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Page 8 of 27 Tian et al. Soft Sci 2023;3:30 https://dx.doi.org/10.20517/ss.2023.21

Table 1. A brief summary of active materials of pressure and temperature sensors towards e-skin
Material categories
Mechanisms Metal- and metal-oxide- Carbon- and polymer-
based based Hybrids and others

Static pressure sensing Piezo-capacitive / CNMs Graphene Fbric
(Dielectric GO PDMS Fluidic ionic liquids
materials) Ecoflex PMMA
Piezoresistivity Ag/Cu/Au NMs CNMs Graphene MoS 2 MXene
GO rGO
Dynamic pressure sensing Piezoelectricity ZnO BaTiO 3 PVDF Graphene PbTiO 3
Mn partices P (VDF-TrFE) NWs/graphene
PLLA heterostructures
Triboelectricity Al/Cu FEP TPFE Silk Paper
Temperature pressure Thermoeletricity Ag NMs Bi 2 Te 3 CNMs Graphene IOTEs(e.g., Te NWs)
sensing
PETOD:PSS
Pyroelectricity ZnO NMs BaTiO 3 PVDF Graphene PVDF/CuO composite
PZT BFO P(VDF-TrFE) PVDF/graphene film
Thermoresistivity Pt Cu Ni CNMs NIPAM MoS 2 MoSe 2
Poly(ionic liquid)

BaTiO : Barium titanate; BFO: bismuth ferrate; CNMs: carbon nanomaterials; FEP: fluorinated ethylene propylene; GO: graphene oxide; IOTEs:
3
inorganic thermoelectric materials; NIPAM: n-isopropyl acrylamide; PEDOT:PSS: poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate); PLLA:
polylactic acid; PMMA: polymethyl methacrylate; PTFE: polytetrafluoroethylene; PVDF: polyvinylidene difluoride; P(VDF-TrFE): poly(vinylidene
difluoride and trifluoroethylene); PZT: lead zirconate titanate piezoelectric ceramics; rGO: reduced graphene oxide.

temperature sensing. Nevertheless, we need to employ artificial means to identify coupled signals or
[3]
minimize the troublesome crosstalk . Data processing methods, such as machine learning, are applied for
[68]
decoupling different kinds of sensing information . Therefore, many explorations and much research of
new active sensing materials have been continued to raise the compatibility with the increasingly advanced
fabrication of pressure and temperature sensors.

BASIC SENSING MECHANISMS AND EVALUATION PARAMETERS FOR PRESSURE AND
TEMPERATURE SENSORS
Before proposing a comprehensive scheme for integrated pressure and temperature sensors, it is extremely
vital to understand multiple single pressure and temperature sensing mechanisms and evaluation methods
in this section. This not only matches the active materials described above to the various sensing
mechanisms but also provides a theoretical basis for the next step in the design of integrated pressure and
temperature sensors. In general, wearable sensors transduce physical signals (pressure, strain, or
temperature) into electrical signals (resistive, potential, and capacitive signals) and nonelectrical signals
(mainly optical and magnetic signals), as presented in Figure 5. Thanks to sensitive and convenient
detection, electrical output signals are broadly predominant, which can be increasingly reported in recent
studies. Additionally, the change of resistance, capacitance, and voltages can be detected with the help of
multiple instruments to achieve a wider range, higher resolution, and more rapid response. More
importantly, the piezoelectric and triboelectric output can achieve self-powered elements for eco-friendly
applications .
[2]

Basic sensing mechanisms and evaluation parameters for pressure and temperature sensing are discussed in
this section. With regard to pressure sensing, we can classify mechanisms into two categories, respectively,
for static and dynamic stimuli detections. In summary, piezoresistive and capacitive pressure sensors are