A waterproof and ultra-elastic thermoelectric foam for underwater human signal detection

Domain: physics
Published: 2026-01-12
Editorial outcome: major_revision

Abstract
Underwatertaskssuchasoceanexplorationandemergencyrescuedemandadvancedwearablesensors.However,multifunctionalunderwatersensorscapableofintegratingself-poweredsignaltransmission,effectivethermal-moistureregulation,andmulti-signaldecouplingremainunreported.Here,wepresentathree-dimensionalmulti-functionalthermoelectricdevicecomposedofhighlyporouspolyurethanefoamcoatedwithawaterproofconductivelayermadefromsingle-walledcarbonnanotubes,poly(3,4-ethylenedioxythiophene)-polystyrenesulfonate,andwaterbornepolyurethane.Hydrogenbondingbetweenthesulfonategroupsinpoly(3,4-ethylenedioxythiophene)-polystyrenesulfonateandthe-NHgroupsinwaterbornepolyurethaneenhanceswaterresistance(contactangleof112°)andmechanicaldurabilityunderrepeatedcompression(20,000cycles),whileachievinganultra-fastresponsetimeof40ms.Thedeviceexhibitshighbreathability(406mms−1)owingtoitsporousthree-dimensionalarchitecture.Additionally,itenablesprecisetemperaturesensingwitharesolutionof0.05Kandaresponsetimeof400ms.Importantly,itsuccessfullydecouplestemperatureandstrainsignalsinunderwaterenvironments.Leveragingitswaterproofandsignal-decouplingcapabilities,wefurtherdemonstrateafullyintegratedunderwatermonitoringandinteractionsystemencompassingsensinghardwareanddecision-makinglogic.Thisworkrepresentsasignificantadvancementinwearableunderwaterelectronicsandoffersanotherperspectiveforreliable,real-timehuman-machineinteractioninaquaticsettings.

Introduction
Underwater exploration plays a vital role in enhancing marine ecosystemunderstanding,optimizingoceanresourcemanagement,andrevealing the complexities of aquatic environments. However, the dynamic and unpredictable nature of underwater conditions poses significant risks to divers. To address these challenges, recent breakthroughs in flexible wearable sensor technology for real-time physiological monitoring have provided critical support for safe underwater operations1–5. To prevent accidents and ensure timely, effectiveresponsesinemergencies,itisessentialtodevelopflexiblewearablesensorscapableofcontinuouslyandaccuratelymonitoringphysiological parameters such as body temperature, motion, and respiration6–9. These sensors convert external stimuli, such as mechanicalforcesortemperaturechanges,intoelectricalsignalsforreal-timehealthmonitoring.However,mostofthesedevicesrelyonexternal power sources or require frequent recharging, which is a majorlimitationforunderwaterapplications.Toovercomethis,self-powered technologies based on multi-modal signal fusion have emergedasakeysolution10–17.Byintegratingandanalyzingtri-modal data (respiration, temperature and motion), these systems enable precise physiological assessments and real-time responses without externalpowerdependency18.

Among self-powered underwater sensors, triboelectric-based sensorshaveattractedconsiderableattentionfortheirabilitytogenerate electricalsignals by harvesting mechanical energy from environmentalstimulisuchaspressureandmotion19–23.Forexample,Houet al.developedaself-poweredunderwatersensorbasedonaT-shaped triboelectricnanogeneratorcapableofsimultaneouslydetectingboth normalandtangentialforcesonsubmergedobjects.Underwater,the sensordemonstratedresponsetimesof50msfornormalforceand 150ms for tangential force24. Zou et al. introduced a bioinspired stretchable triboelectric nanogenerator for underwater sensing and energy harvesting in human motion monitoring. After more than 50,000 stretching cycles, the device maintained stable output performance, demonstrating good durability and reliability25. However, triboelectric-basedsensorsoftensufferfromreducedefficiencyand stabilityinhigh-humidityenvironments,necessitatingencapsulation. This not only impedes heat and moisture exchange with the body, affectingwearability,butalsolimitsintegrationwithfabricswornclose to the skin. Furthermore, because triboelectric sensors rely on mechanical motion to generate power, they cannot operate continuouslyunderwaterwithoutexternalmechanicalinput.Additionally, they typically support only single-parameter monitoring, making it difficulttomeetthemulti-dimensionalsensingdemandsofcomplex underwaterenvironments.

In contrast, thermoelectric-based sensors can directly convert low-gradewasteheatfromthehumanbodyandsurroundingenvironmentintoelectricalenergy,offeringamoresustainableandreliable solution for underwater applications26–36. For example, Chen et al. developed flexible thermoelectric thin films based on Bi2Te3 that achievedapowerfactor(S2σ)of18.5μWcm−1K−2atroomtemperature, demonstratinghighthermoelectricperformance37.After1000bendingcycles,theperformancedegradationwasonlyabout2%,indicating high reliability and flexibility. Yang’s team fabricated high-performance p-type ultrathin flexible thermoelectric devices with a maximumnormalizedpowerdensityof~30μWcm−2K−238.However, mostofthesestudieshavefocusedonimprovingmaterial-levelthermoelectric performance, with limited attention to practical adaptability in real-world scenarios39,40. Moreover, their single-modality sensing capability restricts theirpotential in multi-dimensional physiological monitoring41. To overcome these limitations, elastic thermoelectric sensors with dual-mode temperature-pressure sensing capabilities have emerged as a promising research direction. These sensorscanmeasuretemperatureviatheSeebeckeffectandpressure via the piezoresistive effect, allowing decoupled sensing of both signals42–47.Forinstance,Tianetal.fabricatedalayeredporouscomposite aerogel using carbon nanotubes and MXene combined with reinforced cellulose nanofibers, enabling dual-mode thermoelectric-piezoresistivesensing48.Similarly,Chenetal.developedadual-mode sensorwithdecoupledthermoelectricandresistiveresponsesusing commercialmelaminefoam49.However,suchporousmaterialstendto absorbwaterandswellinhigh-humidityorunderwaterenvironments, leading to a reduction in Seebeck coefficient (S). Although hydrophobic coatings (e.g., polydimethylsiloxane, PDMS) can suppress waterabsorption,theyseverelyreducebreathabilityandcompromise wearingcomfort.Asaresult,applicationsinunderwaterenvironments remainlargelyunexplored, particularly intermsof practical performancemetricssuchasmulti-modalsignaldecoupling,wearingcomfort, and environmental adaptability. Systematic research in these areasisstilllacking.

Here,we propose athermoelectric polyurethane foam(TEPUF) characterized bywaterproof, high elasticity, and a unique ability to decouple temperature and strain sensing. Poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT: PSS) is used as the core conductive material due to its high electrical conductivity (σ) and environmentalstability50.Theformationofahydrogen-bondingnetwork with waterborne polyurethane (WPU) imparts superior waterproof performance (water contact angle of 112°) and enhances the mechanicalpropertiesofthehighlyporouspolyurethanefoam(PUF) substrate. These features ensure that the thermoelectric device maintains stability over 20,000 compression cycles and exhibits an ultrafaststrainresponsetimeof40ms,eveninunderwaterenvironments.Thedevicealsodemonstratesappealingtemperaturesensing performance, with a resolution of 0.05K and a response time of 400ms,enablingaccurate,real-timetransmissionofthermalstimuli. Inaddition,thethree-dimensional(3D)porousstructureofthePUF offers high breathability (406mms−1), facilitating efficient heat and moistureexchangebetweenthebodyandtheenvironment.Notably, thedecouplingoftheSeebeckandpiezoresistiveeffectsinthePUF enablesthedevicetomaintainstablevoltageoutputevenunderlarge deformationsofupto60%.Buildingonthis,wedevelopedasmart glove for underwater interaction by integrating a support vector machine(SVM)-basedmachinelearningmodel,achieving100%accuracy in recognizing complex sign language gestures. Furthermore, thermoelectricmodulescanbeembeddedinfacemasksandjointsto construct a synergistic monitoring system capable of wirelessly trackingdivers’motion,respiratoryrate,andbodytemperature.These signalsareprocessedvialogiccircuits,enablingindependentsensing andfusionanalysisoftri-modaldatatoprovidereal-timefeedbackona diver’sphysiologicalcondition.

Results
Toenablemulti-modalmonitoringofunderwaterhumanphysiological signals, we developed a wearable underwater monitoring system basedonadistributedsensornetwork.Bycoordinatingtheacquisition andfusionofrespiratory,bodytemperature,andmotionsignals,the system enables comprehensive assessment of physiological states (Fig.1).Flexiblesensornodesarestrategicallydeployedonkeybody areas(Fig.1a)tocapturerespiratoryrate,temperaturegradients,and swimmingposture,formingamulti-dimensionalphysiologicalsensing matrix.Weselectdeviceplacementbasedonthemostsuitablebody regions for accurately capturing breathing, motion, and body temperaturesignals.Forrespiratorymonitoring,thedeviceisintegrated into the mask to directly interact with airflow and precisely detect breathingrhythms.Formotionsensing,devicesarepositionedatkey joints(e.g.,kneesandwrists)toeffectivelycapturelimbmovements. Forbodytemperaturemonitoring,placementonthechest(closeto theheartandmajorbloodvessels)enablesaccuratetrackingofcore temperaturechanges.Thisplacementstrategyissupportedbyexisting studies, which highlight the importance of sensor positioning in improving signal acquisition quality and enhancing recognition accuracy51–53. At the core of this system lies the innovative sensor architecture(Fig. 1b):the TEPUF features a multi-modal decoupling structureachievedthroughmaterialdesignandstructuralengineering, ensuring signal independence, environmental robustness, and usercomfort.Specifically,single-walledcarbonnanotubes(SWCNTs)34 and PEDOT: PSS are chosen as thermoelectric fillers, and sulfonate groupsonthePSSchainsformhydrogenbondswiththe-NHgroupsin WPU to create an interpenetrating network (Figure S1). This design ensuresuniformfillerdispersionwhilethehydrophobicchainsinWPU provide a barrier effect that contributes to stable waterproofing.

TEPUFfeaturesaunique3Dporousarchitecturewithhighporosity, formingsubstantialinternalstaticairvolume(FigureS2).Thepresence of axial pores facilitates efficient heat diffusion, contributing to its ultralow thermal conductivity (~0.0445Wm−1K−1). Under elastic deformation,theporewallscomeintocontact,increasingconductive pathways and thereby reducing electrical resistance. Thus, the 3D porousPUFsubstrateovercomestraditionalencapsulationlimitations, maintaining out-of-plane temperature gradients under high breathabilityandofferingsufficientelasticityforstrainsensing,thusenabling physicaldecouplingoftemperatureandmotionsignals.Akeybreakthrough of this system is its multi-modal signal fusion and alert response mechanism.Inspired by recent advancements inAI-driven multi-modalwearable sensingsystems,severalnotable studies have demonstrated the integration of intellligentalgorithmswithadvanced sensing materials. For example, Kim et al. developed high-performancepiezoelectricyarnscoupledwithaconvolutionalneural network(CNN)toaccuratelyclassifyhumanmotionactivitiesinreal time51. Similarly, Xu et al. integrated soft, stretchable triboelectric sensors with artificial intelligence of things (AIoT) technology to effectivelyidentifyandclassifyhumanbehaviorsandpostures52.Thus, to ensure independent processing and accurate transmission of respiration,temperature,andstrainsignals,weemployedamachine learningalgorithmtoclassify,encode,anddecodethesignalsbasedon distinctphysiologicalstates,convertingthemintoidentifiablebinary outputs(Fig.1c).Specifically,theoriginalmulti-modalsignalsarefirst temporally aligned and structured into a unified two-dimensional feature matrix. To eliminate numerical scale differences across different modalities, z-score standardization is applied to all features, ensuring numerical stability and improved convergence efficiency during model training. For the classification model, an SVM with a radialbasisfunction(RBF)kernelisemployedduetoitseffectiveness inhandlingnon-lineardata.Tooptimizemodelperformance,5-fold cross-validation is used in combination with a grid search across a predefinedparameterspacetoidentifytheoptimalhyperparameter configuration.Thesebinarycodesaretheninputintologiccircuits, enablingreal-timefeedbackontheuser’sphysiologicalstatusviaan integrated alert system (Fig. 1d). Notably, compared to recently reportedwearablemultifunctionalthermoelectricdevices,ourTEPUF setsbenchmarksinkeyperformancemetrics,includingwaterproofing, breathability (measured at 100Pa, 25°C), sensitivity, temperature response time, strain response time, and long-term durability (Fig.1e)54–58.Furthermore,whencomparedtostate-of-the-artunderwater sensing systems, TEPUF demonstrates superior underwater durability, faster response time, and the ability to sense multiple modalitiessimultaneously(Fig.1f)59–68.

Toaddressthelimitationsoftraditionalunderwatersensors,such asmechanicalbrittlenessandlimitedenvironmentaladaptability,the fabricatedTEPUFisextremelylightweight,somuchsothatitcanrest atopafoxtailgrassplumewithoutbendingthedelicatestrands.Under externalpressure,TEPUFalsoexhibitshighresilience,fullyrecovering itsoriginalshapeafter90%compression(Fig.2a),indicatingitslow density and strong elasticity. Compared to bare PUF, TEPUF shows significantlyenhancedcompressivestrength(FigureS3),attributedto reinforcement from the conductive SWCNTs/PEDOT: PSS/WPU coating and the highporosity ofthe PUFmatrix. Scanningelectron microscopy(SEM)imagesrevealthatPUFhasa3Dporousstructure, whichfacilitatesthepenetrationandadhesionoftheSWCNTs/PEDOT: PSS/WPUconductivefillers(FigureS4a).AsshowninFigureS4b,the PUF surface becomes rougher after treatment with the conductive solution. This roughness arises from strong chemical compatibility between WPU and the polyurethane-based PUF, allowing for substantialintermolecularinteractionssuchashydrogenbondingandvan derWaalsforcesbetweentheSWCNTs/PEDOT:PSS/WPUcoatingand thePUFframework.Theseinteractionsensuretheconductivecoating adheres firmly to the PUF skeleton, forming efficient and stable waterproof conductive pathways. These pathways are uniformly coatedwiththePEDOTlayerandSWCNTsnetwork,ultimatelyforming a robust waterproof conductive network (Figure S4c). As demonstrated in Figure S5, TEPUF can function underwater (in ultrapure water)asaconductivewiretolightupasmallbulb.Thebrightnessof the bulb increases with applied pressure, indicating TEPUF’s high waterproofingandconductivity.Becauseairpermeabilityandwater resistanceinfoammaterialsaretypicallyinverselyrelated,achieving anoptimalbalancebetweenthesepropertiesremainsafundamental challengeinmaterialsdesign.Toaddressthis,wetunedtheratioof WPU to SWCNTs/PEDOT: PSS to balance breathability and waterproofing.AsshowninFigureS6,theWPU-freesample(0:2)exhibits highairpermeability(527mms−1at100Pa),butitshydrophilicsurface readilyabsorbswater,makingitunsuitableforhumidorunderwater environments(FigureS7a).Incontrast,thethick2:2coatingprovides good waterproofing (Figure S7b) but drastically reduces air permeability to 9.97mms−1, compromising wearer comfort and device practicality.The1:2WPU:SWCNTs/PEDOT:PSSratioofferstheoptimal balance,achievinghighairpermeability(406mms−1)andstrongwater resistance,withawatercontactangleof112°.Furthermore,thewater contactangleremainsnearlyunchangedafter25min,confirmingthat the SWCNTs/PEDOT: PSS/WPU coating significantly enhances water resistance(Fig.2b).Extendedwaterimmersiontestsfurthersupport this:after8hofsoaking,nodetachmentofconductivematerialwas observed,andthewatercontactangleremainedstable(FigureS8).In additiontowaterresistance,TEPUFalsoresistscommonliquidssuch ascoffee,milk,tea,andink(FigureS9).Importantly,TEPUFexhibits high breathability, meeting the requirements for wearable electronics(Fig.2c).

In addition to its waterproofing and breathability, TEPUF also exhibits good thermoelectric temperature-sensing capabilities. As showninFigureS10,underambientconditions(relativehumidityof 60%andambienttemperature(T0)of24°C),thetemperature difference (ΔT) across the TEPUF displays a linear relationship with the outputthermoelectricvoltage.Fromtheslopeofthefittedcurve,theS iscalculatedtobe38.24μVK−1,withahighlinearcorrelationof99.9%. Remarkably, due to its waterproof nature, TEPUF maintains nearly identicalthermoelectricperformanceunderwater,withanSvalueof 35.79μVK−1.Furthermore,weevaluatedtherateofchangeinSand resistance(R)undervaryingrelativehumiditylevels(40%,50%,60%, 70%, 80%, 90%) and in underwater conditions. Remarkably, these variations were negligible (Fig. 2d). After 8h of water immersion, TEPUFretainedastableScomparedtosimilarmaterialswithoutWPU, further validating its robustperformance(FigureS11).To verify the self-poweredtemperaturesensingabilityofTEPUFunderwater,asmall temperaturegradientwasapplied,producingathermoelectricvoltage of2.02μV.Fromthis,theminimumdetectableΔTwasdeterminedto be0.05K,indicatinghightemperatureresolution(Fig.2e).Theability ofthesensortorecognizetemperaturesignalswasfurtherevaluated byapplyingaseriesofΔTvaluesrangingfrom0to25K,resultingina linearvoltageincreasefrom0to0.95mV,highlightingitspotentialasa self-poweredtemperaturesensor(FigureS12).ThiswasfurtherconfirmedbyexposingthetopsurfaceofTEPUFtohotandcoldobjects. Contactwithahotobjectledtoarapidpositivethermoelectricvoltage response, while contact with a cold object produced a negative response (FigureS13). The device exhibited a fastresponse timeof 400msunderaΔTof3K,surpassingthatofrecentlyreporteddevices (Fig.2f).Additionally,underaΔTof2K,TEPUFshowedastablevoltage responseovera5000-secondcycle(FigureS14),demonstratingconsiderabledurabilityandreliabilityforpracticalapplications.Tofurther understand the internal temperature sensing mechanism, we employedfinite elementanalysis (FEA) tovisualizethe temperature andpotentialdistributionwithinthesensor(FigureS15).A3Dporous modelofTEPUFwasconstructedbasedonSEMimages,andsimulationswereperformedunderΔTsof5,10,and15K.Theresultsshowed a proportional increase inoutput voltage with applied thermal gradients,indicatingastrongcorrelationbetweenΔTandvoltage,and confirmingthepotentialofTEPUFasahigh-precisiontemperature sensor.Importantly,whencomparedtostate-of-the-artthermoelectric temperature sensors, TEPUF demonstrates leading performance in bothminimumtemperaturedetectionandresponsetime,representingoneofthehighest-performingthermoelectricdevicesreportedto date(FigureS16)5,54–57,69,70.

TheinherentlyinterconnectedporousnetworkofTEPUFendows itwithhighpiezoresistiveproperties,makingithighlypromisingfor underwater wearable monitoring applications. TEPUF exhibits consistentcompressiveRchangesunderlowhumidity,highhumidity,and underwater conditions, primarily due to the formation of a robust waterproofconductivenetwork(FigureS17).Waterimmersiontests furtherconfirmthatWPUplaysakeyroleinmaintainingstablepiezoresistive signals underwater (Figures S18 and S19). We further investigatedtheunderwaterpiezoresistiveperformanceofTEPUF.As showninFigureS20,stress-straincurveswereobtainedunder20%, 40%, 60%, and 80% compressive strain. The sensor shows no significanthysteresisorfatigue,retaininghighRsensitivityandrecovery capability.Duringdynamiccompressionandreleasecycles,theclosing and reopening of the porous structure enhance the piezoresistive effect.Thedeformationprocessduringcompressioncanbedivided intothreestages:aninitiallinearstage,wherethe3Dporesundergo elasticdeformation;agradualtransitionstage,wherelargerinternal poresbegintocollapse;andafinalrapidgrowthstageathighstrain, where the structure becomes denser and volume decreases significantly. During compression,the reductionin poresize increases contactareas,formingadditionalconductivepathways(FigureS21).As a result, the R change confirms that TEPUF exhibits high pressure sensitivity across a wide strain range (20~80%) (Figure S22). The changeinRwithstrainistypicallyquantifiedusingthegaugefactor (GF),definedasGF=(ΔR/R0)/strain(ΔR:Rrateofchange;R0:initial resistance).TheGFduringcompressioncanbecategorizedintothree regions:A,B,andC.Whenstrainexceeds60%,theGFreachesapeak valueof~1.1,whichalignswiththeequivalentRmodelwepreviously described(FigureS23).Moreover,TEPUFexhibitsafastresponseand recovery time of just 40 ms and 50ms, respectively, under large deformation, fully meeting the real-time requirements of wearable devices(Fig.2g).Mechanicalstabilityanddurabilityarecriticalmetrics for wearable sensors. TEPUF maintains consistent signal intensity regardlessofcompressivestrainorfrequency(FiguresS24andS25). TovisualizethedeformationbehaviorofTEPUFunderexternalforce, weconductedin-situSEMobservationsandFEA.Thein-situSEMseries captures the complete evolution of the structure from 0% to 80% compressionandsubsequentunloading(FigureS26).Uponunloading, thestructurenearlyreturnstoitsoriginalconfiguration,demonstratingfullyreversibledeformation.ThisconfirmsthatTEPUFpossesses highelasticityandcyclicstabilityunderrepeatedcompression,with theporousskeletonexhibitingnear-completereboundandrecoverability. Consistent with these observations, the FEA results further support TEPUF’s mechanical robustness. The simulated stress distributionmaprevealsthatstressisprimarilyconcentratedalongthe TEPUF skeleton, particularly at junctions and curved regions, identifying the skeleton as the main load-bearing component. This stress localization within the structural framework contributes to TEPUF’s high structural stability and mechanical resilience. Furthermore, 20,000 underwater compression cycles were conducted to assess long-term fatigue R (see Movie S1). Throughout repeated loading, the sensor retained stable pressure-sensing performance, confirmingitsdurabilityandlong-termreliabilityforpracticalapplications(FigureS27).Similarly,theσ–εcurvesexhibitminimalplastic deformation over repeated cycles, indicating considerable elastic recovery(FigureS28),andthestress-strainresponseexhibitsmarked nonlinearity,withlowhysteresislossandhighelasticreboundduring cycliccompressionhallmarksofhyper-elasticity.TEPUFconsistently returns to its original shape after repeated loading and effectively withstandscyclicmechanicalstress.FigureS29furthershowsonlya slightdecreaseinmaximumstressover20,000cycles.Notably,after 20,000cycles,theelasticrecoveryremainsashighas92%,whilethe energy dissipation coefficient decreases to 0.41. Theseresults highlightTEPUF’sgoodmechanicalperformanceinunderwaterenvironments.Unliketraditionalgel-structuredmaterials71,72,TEPUFdissipates energythroughintrinsicviscoelasticdeformationandtherecoveryof its porous architecture. Importantly, TEPUF lacks hierarchical interfaces,eliminatingtheriskofinterlayerdelaminationorfailurecommonly seen in multilayer systems. Its coherent skeleton provides robust mechanical support, while the continuous porous structure ensuresstructuraluniformityandlong-termcyclicstability.Thus,even after 20,000 compression cycles, the R and S of TEPUF remained unchanged,indicatingthatthe3Dporousarchitectureprovidesreliable structuralsupport(Fig.2h).Meanwhile,SEMimagingafter20,000 compressioncyclesshowsthatTEPUFretainsaclearlyvisibleandwell-definedporenetwork,withnosignsofsurfaceorinterfacialcollapse (FigureS30).Theporespacingremainsuniform,andtheframework structure isintact,indicating goodmacroscopicstabilityafter repeated deformation. Microscopic observations further reveal smooth, continuoussurfaceswithoutcracks,faults,orlocalizedcollapse.These findingsconfirmthemechanicalrobustnessofthematerialandvalidate theeffectivenessandpracticalityofourstructuraldesignstrategy.ToexplorethecouplingbetweeninternalRandoutputvoltage during dynamic operation, we evaluated the S under various compression strains (Fig. 2i). Remarkably, the S remains unaffected by mechanical deformation, which supports further study of thermoelectricvoltageandRbehaviorunderdynamicconditions.

ToinvestigatethedecouplingcapabilityofTEPUF,weconducted aseriesofexperimentsinvolvingbothindependentandsimultaneous stimuli.Weexaminedtheelectricalresponseofthesensorunderdifferent conditions. First, the baseline current-voltage (I-V) characteristics of TEPUF were recorded (Figure S31a). When mechanical pressure was applied, the 3D porous structure of TEPUF was compressed,reducingthegapsbetweenporesandincreasingthecontact areaoftheconductivematerials,therebyenhancinginternalpathways. According to the modified Ohm’s law (R=ΔV / ΔI) (ΔV: V rate of change;ΔI:Irateofchange),thisledtoadecreaseinRandanoticeable shiftintheI-Vcurve(FigureS31b).WhenaΔTwasapplied,theI-Vcurve shiftedtotheleftwithoutachangeinslope,indicatingthattemperature variation had no effect on the pressure-induced signal output (FigureS31c).Additionally,under a constantΔT, the thermoelectric voltageoutputfollowedS×ΔT,confirmingthattheinternalRofthe sensorremainedunaffectedbytemperaturechangesduringthermoelectric voltage generation. Subsequently, when compressive stress wasappliedagain,theI-Vcurveshiftedaccordingly,indicatingthatR changesweresolelyinfluencedbymechanicalpressure(FigureS31d). To improve experimental accuracy, we conducted continuous measurementsacrossmultiplegradients.UnderafixedΔT,increasing theappliedpressureledtoasteeperslopeintheI-Vcurves;however, the curves consistently intersected the origin, indicating that the temperaturesensingperformanceremainedstableandunaffectedby external pressure (Figure S32). As shown in Figure S33, when the temperature gradient across the sensor varied (−2, 0, 2K), the I-V curvesoftheuncompressedTEPUFexhibitedhorizontalshifts.Thex-axisinterceptscloselymatchedthecalculatedSeebeckvoltages(V=S × ΔT), while the slope remained unchanged across ΔT values, confirming stable current output. These results demonstrate that the thermoelectric effect enables precise temperature sensing without interferencefrompressure-inducedcurrentsignals.Wesubsequently subjectedTEPUFtoatemperature-controlledcompressiontesterinan underwater environment to systematically investigate its behavior undervaryingpressuresandΔTs(FigureS34).FigureS34aprovidesa schematicoftheexperimentalsetup.AsshowninFigureS34b,when ΔT isvaried under fixed compressive strains, the relative resistance change(ΔR/R0) isprimarilygovernedbymechanicalstrain,with ΔT havinganegligibleimpact.Asaresult,theresistance–straincurvesat differentΔTsnearlyoverlap.Conversely,FigureS34cshowsthatwhen compressivestrainisvariedunderfixedΔT,thethermoelectricoutput voltageincreaseslinearlywithΔT,whileremaininglargelyunaffected by mechanical strain. In addition, we systematically benchmarked device behavior across multipleΔT magnitudes,from ultra-small to comparativelylarge,underdifferentcompressivestrains(FiguresS35-S37). Across all ΔT levels, the thermal-electrical pathway and the mechanicalresponseremaindecoupled,withnoobservablecross-talk between thermoelectric output and strain-induced effects. These results clearly demonstrate that the system achieves independent regulationandeffectivedecouplingofthermalandmechanicalsignals. No observable interference is detected between the thermoelectric voltageandpiezoresistiveresponses.Thisconfirmsthesystem’scapabilityforprecise,dual-channelsensingandhighlightsitssignificant advantages in managing complex multi-physical signals in dynamic environments.Overall,these observationsconfirm thattheSeebeck andpiezoresistiveeffectsinTEPUFarefullydecoupled.

Tofurtherdemonstratethedecouplingcapabilityofthesensor, we designed a five-stage stimulus sequence (Fig. 3a). In the initial stage, nopressure orΔT wasapplied, andbothV andR remained stable. In the second stage, pressure was applied without a ΔT, resultinginasignificantdropinRwhileVremainedunchanged.Inthe third stage, both pressure and a ΔT were applied; R continued to decrease,andVincreasedsignificantly.Inthefourthstage,pressure wasreducedwhilemaintainingtheΔT,leadingtoasharpincreasein RwithnochangeinV.Finally,bothpressureandΔTweregradually removed,returningtheRandVtotheirinitialvalues.Thisprocess confirmsthatTEPUFcansimultaneouslydetectΔTsandmechanical strain independently. In addition, we simulated the above process usingamulti-physicsframework(Fig.3b).Thesimulationshowsthat stresspropagatesprimarilyalongthefoamskeleton,withlocalized concentrationsatskeletaljunctions,confirmingthattheskeletonis the main load-bearing structure at the contact interface. These resultsclarifythemechanicalresponsemechanism,whichisjointly influencedbythefoam’sgeometricdeformationandthestiffnessof itsskeleton.Moreover,underaconstanttemperaturedifference,the thermoelectric potential field remains stable despite variations in external pressure. This simulation outcome aligns well with our experimental observations, demonstrating that external pressure has minimal impact on the thermoelectric output. We have also added experimental data and simulation for thermal-mechanical decouplingatthemicro-voltlevel(FiguresS38andS39).Thesame result was obtained. Furthermore, we conducted additional 2D simulations toobtaina more detailedunderstandingofthedeformationbehaviorofthefoam.Theresultsshowthatascompressive strain increases, the initially open cells progressively deform into flattenedshapes.Theporewallsmoveclosertogetherandeventually pressagainsteachotherunderload,transitioningfromanopen-cell geometry to a flattened-cell structure at higher strains (Fig.3candS40).Theporesizedecreasescontinuouslywithstrain, and the simulations indicate that deformation is accommodated primarilythroughelasticbendingofthecellwallsratherthanpermanentcollapse,anintrinsiccharacteristicofthefoamhyperelastic response. Even at high strain, the porous scaffold remains intact, enablingthefoamtofullyrecoveritsoriginalshapeuponunloading. This retention of porous structure under substantial compression directlysupportsthematerial’selasticreboundandlong-termcyclic durability. In parallel, we performed a voltage-distribution simulationunderatemperaturedifferenceofΔT=12°C(Fig.3dandS41). Theresultingpotentialfieldremainsuniformandunchangedeven underlargecompressivestrains,confirmingthatthethermoelectric signalisunaffectedbymechanicalloading.Thesecombinedobservationsstronglyvalidatethedevicedesignprincipleofdecoupling thermalandmechanicalsignals,ensuringaccurateandindependent multi-physicalsensing.ThedecouplingperformanceofTEPUFwas further evaluated in practical scenarios. When the device was repeatedlycompressedbyaheatsource,Rchangedsystematically due to the piezoresistive effect (Figure S42), while V increased as expectedfromtheSeebeckeffect.Thisconfirmsthatthetwosignals in the device are monitored independently without mutual interference.Similarly,whencompressedbyacoldsource,theRexhibitedthesametrend,buttheVdecreasedaccordingly(FigureS43).In summary,TEPUFexhibitsgoodwaterresistance,dual-modesensing capabilities,andsignaldecouplingperformance.

Underwater resource exploration primarily relies on diving operations.However,intheabsenceofaneffectiveunderwatermonitoring system, unforeseen events canposeserious, life-threatening risks, especially when timely intervention is not possible. Recent advancesinface-masktechnologyhaveintroducedinnovativematerialsand design strategies aimed at enhancing both protection and functionality73,74.AsshowninFig.4a,wedevelopedadeviceconsisting of a 3×3 pixel dual-mode sensor array, which is integrated into the diver’smasktomonitorbreathingconditionsundervariousphysiologicalstates.Oneendofthedeviceispositionednearthelips,while theotherendissecurelyattachedtothesurfaceofthemask.Theend nearthelipsservesasthesensingregion,whilethepartincontactwith themaskactsasatemperaturereference.Duringbreathing,airflow inducestemperaturefluctuationswithinthedevice,leadingtochanges in thermoelectric output voltage. As shown in Figure S44, it is a schematic diagram of this test setup. By analyzing the rate and amplitude of these voltage signals, different breathing states associatedwithdistinctphysiologicalconditionscanbeidentified.Under normalbreathing,thevoltagesignalshowsamoderatefrequency(12 cyclespermin)withminimalfluctuationsofabout1.3mV,indicatinga stable physiological state (Figure S45). In contrast, during deep breathing,thefrequencydecreases(6cyclespermin),andthevoltage amplitudenearlydoublestoaround2.5mV(FigureS46).Duringrapid breathing,thefrequencyincreases(over20cyclespermin),butthe voltage amplitude gradually diminishes, signaling potential hypoxia (FigureS47).Moreover,thedevicecandistinguishbetweenmouthand nasalbreathing.Whenthediverbreathesthroughthenose,theoutput voltageisrelativelylow,~0.4mV(FigureS48).AsshowninFig.4b,we quantifiedthedynamicpressuregeneratedbythebreathingairflow. Thesystemsupportslong-termrespiratorymonitoring,capturingreal-time changes in breathing patterns. Meanwhile, we found that regardlessofchanges in respiratory status,the resistance remained essentially constant. Furthermore, we performedawide-rangesimulation experiment using a ventilator simulator to mimic human respirationatdifferentpressureswhilesimultaneouslymonitoringthe VandR.TheresultsshowthatatΔT=0K,neithertheresistancenor thevoltageexhibitsanymeasurablechangeundervaryingrespiratory pressures(FigureS49).Thisdemonstratesthatthemechanicalpressuregeneratedduringbreathinginducesonlyanegligibleeffectonthe resistanceresponseofthedevice.Therefore,usingthevoltagesignal tomonitorrespiratoryactivityisbothreliableandrobust.Importantly, it also provides earlywarnings incases of asphyxia(FigureS50). In suchevents,thenormalfluctuatingvoltagesignaldisappearsandis replacedbyaflatline,whichtriggersanalertonaconnectedmobile device.Additionally,byintegratingthedeviceintoadiver’schest,real-timebody temperature monitoring is enabled. As shownin Fig. 4c, when the ambient temperature changes from ambient temperature (T0=25°C),acorrespondingvoltageisgenerated.Usingtherelation ΔT=ΔV/S,thetemperaturechangeandthusthereal-timetemperaturecan becalculated.AsdemonstratedinFig.4d,anyvariationin externaltemperatureleadstoacorrespondingvoltageshift,allowing accurate,real-timetemperaturemonitoringviavoltagereadout.We also found that, regardless of changes in body temperature, the resistance remained essentially constant. This further confirms the decoupling of temperature and pressure signals in our device. In addition to sensing capabilities, the device also performs well in energyharvesting.Whenwornondifferentpartsofthebody,itgenerates distinct open-circuit voltages: ~2.24mV on the wrist (FigureS51a),1.23mVontheknee(FigureS51b),and1.56mVontheelbow (FigureS51c).Theseresultsdemonstratethedevice’seffectivenessin harvestingbodyheatanditssensitivitytolocalizedthermalgradients. Moreover,oursensorexhibitshighspatialresolution,capableofdistinguishingsignalintensitiesacrossdifferentregions.Forsmallcontact areas, pressure signals peak at the center and decay radially, indicating strong central focusing and edge attenuation (FiguresS52aandS52c).Asthecontactareaincreases,thepressurefield becomesmoreuniform,althoughedgesignalsremainslightlylower than those at the center (Figures S52b and S52d). A similar spatial gradientisobservedinthetemperaturemaps(FiguresS52eandS52f). Withalocalizedheatsource,temperaturepeakssharplyatthecenter, whilesurroundingregionsshowmoderaterises.Expandingorshifting the heat source smooths the temperature distribution and reduces edge amplitudes. These findings confirm that our sensor can accuratelyresolvesubtlespatialvariationsinbothpressureandtemperature, a capability thatis especially criticalfor high-precision subsea monitoringandwearableapplications.

Inaddition,asaresistivesensordesignedforunderwaterwearableapplications,conventionalsensorsoftensufferfromsignalinaccuraciesduetointerferencefromskincontact,water,andtemperature fluctuations. However, our TEPUF effectively shields against such interference during R measurements, ensuring robust and reliable performance. To demonstrate its versatility, we designed a multifunctional sensor based on TEPUF (Figure S53). To evaluate itseffectivenessinunderwaterenvironments,wemountedthesensoronthe knee,fingerjoints,andwristtoaccuratelydistinguishvariousmovementamplitudesviathepiezoresistiveeffect(Figs.S54,4e,f).Meanwhile,wefindthattheoutputvoltageremainedstableregardlessofthe movement. Furthermore, we developed a smart glove capable of converting finger motion signalsinto electronic outputs, enhancing interactionandcommunicationforunderwateroperators.Asshownin FigureS55,compressionstrainsensorswereintegratedintotheglove’s joints,allowingpressurechangesduringfingerandwristmovements to becaptured and transmitted to a personal computer for performance analysis. By integrating signals from multiple points on the hand,thesmartglovenotonlyaddressestheinherentchallengesof underwaterinteractionbutalsointroducesaremotecommunication approach. Figure S56 illustrates several complex hand gestures, includingneedtoshareoxygen,lowoxygen,andearpressureimbalance.Thesespecificmeaningsareconveyedthroughdifferentcombinationsoffingerandwristmovements.Thesignalscollectedbythe smartglovecanbeinterpretedbyanalyzingmotionpatternsofthe fingers to decode the intended sign language. To ensure accurate recognition of these gestures, we designed and implemented a machine learningmodelbasedonSVMtoclassifyandidentifycomplex sensorsignalswithhighprecision.WealsodevelopedanSVM-assisted gesturetrainingstrategytoimproverecognitionreliability.Ultimately, the model achieved 100% classification accuracy across multiple independenttestdatasets(Fig.4g).Thisapproachdemonstratesthe effectivenessofTEPUFinminimizingenvironmentalinterferenceand highlightsitssignificantpotentialforreal-time,accurateunderwatersensingandcommunicationapplications.

Toconstructamulti-modalunderwaterriskwarningsystem,we developed an underwater safety monitoring platform based on multi-modalsignalfusion,asillustratedinFig.5.Leveragingtheself-powered, signal-decoupling capabilities of the TEPUF device, the system cansimultaneouslycapture dynamicchanges inthe diver’s motion, breathing patterns, and body temperature. This enables a comprehensivereal-timeassessmentofphysiologicalconditionsand providesearlywarningsofpotentialunderwaterhealthrisks.Ergonomicallydesignedsensorarraysaredeployedonthelegsandarms to monitor joint deformations, allowing accurate recognition of activity patternssuchasfreestyle swimming(periodicstrain waveforms), treading water (high-frequency, small-amplitude oscillations), and drowning (irregular, intense deformation) (Fig. 5a-c). Additionally,aTEPUFdeviceispositionedinsidethedivingmaskto enablereal-timemonitoringofvariousbreathingpatterns(Fig.5d). Eachtypeofphysicalactivityaffectsbodyheatdifferently,whichis captured through monitoring temperature changes across three stages(up,slowdescent,orfastdescent)accompaniedbyconsistent voltageresponses(Fig.5e).TodistinguishwhetherthisVsignalisa thermoelectricsignalratherthanbeingaffectedbythehydrovoltaic effect,wediscussedthemaininfluencingfactorsofthehydrovoltaic effect75–82.Theexperimentalresultsshowthatunderalltestconditions,whetherstillordynamicwaterflow,differenthumidity,single dropletimpact,orseawater,theoutputvoltageoftheTEPUFsamplesisclosetobaselinelevels,withnosignificantadditionalpotential generationdetected(FiguresS57-S61).Therefore,weareconvinced that our device can accurately capture thermoelectric signals underwater. To integrate and analyze these signals, the collected dataiswirelesslytransmittedtoacomputer.Analarmsystemalgorithmthenconvertstheinputsignalsintologicalformats,encoding each sensing module (motion, respiration, and temperature) as a two-bit binary signal (Figure S62 and see Table S1 for specific encoding).Thesebinarysignalsarepassedintoacustomlogiccircuit for further processing. To streamline logic circuit design, we first generated intermediate signals for each condition using Boolean algebra, which were then used for subsequent logic combinations (seeTableS2).Avalueof1indicatesahighsignal,and0indicatesa lowsignal.Basedontheseintermediatesignals,Karnaughmapswere constructed(Fig.5f). Theoutput follows thislogic: iftwo ormore greensignalsarereceived,theoutputisagreenlight;iftwoormore yellowsignalsarereceived,theoutputisayellowlight,andiftwoor moreredsignalsarereceived,theoutputisaredlight.Accordingly, wedesignedacompletecircuitdiagram(FigureS63).Tovalidatethe accuracyofthecircuit,wesimulateddifferentscenarios.Forgreenlight validation, we mimicked a diver in a safe state performing freestyleswimmingwithnormalbreathing.Theinputsincludedtwo greensignals,andthecircuitcorrectlyoutputagreenlight(Fig.5g). Conversely,red-lightvalidationsimulatedadiverentangledinseaweed,showingsignsofdrowningandrespiratorydistress.Theinputs includedtworedsignals,andthecircuitaccuratelytriggeredared light warning (Fig. 5h). This monitoring system offers a critical solutionforreal-timedivertrackingandsignificantlyenhancesdiver safetybyenablingearlydetectionandresponsetopotentialhazards duringunderwaterexploration.

Methods
Materials
PEDOT:PSS(1.3wt%dispersedinwater,conductivegrade)waspurchasedfromSigma-AldrichTradingCo.,Ltd.(Shanghai,China).The SWCNTs dispersion (diameter = 1~2nm, dispersed in water) was obtained from Chengdu Organic Chemicals Co., Ltd. (Chengdu, China). Dimethyl sulfoxide (DMSO) and anhydrous ethanol (99.5%) were supplied by Sinopharm Chemical Reagent Co., Ltd. (China). CommercialWPUwaspurchasedfromShenzhenJitianChemicalCo., Ltd.(Shenzhen,China).CommercialPUFwith97%porositywasprovidedbyShenzhenCanghaoIndustrialCo.,Ltd.(Shenzhen,China).All chemicals and materials were used as received without further purification.

FabricationofTEPUF
First,PEDOT:PSSandDMSO(5wt%)wereaddedtodeionizedwater andstirredatroomtemperaturefor1htopreparethePEDOT:PSS solution.TheSWCNTsdispersionwasmixedwithdeionizedwaterata 2:1 ratio and sonicated for 30min. The SWCNTs and PEDOT: PSS solutionswerethencombinedandfurthersonicatedfor1htoensure uniformdispersion.Subsequently,WPUwasaddedtothemixturein ratios of 0:2, 1:2 and 2:2 respectively, and ultrasonically treated for 20mintoobtainsuspensionsofSWCNTs/PEDOT:PSS/WPUindifferentratios.Finally,thePUFwasimmersedintheSWCNTs/PEDOT:PSS/WPUdispersion,sonicatedfor 30min,and dried at80°Cfor 1hto yieldtheSWCNTs/PEDOT:PSS/WPU@PUFcomposite(TEPUF).

FabricationoftheTEPUFsensorarray
EachTEPUFunitwasfabricatedasacylinderwithaheightof0.5cm and a base diameter of 0.3cm. A total of nine TEPUF blocks with identical dimensions were prepared. To minimize the influence of contact R, two thin copper electrodes (0.2mm in diameter) were attachedtothetopandbottomsurfacesofeachTEPUFusingsilver adhesive. TheseTEPUF units were then interconnected to form the completesensorarray.

Characterizationsandperformanceevaluation
Themorphologyandmicrostructureofthesampleswereexamined using field-emission scanning electron microscopy (FE-SEM, Hitachi SU-8010). The water contact angle was characterized by a contact anglemeasuringinstrument(KINOSL200KS).Strainperformancewas evaluated using a universal testing machine (CTM2050, Xieqiang Instrument Manufacturing Co., Ltd., China). Air permeability was measured with a YG461G automatic fabric air permeability tester. Thermalimagesofthesampleswerecapturedusinganinfraredcamera(Fotric226,China).Washabilitytestswereconductedbystirring thesamplesindeionizedwaterat1000rpmforvariousdurations.To measure the thermoelectric performance, a semiconductor Peltier moduleconnectedtoaprogrammablelinearDCpowersupply(KeysightE3634A)wasusedtogeneratedifferenttemperaturegradients, andtheSeebeckvoltagewasrecordedusingaDAQ970Adataacquisition system (Keysight Technologies). All sensing signals from the deviceswerecollectedusingaKeithley2450sourcemeter.Allthetests wereconductedinstandardlaboratories.FEAofthedual-modetemperature-pressure sensing performance of TEPUF was conducted usingCOMSOLMultiphysics6.2software(seedetailsinSupplementaryInformation).Thetestsinthissectionhaveobtainedthewritten informedconsentofallvolunteers.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript presents a three-dimensional (3D) multifunctional thermoelectric device technology consisting of porous polyurethane foam (PUF) coated with a waterproof conductive layer made from single-walled carbon nanotubes (SWCNTs), poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS), and waterborne polyurethane (WPU). The authors described that the Hydrogen bonding between the sulfonate groups in PEDOT:PSS and the -NH groups in WPU enhances water resistance (contact angle of 112°) and mechanical durability under repeated compression (20,000 cycles), maintaining a fast response time of 40 ms. The device has waterproof and signal-decoupling capabilities, it was demonstrated as an integrated underwater monitoring and interaction system. The concept sounds cute and fits to the journal scope well. The multifunctional sensing structure/patterned unit that can operate as a smart functioned HMI has been widely studied, but there are still more gaps to be bridged. But I have some reservations as showing below.\nThe top concern is that the Design and working mechanism of the Multi-modal monitoring system need be more explicit. The link between the design to the coupled effect seems very disconnected. Some references might be helpful to extend the scope (https://doi.org/10.1002/eom2.12448; https://doi.org/10.1002/eom2.12384).While the influencing factors have been discussed, the context need show analysis in the deformation and the associate geometrical factors in the region, to show the mechanical/thermal energy distribution. The mapping of critical dependent on the deployed location should be justified, the current evidence is confusing. The thermal/mechanical decoupling on the device systems deploy on inhaling mask and limb should be clearly highlighted. While the influencing factors have been discussed, the context didn’t show enough advantages in the control. Some results only contain limited data. I guess the contact mechanics should be presented here, some FEA data should be supplied to support the claim. The current details in Fig 3f seems far from enough. Moreover, the responding signal under certain pressure or load, seems never been justified under the proper geometrical area? The mechanics interpretation seems be largely missing in this work. Upon applying the load/pressure, how’s the interaction between layers, and energy dissipations? Please see the following references for the example details(https://doi.org/10.1002/adfm.202301117; https://doi.org/10.1002/adfm.202505048). The in-situ observation on the deformation of layer(s) should be interesting, to help the understandings.\nThere are also a few points for consideration:\n1. The structural characterization and illustration are missing in Figures. How can we justify and creating the structure-property relationship without this?? The in-vivo validation seems be limited on the video, and less quantified. It hardly can say as convincing.\n2. In Figure 2-3, the detailed mechanics analysis should be added, rather than only FEA. How the energy conversion rate? And energy loss in the multi-layer structure? The above discussion could be added to elaborate more on the result.\n3. The logic in Fig 4-5 seems in adequate in terms of justify the operation of the proposed system, the demonstrations were incremental.\n4. The technical details including surface/interface condition, the porous area during the deformation, which should be discussed. The degradation/failure of micro-structure can increase the deviation and lead to the inaccuracy of the output.\n5. The writing and language in this manuscript also needs significant work. There are large chunky paragraphs and frequent language issues, which significantlt reduced the reading experience. I would recommend authors to revise and polish the context accordingly to a higher standard with an improved scientific interpretation.\nTherefore, I would recommend to a rejection and transfer to a sister journal.", "reviewer_2": "The author proposed a three-dimensional thermoelectric foam (TEPUF) for underwater physiological signal monitoring for the first time, which possessed excellent waterproof performance, ultrahigh elasticity and dual-mode signal decoupling capability. The author systematically demonstrated the great potential of TEPUF in practical applications such as respiratory monitoring, body temperature recognition, swimming state recognition and gesture recognition. Further combining with sensor networks, machine learning algorithms and logic circuits, this work constructed an underwater early warning system, highlighting the practicality and innovation of this research. Overall, the manuscript is well-organized and will expand the application of thermoelectric materials and devices. Therefore, I strongly recommend that this work can be published in Nature Communications.\n1. The manuscript reports that the Seebeck coefficient and resistance remain stable over 20,000 compression cycles (Fig. 2h), but the supporting information only provides resistance change data up to 2,000 cycles (Fig. S24). To ensure consistency and completeness, the authors should include resistance-change data for all 20,000 compression cycles.\n2. Thermoelectric materials are also often used in wearable energy harvesting. It is suggested that the author supplement the data and tests related to energy harvesting.\n3. The manuscript indicates that TEPUF has high air permeability and makes comparisons with other wearable multi-functional thermoelectric devices. It should be clearly stated whether these comparison devices were tested under the same pressure conditions.\n4. It’s suggested to fully discuss the stability and adaptability of TEPUF under different water conditions.\n5. The manuscript mentions the realization of multi-modal signal fusion and classification through machine learning algorithms, but the specific details and implementation process of the algorithms should be described in detail.", "reviewer_3": "The authors provide a multi‐modal underwater thermoelectric foam for wearable sensors. The thermoelectric foam not only has a water contact angle of 112°, a strain response of 40 ms, and a temperature resolution of 0.05K, but also has 408 mm s⁻¹ air permeability and 20000 times compression stability. The foam’s 3D porous structure enables efficient heat and moisture exchange while maintaining signal integrity underwater. The authors further integrate thermoelectric foam into underwater wearable devices for physiological parameter monitoring. The manuscript is well-structured and will expand the applications of thermoelectric devices in underwater environment. Therefore, I recommend this manuscript for publication after minor revisions.\n1. The introduction appropriately emphasizes triboelectric nanogenerators in the context of self-powered sensors. However, it does not address other established self-powered mechanisms such as hydroelectric and piezoelectric technologies. A brief discussion of these alternatives would provide a more balanced overview and strengthen the contextual foundation of the manuscript.\n2. Although the application of waterborne polyurethane (WPU) enhances circuit protection, the potential impact of excessive coating on the foam’s air permeability remains unaddressed. The authors should clarify how to control the prevent obstruction of the foam’s porous structure and ensure air permeability.\n3. The manuscript introduces a underwater wearable monitoring system based on a distributed sensor network, yet it lacks a clear explanation of its innovative aspects. The authors should elaborate on the rationale behind employing an array-structured sensor system instead of miniaturized integrated units.\n4. The test results (air permeability and water contact angle) were not accompanied by statistical analysis. To verify the reliability and repeatability of the research results, the author should include statistical indicators, such as standard deviation or error bars.\n5. A key claim of the manuscript is the decoupling of multiple stimulus signals. However, the practical applications shown in Figures 4 and 5 do not clearly highlight the advancedness of such decoupling. The authors are encouraged to justify the relevance of signal decoupling in practical applications and provide corresponding evidence."}, "author_response": "We sincerely thank Reviewer 1 for the valuable and constructive feedback, which has greatly contributed to improving the quality of our manuscript. Author reply: We sincerely thank the reviewer for the insightful comments regarding the design logic and working mechanism of the multi-modal monitoring system. After carefully reviewing the suggested references, we have revised the manuscript to enhance the logical coherence between material design, structural engineering, and signal decoupling mechanisms. We would like to clarify that our approach enables functional decoupling and integration within a single device, rather than simply stacking separate device units. Specifically, our multi-modal monitoring system adopts a synergistic strategy that combines material, structural, and algorithmic design. Material design: The 3D porous PUF is coated with a conductive composite of SWCNTs, PEDOT:PSS, and WPU, which significantly enhances the device’s waterproofing (water contact angle of 112°) and mechanical stability. This improvement is attributed to strong hydrogen bonding between the sulfonic acid groups of PEDOT:PSS and the –NH groups in WPU, effectively stabilizing the conductive coating under repeated mechanical stress and underwater conditions (Fig. R1). Structural design: TEPUF exhibits a unique 3D porous structure with high porosity, generating substantial internal static air volume (Fig. R2). Axial pores serve as heat diffusion channels, resulting in an ultralow thermal conductivity (~0.0445 W m−1 K−1). Upon elastic deformation, pore walls come into contact, increasing conductive pathways and reducing electrical resistance. These deformable pore walls function as strain-responsive units (Fig. R3), enabling intrinsic spatial decoupling of temperature and pressure signals. During compression, the pore walls bend rather than collapse, preserving structural integrity and ensuring that the temperature difference (ΔT) remains unaffected by strain, thereby maintaining dynamic stability. Algorithmic design: Inspired by recent advancements in AI-driven wearable sensing systems. For example, Kim et al. developed high-performance piezoelectric yarns integrated with a convolutional neural networks (CNN) algorithm to precisely classify human motion activities in real-time 1. Similarly, Xu et al. integrated soft, stretchable triboelectric sensors with artificial intelligence of things (AIoT) technology to accurately identify and classify human behaviors and postures 2. Thus, to ensure independent processing and accurate transmission of respiration, temperature, and strain signals, we employed a machine learning algorithm to classify, encode, and decode the signals based on distinct physiological states, converting them into identifiable binary outputs. These binary codes are then input into logic circuits, enabling real-time feedback on the user’s physiological status via an integrated alert system. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 6 and 7). Comment 2: While the influencing factors have been discussed, the context need show analysis in the deformation and the associate geometrical factors in the region, to show the mechanical/thermal energy distribution. The mapping of critical dependent on the deployed location should be justified, the current evidence is confusing. Author reply: We sincerely thank the reviewer for the insightful comments. In response to the concerns regarding deformation analysis, geometric factors influencing mechanical and thermal energy distribution, and the mapping of critical parameters based on deployment location, we have provided new experimental data to address these aspects. Regarding the mechanical deformation and geometric factor analysis, we appreciate your request for a more intuitive representation of internal stress distribution and heat conduction within the sensor material during deformation. In response, we performed new finite element analysis (FEA) and experimental validation to illustrate the stress and temperature distributions in TEPUF under relevant conditions. Updated FEA results reveal that stress is primarily concentrated on the TEPUF skeleton, which functions as the main load-bearing framework within the porous 3D structure (Fig. R4). Furthermore, multi-physics simulations were conducted to model the temperature gradient and corresponding potential distribution across TEPUF under applied ΔT. These simulations confirm that external pressure has minimal impact on the thermoelectric potential distribution (Fig. R5). To experimentally verify the mechanical and thermal energy distribution, we conducted infrared thermal imaging to monitor the real-time temperature distribution in TEPUF under one-sided heating. The results revealed a stable internal temperature gradient, consistent with the finite element simulation (Fig. R6). Additionally, we performed an in-situ SEM visualization of the sensor under dynamic compression, which clearly captured the evolution of the pore structure during deformation (Fig. R7). These experiments further support and validate the conclusions drawn from our FEA analysis. Regarding the rationality of device placement and signal mapping, we appreciate the reviewer’s observation regarding potential ambiguities in our previous description. To address this, we now provide a more detailed explanation of how sensor positioning influences response characteristics. Sensor placement is strategically determined based on the most effective anatomical locations for capturing specific physiological signals. For respiration monitoring, devices are integrated into the mask to directly interact with airflow, enabling accurate detection of breathing patterns. For motion monitoring, sensors are positioned at key joints (e.g., knees and wrists) to capture limb movements with high sensitivity. For body temperature monitoring, placement on the chest, proximal to the heart and major blood vessels, allows reliable tracking of core temperature changes. This deployment strategy is supported by prior studies. For example, Xu et al. demonstrated high-precision physiological signal recognition in an AIoT health monitoring system by placing sensors at various body locations (e.g., insoles, cushions, pillows), enabling accurate detection of gait, posture, and head movement through machine learning 2. Their findings underscore the importance of appropriate sensor placement to optimize signal quality and recognition accuracy. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 6 and 16). Comment 3: The thermal/mechanical decoupling on the device systems deploy on inhaling mask and limb should be clearly highlighted. Author reply: We sincerely thank the reviewer for the insightful comments regarding the thermal/mechanical decoupling characteristics. In response to the comment that “the thermal/mechanical decoupling on the device systems deployed on the inhaling mask and limb should be clearly highlighted,” we have conducted additional analyses to clarify this point. During respiration and body temperature tests, we simultaneously monitored the device’s resistance (Figs. R8 and R9). As shown in Fig. R8, the resistance remains essentially stable across different respiration states. In Fig. R9a, a rise in body temperature generates a stable thermoelectric voltage (~0.07 mV), while the corresponding resistance remains nearly unchanged, indicating that temperature gradients do not interfere with the strain-resistance response. This confirms the independence of thermal and mechanical signals. Moreover, during dynamic heating, the device continuously outputs a stable voltage signal while the resistance remains at baseline, further supporting complete thermal-mechanical decoupling (Fig. R9b). To validate this under mechanical deformation, we conducted 30°, 60°, and 90° bending tests on fingers, wrists, and knees (Fig. R10). The strain-resistance signal varies significantly with bending angle, whereas the thermal-voltage signal remains stable, as shown in Figs. R10a-c. These findings clearly demonstrate the decoupling of thermal and mechanical responses in practical deployment scenarios. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 16, 17, 34 and 35). Comment 4: While the influencing factors have been discussed, the context didn’t show enough advantages in the control. Author reply: We sincerely thank the reviewer for the insightful comments noting that, although influencing factors were discussed, the manuscript did not adequately demonstrate the advantages in control. In response, we have designed and conducted additional experiments to more clearly illustrate the superior controllability of our device. Thermal-mechanical signals are mutually interfering: We designed and conducted additional experiments to independently regulate thermal and mechanical signals, aiming to verify that the TEPUF device responds to thermal and mechanical stimuli in a mutually independent and precisely controllable manner. As illustrated in Fig. R11, the thermoelectric voltage and resistance responses of TEPUF were measured under varying ΔT and compressive strain conditions. Fig. R11a presents a schematic of the experimental setup conducted underwater. In Fig. R11b, when ΔT is varied at fixed compressive strains, the relative resistance change (ΔR/R0) is governed primarily by mechanical deformation, with ΔT having a negligible impact. As a result, the resistance–strain curves measured under different ΔT conditions nearly overlap. Conversely, Fig. R11c shows that when compressive strain is varied at a fixed ΔT, the thermoelectric voltage increases linearly with ΔT, while remaining unaffected by mechanical strain. These results confirm that our system achieves clear signal decoupling, with no observable crosstalk between thermoelectric and piezoresistive responses. The thermoelectric voltage exclusively reflects temperature gradients, while resistance changes solely correspond to mechanical strain. This enables the simultaneous and interference-free detection of two independent signals, achieving hardware-level signal decoupling. A simple and practical multi-modal sensing architecture: This study demonstrates simultaneous sensing of temperature and pressure using a single device, highlighting a simplified approach to multifunctional sensor design. Unlike conventional systems that rely on multiple sensor arrays, our integrated design reduces structural complexity and improves flexibility for wearable applications. Effective multi-physical signal management requires extracting rich information without substantially increasing device size or readout circuit complexity. Compared to planar splicing or vertical stacking strategies, integrating multiple sensing mechanisms into a single unit minimizes packaging demands and simplifies signal processing 3. Our device adopts this approach, enabling multimodal sensing within a compact, unified structure. High sensitivity and stability: Independent signal decoupling simplifies device architecture while preserving each channel’s sensitivity to its respective stimulus. Our TEPUF device exhibits a distinct thermoelectric response to subtle temperature variations and rapid, sensitive piezoresistive responses to pressure stimuli. These results demonstrate high sensitivity and low detection limits for both sensing channels (Figs. R12a and R12b), comparable to those of recently reported state-of-the-art multimodal sensors (Table 1). Moreover, after 20,000 underwater compression cycles, both the Seebeck coefficient and resistance remained virtually unchanged, underscoring the device’s robustness and long-term stability in harsh environments (Fig. R12c). These advantages align well with current trends in multifunctional sensing and thermoelectric technologies, and the experimental results underscore the uniqueness and superiority of our approach. Our work offers an efficient and robust solution for fully decoupled, precisely controlled thermal and mechanical sensing, delivering high sensitivity and long-term stability. This directly addresses the reviewer’s concerns regarding the control advantages of our system. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 14, 32 and 33). Comment 5: Some results only contain limited data. I guess the contact mechanics should be presented here, some FEA data should be supplied to support the claim. The current details in Fig 3f seems far from enough. Author reply: We sincerely thank the reviewer for the insightful comments. In response, we conducted a comprehensive thermo-electric-mechanical finite element analysis (FEA) of TEPUF, investigating the distributions of stress, temperature, and electric field under various compressive strain rates. Finite element analysis: Accurate selection of material properties is essential, as they directly influence the reliability of FEA results. The elastic modulus, Poisson’s ratio, and density of TEPUF were obtained from COMSOL’s built-in material library. The Seebeck coefficient and thermal conductivity were set to 38.24 µV K−1 and 0.0445 W m−1 K−1, respectively. After defining the material parameters, we activated the solid mechanics, electric currents, and heat transfer modules for coupled analysis. In the solid mechanics module, rigid pressure plates were assigned to the upper and lower surfaces of the model. A parametric pressure load was applied to the upper plate, while the lower plate was fixed to simulate compression. The model obeys the linear-elastic equilibrium equation: 0=∇·S +F (R1) T V Where S is the stress tensor (Pa), F is the body force (N m−3). In linear elasticity, stress and strain are related through Hooke’s law: S =Ε ·ε (R2) T m where S is the stress tensor (Pa), E is the elastic modulus matrix (MPa) and ε is the strain tensor. T m The mechanical field setup was then completed. The stress-strain field was coupled to the electrostatic field via the piezoelectric multi-physics interface for subsequent electric-field analysis. The electromechanical behavior of the piezoelectric material follows the constitutive equations given below: S =sET +dTE (R3) T D=dT +εTE (R4) Where S is the strain tensor (Pa), T is the stress tensor (Pa), E is the electric-field intensity (V m−1), T D is the electric displacement vector (C m−2), sE is the elastic compliance matrix, d is the piezoelectric strain-coefficient matrix and εᵀ is the dielectric-permittivity matrix. In the electric current module, the upper boundary was set to 1 V, the lower boundary was grounded, and charge conservation was enforced across the entire domain. Simulations conducted on various structural configurations yielded the corresponding electric field distributions across the electrode surfaces. The governing equations are: ∇·J =Q (R5) j,v J =σE+J (R6) e E=−∇V (R7) Where J is the current density (A m−2), Q is the charge density (C m−3), σ is the electrical conductivity (S m−1), E is the electric-field intensity (V m−1), V is the electric potential (V). In the heat-transfer module, the upper boundary temperature load served as the heat source, and a heat-flux boundary condition was prescribed. The governing energy equation is: ρC u·∇T +∇·q=Q+q +Q (R8) p 0 ted q=−κ∇T (R9) Where ρ is the density (kg m−3), u is the fluid velocity (m s−1), C is the specific heat capacity at constant pressure (J kg−1 K−1), q is the heat flux (W m−2), Q is the volumetric heat source (W m−3), q is the boundary heat-flux density (W m−2), Q is the heat-source correction term (W m−3), κ is the thermal conductivity (W m−1 K−1). This simulation incorporates the thermoelectric effect, where heating a material generates an electric current, and conversely, current flow produces thermal energy. These coupled phenomena influence each other and require a multi-physics approach. To accurately model this, the simulation couples the solid heat transfer and electric current interfaces, incorporating the thermoelectric power expression, the heat transfer contribution from the thermoelectric effect, and the thermoelectric current density formulation. Relevant formulas are as follows: P=ST (R10) q= PJ (R11) J =−σS∇T (R12) e where P is the thermoelectric power (W), S is the Seebeck coefficient (V K−1), T is the absolute temperature (K), q is the heat transferred through the thermoelectric effect (W), J is the current density (A m−2), Je is the thermoelectric current density (A m−2), σ is the electrical conductivity (S m−1). After all physics were configured, meshing was performed. The mesh critically affects computational accuracy. Therefore, we balanced element size to maintain accuracy while limiting computational cost. A tetrahedral unstructured mesh was adopted for the entire model. The mesh contained 29768 nodes and 99624 elements, the minimum and average element quality factors were 0.05 and 0.58, respectively. The meshing step was completed. The model was then solved. Post-processing yielded contour maps of stress, electric potential, and temperature, along with the corresponding data sets. Analysis of simulation results: We simulated the thermal–mechanical decoupling process using a multi-physics framework (Fig. R13). The results show that stress propagates primarily along the foam skeleton, with localized concentrations at skeletal junctions, confirming that the skeleton governs load transfer at the contact interface. This clarifies the mechanical response mechanism, which is jointly influenced by the foam's geometric deformation and the stiffness of its skeleton. Notably, under a constant temperature difference, the thermoelectric potential field remained stable despite variations in external pressure. This aligns well with experimental results, demonstrating that external pressure has minimal impact on thermoelectric output and validating the device’s design principle of decoupling thermal and mechanical signals. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 15, 22, 33 and 34) and the revised Supporting Information (Pages 1-4). Comment 6: Moreover, the responding signal under certain pressure or load, seems never been justified under the proper geometrical area? Author reply: We sincerely thank the reviewer for the insightful comments regarding “signal verification under effective geometric area.” In response, we conducted additional experiments to systematically examine sensing performance under varying loading areas, pressure locations, and heat-source distributions. The results were visualized as pressure–temperature distribution maps (Fig. R14), providing a clear understanding of how contact area and position influence sensing signals. For small contact areas, pressure signals peaked at the center and decayed radially, indicating strong central focusing and edge attenuation (Figs. R14a and R14c). As the contact area increased, the pressure field became more uniform, although edge signals remained slightly lower than those at the center (Figs. R14b and R14d). A similar spatial gradient was observed in the temperature maps (Figs. R14e and R14f): with a localized heat source, temperature rose sharply at the source and only modestly in the surrounding regions. Expanding or shifting the heat source smoothed the distribution and reduced edge amplitudes. These results confirm that our sensor can accurately resolve subtle spatial variations in both pressure and temperature. The heatmaps demonstrate high spatial resolution and the ability to distinguish signal intensities across different regions. In underwater environments, this enables precise detection of local stress concentrations, contact edges, and small temperature gradients, critical capabilities for subsea applications. For example, postural changes alter the contact area and pressure distribution between a diver and their suit; our device can detect such variations to monitor posture and movement. It can also identify local skin temperature drops caused by cold-water ingress or impaired circulation, providing early warnings to divers. These features are essential for ensuring the safety and comfort of underwater personnel. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 17). Comment 7: The mechanics interpretation seems be largely missing in this work. Upon applying the load/pressure, how’s the interaction between layers, and energy dissipations? Please see the following references for the example details (https://doi.org/10.1002/adfm.202301117; https://doi.org/10.1002/adfm.202505048). Author reply: We sincerely thank the reviewer for the insightful comments and the recommended references, which we have carefully reviewed to strengthen the theoretical foundation of our study. Wang et al. 9 reported a stratified, flexible gel composite in which energy dissipation is achieved through reversible, non-covalent interfacial interactions. Their soft multilayer structure features exceptionally tough interfaces and retains high durability after 10,000 cycles. Interlayer sliding was identified as the primary energy dissipation mechanism. In another work, Wang et al. 10 developed a dual-ion hydrogel network incorporating hydrogen bonding, electrostatic interactions, and polymer chain entanglement. This synergistic molecular design imparts high water retention, mechanical strength, and dynamic tunability, exemplifying effective molecular-level toughening and energy dissipation. In contrast, the TEPUF investigated in our study is a continuous foam that integrates elements of both mechanisms mentioned above. Its porous skeleton dissipates energy through intrinsic viscoelastic deformation and pore structure recovery. Unlike stratified systems, TEPUF lacks hierarchical interfaces, which eliminates the risk of interlayer delamination or failure. The coherent skeleton ensures robust mechanical support, while the uniform porous structure provides consistent performance and cyclic stability. These features collectively enable the device to maintain durability under prolonged cyclic loading. In repeated compression cycle tests, we observed a gradual reduction in the area of the stress–strain hysteresis loop for the TEPUF material, leading to a marked decrease in the energy loss coefficient after 20,000 cycles (Fig. R15). This suggests diminished energy dissipation during cyclic loading. The energy loss coefficient, defined as the ratio of dissipated energy to total input energy during a loading–unloading cycle, typically decreases as internal friction is reduced and elastic recovery improves. This behavior is consistent with the Mullins effect observed in polymer elastomers, where repeated deformation leads to rearrangement of polymer chains, resulting in decreased stiffness and hysteresis loss. In TEPUF, such adaptive microstructural reorganization likely occurs after initial cycles, enabling more reversible elastic deformation in subsequent loading. These findings suggest that TEPUF undergoes an initial “training” phase, after which it exhibits reduced mechanical loss, enhanced elasticity, and greater stability under long-term cyclic compression. Therefore, the decreasing hysteresis loss with increasing cycles highlights the material’s excellent mechanical durability and reversible deformation characteristics, supporting its suitability for applications involving repeated mechanical loading. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 12). Comment 8: The in-situ observation on the deformation of layer(s) should be interesting, to help the understandings. Author reply: We sincerely thank the reviewer for the insightful comments. To investigate the behavior of TEPUF’s microscopic skeleton under large strains, we conducted in-situ SEM compression experiments (Fig. R16). The results show that during compression, the foam’s microscopic framework undergoes continuous compression, bending, and localized buckling. Upon unloading, the microstructure largely recovers its original morphology. These observations confirm the reversibility and strain stability of TEPUF at the microscopic scale, providing direct visual evidence of its energy dissipation and recovery mechanisms. Comment 9: The structural characterization and illustration are missing in Figures. How can we justify and creating the structure-property relationship without this?? The in-vivo validation seems be limited on the video, and less quantified. It hardly can say as convincing. Author reply: We sincerely thank the reviewer for the insightful comments. We acknowledge that the manuscript currently lacks detailed characterization of the highly porous TEPUF, which limits the clarity of the structure-performance correlation. To address this, we will incorporate comprehensive structural analyses to elucidate the internal hierarchical architecture of TEPUF and its influence on signal stability. Structural characterization: We performed in-situ SEM observations of the porous TEPUF under compressive strains of 0%, 20%, 40%, 60%, and 80% to track the microstructural evolution. As shown in Fig. R16, the morphology after full unloading and recovery was also documented. In the initial state, TEPUF exhibits a highly porous architecture with intact, well-defined pores (Figs. R16a and R16b). At 20% strain (Fig. R16c), the porous skeleton contracts slightly, and the pores remain largely regular with only minor reductions in size. Initial bending of the pore walls is observed, with deformation dominated by elastic wall bending rather than fracture, indicating that the skeleton remains structurally intact. The inter-pore spacing decreases slightly but remains uniform, suggesting a homogeneous compression response. At 40% strain (Fig. R16e), pores further flatten into oblate or polygonal shapes, and the framework becomes significantly denser. Increased wall curvature and early signs of wrinkling are seen (Fig. R16f), though no cracking is observed, highlighting the material’s excellent damage tolerance. The strain is primarily absorbed through wall buckling, with uniform pore shrinkage and stable global structure. At 60% strain (Fig. R16g), pores are highly compressed, and inter-skeletal spacing is further reduced. Wall buckling and intersecting wrinkles become more prominent (Fig. R16h), forming a compact but crack-free network. At 80% strain (Fig. R16i), the structure approaches its compression limit, and the skeleton height is significantly minimized. Severe wall bending, folding, and localized undulations appear (Fig. R16j), yet no large-scale fractures or collapse occur. Energy dissipation at this stage is primarily governed by wall buckling, with visible crease marks but maintained structural integrity. After complete unloading, the structure nearly returns to its original geometry. Figs. R16k and R16l show that the skeleton height and morphology are almost fully recovered, with pores reopening and only minor residual bending. These observations confirm TEPUF’s excellent geometric stability and microstructural resilience, demonstrating its ability to withstand large strains while maintaining reversible deformation behavior. Structure-property relationship: FEA was performed to simulate the stress distribution within the TEPUF porous structure under compression, providing intuitive insights into its mechanical behavior. Just as we replied in Comment 2, the simulation reveals that, under external compression, stress is primarily concentrated along the material’s 3D framework, specifically the pore walls and structural supports, while stress within the pore interiors remains negligible. This is expected for open-cell foams like TEPUF, where the interconnected polymer skeleton bears the mechanical load, and the voids serve merely as structural space without contributing to stress transmission. The simulated stress distribution highlights pronounced stress concentrations at skeletal junctions and curved regions, while most pore spaces exhibit minimal stress (Fig. R2). These results align with established understanding of porous materials, where mechanical performance is largely governed by the composition and geometry of the skeletal framework. Our findings confirm that TEPUF’s mechanical strength is determined primarily by the architecture of its skeleton. Geometric factors such as pore wall thickness and connectivity dictate how stress propagates through the network. When properly engineered, the skeleton distributes stress uniformly, minimizing localized concentrations and enhancing overall mechanical resilience. The FEA results clearly illustrate TEPUF’s characteristic load-bearing porous architecture, in which the solid frame is the principal stress carrier. This structural design explains its stability and resistance to collapse under compressive loads, supporting its suitability for demanding, cyclic mechanical environments. Quantified analysis: To strengthen the correlation between microstructure and functional performance, we conducted quantitative mechanical testing over 20,000 compression cycles. After cycling, the maximum stress decreased by only 8.8% (Fig. R17), and the resistance signal remained stable throughout (Fig. R18). These results clearly demonstrate the excellent structural durability of TEPUF and its positive contribution to long-term signal stability. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 11 and 12). Comment 10: In Figure 2-3, the detailed mechanics analysis should be added, rather than only FEA. How the energy conversion rate? And energy loss in the multi-layer structure? The above discussion could be added to elaborate more on the result. Author reply: We sincerely thank the reviewer for the insightful suggestions and have carefully considered each comment. As highlighted in our response to Comment 7, the TEPUF used in this study features a continuous foam structure. Its porous skeleton dissipates energy through viscoelastic deformation and pore recovery. Importantly, the absence of hierarchical interfaces eliminates the risk of interlayer failure often observed in multilayer designs. The continuous architecture also ensures structural uniformity and excellent cyclic stability, enabling high durability under prolonged loading. In this context, we conducted a comprehensive analysis addressing the reviewer’s concerns, extending beyond FEA to include experimental validation and mechanistic insights. In our system, the WPU coating primarily serves to protect the conductive network and impart waterproofing. Its strong adhesion to the foam is achieved through chemical cross-linking and hydrogen bonding, forming a robust and stable interface. This interface stability is critical for preserving TEPUF’s performance under diverse environmental conditions. To validate this, we conducted 20,000 underwater compression cycles. Only slight plastic deformation was observed. As show in Fig. R17, the stress-strain (σ-ε) curves exhibit minimal deviation across cycles, indicating excellent elastic recovery. TEPUF consistently returns to its original shape after repeated loading and withstands cyclic mechanical stress. Fig. R19 shows a modest decline in maximum stress during cycling. Notably, after 20,000 cycles, the elastic recovery remained at 92%, while the energy dissipation coefficient decreased to 0.41. These results confirm TEPUF’s mechanical resilience and durability under prolonged, water-submerged cyclic loading. Overall, these results confirm TEPUF’s exceptional mechanical performance under underwater conditions. Notably, after undergoing 20%, 40%, 60%, and 80% compressive strains, TEPUF fully recovers its original shape upon load removal (Fig. R20), demonstrating that its porous and highly elastic structure provides excellent long-term stability in aquatic environments. This recoverability is critical for underwater devices that require prolonged operation without risk of permanent deformation. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 12). Comment 11: The logic in Fig 4-5 seems in adequate in terms of justify the operation of the proposed system, the demonstrations were incremental. Author reply: We sincerely thank the reviewer for the insightful suggestions. To address this point, we conducted supplementary experiments in which the device’s resistance was monitored during both breathing and body-temperature tests. As noted in our response to Comment 3, the results show that the resistance remains nearly constant regardless of respiratory activity or temperature variation (Figs. R8 and R9). These findings confirm that breathing and temperature changes have minimal impact on the resistance signal, demonstrating effective decoupling of thermal and mechanical channels. Additionally, during mechanical strain tests, we measured the device’s thermoelectric voltage. The results indicate that even at varying stretch levels, the thermoelectric output remains essentially unchanged (Fig. R10). This further confirms that mechanical deformation has little influence on the thermoelectric response, providing additional evidence of robust signal decoupling between strain and temperature sensing. Building on the decoupling results, we designed the application shown in Fig. 5 of the manuscript. During real-time wear and motion, both the output voltage and resistance exhibit high stability and reliability, confirming the device’s multifunctional capability. Fig. 5 extends the decoupling evidence presented in Fig. 4, further validating the system’s effectiveness in practical scenarios. In summary, Fig. 4 clearly demonstrates decoupling between the thermal and mechanical sensing channels, providing strong support for the device’s operating principle, while Fig. 5 showcases its robust performance under real-world conditions, together forming a coherent and complete validation of the system. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 16, 17, 18, 34 and 35). Comment 12: The technical details including surface/interface condition, the porous area during the deformation, which should be discussed. The degradation/failure of micro-structure can increase the deviation and lead to the inaccuracy of the output. Author reply: We sincerely thank the reviewer for the insightful comments. In response to concerns regarding potential output drift caused by surface/interface conditions, deformation of the porous area, or microstructural degradation/failure, we provide new experimental data for clarification. As noted in our reply to Comment 8 and Comment 9, we performed in-situ SEM imaging at compressive strains of 0%, 20%, 40%, 60%, and 80% to monitor the structural evolution during loading. With increasing strain, TEPUF exhibits gradual and uniform pore contraction. Importantly, no pore-wall rupture, local instability, or irreversible damage was observed throughout the compression process. The foam maintained an intact framework, indicating high fracture resistance and structural stability over a wide strain range. Following load release, the in-situ SEM images reveal that the pore network re-expands, and the overall morphology closely matches that of the uncompressed state. These observations confirm excellent elastic recovery and microstructural reversibility, even under large strains. This high degree of recoverability is attributed to the continuous, interconnected pore architecture of TEPUF, which supports stable deformation and mitigates output drift during repeated mechanical loading. We next examined TEPUF after 20,000 compression cycles using both SEM and micro-CT to assess structural integrity. As shown in Fig. R21a, the pore network remains clearly visible, with no evidence of surface or interfacial collapse. Pore spacing remains uniform, and the framework structure is intact, indicating excellent macroscopic stability after prolonged deformation. Figs. R21b and R21c further confirm smooth, continuous surfaces without cracks, faults, or localized collapses, demonstrating that repeated compression causes negligible microscopic damage. Both surface and internal structures remain essentially unchanged. Micro-CT imaging (Fig. R22) further visualizes the 3D pore architecture. Even after 20,000 cycles, the pore network remains uniformly interconnected, with no signs of dense collapse or structural distortion. This uniform morphology confirms the absence of localized failure, which is critical for maintaining consistent device output. We also monitored the resistance signal over 20,000 compression cycles (Fig. R18), observing only minimal change, further supporting the device’s signal stability under long-term mechanical loading. Together, the SEM and micro-CT analyses reveal no evidence of skeletal fracture, interface delamination, or pore collapse. Correspondingly, the electrical signals remain stable throughout cyclic loading. This structural robustness is key to preventing signal drift and ensuring accurate, repeatable performance in practical applications. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 12 and 13). Comment 13: The writing and language in this manuscript also needs significant work. There are large chunky paragraphs and frequent language issues, which significantlt reduced the reading experience. I would recommend authors to revise and polish the context accordingly to a higher standard with an improved scientific interpretation. Author reply: We sincerely thank the reviewer for the insightful comments. We have carefully considered the suggestion and thoroughly revised the manuscript to improve grammar, structure, and overall clarity. These revisions have significantly enhanced the manuscript’s readability and overall quality. Author reply: We sincerely thank Reviewer 2 for the valuable comments and constructive feedback. The insightful suggestions have greatly contributed to improving the overall quality and clarity of the manuscript. Comment 1: The manuscript reports that the Seebeck coefficient and resistance remain stable over 20,000 compression cycles (Fig. 2h), but the supporting information only provides resistance change data up to 2,000 cycles (Fig. S24). To ensure consistency and completeness, the authors should include resistance-change data for all 20,000 compression cycles. Author reply: We sincerely thank the reviewer for the insightful comments. In the original submission, we mentioned that our device endured 20,000 compression cycles; however, the full dataset was not clearly presented in the Supporting Information. In the revised version, we have now included the complete resistance-change data across all 20,000 compression cycles. As shown in Fig. R18 on page 25 of this response letter, the resistance remains stable throughout the entire test, confirming the excellent mechanical durability and long-term stability of the TEPUF device. Comment 2: Thermoelectric materials are also often used in wearable energy harvesting. It is suggested that the author supplement the data and tests related to energy harvesting. Author reply: We sincerely thank the reviewer for the insightful comments regarding the demonstration of the device’s thermoelectric energy harvesting capability. In response, we conducted additional experiments with TEPUF worn on the wrist, knee, and elbow to harvest body heat, as shown in Fig. R23. At an ambient room temperature of 25 °C, the temperature difference between the skin and the environment drives a thermoelectric voltage across the TEPUF. Our results show that the device generates distinct open-circuit voltages depending on the body location. When worn on the wrist, it produces a stable voltage of approximately 2.24 mV (Fig. R23a); on the knee, approximately 1.23 mV (Fig. R23b); and on the elbow, approximately 1.56 mV (Fig. R23c). These findings confirm that TEPUF can function as a self-powered thermoelectric generator capable of utilizing human body heat for energy harvesting. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 16 and 17). Comment 3: The manuscript indicates that TEPUF has high air permeability and makes comparisons with other wearable multi-functional thermoelectric devices. It should be clearly stated whether these comparison devices were tested under the same pressure conditions. Author reply: We sincerely thank the reviewer for the insightful comments. In the original manuscript, we compared the breathability of TEPUF with that of other thermoelectric devices. However, most of the referenced studies did not report quantitative air-permeability values or adhere to standardized testing protocols. For instance, among the works cited in Fig. 1e, only Cui et al. qualitatively demonstrated airflow through their sensor, without providing a standardized air-permeability value 8. It is important to note that the studies included in Fig. 1e were selected not solely for their breathability, but because each exhibited excellence in at least one key performance metric relevant to multifunctional thermoelectric devices. These metrics include waterproofing, sensitivity, response times to temperature and strain, and long-term durability. By benchmarking TEPUF against these representative studies, we demonstrate that our material achieves a well-balanced performance profile, combining good breathability with exceptional waterproofness, rapid signal response, mechanical robustness, and stable output. Additionally, we emphasize that TEPUF’s air permeability was measured under rigorously defined and standardized conditions, following a method analogous to textile testing. The measurements were conducted at a pressure differential of 100 Pa and an ambient temperature of 25 °C, ensuring reliable and comparable results. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 8). Comment 4: It’s suggested to fully discuss the stability and adaptability of TEPUF under different water conditions. Author reply: We sincerely thank the reviewer for the insightful comments. We fully agree that a thorough discussion of device stability and adaptability in diverse aquatic environments is essential. In response, the revised manuscript now includes an expanded evaluation of TEPUF’s performance in both seawater and lake water. TEPUF is equipped with a robust waterproof coating comprising a PEDOT:PSS conductive network embedded in waterborne polyurethane, providing high water resistance (water contact angle of 112°) and effective protection against ionic contaminants. This coating minimizes ion ingress, particularly in saltwater, thereby preserving the integrity of the conductive network. To assess long-term stability, we immersed TEPUF in seawater for 48 hours and in natural lake water, monitoring the resistance throughout the exposure period (Fig. R24). In both cases, the device exhibited negligible resistance changes. Even in lake water, rich in organic impurities and mineral content, resistance remained stable. These results confirm that the coating effectively shields TEPUF from ion, mineral, and organic infiltration, demonstrating its strong environmental resilience and suitability for prolonged use in real-world aquatic conditions. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 11). Comment 5: The manuscript mentions the realization of multi-modal signal fusion and classification through machine learning algorithms, but the specific details and implementation process of the algorithms should be described in detail. Author reply: We sincerely thank the reviewer for the insightful comments. To achieve effective fusion and classification of heterogeneous multi-modal signals, we have implemented a machine learning framework based on support vector machines (SVM), incorporating feature standardization, kernel function selection, and hyperparameter optimization. The original multi-modal signals were first aligned and structured into a unified two-dimensional feature matrix. To eliminate numerical scale differences among features from different modalities, z-score standardization was applied, ensuring numerical stability and improving convergence efficiency during model training. For model construction, the radial basis function (RBF) kernel was chosen due to its strong capability in handling non-linear classification problems. To identify the optimal model configuration, we performed 5-fold cross-validation combined with a grid search across a predefined parameter space, allowing us to select the best-performing hyperparameter combination for the SVM classifier. Our modification to the manuscript: We have made several modifications in the revised manuscript (Page 7). Author reply: We sincerely thank Reviewer 3 for the valuable comments and constructive feedback. The insightful suggestions have greatly contributed to enhancing the overall clarity, quality, and completeness of the manuscript. Comment 1: The introduction appropriately emphasizes triboelectric nanogenerators in the context of self-powered sensors. However, it does not address other established self-powered mechanisms such as hydroelectric and piezoelectric technologies. A brief discussion of these alternatives would provide a more balanced overview and strengthen the contextual foundation of the manuscript. Author reply: We sincerely thank the reviewer for the insightful comments. As noted, while our introduction emphasized triboelectric nanogenerators (TENGs) as underwater self-powered sensors, it provided limited discussion of other mechanisms such as hydroelectric and piezoelectric technologies. Recent studies have indeed explored hydroelectric harvesters and piezoelectric transducers for underwater sensing and wearable applications. For example, Zhang et al. developed a flexible piezo-acoustic patch capable of sensing, positioning, and underwater wireless communication 11, which successfully monitored divers’ heart rates and transmitted the data acoustically. However, such technologies present notable limitations for underwater wearable applications. They often rely on rigid components, suffer from reduced stability under prolonged immersion, and are challenging to integrate into flexible, skin-conformable platforms. Furthermore, the majority of existing research on underwater self-powered sensing still predominantly focuses on TENGs. As discussed in our manuscript, TENG-based systems typically require bulky encapsulation that compromises comfort and flexibility, and most support only single-mode sensing. In contrast, our TEPUF device was specifically designed to overcome these limitations. It offers multi-modal signal decoupling, intrinsic waterproofing without the need for external encapsulation, and improved wearability, providing a more practical and versatile solution for underwater self-powered sensing applications. Comment 2: Although the application of waterborne polyurethane (WPU) enhances circuit protection, the potential impact of excessive coating on the foam’s air permeability remains unaddressed. The authors should clarify how to control the prevent obstruction of the foam’s porous structure and ensure air permeability. Author reply: We sincerely thank the reviewer for the insightful comments. This issue is indeed critical, as air permeability and water resistance in foam materials are typically inversely related, and achieving an optimal balance between these properties remains a core challenge in materials design. To address this, we conducted supplementary experiments to evaluate the effect of coating composition on performance. We prepared PUF samples with WPU:SWCNTs/PEDOT:PSS mass ratios of 0:2, 1:2, and 2:2, and measured air permeability using a YG461G tester. As shown in Fig. R25, the uncoated sample (0:2) exhibits high air permeability (527 mm s−1 at 100 Pa), but its hydrophilic surface readily absorbs water, making it unsuitable for underwater or humid environments. In contrast, the 2:2 coating significantly enhances waterproofing but suppresses air permeability to just 9.97 mm s−1, which compromises comfort and usability. To further correlate waterproofing with coating composition, we measured water contact angles (Fig. R26). The 0:2 sample shows a contact angle of ~88.7°, confirming its hydrophilicity and poor water resistance. The 2:2 sample exhibits a contact angle of ~129°, indicating strong hydrophobicity but at the cost of reduced permeability. Notably, the 1:2 coated sample achieves a balanced performance, with a water contact angle of ~112° and high air permeability (406 mm s−1), indicating effective waterproofing while maintaining breathability. To assess long-term protection, we subjected the samples to 8 hours of continuous water washing and monitored resistance changes (Fig. R27). The uncoated sample showed a significant resistance drop due to water ingress and degradation of the conductive network. In contrast, the 1:2 coated sample maintained stable conductivity, with negligible resistance change, demonstrating effective protection. While the 2:2 sample also preserved conductivity, its low air permeability limits its practicality for wearable applications. Overall, the 1:2 WPU:SWCNTs/PEDOT:PSS coating offers the optimal trade-off between breathability, waterproofing, and long-term stability, making it the most suitable choice for wearable use. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 9 and 21). Comment 3: The manuscript introduces a underwater wearable monitoring system based on a distributed sensor network, yet it lacks a clear explanation of its innovative aspects. The authors should elaborate on the rationale behind employing an array-structured sensor system instead of miniaturized integrated units. Author reply: We sincerely thank the reviewer for the insightful comments. We fully acknowledge the issues raised and would like to further clarify the innovations and advantages of the proposed sensor array architecture. Underwater physiological monitoring involves multiple parameters, such as temperature, breathing rate, and motion, which are challenging to capture simultaneously and accurately with a single-site or monolithic device. Our distributed sensor array addresses this limitation by allowing individual TEPUF units to be strategically positioned at critical locations, such as joints, inside diving masks, or on the chest. This proximity to the signal sources significantly enhances measurement accuracy and signal stability. The array consists of nine TEPUF elements connected in series, with each unit independently capable of sensing both temperature and pressure. The series configuration enables the summation of individual element voltages, thereby substantially increasing the overall output signal (Fig. R28). Additionally, the spatial distribution allows the array to collect data from multiple body regions or external heat sources, facilitating multipoint sensing and higher signal amplitude. Moreover, distributing the sensing load across multiple elements enhances response stability and improves wearer comfort by reducing localized pressure. Overall, this architecture not only supports multifunctional and high-fidelity sensing but also offers practical advantages in wearable underwater applications. Comment 4: The test results (air permeability and water contact angle) were not accompanied by statistical analysis. To verify the reliability and repeatability of the research results, the author should include statistical indicators, such as standard deviation or error bars. Author reply: We sincerely thank the reviewer for the insightful comments. We acknowledge the concerns regarding the reliability and repeatability of our results and greatly appreciate the suggestion. In response, we conducted replicate measurements of both water contact angle and air permeability to verify data consistency. As shown in Fig. R29 and Fig. R30, the results demonstrate high reproducibility, confirming the robustness and reliability of our measurements. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 2, 5, 20 and 32). Comment 5: A key claim of the manuscript is the decoupling of multiple stimulus signals. However, the practical applications shown in Figures 4 and 5 do not clearly highlight the advancedness of such decoupling. The authors are encouraged to justify the relevance of signal decoupling in practical applications and provide corresponding evidence. Author reply: We sincerely thank the reviewer for the insightful comments. Multi-modal signal decoupling is indeed critical for accurate underwater monitoring. In practical application scenarios, temperature variations and pressure signals often occur simultaneously, for example, body surface temperature changes during swimming, airflow temperature fluctuations during breathing, and pressure shifts from gesture-induced joint movement. Without effective decoupling, the system may misinterpret temperature changes as pressure signals, or confuse motion stimuli with thermal responses, leading to recognition errors and functional cross-talk that significantly compromise monitoring accuracy. In gesture recognition or respiratory monitoring, for instance, body movement or joint compression can alter local temperature, potentially triggering false alerts if signals are not clearly separated. Similarly, temperature fluctuations caused by exhaled breath could be mistakenly interpreted as grip force or motion, further emphasizing the importance of robust signal decoupling to ensure reliable and accurate physiological sensing in dynamic underwater environments. The TEPUF designed in this work strategically leverages the distinct response characteristics of its material structure and underlying physical mechanisms to achieve natural signal decoupling. Experimental results demonstrate that under a constant temperature difference, varying the applied pressure yields a stable pressure–resistance response curve, while the thermoelectric voltage remains virtually unaffected. Conversely, when the temperature difference increases under constant pressure, the thermoelectric voltage rises linearly with temperature, while the resistance remains unchanged (Fig. R31). This independent response behavior confirms the decoupling of the thermoelectric and piezoresistive effects in TEPUF. Such decoupling prevents signal interference and significantly improves measurement accuracy. For example, in respiratory monitoring experiments, periodic fluctuations in thermal voltage corresponding to breathing cycles were observed, while the strain resistance remained stable (Fig. R8 on page 8 of this response letter). Similarly, during underwater limb monitoring, resistance changes were clearly recorded during motion, whereas the thermoelectric voltage remained constant, indicating that mechanical disturbances do not affect thermal gradient measurements (Fig. R10 on page 9 of this response letter). These findings confirm that TEPUF can effectively separate thermal and mechanical signals in complex, dynamic environments. Furthermore, the multi-modal safety system illustrated in Fig. 5 utilizes decoupled inputs, temperature, motion, and breathing, for integrated analysis and real-time early warning. Thus, signal decoupling is central to the system’s reliability, stability, and sensing accuracy. Our modification to the manuscript: We have made several modifications in the revised manuscript (Pages 16, 17 and 18)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "This revision partially clarified the previous queries. Some key concerns remain. Most of them are critically linked with the justification of physical-chemical performance.\nSome critical concerns are:\n1. The multi-length-scale design and phase transformation seems be lack of justification, most of them are based on the illustration and/or with the indirect assessment. I was wondering if there are any possible in-situ measurement to quantify the interaction forces/effects? The response on the porous structure should be distinguished with further mechanic analysis on non-linear regime such as a hyper-elasticity, poroelasticity, etc.\n2. It is interesting that the authors provided the FEA results of the potential and stress distribution of the TEPUF under different temperature difference (ΔTs) and pressures in Figure R5. However, this figure brought a lot unclarity in the data with different temperature difference (ΔTs). The simulation should benchmark the temperature with different magnitudes, as the response could be different within each range.\n3. The testing data obtained from deploying the device in an inhaling mask, has a lot unclarity, the date in Fig 4 a-b, with minor fluctuations on output from temperature change of a few degrees is not convincing. The static charge could cause more fluctuation! Has the device been grounded properly? This should have a detailed schematic illustration for the testing setting.\n4. In Table R1, the comparison shown amazing advantage of the proposed technology. However, this level of precision needs a very critical testing environment to do the experiment, such as clean room. I am not persuaded by the method part as described in this work.\n5. In the simulation results from Figure 3f, there are substantial deviation of the output (in m-Volts) with 50% deformation and 12 degreeC temperature variation. However, the actual change (micro-Volts) is far more less than the condition, I don’t think this is a proper theoretical-experimental validation as the conditions have magnitude gap between each. I can not say that the methods are robust, and results are rigour.\n6. The underwater part is particularly tricky, I would recommend author to check the Professor Wanlin Guo’s work in NUAA, to understand the ‘Hydrovoltaic energy from water’, then justify the influencing factor properly.\nIn conclusion, I would recommend a transfer to sister journal or reject.", "reviewer_2": "The authors have made adequate modifications according to the comments, it can be accepted for publication in its current version.", "reviewer_3": "The comments have been addressed"}, "author_response": "Author reply: We sincerely thank the editor and the reviewers for their time and professional comments during the review process. We benefited a lot from the reviewers’ comments and carefully revised the manuscript in accordance with the comments. In particular, we are grateful to Reviewer 2 and Reviewer 3 for their affirmation of our research at the end of the previous review and their willingness to accept it. This has provided great encouragement for our work. In this revision, we provide a point‑by‑point response to Reviewer 1’s comments below and detail the corresponding changes made to the manuscript. Reviewer #1 (Remarks to the Author): This revision partially clarified the previous queries. Some key concerns remain. Most of them are critically linked with the justification of physical-chemical performance. Author reply: We sincerely thank Reviewer 1 for the valuable and constructive feedback, which has greatly contributed to improving the quality of our manuscript. Some critical concerns are: Comment 1: The multi-length-scale design and phase transformation seems be lack of justification, most of them are based on the illustration and/or with the indirect assessment. I was wondering if there are any possible in-situ measurement to quantify the interaction forces/effects? The response on the porous structure should be distinguished with further mechanic analysis on non-linear regime such as a hyper-elasticity, poroelasticity, etc. Author reply: We sincerely thank the reviewer for the insightful comments. To address the concerns regarding the lack of direct evidence for the multi-scale design, the absence of in-situ measurement, and the insufficient analysis of nonlinear mechanics, we have made the following additions and clarifications. In addition to the existing micro-CT three-dimensional reconstruction, we have incorporated localized in-situ scanning electron microscopy (SEM) observations, which capture the real-time microstructural deformation and contact evolution of TEPUF during compression. Multi-scale design: At the nanoscale, hydrogen bonds between the sulfonic acid groups in PEDOT:PSS and the -NH groups in WPU enhance interfacial adhesion, as evidenced by the absence of coating delamination after 20,000 compression cycles (Fig. 2h in the Revised Manuscript), with negligible changes in resistance and Seebeck coefficient, thereby preserving conductive pathways. At the microscale, the SWCNT/PEDOT:PSS layer conformally envelops the PUF struts, as visualized in SEM cross-sections (Fig. S4 in the revised Supporting Information), ensuring uniform conductivity without aggregation. This is corroborated by stable electrical output under humidity variations (Fig. 2d in the Revised Manuscript). At the macroscale, the open-cell porosity establishes isolated air pockets, yielding the observed ultralow thermal conductivity (~0.0445 W m−1 K−1, Fig. S2 in the revised Supporting Information) and enabling precise thermal sensing (0.05 K resolution, Fig. 2e in the Revised Manuscript). These scales synergistically confer hydrophobicity (contact angle 112°, Fig. 2b in the Revised Manuscript) and breathability (406 mm s−1, Fig. 2c in the Revised Manuscript), arising from the interplay of intramolecular cohesion, surface uniformity, and void architecture, rather than isolated attributes. In-situ SEM imaging demonstrates that, during the initial phase of applied compressive loading, the foam struts exhibit coherent elastic buckling and minor deformation, with the toroidal cell walls undergoing mutual compression while maintaining overall continuity (Fig. R1). Stress is uniformly diffusion across the toroidal walls and scaffold network, thereby preventing unstable buckling. This dissipation mechanism validates the multi-scale architecture’s ability to sustain macroscopic external loads while accommodating microscopic stress relief through the coordinated deformation of the compliant struts. In conjunction with stress-strain curves and metrics such as energy dissipation and elastic recovery ratio, these observations confirm the pronounced nonlinear hyperelastic character of TEPUF (Fig. R2, Fig. R3 and Fig. R4). Specifically, the stress-strain response exhibits marked nonlinearity, with low hysteresis loss and high elastic rebound during cyclic compression hallmarks of hyper-elasticity. In contrast, canonical porous elastomers often display substantial viscoelastic dissipation and time-dependence, neither of which is evident here. Thus, the mechanical response of TEPUF is dominated by the elastic recoil of the solid scaffold, rather than poroelastic effects governed by internal fluid flow within the pores. Our modification to the manuscript: We have revised manuscript on Page 12, with changes highlighted in blue. Comment 2: It is interesting that the authors provided the FEA results of the potential and stress distribution of the TEPUF under different temperature difference (ΔTs) and pressures in Figure R5. However, this figure brought a lot unclarity in the data with different temperature difference (ΔTs). The simulation should benchmark the temperature with different magnitudes, as the response could be different within each range. Author reply: We sincerely thank the reviewer for the insightful comments. To clarify the thermoelectric behavior under different temperature differences (ΔTs) and directly address the concern that device responses might vary across temperature intervals, we performed supplementary finite-element analyses (FEA) over a broadened ΔT range. Guided by the reviewer’s suggestion, we systematically benchmarked sensor behavior across multiple ΔT magnitudes, from ultra-small to comparatively large, under two representative compressive strains (20% and 60%). Simulation set-up and ΔT ranges: At fixed compressive strains of 20% and 60%, we prescribed ΔT at three levels to probe potential thermo-mechanical coupling. Small ΔTs: 0.05 K, 0.1 K (ultra-fine temperature resolution). Medium ΔTs: 1 K, 3 K, 5 K (typical operating window). Large ΔTs: 20 K, 40 K, 60 K (pronounced thermal gradients). For each condition, the specified ΔT was applied at the given strain to evaluate whether responses differ across temperature intervals. Results: Benchmarking across ΔT magnitudes demonstrates robust decoupling between the thermal-electrical and mechanical channels, thereby addressing the reviewer’s concern. Measurable thermovoltages are obtained even at ultra-small ΔTs (0.05K, 0.1K) and are independent of the applied mechanical load (Fig. R5). The device reliably detects minute temperature changes without pressure-induced artifacts. Within this common working range (1K, 3K, 5K), thermo-mechanical decoupling remains stable (Fig. R6). Even under high thermal gradients (20K, 40K, 60K), the imposed pressure exerts a negligible influence on the thermoelectric output (Fig. R7). Across all ΔT levels, the thermal-electrical pathway and the mechanical response remain decoupled, with no observable cross-talk between thermoelectric output and strain-induced effects. The observed decoupling originates from the architecture and materials design of the polyurethane foam with conductive fillers (TEPUF). Under compression, cell walls deform without catastrophic collapse, preserving the integrity of internal temperature-gradient pathways. Mechanical deformation is primarily accommodated by the skeleton and contact points, effectively isolating the heat-conduction routes from mechanical perturbations. Consequently, applied pressure does not materially alter the temperature field and thus does not affect the thermovoltage, the device sustains a stable ΔT under compression. In parallel, the piezoresistive network is governed by strain-driven contact evolution and, within the investigated range, is insensitive to temperature variations. This structural feature underpins the consistent decoupling observed at every ΔT magnitude and confirms independent dual-parameter sensing over a broad operating envelope. Our modification to the manuscript: We have revised manuscript on Page 14 and the Supporting Information on Pages 39, 40, and 41, with changes highlighted in blue. Comment 3: The testing data obtained from deploying the device in an inhaling mask, has a lot unclarity, the date in Fig 4 a-b, with minor fluctuations on output from temperature change of a few degrees is not convincing. The static charge could cause more fluctuation! Has the device been grounded properly? This should have a detailed schematic illustration for the testing setting. Author reply: We sincerely thank the reviewer for the insightful comments. We address the reviewer’s concerns point by point regarding the lack of clarity in the data presented in Fig. 4a-b, the unconvincing nature of the small fluctuations in output resulting from temperature changes of a few degrees, the potential for greater fluctuations due to static charge, the proper grounding of the device, and the need for a detailed schematic of the testing setup. To clarify the perceived lack of clarity in the testing data and the unconvincing small fluctuations in output, these data derive from real underwater respiratory monitoring experiments, in which TEPUF is integrated into a face mask and directly responds to the temperature gradient (ΔT) and mechanical perturbations from exhaled airflow. Fig. 4a provides a schematic of the underwater temperature sensing mechanism, while Fig. 4b illustrates changes in voltage (V) and resistance (R) during long-term respiratory monitoring, with the fluctuations reflecting authentic physiological signals rather than noise. Specifically, respiratory cycles induce ΔT variations typically ranging from 0.5 to 5 K (with exhaled air warmer than the ambient environment), yielding thermoelectric voltage fluctuations of ~0.17 to 1.72 mV, this correspondence is consistent with the thermoelectric devices in other studies 1-3. Such small fluctuations are expected given the modest ΔT in human respiration, but our device’s resolution of 0.05 K (Fig. 2e in the Revised Manuscript) enables their reliable detection. Regarding the possibility of greater fluctuations due to static charge, we agree that static charge could potentially affect sensor performance in a flexible system. To verify this, we used an electrometer to measure the device’s static voltage before and after grounding, showing that grounding reduces static voltage to zero (Fig. R8). We repeated the respiratory monitoring experiments under conditions with and without static charge (including normal breathing, deep breathing, rapid breathing, and nose breathing), and the results indicate that the voltage outputs for the same respiratory intensity are nearly identical. This confirms that static charge has a negligible impact and that the data in Fig. 4b are not influenced by static charge. With respect to proper grounding of the device, we confirm that all experiments were conducted with appropriate grounding, the TEPUF array is connected via copper electrodes and silver paste and linked to a Keithley 2450 source meter (which includes built-in grounding functionality). The device’s substrate is grounded via copper wires. For the detailed schematic of the testing setup, we agree this is a valuable addition to improve reproducibility. We have included a new schematic illustrating the face mask deployment, including the TEPUF integration position, grounding configuration, and data acquisition system (Fig. R9). Our modification to the manuscript: We have revised manuscript on Page 16 and the Supporting Information on Page 46, with changes highlighted in blue. Comment 4: In Table R1, the comparison shown amazing advantage of the proposed technology. However, this level of precision needs a very critical testing environment to do the experiment, such as clean room. I am not persuaded by the method part as described in this work. Author reply: We sincerely thank the reviewer for the insightful comments. To address the potential impact of environmental factors on testing precision, we conducted multiple independent replicate experiments in both a super clean bench (temperature 25°C, relative humidity 60%) and a standard laboratory environment (temperature 25°C, relative humidity 60%), comparing the device’s temperature resolution and strain response time. The results show consistent data across both environments: the minimum temperature resolution is approximately 0.05 K, and the compression response time is approximately 40 ms, with differences within the error range (Fig. R10 and Fig. R11). Additionally, we performed standard deviation statistics on the measurement data, finding that environmental changes have minimal impact on output signal fluctuations. Therefore, we conclude that the superior detection precision arises from the material design itself, rather than relying on stringent clean room conditions. To further demonstrate the validity of the methods and elucidate the scientific principles and innovations underlying the superior performance, we note that the benchmark studies in Table R1 similarly report high-precision metrics (ΔT responses of 0.2-1 K and strain times of 130-510 ms) using standard laboratory methods without clean rooms. Gao et al. used simple dip-coating of melamine sponge with PEDOT:PSS/CNTs, followed by drying under ambient conditions and testing with a Keithley meter in a regular lab setup, achieving a minimum temperature response of ~0.4 K 4. He et al. dispersed CNT ink with chitin nanocrystals via sonication and screen-printed it, with measurements in a standard environment, reporting a minimum ΔT response of ~0.7 K 5. He et al. prepared waste cotton-derived aerogels through sustainable mixing and freeze-drying, tested in typical lab conditions, with minimum temperature responses around ~0.27 K 6. Fu et al. employed roll-to-roll fabrication of chalcogenide glass-polymer films, with sensor tests in ambient labs, achieving ~0.2 K resolution 7. Cui et al. coated fabrics with PEDOT/MWCNTs via immersion and hot-air cross-linking, evaluated in standard setups, with minimum ΔT responses of ~1 K 8. These references consistently demonstrate that high-precision thermoelectric and strain sensing in similar devices can be reliably achieved without clean rooms. Furthermore, from a mechanistic perspective, the achievement of 0.05 K level temperature resolution primarily stems from the synergistic interplay between the three-dimensional open-cell foam structure and the flexible conductive framework. The ultralow thermal conductivity (~0.0445 W m−1 K−1) arises from the high porosity (~97%) 3D porous structure, creating numerous internal static air pockets that minimize thermal diffusion and enable detection of minute temperature gradients. For the rapid compression rebound (40 ms response time), the scientific principle lies in the material’s nonlinear mechanical regime: the hyperelastic behavior of the PUF framework facilitates rapid recovery through structural reconfiguration (pore wall bending rather than collapse), while the waterproof coating enhances durability under repeated cycles (Fig. 2h in the Revised Manuscript). This innovation addresses the trade-off between elasticity and conductivity in flexible sensors, enabling real-time multi-modal decoupling (temperature-strain) in high-humidity settings, surpassing reported response times, and advancing wearable electronics for marine exploration. Our modification to the manuscript: We have revised manuscript on Page 22, with changes highlighted in blue. Comment 5: In the simulation results from Figure 3f, there are substantial deviation of the output (in m-Volts) with 50% deformation and 12 degreeC temperature variation. However, the actual change (micro-Volts) is far more less than the condition, I don’t think this is a proper theoretical-experimental validation as the conditions have magnitude gap between each. I can not say that the methods are robust, and results are rigour. Author reply: We sincerely thank the reviewer for the insightful comments. The reviewer noted that in the simulation results of Fig. 3f in the original manuscript, applying 50% compressive strain and a 12 °C temperature change yielded voltage outputs on the milli-volts (mV) scale, while the actual experimental signal changes are on the micro-volt (μV) scale, indicating a significant gap in the magnitude of the stimulus conditions. Thus, the reviewer questions whether the mismatch between the original simulation and experimental validation conditions may undermine the validity of the result comparison. The FEA simulations in Fig. 3f are intended to illustrate the decoupling mechanism between mechanical strain and thermoelectric potential, rather than to provide an exact quantitative match for specific experimental conditions. These simulations employ a multi-physics approach (coupling solid mechanics, electric currents, and heat transfer modules in COMSOL, as detailed in Eqs. S1-S12 of the Supporting Information) to demonstrate that external pressure has minimal impact on the thermoelectric potential distribution, even under substantial deformation (50% strain) and temperature gradients (ΔT = 12 K). This qualitative and trend-based validation is a standard practice in thermoelectric sensor research, where FEA is often used to predict stress and potential fields under controlled conditions to highlight underlying physics, without accounting for experimental-specific influences. To address this concern, we have made the following improvements in the latest revision. We have added experimental data for thermo-mechanical decoupling at the μV level. As shown in Fig. R12, under 50% deformation, different small temperature differences were applied. Even at weak signals on the μV scale, the two outputs maintain clear separation characteristics. Additionally, the device exhibits dynamic decoupling capability. At low temperature difference magnitudes, multiple experiments still show highly reproducible response curves, demonstrating that the device’s thermoelectric and piezoresistive signals can still be reliably distinguished and stably measured under weak stimulus conditions. We have conducted finite element simulations based on parameters fully consistent with the experiments (Fig. R13). Voltage distributions were calculated under compression strain consistent with the experiments (50%) and different temperature differences, with results showing outputs consistent with experiments, both at the μV level, and spatial distribution trends aligning. This further verifies the effectiveness of our theoretical model under weak signals, indicating that the model can accurately predict the impact of small thermoelectric and piezoresistive changes on output signals. Through the above supplementary experiments and simulation results, we find that theoretical predictions and actual measurements are highly consistent in both signal magnitude and change trends. This effectively addresses the reviewer’s question regarding the previously high simulation output, eliminating the mismatch in comparisons under different magnitudes. We appreciate the reviewer’s suggestions, which guided these targeted additions and enhanced the rigor of our methods and results. Our modification to the manuscript: We have revised manuscript on Page 15 and the Supporting Information on Pages 42 and 43, with changes highlighted in blue. Comment 6: The underwater part is particularly tricky, I would recommend author to check the Professor Wanlin Guo’s work in NUAA, to understand the ‘Hydrovoltaic energy from water’, then justify the influencing factor properly. Author reply: We sincerely thank the reviewer for the insightful comments. As noted by the reviewer, we recognize the potential complexities in the underwater section of our manuscript, particularly the influence of hydrovoltaic effects at water-solid interfaces. Following your recommendation, we have carefully reviewed the pioneering work of Professor Wanlin Guo’s group at NUAA on ‘Hydrovoltaic energy from water’ and conducted an in-depth analysis of hydrovoltaic effects and their key influencing factors based on the literature. The hydrovoltaic effect refers to the generation of electricity through interactions at water-solid interfaces. When nanomaterial surfaces come into contact with flowing water, evaporating water molecules, moisture or ions in solution during dynamic processes, charge rearrangement, electric double-layer changes, or even potential generation may occur at the interface, leading to additional voltage output 9-16. These phenomena could interfere with the thermoelectric signals we intend to measure. After a thorough examination of Professor Guo’s group’s research, we gained important insights: their studies systematically summarize the mechanisms of dynamic energy harvesting from water flow, waves, natural evaporation, and moisture adsorption. These works highlight the tremendous potential of hydrovoltaic effects while reminding us that in underwater or high-humidity thermoelectric monitoring, factors such as charge transfer at water-solid interfaces and ionic concentrations must be carefully evaluated to avoid signal crosstalk. To verify whether our device would be affected by the hydrovoltaic effect and allay the reviewer’s concerns in this regard, we focused on the core influencing factors of the hydrovoltaic effect proposed by Professor Guo’s research group (water flow, evaporation, water adsorption, droplet movement, ion concentration), combined with the actual application scenarios of our materials (underwater physiological monitoring and high-humidity environments, such as breathing, body temperature and motion signal collection). Water flow: Fix the TEPUF sample in an underwater environment, use a peristaltic pump to control the water flow rate (~1 m/s) while maintaining no ΔT conditions, and measure its output voltage. Compare the voltage output under still water conditions (flow rate 0 m/s) with that under water flow conditions to evaluate the influence brought by water flow. Water evaporation: First, soak the TEPUF sample in deionized water for 30 minutes to allow it to fully absorb water (simulating long-term underwater contact). Then transfer the sample to a laboratory environment (temperature 25°C, relative humidity 60%) and continuously monitor the output voltage under no ΔT conditions for 10 minutes to examine the influence caused by evaporation. Moisture adsorption: Place the TEPUF in a constant temperature and humidity chamber and simulate different moisture levels by changing the relative humidity (from 40% to 90%). Maintain no ΔT conditions and continuously measure the sample’s terminal voltage to assess the contribution of moisture adsorption to the output signal. Droplet impact: Simulate water droplet motion under underwater conditions: Use a syringe to precisely release a single water droplet (volume approximately 0.1 mL, falling freely from 10 cm above the sample) to impact the TEPUF surface, and record the transient voltage changes. This experiment can detect whether the kinetic energy of the water droplet interacting with the sample interface generates potential. Ionic concentration: Soak the TEPUF in seawater. Measure the terminal voltage and resistance value of the TEPUF under no ΔT to compare the influence of seawater on voltage and resistance output. The above experiments involve major factors (such as water flow, evaporation, humidity, charge/ion movement) derived from the core influencing factors proposed by Professor Guo’s group. Our purpose is to simulate possible water environmental changes in actual monitoring scenarios and verify their impact on thermoelectric signals. The experimental results show under all test conditions, whether still or dynamic water flow, different humidity, single droplet impact, or seawater, the output voltage of the TEPUF samples is close to baseline levels, with no significant additional potential generation detected (Fig. R14, Fig. R15, Fig. R16, Fig. R17 and Fig. R18). This is also attributed to our material design. We employed a composite waterproof coating of SWCNTs/PEDOT:PSS/WPU, whose hydrogen-bonded network inhibits water permeation, as shown in the supporting information, with a surface water contact angle of approximately 112° and no significant performance degradation in long-term immersion tests. This design minimizes the possibility of water penetrating the sensitive film, thereby reducing the impact of hydrovoltaic effects on thermoelectric signal measurements, ensuring that the measured voltage primarily originates from thermoelectric effects rather than hydrovoltaic effect. Our modification to the manuscript: We have revised manuscript on Page 19 and the Supporting Information on Pages 58, 59, 60, 61 and 62, with changes highlighted in blue."}, {"round": 3, "reviewer_comments": {"reviewer_1": "This revision made some improvements to clarify the advancement and originality of project. While the new data offer a clearer logic to reader, the overall changes appear to be incremental. My concern on the novelty and originality remains, as the author team has not been explicit on the specific working mechanism. The interpretation on the underlying science has a major flaw. The justification of structure-property relationship remains less convincing. The theoretical part need be strengthen, the current interpretation seems a little slim to support the claim.\nThe following things need be also cleared up:\n1. In my comment 1, the concern is about the justification of the change of the porous and the clearance of dynamic of change. While the author offer a variety on the degree, but this is not the typical identification by the homogeneity and degree of deformation. Also the discussion of porosity should consider the local deformation. A multilengthscale approach will offer more academic value on the work. Sadly to say that, all above is missing at current manuscript. I guess a planar simulation in 2D would help.\n2. In comment 5, the overall comparison on the vary of temperatures seems be bit reliable. If it was applied on mask, the breath pressure should be listed as another parameter to compare? Some references on the mask or mask materials would be helpful, i.e. https://doi.org/10.1002/advs.202102189; DOI: 10.1002/smll.202102903\nIn conclusion, the research is of some quality, but doesn’t meet the standard to publish. There are substantial gaps existing in the research rigour and significance, in terms of the justification of the fundamental science. I would recommend another round of major revision."}, "author_response": "Author reply: We sincerely thank Reviewer 1 for the valuable and constructive feedback, which has significantly improved the quality of our manuscript. We also appreciate the reviewer’s acknowledgment of the enhanced clarity and logical coherence resulting from the new data. To address the concerns regarding the specific working mechanism, underlying scientific interpretation, and structure–property relationships, we have made substantial revisions. In particular, we have incorporated additional two-dimensional (2D) simulations to provide deeper analysis and clearer explanations in the revised manuscript. Specific working mechanism: We have clarified the specific working mechanism of the TEPUF in the revised manuscript. The device operates by generating two distinct electrical signals in response to thermal and mechanical stimuli, enabled by a dual-mode thermoelectric–piezoresistive design. A temperature gradient induces a thermal voltage determined by the Seebeck coefficient of the SWCNTs/PEDOT:PSS network, whereas external pressure or strain alters the resistance of the intrinsic conductive framework through the piezoresistive effect. These two outputs are intrinsically decoupled and recorded on separate channels, ensuring the absence of cross-talk between thermal and mechanical responses. The material composition and structural design are purposefully engineered to achieve this decoupling: the incorporation of SWCNTs into the PEDOT:PSS polymer simultaneously enhances electrical conductivity and thermopower, while the hyperelastic three-dimensional (3D) porous WPU foam functions as a thermally insulating, mechanically compliant scaffold that minimizes mutual interference between heat and stress stimuli. Scientific principles: Our thermoelectric device produces a voltage signal in response to temperature differences and a resistance signal in response to mechanical deformation, inherently separating the two stimuli without requiring complex decoupling algorithms. The thermoelectric output arises from charge-carrier diffusion within the SWCNTs/PEDOT:PSS composite, generating an open-circuit voltage described by V = S × ΔT. In parallel, the piezoresistive response originates from the conductive SWCNTs/PEDOT:PSS network embedded within the elastic WPU matrix: when compressed, the network density increases while the contact resistance decreases, yielding a distinct resistance change. We further highlight that the device’s underwater and high-strain performance is supported by well-established physical principles. The porous foam and waterproof WPU architecture prevent water ingress and help maintain a stable temperature gradient, while the robust SWCNTs/PEDOT:PSS/WPU composite network preserves electrical conductivity during repeated deformation. As added validation, we now provide experimental results demonstrating that the TEPUF maintains stable thermoelectric output and piezoresistive response over thousands of cycles and during submersion, confirming that the underlying physics of our design remain reliable under practical operating conditions. Structure-property relationship: The material composition (SWCNTs, PEDOT:PSS, and WPU) together with the foam’s microcellular architecture creates a synergistic structure–property relationship that enables dual-mode sensing with high sensitivity and elasticity. In the revision, we have adopted a multilengthscale approach and complemented it with 2D finite-element simulations to more rigorously interpret the underlying mechanisms (see detailed analysis in Response to Comment 1). Our modification to the manuscript: In response to the reviewer’s comments regarding the specific working mechanism, underlying scientific principles, and structure–property relationships, we have made targeted revisions to the Conclusion section. We have also added a final statement summarizing the multilengthscale approach and the 2D finite-element simulations. These revisions have been incorporated on Pages 20–21, with all changes highlighted in blue. The following things need be also cleared up: 1. In my comment 1, the concern is about the justification of the change of the porous and the clearance of dynamic of change. While the author offer a variety on the degree, but this is not the typical identification by the homogeneity and degree of deformation. Also the discussion of porosity should consider the local deformation. A multilengthscale approach will offer more academic value on the work. Sadly to say that, all above is missing at current manuscript. I guess a planar simulation in 2D would help. Author reply: We sincerely thank the reviewer for this insightful comment. To address the concern, we conducted a 2D finite-element simulation of the foam cross-section under compression and performed a multilengthscale approach to elucidate the underlying mechanisms. As the compressive strain increases, the foam’s initially open cells deform into progressively flatter shapes. The 2D model clearly shows pore walls moving closer together and eventually pressing against one another under load, transitioning from an open-cell geometry to a flattened-cell structure at higher strains (Fig. R1). This behavior is consistent with our experimental observations, where the cell walls gradually flatten and form broader contact interfaces as the foam is compressed. With increasing compressive strain, the pore size steadily decreases. The simulation shows a continuous reduction in pore volume from low to high strain, indicating that the porosity diminishes gradually rather than abruptly. This behavior reflects a uniform deformation of the porous network. As the pores flatten and the pore walls bend, the structure can recover once the load is removed. The 2D simulation confirms that deformation is primarily accommodated through elastic bending of the cell walls rather than permanent collapse, an intrinsic characteristic of the foam’s hyperelastic response. Even at high strain, a porous scaffold remains, enabling the foam to return to its original shape upon unloading. This preservation of porous architecture under substantial compression directly supports the material’s excellent elastic rebound and long-term cyclic durability. In addition to the 2D mechanical stress simulations, we have expanded our analysis to include a 2D thermoelectric potential-field simulation under a temperature difference of ΔT = 12 ℃ (Fig. R2). The resulting voltage distribution remains uniform and unchanged even under large compressive strains, demonstrating that the thermoelectric output is not affected by mechanical loading. This new simulation explicitly validates the mechanical–thermal decoupling mechanism and confirms that a stable thermoelectric potential field is maintained despite applied pressure. We further strengthened the discussion by situating our findings within a multilengthscale framework. At the nanoscale, strong hydrogen bonding among SWCNTs, PEDOT:PSS, and WPU forms a robust yet reversible polymer–nanotube network that preserves electrical conductivity under strain. At the microscale, the open-cell architecture functions as an effective stress-buffering system: under compression, the pore walls deform first at their weakest points, then progressively at the junctions, and ultimately the cells compress along the vertical axis while exhibiting slight lateral expansion. At the macroscale, the interconnected foam network distributes external load uniformly, enabling the device to endure 20,000 compression cycles even under underwater conditions. In summary, the combined 2D simulation results provide spatially resolved, multiscale insights into how the foam’s porosity evolves under compression while maintaining stable signal output. These findings directly address the reviewer’s request for a detailed multiscale explanation of porosity evolution and signal robustness, demonstrating that the device’s porous architecture can undergo substantial deformation without compromising its thermoelectric performance. Our modification to the manuscript: We have revised manuscript on Pages 15-16, 36 and Pages 44-45 in the revised Supporting Information, with changes highlighted in blue. 2. In comment 5, the overall comparison on the vary of temperatures seems be bit reliable. If it was applied on mask, the breath pressure should be listed as another parameter to compare? Some references on the mask or mask materials would be helpful, i.e. https://doi.org/10.1002/advs.202102189; DOI: 10.1002/smll.202102903. Author reply: We sincerely thank the reviewer for the helpful comment regarding breathing pressure and for directing us to the relevant mask-related references. We have carefully examined these works on advanced mask technologies and conducted additional experiments to clarify the influence of breathing pressure in our system. Unlike prior studies that primarily focus on enhancing filtration efficiency or incorporating antimicrobial functionalities at the material level, our work aims to develop a multifunctional mask material that not only satisfies essential protective requirements but also enables integrated on-mask health monitoring 1, 2. We first conducted supplementary experiments using a ventilator simulator to mimic human breathing at different pressures while simultaneously monitoring voltage and resistance. We quantified the dynamic pressure generated by the breathing airflow. The results show that at ΔT = 0 K, neither the resistance nor the voltage exhibits any measurable change under varying breathing pressures (Fig. R3). This demonstrates that the mechanical pressure associated with breathing induces a negligible effect on the device’s resistance response, confirming that breath pressure has minimal influence on the output signal in our design. We further refined our analysis in the revised manuscript by updating Fig. 4b to include the quantified dynamic pressure during breathing (Fig. R4). The periodic voltage fluctuations closely track the temperature variations induced by breathing, while the corresponding dynamic pressure remains low and shows no correlation with the electrical output. This finding confirms that the device’s output is dominated by the thermal voltage generated from breath-induced temperature gradients, with negligible interference from airflow pressure. Consequently, the TEPUF-based mask can reliably monitor respiration even in challenging environments, without producing false signals arising from airflow or pressure fluctuations. Our modification to the manuscript: We have revised manuscript on Pages 17, 37 and Page 49 in the revised Supporting Information, with changes highlighted in blue."}, {"round": 4, "reviewer_comments": {"reviewer_1": "This revision has addressed my previous concerns in full, therefore, I would recommend to accept to publish in NC."}, "author_response": ""}]

Decision letter