh-precisionsignaldetectionrequirescomplexbridgecircuitcalibration,whichnecessitatesmultiplelead\nwires—makingimplementationonflexiblemicro-probesimpractical. Additionally,ensuringspatialmeasure-\nmentaccuracyandminimizingexternalcircuitvariationsdemandsconstructinghigh-resistancesensitiveunits\nwithina1mmdiametercircle,withmultiplewiresextendingoutward. Thisnecessitatestheintroductionof\nmicro/nanofabricationtechniques,significantlyincreasingprocesscomplexity. Incontrast,thermocouple\nsensorsdonotrequirecomplexwiringdesignandcanbestructurallycustomizedaccordingtovisualand\ntactileperceptionrequirementstomeetourneeds.\nTheoretical and experimental research on thermocouple sensing materials is relatively mature. Existing\nresearchindicatesthattelluriumanditscompoundsexhibitoutstandingthermoelectricproperties(Supplemen-\ntaryTableS6). Notably,recentstudiesdemonstratethattelluriumnanomaterialshaveextremelylowthermal\nconductivity(facilitatingpronouncedtemperaturegradients)andexceptionalSeebeckcoefficients(yielding\nhighersignaloutputsforthesametemperaturedifference),makingthemhighlysuitableforthermoelectric\nsensing unit fabrication. This is the rationale behind selecting Te thin films for device construction and\noptimizationinthiswork.\nSIReferences: \"7. Zhou,M.,Su,H.,Pei,J.etal. UltrahighthermoelectricityobtainedinclassicalBiSbTe\n13\nalloyprocessedundersuper-gravity. NatCommun16,7645(2025).\n8.Gong,T.etal. High-Performanceplanarthin-Filmthermoelectriccoolerbasedonsputterednanocrystalline\nBi2Te3/Bi0.5Sb1.5Te3thinfilmsforOn-Chipcooling.ACSAppl. Mater. Interfaces. 17(11),17008–17017\n(2025).\n9. Zheng,G.etal. Highthermoelectricperformanceofp-BiSbTecompoundspreparedbyultra-fastthermally\ninducedreaction.Energ. Environ. Sci.10,2638–2652(2017).\n10. Hao,F.etal. HighefficiencyBi2Te3-basedmaterialsanddevicesforthermoelectricpowergeneration\nbetween100and300C.Energ. Environ. Sci. 9,3120–3127(2016).\n11. Kim,J.H.etal. PossibleRashbabandsplittingandthermoelectricpropertiesinCuI-dopedBi2Te2.7Se0.3\nbulkcrystals. J.AlloyCompd. 806,636–642(2019).\n12. Lin,S.,Li,W.,Chen,Z.etal. Telluriumasahigh-performanceelementalthermoelectric. NatCommun7,\n10287(2016).\n13. Wu,X.,Tao,Q.,Li,D.etal. Unprecedentlylowthermalconductivityofuniquetelluriumnanoribbons.\nNanoRes. 14,4725–4731(2021).\n14. Qiu,G.etal. ThermoelectricPerformanceof2DTelluriumwithAccumulationContacts. NanoLett. 19,\n1955–1962(2019).\"\nRC: Furtherdiscussiononthestability,biocompatibility,andcostestimationoftheproposedsystemwouldbe\nvaluabletoassessitstranslationalpotential.\nAR: Thankyouforyourprofessionalandinsightfulsuggestion. WehavesignificantlyexpandedtheDiscussion\nsectionoftherevisedmanuscript—withafocusonadvancingthetranslationalapplicationoftheT-scope\nsystem—to address these key aspects in detail, and also supplemented relevant content on subsequent\ntranslationalchallenges.\nRevision:\nDISCUSSION:\"Wespecificallydiscussitsperformanceandfeasibilityinthreecoredimensions: stability,\nbiocompatibility,andcost. Stability: Ourexperimentalresultsshowthatasingleprobecanreliablycomplete\nover10k+dataacquisitioncyclesandsupportmorethan20+fullanimalexperimentswhilemaintaining\noperationalfunctionality;toenhancestructuralstability,wedesignanintegratedframeworkwithbothsupport\nandconnectionfunctions,andfullyencapsulatetheentirestructurewithEcoflexsilicone. Wealsoexplicitly\nnote that the probe currently lacks an additional overload-resistant structure and may be damaged under\naccidental force exceeding 5 N, but it is easily replaceable, and its multi-layer elastomer encapsulation\nensures no components will remain in the body, effectively mitigating potential risks for practical use.\nBiocompatibility: ThecorematerialsoftheT-scopesystemincludeEcoflexelastomerandtellurium(Te):\nEcoflexhasmaturebiocompatibilityverificationdatatoconfirmitssafetyforbiomedicalscenarios;AsforTe,\nitistightlyencapsulatedbytwoinnerrubberlayersandanadditionaloutersiliconecoating. Thismulti-layer\nprotectioncompletelypreventsTefromcomingintodirectcontactwithhumantissue,furthereliminating\nbiocompatibilityissuesfortranslationaluse. Costestimation: Weprovideaclearbreakdown: thematerial\ncostformanufacturingasingleprobeisapproximately5USD,alow-costadvantagethatstronglysupports\nthesystem’spotentialforlarge-scalepracticalapplicationinclinicalsettings.\"\nComment#3\nRC: A more detailed description of the experimental setup for temperature measurements would enhance\ntransparencyandreproducibility. Havetheauthorsemployedathermocoupleasareferenceinstrumentto\nacquirethetemperature?\nAR: Thankyouforyourconstructivesuggestions. Asnoted,thisworkemploysaPeltierastheheatsourceduring\nsensor unit testing and utilizes a thermocouple to calibrate temperatures at different locations (Fig. 2k).\nTominimizecalibrationerrorsfromvaryingcontactpositionsandconfigurations,thethermocoupleprobe\nwasfixedtothePeltier,withthethermosensitiveunitcoveringtheprobetosimulatereal-worldconditions\nascloselyaspossible. DifferentbiasvoltageswereappliedtothePeltiertoachievevaryingtemperatures.\nAfterwaitingfor3minutes,thecorrespondingtemperaturevaluewasrecordedasthecontacttemperature.\nFollowingcontacttemperatureacquisition,thethermosensitiveunitwaspositionedbetweenthethermocouple\nprobeandthePeltier. Similarly,differentbiasvoltageswereappliedtothePeltierdevice. Afterwaiting3\nminutes,thecorrespondingtemperaturevalueswererecordedastheupper-sidetemperatures. Basedonthis,\nthetemperaturegradientcouldalsobeobtained. Consideringthissubsystemisprimarilyfortemperature\nsensing,subsequentintegrateddevicecalibrationsonlycollecttemperaturesatthecontactend.\nTofacilitatecontrollabletemperaturecalibration,acommerciallyavailabletemperature-controlledhotplate\nwassubsequentlyusedastheheatsourcetocalibratethetemperaturesensingsubsystemwithintheintegrated\ndevice. To evaluate the stability of the thermostat, we set the thermostat to a specific temperature and\nmaintaineditatthattemperaturefor3minutesbeforemeasuringthesurfacetemperatureusingathermocouple.\nfor subsequent temperature calibration. To avoid misunderstandings, we have provided a more detailed\ndescriptionofthetemperaturemeasurementintherevised\"Methods\"section.\nRevision: ElectricalCharacterizationofTe-basedthermoelectricsubsystem: Weuseasemiconductor\nanalyzer(KeithleyB1500A)torecordthethermoelectricpotentialoutputofthesensingunit. WeuseaPeltier\nelement as a single-side heat source, acquiring different temperature values through voltage control and\ncalibratingwithathermocouple(UNI-T,UT325). Tomaintainthetargetcontacttemperature,weconnecta\nthermocoupleprobetothePeltierelementandplacedathermistorabovetheprobe(SupplementaryNoteS4,\nTableS6). AfterapplyingabiasvoltagetothePeltierelementfor3minutes,thecorrespondingtemperature\nisrecordedasthecontacttemperature. Theopposite-sidetemperatureisobtainedbyplacingaTe-based\nthermistorbetweenthethermocoupleprobeandthePeltierelement. Afterapplyingabiasvoltagetothe\nPeltierelementfor3minutes,thecorrespondingtemperatureisrecordedastheopposite-sidetemperature. To\nfacilitatetemperaturecalibrationandenhancecontrollability,acommerciallyavailabletemperature-controlled\nhotplateissubsequentlyusedastheheatsourcetocalibratethetemperaturesensingsubsystemwithinthe\nintegrateddevice.\nComment#4\nRC: The readability of Figures 2 and 3 is limited; incorporating a legend and clearer annotations would\nsubstantiallyimprovetheirinterpretability.\nAR: Thankyouforyourprofessionalcomments.Wehavethoroughlyrevisedbothfiguresintherevisedmanuscript:\nFirst,weaddedcomprehensivelegendstoFig. 2and3,whichexplicitlyexplainthemeaningofeachcurve,\nsymbol,color,andcomponentinthefigures—ensuringreaderscanquicklyassociatevisualelementswith\nkeyexperimentaldataorresults. Second,weoptimizedtheannotationsbyrefiningthewordingforclarity,\nadjustingtheplacementtoavoidoverlapwithfigurecontent,andenhancingthefontsizeforbetterreadability.\nSpecifically,werevisedFigures2and3,andsupplementedthepreviouslymissingsub-figuresinFigures\n2c2e,and3c.\nRevision:\nRESULTS(2.2): \"Thisuniquecrystalstructureexhibitssignificantlatticescattering,effectivelysuppressing\nlatticeheatconductionandpromotingtheestablishmentofasignificanttemperaturegradient(Fig. 2c). This\nenablesefficientthermoelectricconversionandreducesthetrade-offbetweenthicknessandresponsivity.\nThe fabrication process flow comprises the following key steps (Fig. 2d, Further details in the Methods\nsection and Supplementary Fig. S3): Initial surface cleaning and PDMS composite treatment of 10 um\nPET substrates; Magnetron sputtering deposition of gold electrodes on half-area substrates followed by\nfull-substratetelluriumthinfilmdeposition;LaserdirectwritingprocessingofAuTe-Teinterfacesinto1mm-\ndiametertemperature-sensitiveunit(Fig. 2e). Whenplacedona42◦Chotplate,thetemperature-sensitive\nunitdemonstratescleartemperaturefielddistributioncharacteristicsonitssurfaces,confirmingtemperature\ndetectioncapabilities.\"\n16\na b c\nITO/PET ITO/PET 41.4 °C\nTe\nAuTe PET\ne Top Bottom\nd\nPatterning\nPolycrystalline\nTe film Te/PET\nThermoelectric sensor\nAssembly\nf\nPatterningITO ITO\nTransparent electrodes Temperature sensor With ITO Without ITO\ng h 293.15 K Contact Temperature 313.15 K\nEcoflex\n8 mV\nTe AuTe 2\nPET\nContact surfaces Thermoelectric potential -1 mV\ni j k\nFig. 2|Mechanismandevaluationofthethermoelectricsubsystem. aThestructureoftheTe-based\nthermoelectricsubsystem. bThelatticestructurediagramofTe. cThermalgradientunder42°Cthermal\nloading(Upper: Macroscopicobservation;Lower: Infraredthermographicmapping). dFabricationprocess\nflowforpolycrystallineTetemperaturedetector(Magnetronsputteringthin-filmdepositioncombinedwith\nlaser-assistedmicro-patterning). eAshotofthefinishedTe-basedthermoelectricsensor. fOpticalimageof\nmagnetron-sputteredITOfilmsdepositedonflexiblePETsubstrates,demonstratinghighopticalclarityand\nvisible-lighttransmittance. gComputationalsimulationillustratingtheworkingprincipleofthermoelectric\nsensingelements,incorporatinganelastomericcontactlayeratthetop(tosimulatethethermelectricsubsystem\nimmobilizedonthetactileinterface)andathermallyregulatedboundaryatthebottom(tosimulatedifferent\ncontacttemperatures),withcolormapvisualizationofthethermaldistribution. Thefigureutilizesacontact\ntemperatureof30◦Candanambienttemperatureof25◦C.hTheseebeck-inducedvoltagemappingwithin\nthefunctionallayers,quantitativelycorrelatedwithinterfacialtemperaturemodulationattheactivecontact\nregion,20-40◦C.iDistributionofthermalandelectricalpotentialsunder30◦Ccontacttemperaturealongthe\nupperendofthesubsystem. jTime-dependentvoltageresponsecharacteristicsofthedeviceundervarying\nthermaldifferentials,definedasthedifferencebetweenthecontacttemperatureandtheambienttemperature.\nkQuantitativedependenceofgeneratedelectricalpotentialonappliedtemperature.\nvaryingcontactmagnitudesanddirections(SupplementaryTableS3andS4).Theaverageerrorsofthecontact\ntangentialandnormalforcecomponentsare0.02Nand0.6N,respectively. Errordistributionanalysisreveals\nconsistentpredictionaccuracyacrossdifferentforcemagnitudes,withnoerrorescalationobservedwhen\ncontactforcesincrease(Fig3c(i)). Directionalerroranalysis(SupplementaryFig. S9)indicatescomparable\nperformanceacrossdifferentorientations,thoughslightlyhighererrorsoccurinthecentralanddownward\ndirections. Thisphenomenonmaybeattributedtothecontacthabitsofoperators. Furthervalidationthrough\nrandomizedfingercontacttrials(Fig. 3c(ii))showsstable3Dforceestimationwithconsistentlylowerrors,\nconfirmingthegeneralizationcapabilityofthenetwork.\"\nFig. 3|AI-drivenvisual-tactiledeepneuralnetworks. a(i)Thetactiledatasetcollectionsetup. (ii)Two\ndifferent types of thermoelectric imprints of the T-scope probe. (iii) 18 soft materials used to collect 3d\nforce-tactileimagesamples,withhardnesscoveringvarioustypesofhumantissuesfrom0to100KPa. b\nTheEndoForcenetwork. c(i)Estimatedforceerrordistribution(contactforcemagnitude). (ii)Comparison\nof predicted force and true force when a person’s finger randomly touches the probe. d (i) The coating-\nfreeT-scopesensortocollectvisualinpaintingdataset. (ii)TheProPainternetwork. e(i)RestoredPSNR\ndistribution(coatinglocationandcoatingsize). (ii)Visualizationofvisualinpaintingresultsundervarious\nin-vivoscenarios.\nRC: Theauthorsareencouragedtodiscusswhether,inadditiontovisualfeedback,theintegrationofalter-\nnativemodalities—suchasadvancedhapticfeedbacksystems—couldfurtherstrengthentheclosed-loop\nperformanceoftheinstrument. Includingsuchconsiderationsinthediscussionsectionwouldhighlight\nopportunitiesforfuturedevelopment.\nAR: Thank you for this insightful suggestion. We have supplemented the Discussion section of the revised\nmanuscriptwithadedicatedanalysisofthisaspect,aimingtohighlightopportunitiesforfutureresearchand\ndevelopmentwhileenrichingthecomprehensivenessofourperformanceevaluation.\nRevision: DISCUSSION:\"Futuredevelopmentwillfocusondevelopinganendoscopysystemwithtactile\nfeedback,enablingoperatorstodirectlyjudgethehardness,temperature,andotherconditionsofthecontacted\ntissueinrealtimethroughtactileforcefeedbackfromtheirhands,therebyimprovingdiagnosticefficiency.\"\nGeneralcomment\nRC: This work proposes a tellurium-based thermoelectric visual-tactile endoscope that integrates imaging,\ntemperature sensing, and force feedback into a single platform. While the system is promising for\nmultifunctionalendoscopicapplications,somequestionsremaintobeaddressed.\nAR: Thank you sincerely for your positive evaluation of our work—we greatly appreciate your recognition\nof the tellurium-basedthermoelectric visual-tactile endoscope’s potential for multifunctionalendoscopic\napplications,aswellasyourreminderofremainingquestionstoaddress.\nWe have implemented targeted optimizations in the revised manuscript, including refining the system’s\nstructural design, upgrading the supporting AI algorithm, and correcting animal experiment details by\nexplicitlypresentingtherealin-vivopalpationexperimentsweconducted. Theseadjustmentsaimtobetter\naddressexistingquestionsandfurtherenhancethesystem’sperformanceandreliability.\nComment#1\nRC: Thedefinitionsof’contactbeginning,’’stablecontact,’’fastcontact,’and’slowcontact’areambiguous.\nThismakesitdifficulttointerprettheresultsoftheinvitrocontactexperiment. Pleaseclearlydefinethese\nterms,forexample,byspecifyingthemalongthetimeaxis,toimprovetheclarityoftheanalysis.\nAR: Thankyouforyourprofessioanlcomment. Wehavethoroughlyrevisedtherelevantcontentinthemanuscript:\nWecompletelyupdatedFigure4byintegratingadetailedtimeaxis,onwhicheachcontactstateisclearly\nmarkedwithspecifictimenodesandcorrespondingforce/touchsignalchanges—forexample. Meanwhile,we\nrevisedthecorrespondingtextdescriptionsintheResultssectiontoalignwiththetime-axis-baseddefinitions,\nensuringconsistencybetweenvisualpresentationandwrittenexplanationandsignificantlyimprovingthe\nclarityoftheexperimentanalysis.\nRevision:\nToverifythepracticalefficacyoftheT-scopesysteminclinicalendoscopicenvironments,weconductexvivo\nexperimentsusingfull-scalebiosimulationphantoms. Duringtheexperiments,theT-scopesensingdeviceis\nmountedatthedistalendofastandardendoscopicsystem. Operatorsperformmultiplecontactdetectiontests\nbymanuallymanipulatingtheendoscopewithinthesimulatedmodelsofthehumanbronchus,stomach,and\nlargeintestine(Fig. 4a(i),Fig. 4b(i),Fig. 4c(i)). Thisstudyspecificallyrecordsthedetectiondatafromthe\nsensor’sinteractionwithphysiologicalandpathologicaltissuesintheseanatomicalstructures,andconducts\ncomparativeanalysesonthedual-modalsensingcapabilities(three-dimensionalcontactforceandvision)of\ntheT-scopesystemwhenitcontactsnormaltissuesandsimulatedtumortissues.\nBiomechanicaltestdatafromthebronchialandgastricmodels(Fig. 4a(ii),b(ii))showsthatduetothehigher\nbiomechanicalstiffnessoftumortissue,thefluctuationofitsnormalforcevalueismoresignificantthanthat\nofhealthytissuewhenmaintainingastablecontactstate. Visualinpaintingresults(Fig. 4a(iii),b(iii))indicate\nthattheinpaintingalgorithminthisstudycaneffectivelyeliminatetheocclusionofnormalandabnormal\ntissuescausedbythermoelectricdevices,enablingthenormalvisualobservationfunctionoftheendoscope.\nInaddition,inthehumanintestinalmodel(Fig. 4c(i)),wealsoconductfastandslowcontacttestsonnormal\ntissues: Fig. 4c(ii)and(iii)respectivelyshowthecomparisonofnormalforceandtangentialforcesensed\nbytheT-scopeprobeduringfastcontactandslowcontact. Experimentalresultsshowthattheincreaserate\nofnormalforce(-1.4vs-0.17)andthevibrationamplitudeoflateralforce(-58mNvs21mN)duringfast\ncontactaresignificantlygreaterthanthoseduringslowcontact,whichindirectlyprovesthesensitivityand\n20\naccuracyofthe3Dforcesensingdeepneuralnetworkinthisstudy. Formoredetailedthree-dimensionalforce\nsensingdata,pleaserefertoSupplementaryFig. S13andS14,MovieS3,S4,andS5.\na\n(i) (ii) (iii)\nt=0s t=1.2s t=2.5s\nNormal Tissue Tumor Tissue Tumor\nNormal\nSensor\nb\n(i) Tumor (ii) (iii) t=0s t=1.3s t=2.5s\nTissue\nTumor\nNormal\nTissue\nNormal\nSensor\nc\n(i) (ii) (iii)\nSlow/Fast Contact\nTumor\nTissue\nSensor\nFig. 4|Invitrocontactexperimentsimulatinghumanorganmodel. a(i)Simulatedbronchialtissue\npalpationisperformedusingamanuallyoperatedendoscopesystemequippedwithaT-scopeprobe. (ii)\nNormalforcesequencesaremeasuredinnormaltissueandsimulatedtumortissueatthesamecontactdepth\nwhiletheoperatormanuallyfeedsatsimilarspeeds. (iii)Restorationofvisualobservationduringcontact\n(partial)ina(ii). b(i)Simulatedstomachtissuepalpation. (ii)Normalforcesequencesaremeasuredin\nnormaltissueandsimulatedtumortissueatthesamecontactdepthwhilestablecontact. (iii)Restorationof\nvisualobservationduringcontact(partial)inb(ii). c(i)Simulatedintestinetissuepalpation. (ii)Thez-axis\nforceseriesinnormaltissueandsimulatedtumortissuearemeasuredatthesamecontactdepthwhilethe\noperatormanuallyfeedsatfastandslowspeeds. (iii)Thex-axisforceseriesinnormaltissueandsimulated\ntumortissuearemeasuredatthesamecontactdepthwhiletheoperatormanuallyfeedsatfastandslowspeeds.\nComment#2\nRC: Somefiguresincludedinthemainmanuscriptarenotcitedinthetext. Pleasecheckallfigurereferences\ntoensureeveryfigureisproperlycalledoutanddiscussed.\nAR: Thankyouforyourcarefulcomment. Wehaveconductedacomprehensivecheckofallfigurereferences\nintherevisedmanuscript,withafocusedefforttoaddressissuesinFigures2,3,and4: Weaddedtargeted\ntext descriptions to explicitly cite and discuss these three figures—explaining the core data, trends, and\nimplications presented in each—and corrected any inconsistencies between the figure content and the\n21\ncorrespondingwrittenanalysis. Thisensureseveryfigureisproperlycalledout,anditsroleinsupportingthe\nmanuscript’sconclusionsisclearlyarticulated.\nSpecifically,werevisedFigures2and3,andsupplementedthepreviouslymissingsub-figuresinFigures\n2c2e,3c,4e,4f,and4g. PleasenotethatFigures4e,4f,and4ginouroriginalmanuscripthavebeen\nmodifiedtoFigures4b(ii),4b(iii),and4c(i)intherevisedmanuscript.\nRESULTS(2.2): \"Thisuniquecrystalstructureexhibitssignificantlatticescattering,effectivelysuppressing\nlatticeheatconductionandpromotingtheestablishmentofasignificanttemperaturegradient(Fig. 2c). This\nenablesefficientthermoelectricconversionandreducesthetrade-offbetweenthicknessandresponsivity.\nThe fabrication process flow comprises the following key steps (Fig. 2d, Further details in the Methods\nsection and Supplementary Fig. S3): Initial surface cleaning and PDMS composite treatment of 10 um\nPET substrates; Magnetron sputtering deposition of gold electrodes on half-area substrates followed by\nfull-substratetelluriumthinfilmdeposition;LaserdirectwritingprocessingofAuTe-Teinterfacesinto1mm-\ndiametertemperature-sensitiveunit(Fig. 2e). Whenplacedona42◦Chotplate,thetemperature-sensitive\nunitdemonstratescleartemperaturefielddistributioncharacteristicsonitssurfaces,confirmingtemperature\ndetectioncapabilities.\"\nRESULTS(2.4): \"Experimentalresultsdemonstratethatthesystemachievesexcellentperformanceunder\nvaryingcontactmagnitudesanddirections(SupplementaryTableS3andS4).Theaverageerrorsofthecontact\ntangentialandnormalforcecomponentsare0.02Nand0.6N,respectively. Errordistributionanalysisreveals\nconsistentpredictionaccuracyacrossdifferentforcemagnitudes,withnoerrorescalationobservedwhen\ncontactforcesincrease(Fig3c(i)). Directionalerroranalysis(SupplementaryFig. S9)indicatescomparable\nperformanceacrossdifferentorientations,thoughslightlyhighererrorsoccurinthecentralanddownward\ndirections. Thisphenomenonmaybeattributedtothecontacthabitsofoperators. Furthervalidationthrough\nrandomizedfingercontacttrials(Fig. 3c(ii))showsstable3Dforceestimationwithconsistentlylowerrors,\nconfirmingthegeneralizationcapabilityofthenetwork.\"\nRESULTS(2.5): \"Biomechanicaltestdatafromthebronchialandgastricmodels(Fig. 4a(ii),b(ii))shows\nthatduetothehigherbiomechanicalstiffnessoftumortissue,thefluctuationofitsnormalforcevalueismore\nsignificantthanthatofhealthytissuewhenincontactandmaintainingastablestate. Visualinpaintingresults\n(Fig. 4a(iii),b(iii))indicatethattheinpaintingalgorithminthisstudycaneffectivelyeliminatetheocclusion\nofnormalandabnormaltissuescausedbythermoelectricdevices,enablingthenormalvisualobservation\nfunctionoftheendoscope. Inaddition,inthehumanintestinalmodel(Fig. 4c(i)),wealsoconductfastand\nslowcontacttestsonnormaltissues: Fig. 4c(ii)and(iii)respectivelyshowthecomparisonofnormalforce\nandtangentialforcesensedbytheT-scopeprobeduringfastcontactandslowcontact. Experimentalresults\nshowthattheincreaserateofnormalforce(-1.4vs-0.17)andthevibrationamplitudeoflateralforce(-58\nmNvs21mN)duringfastcontactaresignificantlygreaterthanthoseduringslowcontact,whichindirectly\nprovesthesensitivityandaccuracyofthe3Dforcesensingdeepneuralnetworkinthisstudy.\"\nComment#3\nRC: Asignificantnumberoffigurescontainavarietyoftypographicalanddisplayerrors. Forinstance,in\nFigure4i,thelabel\"contactbeginning\"isimproperlypositionedandoverlapswithothertext. Itishighly\nrecommendedthattheauthorsperformacomprehensiveandmeticulousreviewofallfigures,including\nthesupplementaryfigures,tocorrecttheseissues. Ensuringtheaccuracyofallvalues,labels,andlegends\niscrucialforthecredibilityofthepresenteddata.\nAR: Thankyouforyourexpertfeedback. Weconductedathoroughanddetailedreviewofallmajorfiguresand\nsupplementaryfiguresintherevisedmanuscript. Wecorrectedtypographicalerrors(e.g.,spellingerrorsin\n22\nlabelsorlegends),repositionedtextandlabelstoeliminateoverlap(includingrelabeling\"contactbeginning\"\ninFigure4i), verifiedtheaccuracyofallnumericalvalues(e.g., axisscales, datapointannotations),and\nstandardizedtheformattingoflegendsandsymbolsforconsistency. Thisthoroughrevisionensuresthateach\nfigureisvisuallyaccurateandclearlypresented.\n23"}, {"round": 2, "reviewer_comments": {"reviewer_1": "1. In Figure 3 c(i), the error range for z error appears significantly larger compared to x error and y error. Please explain why the error range is large only for the z-axis.\n2. The accuracy of the z-axis force seems most critical for measuring contact force. However, in Figure 3 c(i, ii) of this paper, the z error shows the largest deviation. Can a system with comparatively less accurate z error (compared to x error and y error) be used for a tactile endoscope? Please explain whether this error range is acceptable by comparing it with previous research.\n3. On lines 323-324, the paper states, \"we conduct ex vivo experiments using full-scale biosimulation phantoms.\" It seems that actual biological tissues were not used, yet the term \"ex vivo\" was. Is the use of the term \"ex vivo\" appropriate here? Please explain this.", "reviewer_2": "I have carefully reviewed the revised manuscript along with the authors’ point-by-point responses. All major issues and suggestions raised in my initial review have been thoroughly and convincingly addressed. The revisions have notably strengthened the manuscript, particularly through the improved clarity and depth of the Introduction and Discussion sections. The scientific rigor, coherence, and overall presentation have been substantially enhanced. Furthermore, the figures have been made more readable, with clearer descriptions and labeling that eliminate previous ambiguities. I am fully satisfied with the current version and have no additional comments.\nI therefore recommend the manuscript for acceptance in its present form.", "reviewer_3": "The authors have addressed all the comments. I recommend the publication on Nature communications."}, "author_response": "Author Response to Reviews of\nSuperelastic Tellurium Thermoelectric Coatings for Advanced\nTrimodal Microsensing\nShaowei Cui, Linlin Li, Zi-Xin Huang, Yanzhe Yu, Mingxue Cai, Xiangyin Bao,\nChaofan Zhang, Tiandong Zhang, Long Cheng, Wenxuan Zhang, Zheng Lou, Shuo\nWang, Wen Gong, Chao-Feng Wu, Lili Wang, Yu Wang\nNature Communications\nRC: Reviewer Comment, AR: Author Response\nReviewer #1\nComment #1\nRC: In Figure 3 c(i), the error range for z error appears significantly larger compared\nto x error and y error. Please explain why the error range is large only for the z-axis.\nAR: We appreciate the reviewer’s careful comments. The z-axis has a larger absolute\nerror because its measurement range (0-1 N) is much larger than the ranges of the\nx-axis and y-axis (-0.15-0.15 N). For most axially mounted multi-dimensional\nforce/tactile sensors, the normal force range is generally significantly greater than the\ntangential force range [1]. This measurement range is sufficient for the needs of\ntactile endoscopy, as most in vivo detection forces are in the range of several\nhundred mN, for example, as mentioned by Guo et al., \" The range of the applied force\nwas 0-200 mN with an interval of 40 mN [2].\" Further literature review suggests that\nfull-size percentage error (%FS) is a more suitable metric for multi-axial force\nerror analysis [3, 4].\nTherefore, we have updated the manuscript to report the error distribution in %FS. As\nshown in the revised figure below, the z-axis error is comparable to those of the x\nand y axes. In terms of data, the full-scale error percentages for the x, y, and z axes are\n6.50 %FS, 5.09 %FS, and 5.96 %FS, respectively. Since the statistical deviations of\nforces along the x and y axes are essentially the same, we used a more academically\nconsistent term in our revision, uniformly representing them as shear force. We\napologize for the confusion caused by the previous presentation of absolute error.\nFig. 1 | The estimated force error distribution within different contact force ranges\n(updated from absolute error, N to full-scale percentage error, %FS).\nReferences:\n[1] Lee H K, Chung J, Chang S I, et al. Normal and shear force measurement using a\nflexible polymer tactile sensor with embedded multiple capacitors[J]. Journal of\nMicroelectromechanical Systems, 2008, 17(4): 934-942.\n[2] Guo J, Chen B, Zhang Z, et al. A novel flexible forceps with fbg-based force-sensing\nand feedback for endoscopic surgery[J]. IEEE Sensors Journal, 2025, 25(15): 28427 -\n28434.\n[3] Aksoy B, Hao Y, Grasso G, et al. Shielded soft force sensors[J]. Nature\nCommunications, 2022, 13(1): 4649.\n[4] Zhang J, Yao H, Mo J, et al. Finger-inspired rigid-soft hybrid tactile sensor with\nsuperior sensitivity at high frequency[J]. Nature communications, 2022, 13(1): 5076.\nRevision:\nFig. 3 | AI-driven visual-tactile deep neural networks. a (i) The tactile dataset\ncollection setup. (ii) Two different types of thermoelectric imprints of the T-scope\nprobe. (iii) 18 soft materials used to collect 3d force-tactile image samples, with\nhardness covering various types of human tissues from 0 to 100 KPa. b The\nEndoForce network. c (i) The estimated force error distribution (full-scale error\npercentage, %FS) within different contact force ranges. (ii) Comparison of\npredicted force and true force when a person's finger randomly touches the\nprobe. d (i) The coating-free T-scope sensor to collect visual inpainting dataset.\n(ii) The ProPainter network. e (i) Restored PSNR distribution (coating location\nand coating size). (ii) Visualization of visual inpainting results under various in-\nvivo scenarios.\nABSTRACT: “microstructured tactile/force feedback (range: 0-1 N (normal) and\n-0.15-0.15 N (shear), accuracy: ~6 %FS).”\nRESULTS (2.4): “The average full-scale error percentage of the contact force\nis about 6 %FS, with the average errors of the tangential force and normal force\ncomponents being 0.02 N (6.50%FS) and 0.06 N (5.96 %FS), respectively.”\nComment #2\nRC: The accuracy of the z-axis force seems most critical for measuring contact force.\nHowever, in Figure 3 c(i, ii) of this paper, the z error shows the largest deviation. Can\na system with comparatively less accurate z error (compared to x error and y error)\nbe used for a tactile endoscope? Please explain whether this error range is acceptable\nby comparing it with previous research.\nAR: We thank the reviewer for this professional comment regarding the critical nature\nof Z-axis accuracy. The resulting errors for the X, Y, and Z axes of our T-scope are\n0.019 N (6.50 %FS), 0.015 N (5.09 %FS), and 0.060 N (5.96 %FS), respectively.\nWe compare our system with previous studies on tactile diagnostic sensors for similar\nmedical applications. Beccani et al. mentioned that \"Calibration was 96% linear with\na goodness-of-fit of 93% and mean absolute error of 0.085±0.096 N [1].\" Xu et al.\nstated that \" Third, the tactile sensor exhibits small hysteresis effects in response to\nnormal force (Fig. 2I; hysteresis error: ~6%) and shear force (fig. S28; hysteresis\nerror: ~6%) [2].\" Meanwhile, Kim et al. noted that \" The average relative errors of\nthe forces correspond to 3.1%, 4.5%, and 8.9% of full-scale output F/T ranges,\nrespectively [3].\"\nReferences:\n[1] Bandari N, Dargahi J, Packirisamy M. Miniaturized optical force sensor for\nminimally invasive surgery with learning-based nonlinear calibration[J]. IEEE Sensors\nJournal, 2019, 20(7): 3579-3592.\n[2] Xu C, Wang Y, Zhang J, et al. Three-dimensional micro strain gauges as flexible,\nmodular tactile sensors for versatile integration with micro-and macroelectronics[J].\nScience Advances, 2024, 10(34): eadp6094.\n[3] Kim U, Kim Y B, Seok D Y, et al. A surgical palpation probe with 6-axis force/torque\nsensing capability for minimally invasive surgery[J]. IEEE Transactions on Industrial\nElectronics, 2017, 65(3): 2755-2765.\nIn summary, the Z-axis force measurement accuracy of the proposed T-scope\nsensor is comparable to or even better than that of tactile/force sensors designed\nfor similar medical applications in terms of absolute error (N) and full-scale\nrelative error percentage (%) (0.060N (Ours) vs 0.085N, 5.96% (Ours) vs 6% and\n8.9%). Specifically, our absolute error (0.061 N) is lower than the 0.085 N reported by\nBandari et al. [1]. Regarding the relative full-scale error, our result (5.96%) falls well\nwithin the acceptable range defined by previous studies, being comparable to the ~6%\nnoted in [2] and notably lower than the 8.9% reported by Kim et al. [3]. Therefore, the\ncurrent error range is acceptable for effective tactile endoscopy.\nComment #3\nRC: On lines 323-324, the paper states, \"we conduct ex vivo experiments using full-\nscale biosimulation phantoms.\" It seems that actual biological tissues were not used,\nyet the term \"ex vivo\" was. Is the use of the term \"ex vivo\" appropriate here? Please\nexplain this.\nAR: We appreciate the reviewer’s correction. We agree that \"ex vivo\" is not the correct\nclassification for the phantom-based experiments conducted in this study. Accordingly,\nwe have deleted this term from the entire manuscript to avoid any confusion.\nRevision:\nRESULTS (2.5): “To verify the practical efficacy of the T-scope system in clinical\nendoscopic environments, we conduct visual-tactile diagnostic experiments\nusing full-scale biosimulation phantoms.”\nReviewer #2\nComment #1\nRC: I have carefully reviewed the revised manuscript along with the authors’ point-\nby-point responses. All major issues and suggestions raised in my initial review have\nbeen thoroughly and convincingly addressed. The revisions have notably\nstrengthened the manuscript, particularly through the improved clarity and depth of\nthe Introduction and Discussion sections. The scientific rigor, coherence, and overall\npresentation have been substantially enhanced. Furthermore, the figures have been\nmade more readable, with clearer descriptions and labeling that eliminate previous\nambiguities. I am fully satisfied with the current version and have no additional\ncomments.\nI therefore recommend the manuscript for acceptance in its present form.\nAR: We strictly appreciate your positive evaluation and recommendation for acceptance.\nWe also deeply value the insightful suggestions you provided throughout the review\nprocess. Taking your advice to heart, we plan to further enhance our work by integrating\nforce/haptic feedback into the current tactile endoscopic system. We remain committed\nto advancing this technology and making continuous contributions to the community.\nReviewer #3\nComment #1\nRC: The authors have addressed all the comments. I recommend the publication on\nNature communications.\nAR: We thank the reviewer for confirming that our revisions have addressed all\nconcerns. We are honored by the recommendation for publication and grateful for the\nconstructive guidance provided throughout the review process."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I have no further comments and recommend this manuscript for acceptance."}, "author_response": "Author Response to Reviews of\nSuperelastic Tellurium Thermoelectric Coatings for Advanced\nTrimodal Microsensing\nShaowei Cui, Linlin Li, Zi-Xin Huang, Yanzhe Yu, Mingxue Cai, Xiangyin Bao,\nChaofan Zhang, Tiandong Zhang, Long Cheng, Wenxuan Zhang, Zheng Lou, Shuo\nWang, Wen Gong, Chao-Feng Wu, Lili Wang, Yu Wang\nNature Communications\nRC: Reviewer Comment, AR: Author Response\nReviewer #1\nComment #1\nRC: I have no further comments and recommend this manuscript for acceptance.\nAR: We are truly delighted that our revised manuscript has met with your approval and\nwish to express our sincere gratitude for your insightful and constructive suggestions,\nwhich have been instrumental in substantially elevating the quality of our work. Thank\nyou again for your valuable time and support."}]

Decision letter