Tunable temperature alarm sensorswere prepared using multilayergraphene and nitrocellulose (NC) to reliably monitor early high temperaturerisks. The graphene/NC alarm sensor keeps in a state of electricalinsulation, however, turns electrically conductive at high temperatures,such as encountering a flame attack. Its response time is limitedto only a few seconds because of a quick chemical reaction of NC.The 90% graphene/NC (wt % ratio 1:9) composite alarm sensor stablyremains insulated at an ambient temperature of 200 °C, resultingin a satisfactory responsive temperature (232 °C), instant responsetime (4.4 s), and sustained working time in the flame below the ignitiontemperature of most combustibles. Furthermore, the response temperatureand time of the alarm sensor can be tuned by graphene/NC ratios toreduce the fire risk of various combustible materials in differentfire-prone scenarios and thus has promising applications in both indoorand outdoor environments. The sensor has also proven to work in theform of paint, wallpaper, and other composites due to its superiorflame retardancy property, as well as under extreme conditions . Drivingthe development of fire safety strategies, especially preventativemethods such as early fire detection that helps to avert severe damagebefore it occurs is, therefore essential in ensuring the welfare oflives and property. Among various existing devices, smoke detectorsand infrared heat detectors are the primary fire sensors that arewidely utilized indoors.2 However, as bothof them are activated by smoke, which is only emitted after the flamingcombustion has already begun, the response time of these traditionaldetectors usually exceeds 100 s.3 The delayedresponse of these detectors makes it almost impossible to providetimely and effective warning signals to reduce losses of life andproperty. To this end, developing an early-warning fire detectionsystem with a faster response time is of critical importance. A severefire accident usually initiates with the induction of a temperatureincrease in some combustible material by an external heat source,leading to its endothermic pyrolysis.4 Thiscauses the vaporization of decomposition products and thus generatesa further rapid increase of temperature, triggering the fire as aresult. Consequently, an early-warning fire detector with an improvedresponse speed would facilitate safety, but only if it also complieswith the following requirements: it must provide warning signals forabnormally high ambient temperatures, and it must maintain structuralstability during a flame attack.Therewere approximately 167 000 fires in the UK from 2017to 2018.5 high mechanical properties,6 and structural stability under high temperatures. Researchers tookadvantage of the electrical insulating features of GO that would bereduced and thus turn conductive in a high temperature environmentand produced a series of temperature sensors. These sensors demonstratea lower thermal response temperature and faster response behaviorwhen compared to traditional fire detection methods which theoreticallyreduce the response time from 100 to 2–6 s.11 Chen et al.8 prepareda fire alarm using fire-resistant inorganic paper as a coating materialbased on ultralong hydroxyapatite nanowires and GO. It was arrangedwith an electrical connection between the composite paper, an alarmlamp, and an alarm buzzer to achieve an instant response time (lessthan 2 s) under a relatively high experimental temperature. Similarmorphology designs have also been successfully utilized by other researchers,who employed different materials in conjunction with GO. Endeavoringto enable fire prevention through detecting high environmental temperatures,that are, meanwhile, below the ignition temperature of combustibles,Wu et al.9 prepared hierarchical coatingson GO and silicone. These coatings were applied to different combustiblesubstrates to facilitate the exhibition of distinct temperature-responsiveelectrical resistance changes, creating a highly effective early-warningsensor. However, the authors did not define the accurate responsetemperature or time of their sensors, which is relevant and necessaryinformation for safety and sensor design as the GO/silicone compositeis coated directly onto a combustible material. Other researchersgrafted silane on GO to manufacture flexible flame-retardant paper.12 Similar to the work of Yu et al.,13 the insulating silane–GO paper couldbe thermally reduced to form a conductive network in a high-temperatureenvironment . Xu et al.11 synthesized rectangle-shaped GO wide-ribbon(GOWR) sheets from carbon nanofoams and fabricated the GOWR-wrappedmelamine–formaldehyde sponge through dip-coat processing. However,such a sponge only started to respond at around 450 °C, whichwas much higher than the desired response temperature.Existing research indicatedthat graphene and graphene oxide (GO)can be used as effective materials for fire alarm sensors due to theirhigh electron mobility, superior thermal conductivity,16 and superior thermalconductivity, have introduced graphene as the optimal candidate fortemperature sensor applications at the micron-scale or even at thenanoscale.18 Given the method for preparinggraphene with liquid-phase exfoliation,23 various polymers have been proven to be effectivein producing uniform graphene dispersion as a dispersant, which contributesa simple strategy to manufacture graphene/polymer composites effectively.Nitrocellulose (NC), one kind of chemically modified cellulose, hasrecently been proven to be a graphene-dispersing polymer that effectivelydisperses graphene in organic solvents. NC, due to its unique characteristicsin instantaneous pyrolysis and oxygen-free combustion, provides aninspiration for its potential in the design of a temperature-sensitiveearly-warning sensor. So far as we know, no substantial research hasreported any use of graphene and NC in temperature alarm sensors.This study innovatively presents a graphene/NC early-warning firesensor that efficiently responds to temperature changes and avoidssevere damage. Although the graphene/NC membrane remains electricallyinsulated normally, it turns conductive at high temperatures and thereforecan be used in sensors of an alarm system. Furthermore, the responsetemperature and sensitivity of these sensors can be tuned by adjustingthe ratio of graphene and NC to react in different fire-prone scenarios(each 1% increase in NC content leads to a ∼1.8 °C increasein the response temperature). Meanwhile, the tunable temperature sensorhas proven to withstand extreme conditions such as underwater or vacuumenvironment as thermal degradation of NC can take place in oxygen-freeenvironments. The flame retardancy test indicates the sensor’ssuperior and stable function when employed on a solid surface . All types of graphene/NC sensors with variousNC content provided continuous danger alarm even when the sampleswere removed from a flame or specific temperature environment, demonstratingeffective and stable fire warning for detecting high fire risk ofcombustible materials for applications in various scenarios.24It isworth noting that the aforementioned studies focused onlyon utilizing the mechanism of GO reduction to achieve transformationof the conductive state, not on other graphene-like materials. Herein,the electrical conductivity of graphene and the insulation of nitrocelluloseare integrated to prepare a new fire alarm sensor. The excellent properties,such as high electron mobility22.1n-butyl acetate (ACS Reagent grade) were purchased fromSigma-Aldrich. Natural graphite flakes  were purchased from Alfa Aesar. Sodium chloride  was purchased from Sigma-Aldrich and used to induce the flocculationof graphene.Collodion solution (4–8%NC in ethanol/diethyl ether), ethyl acetate, acetone, and 2.2–1 aqueous salt solution to inducethe flocculation of graphene and NC. After that, the sediment washarvested and left to dry at 70 °C in an oven. Once the organicsolvent was completely evaporated, the graphene/NC flocculation wasrinsed with deionized water several times until the surplus sodiumchloride was removed. The resulting solid was dried and stored inbottles prior to subsequent use.Graphenewas manufactured from natural graphite flakes by the liquid exfoliationmethod. First, the as-received collodion solution was poured intoa Petri dish and evaporated in a fume hood overnight until no changein weight was observed. Dried NC (10 g) was cut into small piecesand added into a 1000 mL mixed solution in a ratio of 1:4 ethyl acetateand acetone with natural graphite flakes (100 g). With a water-coolingsystem, the mixture was operated in a high shear mixer (SilversonL4RT) for 2.5 h at 6000 rpm and produced a graphene/NC solution thatwas then centrifuged at 3000 rpm for 30 min (three times) to removethe large graphite flakes. The supernatant was collected and thenadded with a 40 g L2.3n-butyl acetate at a concentration of 10 or 30 mg mL–1. Additional NC was added into the suspension to gain different ratiosof NC in the composite. With the abovementioned methods and the originalsuspension, the first fabricated composite where NC content was 60%was marked G@NC60. Extra NC was added to the original suspension toproduce different NC content composites such as G@NC75 and G@NC90.Altogether, three types of samples, where NC content was 60, 75, and90%, respectively, were produced and employed in the current study.The solution was then drop-casted onto a pre-cleaned blank glass slide(7.5 cm long and 2.5 cm wide) and evaporated under ambient conditions,leaving a coating membrane of graphene/NC. The thickness of thesefilms can be controlled by the amount of solution added to the substrate.Two edges of the membrane were connected to copper wires as externalelectrodes for further tests of resistance change.Thegraphene/NC mixture was then dispersed directly in 2.4–1. Ramanspectra of various samples before and after thermal treatment wereacquired from 200 to 4000 cm–1 using a RenishawSystem 1000 Raman spectrometer at ×50 objective, with an incidentpower of 2.3 mW. AFM images of graphene sheets were recorded witha Bruker Dimension Icon in peak-force mode. The spectral resolutionof system was within 1.5 cm–1 at 514 nm. TGA dataof various samples were generated using the TA Instruments Q500 inan air or nitrogen atmosphere at a heating rate of 10 °C min–1 from room temperature to 800 °C. Scanning electronmicroscopy (SEM) images were collected by a scanning electron microscope(Carl Zeiss AG-ULTRA 55). Tensile tests were performed using an Instronsingle column table frames model 3344 (100 N load cell) at a speedof 1.0 mm min–1 at room temperature following theASTM standard 882, and the sample thickness was measured by SEM.To investigatethe chemical changes of the graphene films after the thermal treatment,thermogravimetric analysis (TGA), Raman spectroscopy, atomic forcemicroscopy (AFM) analysis, and Fourier transform infrared (FTIR) spectroscopywere employed. The samples utilized for all the abovementioned characterizationmethods were divided into two types: (i) pre-annealing G@NC filmsand (ii) G@NC samples after thermal treatment at 260 °C. FTIRdata were obtained using an FTIR spectrometer  between 400 and 4000 cm–1. A custom-made LabVIEW programcontrolled the heating rate of the oven, and the sensor data was acquiredfrom a multimeter (Gw Instek GDM-8342) simultaneously between roomtemperature and 260 °C. Other response time tests were performedon various specimens which were instantly placed in the same ovenas stated above, and before testing, the environment temperature inthe oven was set as 100, 200, 300, and 400 °C, respectively.A vertical flame test was also performed to investigate the responsetime of sensors with various NC content in a simulated real fire scene.The fire from an alcohol burner was applied on the sensor samplesconnected with the multimeter and flash alarm. The additional testsare conducted to evaluate the operating state of the alarm sensorunderwater. The response time was recorded using a camera, and thedata reported in this work were the averages of three experiments.Electrical resistance variation of alarm sensors with different NCcontent was monitored utilizing the two-electrode method, and twoopposite edges of the samples were affixed to copper wires as electrodeswith the help of a copper sheet. The response temperature tests wereperformed using an oven (Carbolite LHT 4/30) that allows wires topass through when heating up to measure the temperature and resistancerelationship at various heating rates such as 2.5 °C, 5 °C,and 7.5 °C min33.1–1, which is not high enough to cast a uniform film.Though graphene is dispersed in the solution, the non-spherical graphenesheets are difficult to flow on the surface of a substrate. As thesolvent used in the mixed solution, ethyl acetate and acetone enjoystrong volatility resulting in graphene and NC particles moving slowlytoward the liquid-coated outer layer by evaporation during the evaporationof the organic solvent. The drop-cast composite membrane sufferedfrom the influence of the coffee ring effect when using the relativelylow concentration of graphene/NC solution because graphene particleshave a large amplitude fluctuation on the air–liquid interfacelayer. As the organic solvent decreases during evaporation, the flowof graphene particles might cause clogging. Therefore, it is necessaryto increase the concentration and viscosity of the graphene dispersionto fabricate a uniform and smooth composite membrane.We employed a facile and time-savingmethod, liquid exfoliation, to prepare the graphene from graphite. 2 carbon atoms arranged in a planar two-dimensionalstructure. The electron distribution has π-orbitals on two sidesof the graphene plane which represent electron densities availableto the molecule. The graphene sheets are negatively charged with asuperb store of electrons. As an electrolyte, sodium chloride is ionizedin water, and the cations (positively charged sodium ions) can coagulatethe negatively charged graphene sheets. Additionally, flocculatedgraphene sheets are coagulated into a solid porous structure witha certain mechanical strength due to the presence of NC. Concentrationof the re-dispersed graphene/NC dispersion is adjustable whereas withits highest concentration can reach 60–70 mg mL–1 (NC included), yet is limited by the viscosity of the whole dispersion.Sodium chloride solution was added here to the dispersion to induceflocculation of the graphene/NC composite. Graphene flakes or particlesconsist of sp3.2–1. As shown in TGA was carried out in an air or nitrogenatmosphere from 30 to 800 °C at a temperature ramp of 10 °CminIn comparison with the pristine NC completely degraded at ∼200°C, the graphene/NC composite demonstrated a downward trend incurve after the first weight drop peak at a similar temperature. Thisdifference indicates that the interaction of graphene and NC altersthe decomposition characteristics of the polymer and prevents or delaysthe complete thermal degradation of NC in the composite at ∼200°C because pristine NC should remain only as gases after thethermal decomposition as shown in the formula above. Meanwhile, anothermass loss in air observed at ∼620 °C is consistent withthe characteristics of graphene decomposition between 550 and 650°C. Compared to the TGA curve shown in A small and sharp peak associated with NC at∼198 °Con the TGA curve for G@NC was found to exist but difficult to observe.As decomposition of NC is not typically carried out under mild conditions,it inevitably generated an obvious gas recoil at the instant momentof deflagration. In contrast, the slight mass gain was not observedin the pristine NC TGA curve, which might be explained by the presenceof graphene that imposed restrictions on the escape of decompositionresidue through physical or chemical interactions of NC and graphene.When the graphene/NC composite was heated to 198 °C, it is mostlikely that NC deflagration gas was trapped between the graphene sheetsand released gradually from the film. Meanwhile, compared to graphene/NCcomposite, pristine NC film did not reflect any mass loss peak whichwas attributed to the absence of the sturdy graphene network membraneto catch the gas released by the instant combustion of NC. When instantaneouslyreleased gases were trapped by graphene, reactive force of the gasrecoil caused the instantaneous mass increase.–1 (D-band)and 1583 cm–1 (G band) analogously. The defect densityin graphene is characterized by the relationship between the defect-relatedpeak (D peak) and the main characteristic peak causedby in-plane vibration of carbon atoms (G peak). Ingeneral, both the ratio of peak height (D/G) and peak area (ID/IG) can estimate the quality of graphene.As D/G and ID/IG ratios increasedafter thermal treatment at 260 °C. Lower ratio generally signifiesthe fewer defects in graphene, which can be attributed to the highsp2-content amorphous carbon produced by the decompositionof NC as mentioned in TGA section before. Meanwhile, compared to theheated samples, the graphene/NC composite, before receiving thermaltreatment, demonstrated an additional peak in the band around 1090cm–1, which is roughly consistent with the typicalNC Raman spectrum peak. In addition, both two types of samples havea defect-induced D′ shoulder peak at around1620 cm–1. Regarding the number of graphene layers,it is apparent that graphene prepared with the current method hasmore than four layers as the G′ peak is smallerthan the G peak. However, the layer number dependson the choice of solution and machine for liquid-phase exfoliation.Raman spectroscopyhas become an ideal analytical technique fordetecting the evolution of defects and quantifying the disorder ofgraphene due to its high structural selectivity and high spectraland spatial resolution. Raman spectra of the graphene/NC compositeafter and before thermal treatment exhibited several prominent peaksinvolving two typical bands at 1351 cm–1 related to nitrate functionality are not measurable. This observationis consistent with the previous literature indicating the characteristicof NC denitration and decomposition at around 200 °C.25 Moreover, several prominent peaks in the rangeof 1300–1600 cm–1, indicating the covalentbonding character as shown in the shaded area in –1, which disappeared after annealingdue to the increase of the resulting molecular symmetry leading toa decline in the vibration intensity, are consistent with the skeletalC–C modes of high sp2-content amorphous carbon.26Although Raman spectroscopy provides an effective analysis of graphene,using FTIR spectroscopy was also necessary to investigate chemicalproperties of graphene/NC composites before and after thermal treatment.Generally, the first stage of NC decomposition is the denitrationprocess. In the annealed graphene/NC composite samples, as NC wasdecomposed, the peaks related to nitrate functional groups lose intensity.Therefore, for thermal treatment below 300 °C, although NC wasnot completely decomposed, the peaks at 1651 and 1267 cm3.3–1 whereas the 10 mg mL–1 sample failed to form a continuous smooth surface due to an inadequatecontent of NC. After thermal treatment, as shown in –1 has been clearly observed, which efficientlyavoided the flake-to-flake overlap. Regarding the drop-cast film of10 mg mL–1 solution, graphene flakes were furtherapart in space, resulting in a sparse network structure that negativelyaffected the efficiency of charge transfer. Therefore, a high concentrationof graphene/NC dispersion  iscrucial for excellent electrical conductivity as well as for the rateof resistance variation, which is of great implication for fire alarmpreparations.Themicrostructure of the composite membrane is expected to impact itsperformance characteristics. Theoretically, a dense, close-connectedgraphene network can exhibit excellent mechanical and electrical performance.The microstructures of the films drop-cast before and after thermaltreatment with different samples of graphene/NC solution are comparedto evaluate the influence of concentrations. Before thermal treatment,as Supporting Information) evidentlyproves that the nitro group disappeared after thermal treatment.The cross sections of the filmdistinctly presented the influenceof NC on the electrical conductivity and basic working mechanism ofthe alarm sensor before and after thermal treatment. Wrapping thegraphene flakes tightly before thermal treatment see 3e and th3.4Supporting Information). Mechanicalproperties of the graphene/NC composite films depend not only on fibrilmodulus but also on orientation and degree of interaction betweenNC and graphene within the film. 3.5The mechanism of temperature response, as shownin 2-content amorphouscarbon according to the peaks shown in FTIR spectroscopy results.In comparison with the pristine NC completely degraded at ∼200°C, the graphene/NC composite demonstrated a downward trend inthe curve after the first weight drop peak at a similar temperature.This difference indicates that the interaction of graphene and NCalters the decomposition characteristics of the polymer and preventsor delays the complete thermal degradation of NC in the compositeat ∼200 °C because pristine NC should remain only as gasesafter the thermal decomposition. This is also the reason why the responsetemperature of the graphene/NC alarm sensor is called “Tunable”.In addition, temperature changes strongly influence the thermal motionin graphene, and the increase in temperature can reduce resistivity.For graphene prepared by liquid-phase exfoliation in this study, multilayergraphene (MLG) has a negative temperature coefficient of resistance(TCR) value due to no electric field intensity existing in the interlayers,which will be discussed later.27 However,the characteristic that graphene resistance decreases with temperaturehas no effect on the working principle of the sensor alarm.The interaction betweengraphene and NC is crucial for studying the detailed mechanism oftemperature response. The bonding between graphene and NC after annealingis likely to be regarded as the covalent bonding character such asskeletal C–C modes of high sp28 Unlike the traditional fire alarm, the graphene/NC temperature alarmsensor meets all the requirements of efficient fire detection: (i)extraordinary rapid response and steady performance, (ii) structuralstability during flame attack, and (iii) early warning signal forabnormally high environmental temperature.An efficient alarm sensor for early-fire warning has to offer analarm signal at high environmental temperature with extremely fastresponse time and maintain structural stability throughout the flameattack. Although most polymeric materials ignite around 300–500°C, the majority of commercial temperature-sensitive fire alarmsonly respond between 60 and 80 °C which is much lower than theignition temperature. This may be explained by the fact that the flametemperature of the combustible materials is much higher than the averagetemperature at each point in the burning space. When a fire breaksout in a compartment, the rise of the hot air flowing results in theformation of a higher temperature layer of hot air above the compartmentwhereas the fire temperature commonly refers to the temperature ofthese hot air layers. In most cases, however, the indoor fire alarmis installed on the ceiling of the compartment, leaving it less functionalas its fire response temperature is much lower than the environmentaltemperature around combustible materials. Prior to detecting the extensivefire and sending the alarm signals, commercial temperature-sensitivefire alarms are not able to initiate early-fire warning in the earlystage of fire as in the growth phase (the first stage) of the idealizedfire temperature curve shown by Milan et al.–1). It should be noted thatbecause the graphene/NC alarm sensors were originally non-conductivebefore being heated, the initial resistance (R0) was set as the maximum measuring range (5.1 × 107 Ω) of the multimeter. As depicted in –1 was indicated as 155, 161, and 167 °Cas shown in –1 heating rate resulting in an increase of ∼6 °C in responsetemperature. Similar trends were also observed in G@NC75 as well asG@NC90 . Considering that the ignitiontemperatures of most combustible polymeric materials range from 300to 500 °C, which is similar to the inner and outer flame temperatureof the alcohol lamp, this test environment can effectively simulatethe applications of the graphene/NC alarm sensor in flame rapid detectionand early warning sensors. Response time is one of the most critical characters in a firewarning device. To evaluate the response time of graphene/NC alarmsensors more accurately and to investigate the impact of ambient temperatureon alarm response quantitatively, direct flame attack and differentenvironmental temperatures of 100, 200, 300, and 400 °C in theoven were employed in this study. To simulate the actual working conditionsduring a flame attack, the alarm sensors with different NC contents were set under the same testing setup as shown in 2 V–1 s–1, respectively.29 TCR of graphene is not identically zero no matterif it is single-layer graphene or MLG. Suspended single-layer graphenehas a small TCR because the dominant electron–electron scatteringis dependent on temperature negligibly.30 However, the MLG utilized in this study has a larger TCR  because no electric field intensity can affect the carriermobility in the interlayer channels.27 Testingunder different environmental temperatures was conducted to observethe TCR of the alarm sensor with various NC content. TCR here is calculatedusing the following equation: –1 within the temperature range of 200–220 °C,indicating that the main pyrolysis process of NC occurs in this temperatureinterval which is similar to the observed results from pure NC TGAtests. The TCR of G@NC60 and G@NC75 decreases to ∼ −2%°C–1 within the temperature range of 240–260°C, which means that the decomposition process of NC and residueapproached to finish in this range. Moreover, the resistance variationof G@NC90 in the range of 220–240 °C is similar to thatof low NC content in the range of 200–220 °C, whereasthe TCR of the same sensor is relatively stable at different heatingrates. This phenomenon may indicate that there is a significant differencebetween the initial temperature at the beginning of pyrolysis of alarmsensors with high NC content and low NC content, but not between thewhole NC thermal decomposition process. However, it still does nothave a huge impact on the sensing mechanism of this temperature alarmsensor.The relationship between temperature and resistance of the graphene/NCalarm sensors is further investigated for standardizing by TCR. Underideal conditions, the theoretical and practical electrical conductivityof graphene is ∼185 000 and 200 000 cmSupporting Information). First, the p-value achieved by two-wayANOVA without replication of NC contents and heating rates is 2.33× 10–5 and 3.60 × 10–3, respectively, indicating that the association between these twofactors and the response temperature was statistically significant.Moreover, the influence of NC content was relatively more effective.Obviously, the goodness of fit is higher than 0.98 at any heatingrate, resulting in a reliable fitting degree and hypothesis accuracy.Therefore, the average value of estimated coefficients (1.8) can affirmthe trend where each 1% increase in NC content leads to ∼1.8°C increase in the response temperature. In addition, the two-wayANOVA with replication method was adopted to analyze the originalresponse time data. The p-value has proven that the effects on responsetime from NC contents and environment temperature are also statisticallysignificant when considering the integrated data .The response temperature of graphene/NC alarm sensorsis tunableby different NC contents within limits. To investigate the relationshipbetween various NC contents and response temperature under differentheating rates, the obtained response temperature data were analyzedutilizing linear fitting, as presented in Figure S6 . It follows then that the alarm sensor canwork stably in other types of extreme environments (outdoor) in theform of paint or wallpaper sending high-temperature alarm signalsto protect people’s lives. The excellent adhesion, mechanicalrobustness, and high flexibility of the graphene/NC film are alsoindispensable for high-performance alarm sensors in the form of wallpaper.It is well known that NC is one of the most versatile adhesives asa standard household cement. Comparison tests were carried out byother authors between annealed graphene/ethyl cellulose (EC) and graphene/NCfilms to investigate the adhesion and mechanical properties of graphene/NCfilms using ultrasonic treatment in water. Compared to the distinctdelamination and breakage of graphene/EC film that occurred within10 s in the ultrasonic bath, the graphene/NC film had negligible delaminationand disintegration for over 1 min. However, the film on polyimidesalso showed even better performance in this test (up to 10 min), indicatingthis difference is based on adhesion at the interface between filmsand substrates. Furthermore, the peeling test was adopted to testthe adhesion performance of the graphene/NC film on a glass slide.A piece of scotch tape was applied to the surface of graphene/NC filmand then peeled at a consistent speed. The graphene/NC film showedexcellent adhesion with glass because no evidence showed that visibleresidue was left on the tape. Compared to similar tests conductedon graphene/EC, which exhibits a noticeable change in graphene pattern.On the other hand, uncertainty and variation of the substrate mayalso affect the operating performance of the graphene/NC alarm sensorwhen it is utilized as wallpaper. However, according to previous studies,different substrates do not significantly affect the TCR of graphene.27 The substrate effect is lessened with the increasingthickness of graphene/NC film resulting in a stable electrical conductivityof graphene in annealed composites. Meanwhile, the evidence of thepersistent alarm signal test and long-term stability test  ensure thestability and flame retardancy of graphene as a wallpaper. For instance,G@NC75 film without a carrier burnt in 1.5 s, whereas it took another0.5 s to burn up thoroughly when carried with the polyimide tape.However, G@NC75 with glass slide maintained its initial shape evenwith small bubble formation on the surface and did not catch firein 10 s. Obviously, the flame retardancy of G@NC was superior whenemployed as wallpaper or coating materials. All types of graphene/NCalarm sensors maintained continuous danger alarm even after the sampleswere removed from a flame or specific temperature environment, demonstratingeffective and stable fire warning that can be applied in various scenariosto detect high fire risk of combustible materials.Because theNC thermal decomposition reacts in instances and requires only heat(where oxygen is an indispensable factor), the alarm sensor is ableto work stably in an oxygen-free or vacuum environment. The TGA resultshave proved that the graphene/NC composite reflects the same workingprocess in a nitrogen environment as in normal ones. The extra testswere conducted to evaluate the operating state of the alarm sensorunderwater. The testing setup and electrical resistance change curveare illustrated in 4In summary, we report a fixed temperature firealarm prepared usingNC and MLG to reliably monitor early-fire risk of combustible materials.The graphene/NC alarm sensor remains in a state of electrical insulationthough instantly turning conductive at high temperatures. Once encounteringa flame attack, NC decomposes rapidly at high temperature and inducesa distinct transition in its electrical resistance, causing the transformationprocess of the alarm sensor from being electrically insulated to anelectron conductive state. Consequently, the LED alarm lamp connectedto the graphene/NC sensor provides an ultrafast alarm response andearly-fire warning signals under flame attacks or abnormal ambienthigh temperatures. The response temperature and time of graphene/NCalarm sensor keep similar upward tendencies as the embedded NC contentincreases. For example, the G@NC90 alarm remained stably insulatedat an ambient temperature of 200 °C, resulting in a satisfactoryresponsive temperature (232 °C), instant response time (4.4 s),and sustained working time in the flame below the ignition temperatureof most combustibles (400 °C). Furthermore, the response temperatureand time of graphene/NC alarm sensor can be tuned by graphene/NC ratiosto reduce fire risk of various combustible materials in differentfire-prone scenarios and thus has promising applications in both indoorand outdoor environments. As the research results show, alarm sensorswith lower NC contents (60 and 75%) reflected lower response temperature(161 and 208 °C) and faster response time, up to 1.6 and 1.9s, respectively. Moreover, the graphene/NC composite film can be processedinto various shapes due to its relatively high mechanical strengthand flexibility. This developed fire alarm also broadens the applicationsof chemical-modified cellulose and graphene composites in temperature-inducedresistance transition sensors with smart responsive behaviors, whichprovides a promising concept for its applications concerning publicsafety in terms of fire risk at high fire risk examinations.


The high demand for pressure devices with miniaturization and a wide bearing range has encouraged researchers to explore new high-performance sensors from different approaches. In this study, a sensitive element based on graphene in-plane compression properties for realizing pressure sensing is experimentally prepared using microelectromechanical systems (MEMS) fabrication technology; it consists of a 50 µm thick, 1400 µm wide square multilayer component membrane and a graphene monolayer with a meander pattern. The prepared sample is extensively characterized and analyzed by using various techniques, including atomic force microscopy, Raman spectroscopy, infrared spectroscopy, X-ray photoelectron spectroscopy, COMSOL finite element method, and density functional theory. The sensing performance of the new pressure sensor based on the sensitive element are obtained by theoretical analysis for electromechanical measurements of the sensitive element before and after low-temperature annealing in atmosphere. Results demonstrate that atmospheric annealing at 300 °C enhances the pressure sensing sensitivity by 4 times compared to pristine graphene without annealing, which benefits from the desorption of hydroxyl groups on the graphene surface during annealing. The sensitivity is comparable and even better than that of previous sensors based on graphene in-plane properties. Our results provide new insights into realizing high-performance MEMS devices based on 2D sensitive materials. Graphene, experimentally discovered in 2004 ,2, is thThe post-treatment process can promote rearrangement of the material lattice and clean up the contaminants on the material surface, which is helpful to further improve the sensing performance of devices. The effects of different post-treatment processes on the properties of graphene have been reported. Plasma treatments on graphene surfaces can reduce polymer residue contamination but result in graphene with a defective graphitic structure . New defA graphene MEMS pressure sensor with a Wheatston bridge circuit formed from several graphene resistances integrated on a chip, with pressure sensing achieved only by the in-plane compressible properties of a graphene monolayer with exceptional properties ,30,31, iA commercial single-crystal silicon wafer was purchased. The silicon wafer was grown following the directions in [110], and its thickness was 0.5 mm. A graphene monolayer coated by polymethyl methacrylate (PMMA) was a trivial transfer graphene from ACS MATERIAL .x), was used as the structural element in this pressure-sensing device. As illustrated in P0 is the pressure inside the cavity, and P is the pressure outside the cavity. When differential pressure is applied, the membrane undergoes deflection and deforms into a concave shape.A schematic of the device is shown in x membrane after etching by O2 plasma. From the top view, only the graphene monolayer resistance has the meander pattern. The graphene resistance is above the cavity and acts as a sensitive element.The technological process for fabricating the device is shown in 2 plasma process.The devices are fabricated using standard techniques. The silicon nitride membrane was deposited on the oxide with a thickness of 200 nm for electrical isolation after the silicon wafer was thermally oxidized. Its thickness was about 100 nm. Cr (50 nm) and Au (250 nm) were evaporated onto the silicon nitride layer for the contact. The electrode patterning was acquired by photolithography and chemical etching. The devices must possess electromechanical sensing ability. To this end, 1400 μm-wide square cavities defined with photoresistance were etched 450.3 μm deep into the silicon layer at the backside of the wafer. A piece of glass was bonded with the wafer’s backside in order to seal gas in the cavities, which can form a pressure difference inside and outside of them. The graphene monolayer was transferred to the abovementioned substrate. The graphene with PMMA was rinsed in deionized water and picked up with the chip. The chip was baked for 20 min at 100 °C to allow the graphene to adhere to the silicon nitride layer and the gold electrodes. The PMMA was then dissolved by acetone and rinsed with ethyl alcohol and deionized water. The chip was then baked again for 10 min at 50 °C to dry the graphene. To image the graphene, its patterning was defined by photolithography and etched using an OIn recent years, the atomic force microscope, Raman spectrometer, infrared spectrometer, and X-ray photoelectron spectrometer have become powerful characterization and metrology tools for solid materials at the nanoscale. They are employed to detect the roughness, number of plies, and functional groups of the graphene and to verify its quality on the chip surface.−1 was used for spectral testing. The photoelectron spectrometer used was an ESCALAB 250Xi . This instrument has an energy resolution of 0.45 eV/(Ag 3d5/2) and a spatial resolution of less than 3 μm.The atomic force microscope used was a Dimension Edge . This microscope has an atomic resolution with a lateral resolution of 0.1 nm and a longitudinal resolution of 0.01 nm. The Raman spectrometer was an inVia . The spectrometer was used to test graphene with a laser wavelength of 532 nm and a laser power of 2.4 mW. The infrared spectrometer was a Frontier . Its spatial resolution was 1.56 μm. A resolution of 4 cmThe atomic force micrograph and the Raman spectrum of the graphene are shown in As shown in A COMSOL finite element method was used to analyze the strain distribution caused by the differential pressure across the cavity membrane. The simulation results were obtained through a process that included setting geometric dimensions, setting materials, selecting solid mechanical-physical fields, fine meshing, researching, and computing. The whole strain distributions on the cavity membrane were simulated when pressure differences of 0.1 and 0.5 MPa were applied to this membrane. The strain data were correspondingly extracted and analyzed when pressure differences from 0.1 MPa to 0.5 MPa were applied to the cavity membrane.c axis. Calculations were performed using a 2 × 2 k-point mesh for the supercell surface and using one mesh point along the c direction.Density functional theory (DFT) was used to calculate the difference of the charge distribution and Fermi velocity of graphene absorbing pollutants in order to illustrate the effects of annealing on the device properties. A primitive graphene cell was constructed using two carbon atoms. In our study, we considered a 6 × 6 × 1 graphene supercell consisting of 36 1 × 1 × 1 unit cells, and one pollutant, such as a hydroxide radical, was placed on the top of the carbon atom. Approximately 25 Å of vacuum was added to the graphene surface in order to separate the repeated cells along the K points in the inverted lattice space of the graphene system using the DFT method.For the difference of the charge distribution, the constructed hydroxy-adsorbed graphene system was optimized to the minimum energy needed to obtain a stable system. For the charge distributions of this system, the graphene retained by removing the hydroxyl group from the system and the hydroxyl group retained by removing the graphene from the system were calculated. The charge distribution of the system was subtracted from the charge distributions of the independent graphene and hydroxyl groups. In this way, the charge changes of the adsorbed hydroxyl graphene relative to the independent, clean graphene are obtained. The Fermi velocity was obtained by calculating the energy band along the path of As shown in G = ΔR/Rε. The gauge factor for graphene was obtained by dividing the relative change in graphene resistance at each pressure by the corresponding mean strain in COMSOL simulation was performed using the details provided in R above the cavity acts as sensitive elements, but the remaining R0 is not above the cavity and remains constant. As shown in V is connected to output electrodes 2 and 4. The voltage output ΔV of the Wheatston bridge can be expressed as Equation (1), where U represents the voltage of the DC source.A new pressure sensor based on the above sensitive element is proposed and presented in −5/kPa, is greater than that of the one without annealing. From the performance comparison among the MEMS pressure sensors in The electromechanical performance of the proposed sensor can be obtained by the combination of electromechanical measurements of only the graphene monolayer resistance as a sensitive element in The pressed courses are shown in Reversible performance of the sensor can be obtained for the device in −1 is observed in the infrared spectra. The spectrum line without annealing has a more prominent bulge than that with annealing. The broad bulge of the spectrum line without annealing is most likely the result of the interaction between the major and minor groups around 1400 cm−1. The sample surface contains water molecules, because the sample was rinsed with deionized water in the process or remained in the air. The hydroxyl radicals absorbed on the graphene surface may be formed by the interaction between water molecules attached to the graphene surface and oxygen molecules in air before annealing [−1 [From the data obtained above, it can be determined that the performance of the sensor undergoing 300 °C annealing is more excellent than that of the one without annealing. The samples are contaminated frequently in the process device fabrication. The pollutants, such as hydrogen ions and hydroxide radicals, may be absorbed on the graphene surface when all types of chemical reagents are applied. nnealing . The watnnealing , which rling [−1 , so the From the above-mentioned experimental results, the sensitivity of annealed graphene is higher than that of unannealed graphene, and the difference between the two sensitivities tends to decrease with the increase in deformation. In accordance with Boltzmann’s theory, this phenomenon can be explained by the relative change in the Fermi velocities of the same material under different deformation conditions. The unannealed graphene, which has a hydroxyl group adsorbed to its surface, has a low initial Fermi velocity. The graphene surface becomes cleaner with hydroxyl desorption, and the cleaner graphene has a higher initial Fermi velocity after annealing. The difference between the initial Fermi velocities of the two graphene systems results in the different levels of sensitivity.A theoretical model using a linearized Boltzmann transport equation can accurately describe the charge carrier density and mobility in the strained graphene and the gauge factor . The chaConsidering the scattering mechanism of the defects, the dependence of the mobility on the Fermi velocity is given by Equation (3).Thus, the resistivity is approximately proportional to the inverse of the squared Fermi velocity :(4)ρe(ε)q is the basic unit of charge. The resistance of a strained graphene can be defined as Equation (5).The resistance is further expressed asTherefore, the relative change in strained graphene resistance is expressed asThe gauge factor can reflect the sensitivity of the graphene material. The gauge factor can be determined using Equation (8).K points in the inverted lattice space of the graphene system using the DFT method. Therefore, every gauge factor in The gauge factor of the graphene system under specific deformation can be obtained by calculating the Fermi velocities for the original and deformed graphene systems. The Fermi velocity to be introduced into the formula is obtained by calculating the energy band along the path of In this study, we used MEMS standard technology to propose a pressure sensor based on the in-plane compressible characteristic of monolayer graphene and thoroughly investigate its performance before and after atmospheric annealing at 300 °C. The performance metrics, including sensitivity, response speed, and linear response range, were markedly improved by atmospheric annealing. Atmospheric annealing at 300 °C enhanced the pressure-sensing sensitivity by 4 times compared with the pristine graphene without annealing, which can be proven by the differential degree of the gauge factors of graphene before and after annealing. The response speed of the annealed sensor to gas pressure was faster than that of the nonannealed sensor. The linear response range of 0–70 kPa is an improvement over those of previous sensors. Simultaneously, the research shows the effective response of the in-plane piezoresistive effect of monolayer graphene to gas pressure, and that the performance of the sensor undergoing 300 °C annealing is more excellent than the one without annealing, which benefits predominantly from the desorption of hydroxyl groups on the graphene surface during annealing. The sensitivity of graphene annealed in atmosphere at 300 °C is higher than that of the unannealed graphene under the conditions of small deformation, but it no longer has a remarkable advantage over that of unannealed graphene under the conditions of large deformation. Our results provide new insights into obtaining high performance of MEMS devices based on 2D sensitive materials.


Besides the consequences of retrotransposition, long interspersed element 1 (L1) retrotransposons can affect the host genome through their antisense promoter. In addition to the sense promoter, the evolutionarily recent L1 retrotransposons, which are present in several thousand copies, also possess an anti-sense promoter that can produce L1 chimeric transcripts (LCT) composed of the L1 5′ UTR followed by the adjacent genomic sequence. The full extent to which LCT expression occurs in a given tissue and whether disruption of the defense mechanisms that normally control L1 retrotransposons affects their expression and function in cancer cells, remain to be established. By using CLIFinder, a dedicated bioinformatics tool, we found that LCT expression was widespread in normal brain and aggressive glioma samples, and that approximately 17% of recent L1 retrotransposons, from the L1PA1 to L1PA7 subfamilies, were involved in their production. Importantly, the transcriptional activities of the L1 antisense promoters and of their host loci were coupled. Accordingly, we detected LCT-producing L1 retrotransposons mainly in transcriptionally active genes and genomic loci. Moreover, changes in the host genomic locus expression level in glioma were associated with a similar change in LCT expression level, regardless of the L1 promoter methylation status. Our findings support a model in which the host genomic locus transcriptional activity is the main driving force of LCT expression. We hypothesize that this model is more applicable when host gene and LCT are transcribed from the same strand. L1 retrotransposons represent ~17% of the human genome  (Long interspersed nuclear element 1 (LINE-1 or L1) is a class of autonomous transposable elements that is mobilized lements) .. insertional mutagenesis, creation of new alternative splicing sites, promoting sequence transduction from the donor to new insertion sites) (Besides the consequences of retrotransposition (e.gn sites) , L1 retrn sites) , but seqn sites) ,6. L1-ASn sites) . Moreoven sites) . Its tran sites) . This suL1-MET LCT initiates in the second intron of the gene encoding the tyrosine protein kinase MET (c-MET)  in various malignancies  . In variunctions . Similargnancies .. absence of weakly expressed transcripts in EST libraries). Therefore, to gain insights into the LCT expression profile in a given tissue and into its relevance to cancer development and progression, we and others developed tools to identify transposable element-derived chimeric transcripts from RNA-seq data. These tools include the LIONS suite (These observations stress that recent L1s (L1PA1 to PA8) with a full length 5′ UTR represent an abundant source of alternative promoters that can disrupt the expression of nearby genes in cancer. This highlight the need to identify LCTs in a systematic manner in the different cancer types. Until now, LCTs have been characterized mainly using bioinformatics approaches. For instance, dbEST has been queried to identify spliced ESTs in which an L1 5′ UTR sequence in antisense orientation is spliced with a gene exon ,14,17,18NS suite , a tool NS suite , and ChiNS suite .IDHwt)   ,25. IDHwls (GSC) ,27.IDHwt gliomas and GSC cell lines to evaluate whether they warrant future investigations as potential players in aggressive glioma biology. We found that LCTs are expressed in healthy brain and that their transcriptional activity/deregulation in glioma follows that of their host locus.In the present study, we used CLIFinder to explore the LCT landscape in IDHwt glioma samples with CLIFinder. As the L1-ASP is active in the more recent subfamilies  data to analyze the whole transcriptome  of three healthy brain and 8 families ,7,19, wefamilies . Althougfamilies . Finallyfamilies , and obsfamilies .. they initiated from one of these two L1-ASP regions). To this aim, we designed a RT-PCR 5′ L1 walking approach using three primers, located at different positions of the L1 5′ UTR, and one LCT-specific primer (LCT-Unique Sequence = LCT-US), located in the unique adjacent sequence, to delineate the area where each chimera initiated (i.e. +200 or +450 in the 5′ UTR or upstream)  .We tested 36 chimeras  in two glioma samples (GS#1 and #2). We could amplify 19 of them using the two primers located in the first 500 bp of the 5′ UTR, but not with the “upstream” primer, for instance chimera 1087 and 179 . This paIDHwt GSC lines (GSC1 and GSC2). By pooling the data of these two samples, we could identify by CLIFinder 226 chimeras that involved L1 elements from the L1PA1 to L1PA7 subfamilies. Then, to determine the proportion of chimeras that corresponded to LCTs, we mapped their TSS along the L1 sequence using a long-read single molecule real-time (SMRT) sequencing dataset generated from three GSC lines . Among the 226 chimeras identified by CLIFinder, 22 were not detected in this dataset. The remaining 204 had at least one TSS within the L1 sequence, including the L1 coding region. Nevertheless, we observed a TSS hotspot within the 900 bp of the L1 5′ UTR  may correspond to LCTs that initiate at the L1-ASP. For the rest of this study, we will consider only L1PA1 to L1PA7 as recent L1 subfamilies.Previous studies based on EST querying showed that among the 8744 recent L1 elements with a 5′ UTR sequence from the L1PA1 to L1PA7 subfamilies, 161 (1.9%) are associated with LCT transcription in various human normal tissue and cancer types and cell lines ,17,18,20IDHwt glioma and normal brain.In conclusion, in normal brain and glioma samples, our approach identified 40% of the 161 L1 elements previously associated with LCT-EST production. It also identified 1444 new recent L1 elements implicated in LCT transcription, thus implicating 17.25% of human L1PA1 to L1PA7 retrotransposons (with a 5′ UTR) in LCT expression in n = 453) was 306 bp, and 77% of them were smaller than 400 bp. As the L1 antisense 5′ UTR contains two donor splicing sites, we evaluated the splicing status of these transcripts by analyzing three parameters: the genomic distance between the L1 side and the unique sequence for each chimera, the total chimera size, and the position of the splice junctions identified by TopHat around the L1 first nucleotide in the 11 samples (The size of the 1509 LCTs ranged from 132 to 45 574 bp. The median size of the LCTs identified by only 1 read ( samples . We foun. long transcript). Therefore, we incubated the same RNA samples with a poly(U) polymerase to add an artificial polyU tail to their 3′ end, before the reverse transcription step performed using an oligodA oligonucleotide. In this case, we could amplify 22 of the 24 LCTs  status. To determine whether LCTs were polyA transcripts, we tested the presence of 24 LCTs, selected among the 31 we previously validated, in cDNA obtained by reverse transcription of total RNA from two glioma samples (GS#1 and #2) with random hexamers or with an oligodT oligonucleotide. We could amplify all 24 LCTs in cDNA obtained with random hexamers, but only 11 in cDNA reverse transcribed with the oligodT primer . The abs 24 LCTs , suggestn = 226 versus n = 36)  . Specifi n = 36) . The 13-IDHwt glioma samples  or genomic distribution  contained only 1 LCT-producing L1, 92 genes contained 2 LCT-producing L1, and 33 genes contained 3–5 LCT-producing L1 retrotransposons. The latter genes were large genes with a size ranging from 0.16 to 2.3 Mb  were intragenic, compared with 31.5% for all recent L1 in the human genome . Surpriso 2.3 Mb . Gene Onmponents . The hosIDHwt glioma samples did not allow assessing the LCT transcriptional status in these two tissue types. Therefore, we first quantified, by RT-PCR, the expression of the 31 validated LCTs in 10 brain control and 41 IDHwt glioma samples. All 31 LCTs were expressed in both control and glioma samples  (g effect size (Hedges’ ES)   . This suges’ ES) . To estacontrols . This alificity) .g values obtained for the 1509 LCTs predicted that 244 (16.2%) and 88 (5.8%) of them were down- and up-regulated, respectively, in IDHwt glioma versus control samples   . Note thAltogether, these observations indicated that most LCTs are not glioma-specific. They suggested that most LCTs are produced in healthy brain and also aggressive glioma, and that ~20% of them shows tumor-specific down- or up-regulation.L1-MET LCT in cancer cell lines   . HoweverIDHwt samples. IDHwt samples are characterized by chromosome 7 gain and chromosome 10 loss  in the genomic loci of the 31 validated LCTs in 3 controls and 19  10 loss . Accordiectively . Howeverectively .Combined, these observations indicated that aberrant DNA methylation and genome CNV might contribute, but are not the main cause of LCT deregulation in glioma samples.IDHwt glioma samples tend to localize in genes with brain functions suggests that the L1-ASP activity of recent L1 could be influenced by the host locus transcriptional activity, as observed for the sense promoter (n = 433 genes/485 L1) and of genes hosting one or several recent L1 not associated with LCT production (n = 969 genes/1332 L1) (n = 3) and IDHwt glioma (n = 8) samples indicated that the expression level of genes containing LCT-producing L1 retrotransposons was significantly higher  . Compariy higher . This way higher , and alsy higher . Thus, i. H3K36me3) compared with those of recent L1 elements not associated with LCT production  in 9 controls and 39  samples . Six gen samples . Moreove samples . UnivariIDHwt glioma samples. The gene expression in tumor and control samples was similar to that of their associated LCTs  of genes associated with the 64 and 120 intragenic LCTs predicted to be up- and down-regulated in gliomas, respectively, in controls and ted LCTs . Genes aThis suggests that LCT down- and up-regulation in glioma imply a similar transcriptional deregulation of the relevant host locus.n = 1509) of recent L1 retrotransposons are involved in their production. It also revealed that these events are not tumor-specific, because LCT transcription occurred also in healthy brain, as previously shown in normal colon  gene (IDHwt) . This study was approved by the relevant ethics committees and competent authorities, and the study protocols follow the World Medical Association Declaration of Helsinki. Written informed consents were provided by all patients. Samples were isolated as previously described ,35. In t (IDHwt) .n = 8) and frontal cortex (n = 7), correspond to white matter enriched in astrocytes and oligodendrocytes, and are relevant non-cancer controls for gliomas. Before use, tumor and control samples were homogenized by cryogenic grinding, and each sample was aliquoted in at least three vials for genomic DNA, RNA and chromatin extraction. All samples were stored at −80°C until use.Ten control brain samples  were obtained from the Brain and Tissue Bank of Maryland . These samples, identified by the Brain and Tissue Bank of Maryland as corpus callosum  derived from patients with cterized .The coordinates of L1 elements were obtained from the RepeatMasker database deposited in the UCSC Table Browser. Recent L1 elements were selected based on their RepName . This list was then filtered using repLeft and repStart <400 and repEnd >600 to retain only L1 elements with an ASP. The final list is in n = 3 brain control, n = 8 IDHwt, and n = 2 GSC samples: GSC-1 and GSC-2) and also polyA mRNA from the GSC-6 and GSC-2 samples .. not annotated by Repeat Masker) of ≥30 bp.The associated 3′ end read sequence should contain at least one unique sequence .In the 11 RNA-seq datasets, CLIFinder identified 1677 chimeras associated with the L1 subfamilies L1PA1 to L1PA8 . Among t(30) 3′ SMART CDS Primer II A was replaced by the oligodA(30) 3′ SMART CDS Primer II A. The obtained full-length cDNA (1:10 dilution) was then amplified by PCR (14 cycles) using GXL PrimeSTAR DNA polymerase (Takara) in 20 PCR reactions. PCR products were purified and concentrated (in 21 μl) with two rounds of 1× AMPurePB beads (PacBio) treatment. cDNA size fractionation was then performed on 0.75% agarose gels (without ethidium bromide) to individualize three cDNA fractions: [0.3–2 kb], [2–5 kb] and [>5 kb]. Dedicated biotinylated riboprobes, designed against the 5′ 400 bp sequences of the 8744 recent L1 , were used to perform three independent captures of each cDNA fraction according to the supplier’s recommendations (except for the addition of Block C solution = human Cot-1 DNA). Captured cDNAs were then amplified by PCR using Prime StarGXL DNA polymerase (Takara) with 10, 12 and 14 cycles respectively for the <2, 2–5 and >5 kb cDNA fractions. PCR products were pooled and purified using 0.55× AMPurePB beads (PacBio). The three samples were pooled together and handled for SMRTbell template preparation and sequencing . The obtained sequences were treated as follows: (1) consensus sequence establishment using the Iso-seq3 CCS algorithm; (2) selection of the full-length cDNA sequences including the SMARter IIA adapter at both their 3′ and 5′ ends using the Iso-seq3 LIMA tool; (3) trimming of the polyT tail at the 3′ end of each sequence  and finally (4) alignment of the obtained sequences to the hg19 reference human genome using the minimap2 aligner. Only good quality (MapQ ≥ 30) aligned reads were retained in a SAM file . The genomic coordinates of PacBio read alignments were extracted using the bamtobed tools from the bedtools suite V2.30.0 and the SAM file. Using the GenomicRanges R library, these coordinates were filtered to keep only reads that overlapped with the 226 L1-producing LCTs identified by CLIFinder in GSC Illumina RNA-seq (GSC1 & GSC2) data. Only PacBio reads with potential LCT characteristics were selected: reads containing a 5′ sequence antisense to one of the 226 L1 and a unique genome sequence at its 3′ end. To identify the TSS of the PacBio reads within the L1s, the starting position of each read was repositioned using the L1 coordinates as reference. These data were used to determine the number of L1 that were associated with a PacBio read that initiated in the ASP region or the 5′ UTR of the L1 (i.e. position 0–500 and 0–900 of a L1). To visualize the TSS position of all reads inside each of the 226 L1 elements, the 5′ initiation position of all reads was considered to compute the percentage of reads that initiated along each L1.To sequence full-length polyA and non-polyA LCT transcripts, a modified Iso-seq protocol (PacBio) was used. For each sample, 3 μg of total RNA was poly-uridinylated using a polyU polymerase (New England Biolabs) following the manufacturer’s recommendations. After poly-uridinylated (polyU) RNA purification with the RNeasy kit (Qiagen) and ethanol precipitation, two reverse transcription reactions were performed (each with 1 μg of polyU RNA) using the SMARTer Kit (Takara) in which the oligodTIDHwt glioma samples were used to determine the normalized gene expression (fpkm), as previously described  and 3 controls and 19 escribed . To detehttps://www.ncbi.nlm.nih.gov/geo/) under the following accession numbers: GSE123892 for the stranded total RNA-seq of control samples and IDHwt gliomas; GSE161438 for the stranded total RNA-seq of GSCs; GSM4907328 and GSM180209 for the stranded polyA RNA-seq of GSCs; GSE190930 for the PacBio sequencing of GSCs; and GSE123682 and GSE161275 for the Cytoscan HD data.Data are available at the NCBI Gene Expression Omnibus  were designed for the 36 chimeras selected according to their detection by CLIFinder using high or low reads number, they tumor-specificity or not, and their localization (intragenic or intergenic). This primer was combined with a L1 common primer . Due to sequence homology, a common primer could be designed for the L1PA1 to L1PA7 subfamilies and a specific L1 common primer for the L1PA8 subfamily. Then, chimera detection was validated by RT-PCR using RNA from two glioma samples (GS#1 and #2) already used for RNA-seq. Briefly, 1 μg of total RNA was treated with DNase I (Promega) according to the manufacturer’s recommendations, and then reverse transcribed using Random Hexamers (Invitrogen) and the SuperScript III Reverse Transcriptase Kit (Invitrogen). After dilution (1:5), 2 μl of cDNA solution was used for PCR amplification with the relevant LCT specific primer, LCT-US and L1 common primers. Primer sequences, PCR conditions, and PCR product amplification size are given in The LCT-Unique Sequence (LCT-US) primers  from two glioma samples was used for these experiments. Additional L1 primers, downstream and upstream of the L1-ASP +450 location, were designed using the Primer3 software. Due to the high sequence homology displayed by the 5′ UTR sequence of the L1PA1 to L1PA6 subfamilies, the same L1 downstream and upstream primers were used for chimeras associated with L1 elements from these six subfamilies. However, as some mismatches could impair PCR amplification (when too numerous or when occurring at the 3′ end of the primer), three different L1 downstream primers (PA1 to PA6) were designed and alternatively used. Specific L1 downstream and upstream primers were designed for the L1PA7 and L1PA8 subfamilies. Primer sequences, mismatch number between L1 primer/L1 sequence, and PCR product amplification sizes and results are given in Three parameters were taken into account to identify splicing events in chimeras: (1) the distance between the start position of the unique sequence and the end position of the L1 sequence of each chimera after alignment (R1–R2 distance). A negative or null distance indicates an overlap or a juxtaposition of both sequences, and implies that these chimeras have been identified in multiple reads (either in one or different samples). A distance between 1 and 200 bp is concordant with the size selection made during the library construction (i.e. 280–340 bp) and often relevant of chimeras identified in few reads in all samples. A distance >500 bp may suggest at least one splicing event between the L1 and unique sequence; (2) the LCT size. Chimeras with a size >1000 bp, even if their R1–R2 distance is negative, can present evidences of splicing event(s), because the unique sequence is very large (>700 bp) due to concatenation of multiple reads by CLIFinder; (3) the occurrence of splice junctions identified by TopHat in the RNA-seq data in the ±200 bp region around the L1 start position. One of these parameters was considered sufficient to conclude that a LCT was spliced. LCT with R1-R2 distance between 200 and 499 bp and a size between 600 and 999 bp were considered to have an undetermined spliced status.m oligod(T)n primer (Invitrogen) to specifically target polyA mRNA transcripts. Then, 2 μl of diluted (1:10) cDNA was used for PCR amplification using the LCT-US and L1 common primers.Total RNA from the glioma samples GS#1 and GS#2 was treated with DNase I and reverse transcribed with SuperScript III using 2.5 μm UTP, 1X Buffer and 40 U RNase inhibitor. The resulting poly-uridinylated RNA was purified on RNeasy columns (Qiagen), concentrated after ethanol precipitation, and 1 μg of PolyU-RNA was reverse transcribed using 0.6 μm of oligod(A)n primer (Eurogentec) and Superscript III (Invitrogen). Then, 2 μl of diluted (1:10) cDNAs was PCR amplified with the LCT-US and L1 common primers.Alternatively, 3 μg of total RNA was treated with DNase I and then with 2 U of PolyU polymerase in the presence of 0.5 mR = (ETOI–CtTOI)/(geometric mean EHK—CtHK) with E = PCR efficiency of each primer pair, TOI = Transcript Of Interest (i.e. chimera or gene to be quantified), and HK = housekeeping genes  used to normalize transcript expression. For each sample, experiments were done in duplicate using the two independent RT reactions.500 ng of total RNA was treated with DNase I (Promega) and divided in two independent aliquots (250 ng RNA/each) for reverse transcription using a random hexamer primer (Invitrogen). Then, first strand cDNA was pre-amplified (14 cycles) with the pool of primers used for the microfluidic PCR assays. Primer sequences and qPCR Efficiency (E) are given in P-values were adjusted with the Bonferroni correction. Correlation analyses between intragenic LCT and the associated gene expression levels were performed using Spearman’s correlation.Differences in the expression levels of the LCT or associated gene between tumor and control samples were assessed with the one-way ANOVA and post-hoc Mann–Whitney test, if applicable. Significant L1 positions and classifications were retrieved from the CLIFinder output. Based on these coordinates, chromatin analyses were done with the computeMatrix scale-regions tools from the deeptools suite (Version 3.1.3)  and chromatin data coverages extracted from GeoDataset in WIG format . These WIG files were converted into binary format with the wigToBigWig program from the UCSC server, to be compatible with the computeMatrix program prerequisites. Chromatin profiles surrounding the L1 start and end positions (±1 kb) that corresponded to the mean chromatin coverage over the set of genomic regions were generated using the compute Matrix output and R program.HhaI or HpaII) and methylation-dependent (e.g. McrBC) restriction enzymes. DNA was extracted from frozen samples (21 IDHwt glioma and 7 control brain samples) using the QIAamp DNA Mini Kit (Qiagen) according to the manufacturer’s recommendations. For each DNA sample, four 200 ng DNA aliquots were prepared. Three were incubated with 5 U of HhaI, HpaII, or McrBC (NEB) at 37°C for 2 h. The fourth aliquot was incubated only with buffer (negative control). The published qAMP protocol was slightly modified by adding a restriction enzyme inactivation step by incubation with proteinase K (0.4 mg/μl) at 40°C for 30 min, followed by its inactivation at 95°C for 10 min. The obtained PCR templates were 8-fold diluted in water and stored at −20°C. PCR primers covered approximately the first 300 bp of each L1 promoter in which the restriction sites for each of the three enzymes used are present. L1 primers were designed using the Primer 3 software and combined to the already described LCT US primer. Additionally, primers for control regions with different DNA methylation levels were designed: (1) a control region that does not contain restriction sites for the three enzymes; (2) the promoter of the imprinted gene PEG10 that is hemi-methylated and (3) the GAPDH promoter region that in our samples, has a methylation level <10%. All primers used for the qAMP experiments are given in SssI enzyme (NEB). These two DNA templates were mixed to obtain a standard curve with theoretical DNA methylation levels of 0, 30, 70 and 100%. The efficiency of each primer pair was evaluated using 3 log10 gDNA concentrations. Only primer pairs with an efficiency ≥1.85 and a standard curve corresponding to the expected theoretical DNA methylation percentages were retained. The DNA methylation index of each sample was then evaluated by qAMP on a LightCyclerR©480II (Roche). Four μl of each DNA  was mixed with 1× SYBR Green Master Mix (Roche) and 0.5 μm forward and reverse primers in a final volume of 10 μl. The PCR program was: 95°C for 5 min, and then 40 cycles , and 72°C for 5 min. The DNA methylation index of each sample was calculated using the amplification data obtained for the three DNA samples digested with the restriction enzymes and as previously described using the ∆Ct values (Ct enzyme—Ct sham)  . DifferePinson_et_al_Supp_Fig_ddac056Click here for additional data file.Pinson_et_al_Table_S1_ddac056Click here for additional data file.Pinson_et_al_Table_S2_ddac056Click here for additional data file.Pinson_et_al_Table_S3_ddac056Click here for additional data file.


Electronic devices based on two-dimensional semiconductors suffer from limited electrical stability because charge carriers originating from the semiconductors interact with defects in the surrounding insulators. In field-effect transistors, the resulting trapped charges can lead to large hysteresis and device drifts, particularly when common amorphous gate oxides (such as silicon or hafnium dioxide) are used, hindering stable circuit operation. Here, we show that device stability in graphene-based field-effect transistors with amorphous gate oxides can be improved by Fermi-level tuning. We deliberately tune the Fermi level of the channel to maximize the energy distance between the charge carriers in the channel and the defect bands in the amorphous aluminium gate oxide. Charge trapping is highly sensitive to the energetic alignment of the Fermi level of the channel with the defect band in the insulator, and thus, our approach minimizes the amount of electrically active border traps without the need to reduce the total number of traps in the insulator. The stability of graphene-based field-effect transistors with amorphous aluminium oxide serving as the top-gate oxide can be improved by tuning the Fermilevel of the two-dimensional channel material such that it maximizes the energy distance between the charge carriers in the channel and the defect bands in the gate oxide. In contrast to silicon, 2D semiconductors retain sizable mobilities at atomic layer thicknesses below 1 nm, a thickness that also helps to suppress short-channel effects in FETs and thus allows for physical channel lengths below 5 nm (ref. 2). Furthermore, the integration of 2D materials in van der Waals heterostructures provides design options for energy-efficient transistors that can overcome the limitations of thermal charge-carrier injection. In addition, 2D materials are of potential use in a broad range of applications, including photonics and optoelectronics3, neuromorphic computing4, nanoelectromechanical systems5, and gas and biological sensors6.Two-dimensional (2D) semiconductors are a potential channel material for ultimately scaled field-effect transistors (FETs)7. In addition, there is a lack of suitable gate insulators8 that can ensure high interface quality, scalability9 and a minimum of electrically active border traps, the presence of which in the insulator close to the channel limits device stability. These two challenges are major obstacles for the industrial applications of 2D-based nanoelectronics and, being independent from each other, need to be separately addressed. There has been recent progress regarding the formation of low-barrier contacts for 2D semiconductors using contact gating10 or semimetallic bismuth contacts to achieve ultralow contact resistances11. However, the need to find a suitable insulator with a minimum number of electrically active traps remains. Stability studies of 2D FETs typically show a stability that is at least two orders of magnitude worse13 compared with silicon-based FETs15.There is, however, currently a lack of low-resistive contacts to 2D semiconductors, which minimize the prevalent Schottky barriers16 and stability of threshold voltage under prolonged periods of applied elevated gate biases and temperatures (bias temperature instability (BTI))14. Charge trapping inside the gate oxide has been identified as the root cause of BTI17. At elevated gate biases and temperatures, charges are transferred between the channel and gate oxide in a phonon-mediated transition18, with charging time constants spanning a wide range, from picoseconds to years19. Border traps in the gate oxide close to the channel determine the long-term stability and reliability of silicon FETs15, whereas in 2D-material-based FETs, they typically limit device stability on much shorter timescales20.Measurements of FET stability typically evaluate the hysteresis in the transfer characteristics18. In the first approximation, the energy levels of defects follow a normal distribution around the average defect levels, forming defect bands21. Consequently, the overall density of border traps and the widths of the corresponding defect bands can be considerably reduced by using crystalline insulators, such as hexagonal boron nitride (hBN) or calcium fluoride8 (CaF2). However, these insulators are difficult to synthesize and have several technological challenges. For example, current state-of-the-art crystalline hBN can be grown only at temperatures above 1,200 °C (ref. 22) and CaF2 requires a crystalline silicon(111) substrate for growth, allowing only back-gated configurations23. In addition, hBN is unsuitable for use as a scaled gate insulator because of its small dielectric constant9.In amorphous oxides, the defect trap levels vary due to the differing surroundings of every instance of atomic defectsEF) of the 2D channel material such that it maximizes the energy distance between the charge carriers in the channel and the defect bands in the gate insulator during device operation. This can be achieved via a careful selection of the 2D material and amorphous gate oxide, as well as by doping the 2D layer to shift EF away from the defect bands in the gate insulator. Graphene FETs (GFETs) with aluminium oxide (Al2O3) as the top-gate oxide are measured and compared, where one of the device batches uses a p-doped graphene layer. The GFET batch where EF is tuned away from the Al2O3 defect band edge shows reduced hysteresis and BTI. We further verify the approach with technology computer-aided design (TCAD) simulations24. In addition, double-gated GFETs are fabricated, where the back gate is used to directly tune the Fermi level in the graphene monolayer via electrostatic doping. This shows that the stability observed for top-gate operation strongly depends on the location of EF. Our approach aims to design a metal–oxide–semiconductor (MOS) system with a minimal amount of electrically active border traps without the need to reduce the total number of traps in the insulator.In this Article, we show that the stability and reliability of 2D-material-based FETs with amorphous gate oxides can be improved by tuning the Fermi level (2O3 (oxide) and graphene (semiconductor). The corresponding band diagram of a cut through the MOS stack , HfO2 (refs. 31) and Al2O3 (ref. 28) insulators. Besides the location of the defect bands, another essential property of insulator traps is their extremely broad distribution of time constants, ranging from the picoseconds regime up to years19. As these insulator traps lead to noise, hysteresis and drifts, it is important to thoroughly characterize both traps’ time constants and their energetic location within the defect bands.The energetic position of defect bands in amorphous oxides is an intrinsic material property2O3, we can predict the electrical stability of the threshold voltage in these FETs. In Fig. 33. This graphene layer’s EF lies in the middle of the Al2O3 defect band. Due to this alignment within the defect band, charge traps in the oxide capture and frequently emit charges. As the applied gate voltage modifies the charging probabilities of the defects according to the electric field19, VTH depends on the biasing history and a pronounced hysteresis is visible. In addition, VTH drifts considerably during prolonged periods of applied gate biases.Based on the band alignment of the graphene work function to the defect bands in AlEF down by p doping the graphene layer. Here the EF value of graphene of 5.1 eV can be achieved through p doping34. As the graphene Fermi level is located below the Al2O3 defect band, charge transfer is unlikely. Therefore, the oxide defects are electrically inactive, resulting in stable VTH throughout device operation, independent of the applied biases. In graphene, doping with different adsorbates and substrates results in a quasi-continuous variation in the Fermi level between 3.4 and 5.1 eV (refs. 36), which can be used to tune the Fermi level during device design to minimize the impact of oxide defect bands.However, the theoretical considerations of Fig. 2 FET with HfO2 top-gate oxide. If the Fermi level is aligned close to the conduction band, electrons within WS2 are the majority charge carriers dominating the current flow in Schottky-barrier FETs7. As the conduction band edge of WS2 is aligned with the electron-trapping defect band of HfO2, charge transfer to oxide defects is frequent. If WS2 was p doped instead of n doped, holes at the valence band edge would be the majority , WS2/SiO2 (ref. 39) or graphene/SiO2 (ref. 40). This evidence suggests that there might be a loss of charge neutrality at the ill-defined interfaces between van der Waals–bonded 2D layers and amorphous oxides, causing deviations from the Schottky–Mott rule25. These deviations result in offsets to the band alignments that can be determined, for example, with internal photoemission measurements41 or scanning probe techniques42. Although these offsets would need to be taken into account for optimum matching of the Fermi level at a maximum distance to the oxide defect bands, they are neglected for the proof-of-concept study presented here.It is worth noting that several studies have reported high densities of fixed charges at the interfaces of 2D materials with amorphous oxides, for example, MoS43. However, fixed charges at the interfaces would also degrade the mobility in the semiconducting 2D channel25. This could be avoided by using more complex gate stacks with electric dipoles at the interfaces between different oxides. Such a dipole engineering approach has been successfully used to improve the reliability of silicon FETs with an HfO2/SiO2 gate stack44.At the same time, the intentional placement of charges at the interface could be used to shift the band edges away from the oxide defect bands using, for example, surface charge transfer dopingECB. For simulations, we used the previously developed drift-diffusion-based TCAD methodology45 coupled to a non-radiative multiphonon model18 (Supplementary Section 2 with a back-gate oxide of SiO2 (ref. 45). We evaluated the hysteresis width at VTH, defined here as the voltage where the Fermi level is located –0.05 eV below the conduction band edge . Thus, we would expect that n-type WS2 FETs with an HfO2 gate oxide are more stable when using bulk WS2 as a channel compared with thinner WS2 layers. In cases where an ultimately thin monolayer channel is required, electrically stable FETs could be designed by choosing a different combination of 2D semiconductor and insulator. For example, increased electrical stability is predicted for BP/HfO2 FETs and for ZrSe2/Al2O3 FETs . Independently, graphene, with its continuous tunability of EF over an interval of nearly 2 eV, provides the largest design freedom. Due to the possibility to tune the Fermi level in graphene by a few 100 meV through moderate doping, we chose graphene/Al2O3 as a model system to experimentally verify our stability-based design approach.It should be noted that for narrower defect bands, the improvement accessible by tuning the semiconductor band edges is much larger. For example, we repeated the calculations shown in Fig. 48. In the first two batches, graphene monolayers form a channel with an area of W × L = 100 μm × 160 μm on top of mechanically flexible polyimide (PI) substrates49  process and layer transfer. Type 1 graphene exhibits a work function that results in a small distance of EF to the Al2O3 trap band  and transfer (ID–VG) characteristics are shown for a representative Type 1 GFET 34. Pristine graphene has a work function of 4.56 eV (ref. 50), which is shifted towards higher values by p doping34 and towards smaller values by n doping35. To calculate the Fermi-level location in the two graphene types, we obtain the charge-carrier concentration (n) based on the analytic expression for n in the MOS capacitor51. At a top-gate bias of 0 V, we extract the charge-carrier concentration (n) caused by the intrinsic doping of graphene samplesCtot is given by the capacitance of Al2O3 (Cox) in series with the capacitance of 0.5 nm van der Waals gap (CvdW) and the quantum capacitance of graphene52 (Cq), amounting to Ctot = 0.16 μF cm−2. This expression gives a p-doping density for Type 1 graphene of n1 = 5.5 × 1010 cm−2 and for Type 2 graphene of n2 = 2.8 × 1012 cm−2. Thus, Type 2 graphene is more p doped by an additional doping density of approximately 2.75 × 1012 cm−2. These hole densities in the graphene layers at 0 V gate voltage determine the work function via42νF = 1.1 × 106 m s−1 (ref. 53). Consequently, we obtain EW1 of Type 1 graphene to be 4.6 eV and EW2 of Type 2 graphene to be 4.8 eV, that is 0.2 eV higher  of Al2O3, which determines the location of the conduction band edge, varies in the literature. Here we use 1.96 eV, as obtained from internal photoemission measurements41. For all the measurement ranges used in our work, we only probe the lower part of a potentially wider defect band further up, as reported using other methods55. This is illustrated in Fig. 55. For Type 1 graphene, EF is aligned within the defect band  Fig. , whereasle) Fig. . Below, VH as a function of the inverse sweep time (tSW), namely, the sweep frequency (f = 1/tSW). In Fig. VH than Type 1 devices, which is linked to the increased variability of VDirac on Type 2  curves after biasing the devices at a static VBG. Subsequently, the top-gate hysteresis was measured at different sweep rates. In Fig. VBG. It is expected that hysteresis can be reduced for high negative back-gate voltages, as the work function of the graphene channel is the highest at 4.3 eV for a higher negative VBG ..ID (VTG)VH over different measurement rounds on two double-gated GFETs, namely, D1 and D2  after static elevated gate voltages  were applied for varying charging times (tcharging). We record the magnitude of the initial ΔVDirac shift and monitor the recovery after the increased gate-biasing period with fast ID (VG) sweeps at logarithmically spaced recovery times. In Fig. ID (VG) sweeps recorded during the recovery from negative gate biasing (negative-bias temperature instability (NBTI)) at –10 V are shown. Such BTI measurements give a complementary perspective on the long-term stability and reliability of FETs compared with the hysteresis measurements discussed earlier. Although during hysteresis measurements, GFETs are subjected to slow up and down gate-voltage sweeps, during a BTI measurement, an elevated gate bias is applied for a certain charging time and the recovery of the Dirac point is recorded. With this well-established measurement scheme, the impact of border traps is studied15. Thus, in a BTI measurement, the observed hysteresis during the probing sweeps is small and not in focus. To avoid measurement artefacts coming from fast traps causing the hysteresis in the probing ID (VG) curves, the down-sweep ID (VG) curves are used to evaluate the VDirac shifts for all NBTI measurements and the up-sweep ID (VG) curves for positive gate biasing (positive-bias temperature instability (PBTI))  sweeps used for the BTI evaluation of Type 2 GFETs  sweeps measured after a positive bias at 10 V are shown, together with the corresponding recovery traces for Type 1 GFETs , have a smaller hysteresis and increased stability of their Dirac voltage when subject to prolonged elevated gate biases. Furthermore, by electrostatic doping of the graphene channel via a back gate, the hysteresis width can be reduced by a factor of up to 4.5. These results suggest that more stable and reliable 2D-material-based FETs using common amorphous gate oxides can be built by minimizing the impact of defect bands in the gate oxides during design.We have reported an approach to improve the electrical stability of FETs based on 2D materials. Charge trapping at the border traps in amorphous oxides is the principal cause of the threshold-voltage drifts and reduced long-term stability in 2D FETs. Therefore, the impact of defect bands in amorphous gate oxides can be reduced by tuning the energy alignment of the Fermi level. We demonstrate our approach using GFETs with Al8. However, future studies will be necessary to clarify what levels of stability can be achieved by Fermi-level tuning in systems based on amorphous oxides and crystalline insulators. In addition, the stability-based design approach relies on prior knowledge about the energy location of the defect bands in the oxide, which at the moment is incomplete.In 2D semiconductors, the design options mainly consist of choosing suitable materials depending on n or p doping, or varying the thickness of the channel material. There is more design freedom with graphene, as the graphene Fermi level can be tuned over a range of up to 2 eV. Moreover, our approach to improve stability may be universally applicable to other insulators, such as crystalline insulators, where the impact of narrow insulator-defect bands can be reduced further than in amorphous oxides59; for Type 2 GFETs, the transfer was performed by vendor 2. The Type 1 graphene flake covered an area of 2 × 2 cm2 and was of higher quality than the Type 2 flake (which covered a six-inch wafer). The different qualities of the graphene layer were confirmed by Raman spectroscopy  of 160 μm and width (W) of 100 μm. In the next step, the source and drain contacts were deposited by sputtering 50 nm Ni, followed by a lift-off process. This step was followed by growing 40 nm Al2O3 with atomic layer deposition (ALD) on top of the devices to form the gate oxide in a top-gated configuration. To finalize the GFETs, the top-gate electrode was fabricated by sputtering 10 nm Ti and 150 nm Al and patterned in a lift-off process. To be able to contact the source and drain pads, vias were opened through the Al2O3 with a wet-buffered oxide etchant. For our double-gated GFETs, we transferred CVD graphene monolayers from vendor 1 using a PMMA-assisted wet transfer method59 to a 90 nm SiO2 on a Si wafer. Subsequently, the graphene layer was patterned in an oxygen-plasma etch step to form channels of L = 80 μm and W = 50 μm and the source and drain contacts were deposited by sputtering 50 nm Ni followed by a lift-off process. After this step, the gate oxide of 40 nm Al2O3 was grown using ALD and the top-gate electrode was deposited with a sputter process.Our top-gated GFETs were fabricated on spin-coated PI substrates using photolithography. First, the flexible substrate was prepared by spin coating PI in the liquid form on a Si wafer and subsequently curing the layer. The thickness of the solidified PI film was about 8 μm. During the fabrication process, a rigid Si substrate was used as a support layer. In the next step, a CVD-grown graphene layer was transferred to the PI substrate. We study two batches of GFETs where the channel is formed by graphene samples purchased from different vendors, namely, vendor 1 (Type 1) and vendor 2 (Type 2). For Type 1 devices, CVD graphene was transferred from the copper growth substrate using a polymethyl methacrylate (PMMA)-assisted wet transfer method2 V−1 s−1 for Type 1 graphene and 1,000 cm2 V−1 s−1 for Type 2 graphene. The Hall mobility of both the samples was found to be slightly higher. The hysteresis was analysed by measuring the double-sweep ID–VG characteristics using different sweep times tSW and sweep ranges of VH was extracted as the difference between the forward- and reverse-sweep VDirac value. As suggested in our previous work20, we expressed the hysteresis dynamics using ΔVH (1/tSW) traces. Finally, the BTI degradation/recovery dynamics were analysed using subsequent degradation/recovery rounds with either fixed stress time tdeg and increasing high-voltage levels VG,high, or fixed VG,high and increasing tdeg. During the recovery period, we applied a constant recovery voltage of VG,recovery = 1 V between the sweeps. This voltage is chosen to be close to the charge-carrier equilibrium at VDirac. To avoid artefacts from fast traps charged during the sweep, the down-sweep ID–VG curve is used to monitor the recovery of NBTI13. The characteristics obtained when using up-sweeps to measure the NBTI recovery are shown in Extended Data Fig. 13; thus, we used ID–VG sweeps from negative to positive voltages for the evaluation of PBTI. As was suggested in our previous study on GFETs13, we expressed the BTI degradation magnitude using a Dirac-point voltage shift ΔVDirac and plotted it versus the relaxation time tr. To gain more statistics, all our measurements were repeated on several devices.Our electrical measurements were performed in a vacuum at room temperature and in complete darkness. The devices were examined with the PI supported on a silicon wafer. From two-probe measurements, we extracted the field-effect mobility of the GFETs and found it to be 4,000 cmSupplementary InformationSupplementary Sections 1–12, Figs. 1–3 and Table 1.