Currently, integrated humidity sensors with fast-response time are widely needed. The most commonly used polyimide capacitive humidity sensor has a long response time, which is difficult to meet the need for a fast response. Most studies focusing on technology and materials have a high cost and are difficult to ensure compatability with the CMOS process. The dynamic compensation method can shorten the response time by only adding digital circuits or software processing. However, conventional compensation technology is not suitable for humidity sensors due to temperature coupling. This paper proposes a new dynamic compensation method for humidity sensors based on the decoupling of temperature factors by analyzing the coupling relationship between sensor dynamic characteristics and temperature. Simulations and experiments were used to verify the proposed method. The experimental results show that the proposed method reduces the humidity response time of the sensor by 85.6%. The proposed method can effectively shorten the response time of humidity sensors. The integrated sensors, which include sensing front-end circuits, an analog-to-digital converter, and a digital processing part, are developed rapidly due to their low cost, small size, and ease of use. Humidity sensors are widely used in many applications, such as environmental monitoring , process control , medical equipment, and biotechnology ,2,3,4,5.There are two methods to achieve a fast-response humidity sensor. One way to improve the response speed is to increase the contact area between the probe and the air using specific process technologies, such as new moisture-sensitive materials, ultra-thin moisture-sensitive films, special moisture-sensitive probe structures, and surface treatment of the moisture-sensitive layer ,14,15,16The other way to improve the response time is to compensate the sensor output dynamically. Dynamic distortions are compensated by digitally processing the sensor output, and results can be obtained as close as possible to the actual measurement values ,18,19,20This paper aims to solve the effect of temperature coupling on humidity sensors and improve the response time with a dynamic compensation method. A dynamic compensation algorithm is proposed based on temperature and humidity decoupling by modeling and analyzing the coupling effect of temperature on sensing humidity. After decoupling, the sensor system is transformed into a linearly time-invariant system, and the dynamic compensation is realized. The rest of this study is organized as follows. First, First, the humidity-sensing process is analyzed. The media and structures of capacitive humidity sensors are various. This paper studies a common type of sensor as an example. As shown in i.Medium is homogeneous. A polyimide probe is a uniformly isotropic porous medium with the same porosity. The change in diffusivity is consistent with temperature. Gases, including water vapor in the medium, are ideal gases that do not react with the polyimide medium. Ignoring the diffusion resistance of the film surface, the water vapor concentration at the contact position between the medium and the air is uniform and the same as those in the ambient air.ii.The temperature is uniform. In polyimide probes, the diffusion equations for temperature transfer and water molecule transfer take the same form. However, the thermal diffusivity in polyimide and silicon wafers is much greater than the water molecule diffusivity in polyimide. As shown in iii.Signal processing time can be ignored. This is because the time required for signal amplification and digitization of the probe is milliseconds.In order to catch the main factors affecting the dynamic characteristics of a sensor, the following assumptions are made:As shown in The integrated humidity sensor is calibrated so that the sensor readings correspond to the correct water molecule concentration in the probe. Therefore, the concentration of water molecules in the probe corresponds linearly to the sensor readings in Process B. Process A, in which atmospheric water molecules diffuse into the probe medium, is the main process affecting the dynamic properties of the humidity sensor.Nin is the concentration of water molecules in the air, RHin is the percentage of ambient relative humidity, ρv(T) is the density of saturated vapor at temperature T, which varies with T, and M is the molar mass of water. The curve of ρv(T), as a function of temperature, is shown in RHin changes with ρv(T) even if Nin is constant, i.e., RHin itself is coupled with temperature.The relationship between the concentration of water molecules in the air and the humidity is given by Equation (1):Nin diffuses into the polyimide layer of the probe. This diffusion of water molecules can be described according to Fick’s law as follows:t is the diffusion time, N is the concentration of water molecules in the polyimide probe, N = N, and De is the effective diffusion coefficient of water molecules diffusing through the polyimide. The boundaries of the polyimide medium can be divided into two parts. One boundary (airS) is in contact with the air (Boundary 1 in closeS) is the boundary where no exchange of water molecules occurs  can be written as follows:N is the concentration of water molecules in the polyimide probe when t = 0. Process A is a definite solution problem consisting of the diffusion Equation (2) and boundary conditions Equations (3) to (5). The coupling effect of temperature on humidity sensing is found to be mainly in two aspects:i.RHin is affected by both temperature and Nin.According to Equation (1), ii.De is affected by temperature, the diffusion Equation (2) is coupled with temperature. The relationship between De and temperature is written as follows [Since  follows :The change in T0 is the reference temperature, and De0 is the diffusion coefficient at the reference temperature.The above two coupling influences are present in most humidity sensors. The first influence is suitable for humidity sensors measuring relative humidity. The second influence is suitable for most humidity sensors because even though different humidity sensors convert humidity into different physical quantities, most sensors measure humidity depending on the concentration of water molecules in the moisture-sensitive material. For water molecules diffusing through different moisture-sensing materials, only the relationship between diffusion coefficient and temperature differs from Equation (6).N changes the probe’s dielectric constant, leading to a change in the probe’s capacitance. The capacitance of the probe can be obtained from the empirical formula for the relationship between dielectric constant change, water molecule concentration, and the electrostatic field equation [εPI* is the relative permittivity for the mixture of polyimide and water, εPI is the relative permittivity for pure polyimide, and εH2O is the relative permittivity for water.Process A determines the water molecule concentration distribution in the PI membrane, since water molecules are polarized in an electric field, a change in water molecule concentration equation . The aboD and the electric field strength E can be obtained through the electrostatic field equation:ρf is the surface density of free charge, which is 0 inside the PI film. From the above results, we can integrate the entire domain Ω to find the electrostatic energy W carried by the capacitor:The concentration distribution of water molecules in the PI film determines the dielectric constant distribution of the capacitive medium of the probe. After determining the boundary conditions of the electric field , the electric displacement vectors U is the potential difference between the electrodes.So far, we can find the capacitance value:We tested the capacitance value of the capacitance probe samples we designed and tape-out under different temperatures and humidity. It can be seen from The temperature and humidity characteristic curve must be calibrated before the temperature and humidity sensor leaves the factory. The probe capacitance hardly changes with the temperature, which greatly reduces the calibration cost of the humidity sensor. The calibrated temperature and humidity sensor ensures the accuracy of the output results in the steady state and also calibrates the measurement deviation caused by the nonlinearity of the PI dielectric constant or the influence of temperature in Process B. Therefore, the dynamic characteristics of a well-calibrated humidity sensor are negligibly affected by the factors in Process B.s(z−1) and Σc(z−1), respectively. The dynamic characteristics of the sensor Σs(z−1) can be compensated using a series compensation filter Σc(z−1). The parameters of Σc(z−1) can be obtained by parameter identification from the experimental data in,exu and out,exy during the off-line stage. The specific solution method is explained in the next section.The conventional dynamic compensation method for an LTI system is introduced in this section firstly. The compensation process is shown in Suppose that the compensation filter transfer function is as follows:The output compensation series is as follows:k − n ≤ 0 occurs when compensating for the first few samples, so we need the given pre-measurement data. In this case, the sensor is in a steady state before the measurement, i.e., when k − n ≤ 0.The case of s(z−1). However, there are cases where the inverse system Σs−1 (z−1) does not exist or causes divergence in compensation results. In this case, an optimal approximation of the inverse system Σs−1 (z−1) can be obtained by the least-squares method or particle swarm optimization to ensure convergence of the compensation system.The purpose of solving the compensation system is to obtain the parameter of the compensation filter. The most direct way to solve the compensation filter is to find the inverse system of the sensor system Σc(z−1), an offline experiment is performed. In the experiment, a controlled input series inu,ex(k) and the output series out,exy(k) of the sensor are obtained as the apriori information for the parameter identification. The aim of the parameter identification is to make the compensated series inxC(k) most approximate to the input series inu,ex(k).In order to identify the parameters of Σc(z−1), the order of Σc(z−1), or n in (15), must first be determined. After comparing the residuals of models of different orders, the appropriate model order can be judged. Once the model order is determined, the difference equation for the transfer characteristics of the digital compensation filter can be expressed as follows:Considering the feasibility of the experimental design and the accuracy of the compensation, the step-change condition of the external environmental humidity is adopted in our experiment. To identify the parameters of ΣJcd(z−1) = 1 + d1z−1 + … + ndz−n, and Σcc(z−1) = 0c + 1cz−1 + … + ncz−n. In this paper, particle swarm optimization is used to solve the optimal approximation of Σc(z−1).Our goal is to find the optimal solution for the digital compensation filter parameters to minimize the following objective function cd(z−1) and Σcc(z−1) for a humidity sensor only corresponds to a single temperature. Namely, every temperature needs a new series of compensation parameters. Therefore, the conventional method is not suitable for humidity sensors.It should be noted that due to the temperature influence on the humidity sensor output, the solution of ΣA new dynamic compensation method based on temperature and humidity decoupling is proposed in this section. To eliminate the influence of temperature coupling factors, two decoupling procedures are designed to ensure an effective compensation when the temperature changes. De is introduced. These two decoupling procedures will be introduced in two subsections of this section. The low-pass filters are added to the compensation process to reduce the high-frequency noise amplified by dynamic compensation.The temperature decoupling of RH is performed before the compensation filter. The parameters of the compensation filter are also obtained from an offline experiment. During the experiment, temperature decoupling of outRH(k) can be converted into the water molecule concentration output outN(k) by Equation (1). After the compensation is completed, the compensated results inNC(k) are restored to the relative humidity result inRHC(k). As described in Tensors, and the temperature used during RH recovery is the ambient air temperature airT. Because Tensors is usually delayed from actual ambient air temperature, airT is obtained by dynamic compensation of Tensors using the conventional method described in It should be emphasized that the temperature used during RH decoupling is the temperature measurement results of the sensor, eD. It can be seen that temperature affects the diffusing process of water molecules through De in Equation (2). The method of decoupling the temperature factor of De is to use variable substitution so that an equivalent diffusing process is not affected by temperature.After the temperature decoupling of RH, it is only necessary to focus on the diffusion coefficient T0 is the reference temperature. Then, the following relationship is obtainedVariable substitution:Substitute (21) into the diffusion Equation (2) to obtaint with t*, Equation (22) is not affected by temperature, i.e., the sensor system with time t* (regarded as Σs*(s)) has the same parameters as the system with time t at the temperature T0 (regarded as Σs0(s)). The meaning of the variable substitution is to make the time change rate of t* proportional to eD so that the diffusion Equation (22) with time t* is not affected by temperature. In the following discussion, t* refers to the time after substitution.After replacing time t* domain is temperature independent, the sensor system Σs*(s) can be compensated by a method similar to the conventional technology. However, since the sampling of Σs*(s) in the t* domain is unequally spaced, the parameters of compensation filter Σc* are not constant. The compensation filter system is regarded as Σc*. As shown in De works during the offline experiment to obtain the variable compensation parameters. Because the diffusing process of a humidity sensor in the s*(s) and Σs0(s) discussed earlier is for a continuous system. When time t is replaced by t*, the temperature factor is decoupled, but the compensation filter system Σc* must be solved at t* to compensate the sensor. It is important to note that when t* replaces t, the sampling points correspond one-to-one, and the sampled sensor systems Σs* and Σs are identical. Therefore, Σc* can be used to compensate the sensor system Σs with time t.The relationship between the sensor systems Σc* can be obtained by the compensation system Σc0(z−1) at a constant temperature. Σc0(z−1) can be solved by the conventional method. The process of solving Σc* from Σc0(z−1) is shown in s0(s) and Σc0(s) are the continuous sensor and compensation systems at time t and temperature T0. Σs*(s) and Σc*(s) are the continuous sensor and compensation systems at time *t. It should be noted that Σs0(s) and Σs*(s) have the same mathematical form. Σc* can be sampled by Σc*(s), and Σc0(s) can be recurrenced from Σc0(z−1). k represents the change in the transfer function of the system over time. inN(t), outN(t), and inNC(t) are the environmental input, sensor output, and compensation signals of water molecule concentration, respectively. The required compensation system Σc* from Σc0(z−1). Suppose the identified Σc0(z−1) as follows:Now we specifically solve Σc*, the temperature T(t*) at each moment must be given continuously. Therefore, the temperature at each moment must be estimated. For simplicity, we assume that the temperature between two samples is equal to the temperature measured in the previous sample, which is expressed as follows:Information is lost during the sampling, and the state of the system at each moment cannot be known. To solve ΣT(1) as time t = 0, the sampled t*(k) can be obtained from Equation (20) as follows:Considering t* and t into T(t) to obtain T(t*).Substitute the relationship between The sampling time is related to:We need to solve the following transfer function of the non-uniform sampling compensation system.c0(z−1) and Σc* are as follows:x(k) is the state variable. A, B, C, and D are the state-space model parameters obtained from the transfer function parameter in Equation (23). We aim to solve the parameters An, Bn, C, and D in Σc*.In the subsequent analysis, the state-space model of the system is used. The state-space models corresponding to the transfer functions Σt domain and t* domain are as follows.The temperature and humidity output by the sensor between the two sampling points is assumed to be constant with the results of the previous sampling point. The compensation system is an LTI system with constant inputs between the two sampling points. The state transition matrix (STM) can represent the system state change between the two sampling points. The STMs at the s0(s) and Σs*(s) are identical in physics, the corresponding Σc0(s) and Σc*(s) have the same parameters, and Φτ is equal to Φτ*.Since Στ = Δt and *τ = Δt*(k) into Equations (30) and (31), respectively. The following relationships are obtained.Substitute Φ0 can be obtained from the parameters of the state-space model in Equation (28).Φk* and Φ0 is as follows:The relationship between Thenc* in Equation (27) can be obtained from Ak, Bk, C, and D.The parameters of the system ΣThe finite element method is used to simulate the operating process of the humidity sensor, and the software used for the simulation is COMSOL Multiphysics. The dynamic output results of the humidity sensor under different temperatures and humidity are obtained and compensated by the dynamic compensation methods. Finally, the compensation results are compared with the given environmental humidity changes. To verify the effectiveness of the proposed dynamic compensation method, it is compared with the conventional method .The simulation uses a polyimide humidity sensor in N in the probe changes over time as the air humidity changes (increases) stepwise.The simulation equations and boundary conditions for the diffusion of water molecules in the probe use the definite solutions given by Equations (2) to (5). For simplicity, the sensor temperature is considered to be the same as the ambient temperature in the simulation. After the water molecule concentration distribution is obtained, the dielectric constant distribution in the probe can be obtained from Equations (7) to (10), and the capacitance value of the probe can be obtained through Equations (11) to (14). In the actual sensor, the humidity output is obtained through signal processing and digital calibration of the capacitance change of the probe. In the simulation, we realize the function by mapping the capacitance and temperature to the humidity. This function is obtained by interpolating the capacitance value of each temperature and humidity point in a steady state. c0(z−1) are as follows:The first verification is carried out when the temperature is constant, and the humidity changes. Two humidity change forms are considered. One is a step change, and the other is a sinusoidal change. The results are shown in t63.2%, that is, the time when the output response reaches 63.2% of the input response Δ. The response time of the sensor system in c0(z−1) are the same as Equation (37).The second verification is carried out when temperature and humidity change at the same time. Four kinds of changes are considered, i.e., simultaneous step change of temperature and humidity, temperature and humidity staggered step change, sinusoidal temperature change and humidity step change, and temperature and humidity both sinusoidal change. The results are shown in To verify the effectiveness of the proposed method, an experimental platform is set up, as shown in c01(z−1). c02(z−1). The results are shown in The parameters of the compensation filter in the experimental verification are as follows:It can be seen in The dynamic compensation model proposed above is actually the condition that the recovery and response time are the same. Under this condition, the response and recovery process has the same transfer function, and the transfer function of the response process can be used to dynamically compensate the humidity sensor. However, due to the force between the moisture-sensing medium and water molecules, the response time and recovery time of some humidity sensors are not the same, especially for some fast-response humidity sensors, which use this effect to achieve rapid moisture absorption. If the proposed dynamic compensation method is to be used to compensate for this kind of humidity sensor, the process of moisture absorption and dehumidification needs to use two compensation filters with different parameters , and it is also necessary to It is judged whether it is currently hygroscopic or dehumidified. The judgment method can select the faster one of response time and recovery time then use its corresponding compensation filter to compensate and see if the compensation result is higher or lower than the current humidity value to judge whether the compensation filter currently used is correct. If not correct, another compensation filter is used. The reason for choosing the faster one for the response and recovery time is that when we compensate for the faster process with another compensation filter (which amplifies the high-frequency noise more strongly), it creates a situation where the compensation result diverges. Unfortunately, our current research work has not been able to verify the dynamic compensation method when the response time and recovery time are different, so this part of the content is put in the discussion.The long-term stability of the humidity sensor is a key factor affecting its measurement accuracy, but its research is mainly in steady-state measurement. Long-term drift also affects dynamic characteristics. For example, if the sensor is stored in a high-humidity environment for a long time, it will not be able to return to a dry state, and the influence of this phenomenon can be basically eliminated by heating. However, the influence of different external conditions on the long-term stability of dynamic characteristics, the extent to which this long-term drift is irreversible, and whether it affects the correctness of dynamic compensation results, etc., require further research.This paper proposed a new dynamic compensation method for humidity sensors based on the decoupling of temperature and humidity by analyzing the coupling relationship between humidity and temperature in capacitive humidity sensors. The proposed method was verified by simulation and experiments. The experiment results show that the response time in the experiment is reduced by 85.6%. This method effectively reduces the deviation caused by the temperature coupling factor compared with the conventional method. The proposed method can still remain accurate when the traditional method can not compensate correctly. The proposed method can be applied to various humidity sensors whose capacitance and resistance change due to the diffusion of water molecules, or to gas sensors that detect the diffusion of gas molecules, simply by adding digital circuits to existing sensors or performing digital processing on a host computer. Therefore, the proposed method can also be easily applied to existing temperature and humidity sensors. For the most commonly used polyimide capacitive integrated humidity sensors, the sensor response time can be reduced to the level required in areas such as respiratory monitoring.


Here, we found that soluble graphite produced by mechanochemical reaction with salts overcomes the above three drawbacks. Soluble graphite was exfoliated into monolayer graphene with more than 10% yield in five minutes of sonication. The modified graphite was easily exfoliated in a low-boiling point solvent such as acetone, alcohol and water without the aid of a surfactant. Molecular simulation revealed that the salt is adsorbed to the active carbon at the graphite edge. In the case of weak acid salts, the original bonding nature between the alkali ion and the base molecule is retained after the reaction. Thus, alkali metals are easily dissociated in a polar solvent, leading to negative charge of graphene, enabling the exfoliation of graphite in low boiling point solvents. The approach proposed here opens up a new door to practical usage of the attractive 2D material.Developing a mass production method for graphene is essential for practical usage of this remarkable material. Direct exfoliation of graphite in a liquid is a promising approach for production of high quality graphene. However, this technique has three huge obstacles to be solved; limitation of solvent, low yield and low quality ( The salts adsorbed at the graphite edge facilitate the exfoliation of graphite in liquid. Bottom-up approaches like chemical vapor deposition can fabricate large-area high-quality graphene, but the productivity is usually at the milligram-scale and it is not likely to become a mainstream mass production technique.7 Thus, a top-down approach—i.e., exfoliation of graphite—is the only feasible method to produce graphene at the ton scale.Graphene has received enormous attention in the field of microelectronics and composite materials. A wide range of applications such as high-sensitivity sensors, thin film transistors, transparent conductive films, and anti-corrosion coatings have been proposed up to now.8 Of course, this method requires considerable labor and is not appropriate for mass production. It is well known that several atomic or molecular species can be chemically inserted between graphene layers of the host graphite, a process known as intercalation. Graphite intercalation compounds (GICs) can be produced by means of anodic or chemical oxidation; in general, 0.11 wt. equiv. of potassium permanganate (KMnO4) is added into concentrated sulfuric acid (98%) to covert 1 wt. equiv. of graphite to stage 1 GICs.9 Expanded graphite is produced by intercalation of a strong acid following gasification of the intercalant.10–12 After that, the expanded graphite is exfoliated to produce multi-layer graphene (>10 layers). This method is the simplest and its feasibility for mass production has already been established. However, there are no repulsive forces between the platelets in dry powder form , only attractive van der Waals forces. This results in agglomeration of the multi-layer graphene platelets that are difficult to disperse due to their large face-to-face contact area. When 6 wt. equiv. of KMnO4 is added during the intercalation process, the GIC is converted to graphene oxide, from which graphene can be obtained by reduction.13,14 This route tends to generate high material and processing costs. In addition, the defects that are induced in the basal plane of graphene during oxidation are not able to be fully recovered by the reduction process. Thus, in the present state, it is very challenging to develop a low-cost production route to graphene with high quality via graphene oxide.Graphene was first produced by mechanical cleavage using scotch tape to literally peel off layers from natural graphite.15 Although high quality graphene can be obtained by this method, electrical connectivity to the graphite feed materials must be maintained during the entire process, and if contact is broken the graphene yield dramatically decreases. Furthermore, the high quality stock graphite materials that are required—such as rods, foil or highly oriented pyrolytic slabs—lead to high material cost. It was proposed that there is a fundamental need to re-engineer this method so that the electrochemical driving force can be applied to graphite materials more efficiently and effectively.16With respect to electrochemical exfoliation, either cathodic or anodic potentials drive guest ions into graphene layers of the host graphite, which leads to expansion of graphite flakes. Gasification of the intercalated species then facilitates the exfoliation of the expanded graphite.17 Shear mixing is the simplest LPE method in terms of equipment and it is scalable,18 so it has strong potential for encouraging the commercialization of non-oxide graphene. To achieve good exfoliation and dispersion performance with LPE, it is imperative to choose a compatible solvent—meaning its surface tension is close to that of graphene (the surface energy is ∼68 mJ m−2), such that the enthalpy of mixing is minimized.17,19,20 Although the LPE method holds promise for the mass production of non-oxide graphene, it faces three issues that must be overcome before widespread practical application can be realized.Graphene cannot be stored in dry powder form, as mentioned above; in a liquid, however, repulsive forces such as steric and electrical repulsion are available to stabilize the graphene dispersion. A method known as liquid-phase exfoliation (LPE) was introduced in 2008, in which graphite is subjected to sonication or shear mixing in a liquid to produce few-layer graphene.N-methyl-2-pyrrolidone (NMP) and dimethylformamide (DMF) are commonly acknowledged as the most appropriate solvents, because the surface tension of these solvents matches that of most nanocarbons.17,18 However, drawbacks such as a high boiling point make it difficult to prepare these dispersions for subsequent processing such as ink jet printing or coating, and toxicity is also a concern for human health. For example, a typical solvent exchange process involves switching the exfoliated graphene from NMP to chloroform or alcohol;1,2 however, the filtration of well-dispersed graphene is time-consuming, creating a bottleneck that impedes so-called “one pot” synthesis strategies and ultimately slows down the industrial usage of graphite exfoliated via LPE.The most serious one is the limited selection of compatible solvents: i.e., large lateral size with a small thickness) is ideal.21,22 The average layer number (N) and aspect ratio of exfoliated graphene are usually between 3 and 7 and 50 and 100, respectively.18 If we separate monolayer graphene with a higher aspect ratio from few-layer graphene (FLG) with a lower aspect ratio in terms of their material properties used in engineering design, it is clear that a variable mixture of monolayer/FLG (polydispersity) would add difficulty to the design and manufacture of the final product. Thus, efficient production of graphene with uniform dimensions is ideal.The second problem is polydispersity of the thickness and a low aspect ratio. To make effective use of graphene's phenomenal properties in applications such as high-performance polymeric nanocomposites, a high aspect ratio . Graphene yield using microfluidization was reportedly 10 times higher than that using high-power probe sonication.25 Karagiannidis et al. produced conductive printable graphene inks with a 100% exfoliation yield .27 Although it appears that the low yield of graphene by LPE might be drastically improved by microfluidization, the exfoliation degree  of graphene by this method is usually insufficient; 96% of flakes fall in the 4–70 nm thickness range.27 Moreover, as mentioned above, the limitation of compatible solvents such as NMP and DMF systems is still the critical issue, and these facts restrict the potential of the microfluidization method and thus the application of exfoliated graphene.Recently, microfluidization was proposed by several authors as an alternative to shear mixing or sonication.Until now, there was no single method that could address all three of the above drawbacks. In this paper, we present a new modified graphite that undergoes exfoliation in low boiling point solvents to monolayer graphene, with a total yield of more than 10%. Carbon radicals induced by fragmentation of graphite in a ball milling process react with some selected salt molecules . This mevia ball milling has been widely investigated.28–35 Baek's group found that edge-functionalized graphene nanoplatelets could be prepared by dry ball milling in the presence of hydrogen, carbon dioxide, or sulfur trioxide which acts as an electrocatalyst for the oxygen reduction reaction.28,29 Salt such as sodium chloride or sodium sulfate is added to facilitate the delamination of graphite.30,31 However, the crystal size of graphene gradually decreases because of the fragmentation caused by the impact of the balls, making it difficult to maintain a layered structure after a long milling time (>48 h). Because so many defects are introduced if ball milling continues for long durations, the milled graphite tends to become very fine with an amorphous structure, rather than crystalline graphene.36,37 To avoid this problem, a protective agent such as naphthalene, pyrene, melamine, or ammonia gas is introduced during ball milling.32–35 Although these additives help produce high-quality FLG, the thickness is usually not uniform and the milled powder can only be dispersed in NMP, DMF, or a water/surfactant solution.Planetary ball milling is conducted to induce the mechanochemical reaction of graphite with salts. The approach to produce graphene A of the dispersion at 660 nm was measured with a spectrophotometer. The concentration of graphene C in the liquid was calculated using the Lambert–Beer law A = αcl where l is the light path length, c is the graphene concentration, and α is the absorption coefficient. The absorption coefficient was 3300 L g−1 m−1.The yield of graphene (C/Ci) was calculated by dividing the output graphene concentration by the initial graphite concentration (Ci = 3 g L−1).In our process, we added weak acid salts such as potassium carbonate or sodium acetate to modify the graphite structure. The milling time, quantity of salt, and type of salt all have dominant effects on the solubility and quality of the resultant graphite; hence we carefully investigated these parameters. The functionalization process is extremely simple. The mixture of graphite and salt was milled for an arbitrary amount of time, and then the mixture was washed several times until the pH of water became neutral. The filtered cake was dried at 60 °C overnight, and then ground in a mortar to obtain soluble graphite powder. To assess the quality of the powder, Raman and XRD analyses, as well as SEM observation, were conducted. In order to investigate the solubility of graphite, 0.3 g of the produced graphite was added into 100 ml of isopropanol and sonicated for 5 min, after which the dispersion was centrifuged at 1500 rpm for 30 min to remove unexfoliated flakes. An optical absorbance ID/IG values were scattered, depending on the laser position in this characterization. Therefore, we measured Raman spectra of at least 5 spots , and the average ID/IG was obtained. This method is often used to characterize the defect or size of graphene, which has a smaller diameter than the laser spot.18 The spectra are normalized by the intensity of the G band (∼1590 cm−1). The D peak (∼1350 cm−1) and D′ peak (∼1620 cm−1), which indicate graphite defects, increased with the increasing time. The type of defects that appear in graphene—sp3 defects, vacancy-like defects, and edge defects—can be distinguished by the intensity ratio of the D and D′ peaks.38 A low ID/ID′ value of approximately 2.1 was calculated for all the milled samples, indicating that only edge defects are introduced during the ball milling process rather than basal plane defects  and short sonication time. Although exfoliation was conducted in an incompatible solvent, the yield of graphene reached 25% when we used the salt-modified graphite after milling for 30 min. The yield increased to 60% when 2 h of salt-assisted ball milling was applied, but beyond 2 h the graphene yield decreased with increasing milling time—presumably due to the structural changes described above.ID/IG value of milled powder gradually decreased with the increasing salt content  salts like sodium acetate, potassium sodium tartrate, and potassium carbonate improve the yield of graphene 700 times more than milling without salt  showed low yield (<0.03%), which points to the important role of the cation in the mechanochemical reaction and dispersion mechanisms. Salts including alkali metals  improve graphene yield, whereas copper carbonate and copper phosphate have no effect on solubility of exfoliated graphene  Fig. S2. It shout Fig. S3 indicati Table S1. The rea Table S1. Cationsd-spacing of milled graphite calculated from the peak position of the (002) reflection was 0.3358–0.3364 nm, which is almost the same d-spacing d-spacing slightly increased after ball milling because the graphene structure changed from regular stacked layers to turbostratic. This value is lower than the d-spacing of reduced graphene oxide (0.356) or electrochemically exfoliated graphene (0.348).39,40 This implies that there is no intercalant and no functional group on the basal planes of graphene, which is consistent with the results of Raman analysis (defects are introduced only at the edge). The intensity of the 002 peak gradually decreased as ball milling progressed. The crystallite thickness Lc can be obtained from the full-with at half-maximum (FWHM) of the 002 profile, and the crystallite size La is determined from a 110 profile of carbon , but not to few-layer graphene (N < 10). In the case of powder treated by 12 h of milling, the Lc value could not be determined correctly because the 002 peak was asymmetric and small. The graphite structure became amorphous after 12 h of milling, with La = 23 nm; this might make it difficult to maintain the layered structure, leading to a spherical agglomeration .After the milled graphite strongly aggregates into spherical agglomerations after being washed and dried due to the relative strength of van der Waals forces, the size decreases with the increasing milling time Fig. S4. Powder n Fig. S5.41 The c Fig. S4d. These e−) appears around 1720 cm−1  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O groups increased from 2% to 9% , Fourier transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS) were performed. Based on the elemental analysis of EPMA, the potassium content and oxygen content almost linearly increased with milling time. These elements gradually decreased with increasing washing time but could not be removed completely after more than five times. There are no functional groups on the graphene basal plane; thus it is reasonable to consider that the potassium carbonate adsorbs only along the edge of graphite during salt-assisted ball milling. In the FT-IR results, the characteristic peak for carboxylate . To check the solubility of graphite, the modified graphite with salt was added to various solvents and then mixed with 5 min of sonication followed by 30 min of centrifugation. As shown in −1 in THF when the initial concentration of milled powder was 3 mg ml−1. This means the yield of graphene reaches 20% after only 5 min of sonication. The graphene concentration in acetone was 0.32 mg ml−1, indicating a 10% yield. Preparing concentrated graphene dispersions with these solvents is typically regarded as impossible because of the significant difference in surface tensions between the solvents and graphite. In fact, the graphene concentration was 0.0005 mg ml−1 in acetone when we use milled graphite without salt  showed the same general trend as the milled graphite without salt, with a peak around 40 mN m−1 followed by a gradual decrease. However, the soluble graphite showed higher yield values compared to the non-functionalized graphite for the entire range of surface tension values. This indicates that the surface characteristics of graphene did not vary after salt-assisted ball milling, which is consistent with the Raman and XRD analysis .The surface tension of the solvent can be varied by controlling the water/alcohol content. The cosolvent approach is often applied to find the best surface tension of the solvent for exfoliation of layered materials. For milled graphite without salt, the best surface tension was confirmed to be around 40 mN m−1 , which iFollowing from the results of ε of the liquid has a dominant effect on the stability of the dispersion.43 If the dielectric constant ε is sufficiently large (ε > 5), some electrolyte dissociation does occur which generates an electrostatic repulsion force strong enough to stabilize the dispersion. However, if ε < 5 then negligible dissociation occurs and the electrical double layers are extended, making it difficult to obtain an electrostatically stable dispersion system. These phenomena explain why the soluble graphite could not be exfoliated in hexane (ε = 1.9) or toluene (ε = 2.3). These solvents are categorized as non-polar solvents, so an electrical repulsion force is not expected.In the case of electrical repulsion, the dielectric constant −1) after 2 h of sonication, which is the highest value obtained for the LPE process. In the case of pure IPA, a yield of 20% was obtained after 10 min of sonication. It was reported that it took 300 h to obtain a dispersion of few-layer graphene with a yield of 15% when natural graphite was used.35 The yield of graphene in IPA gradually decreased after more than 10 min of sonication; the reason for this phenomenon is not clear, but possibly aging of IPA might occur during sonication.44The effect of sonication time on the yield of graphene was also investigated . The yie18 We measured the thickness of over 200 graphene nanoplatelets, and none with a thickness above 0.8 nm could be found. Thus, we assumed that nanosheets dispersed in the solvent were monolayer graphene. The proportion of monolayers was 100%. Few-layer graphene was not observed in this study, which is unusual because the centrifugation conditions were mild  and few-layer graphene is usually obtained under these conditions. We presume that the repulsive force generated by negative charge further contributes to exfoliation during sonication. The average length of graphene was 366 nm for the IPA/water cosolvent and 227 nm for the IPA solution  was 0.01% for pyrene-assisted milled graphite and 1.03% for melamine-assisted milled graphite, whereas the yield of salt-assisted milled graphite exceeds 3.0%  and a rectangular graphene fragment with three sides terminated by hydrogen by using DMol3,45,46 in Materials Studio with the DNP+ basis set and the meta-GGA functional SCAN47 in density functional theory. After structural optimization, we found that a –CO2, –SO2, or –NO2 base is adsorbed on top of one edge carbon atom in a “Y”-shape perpendicular to the graphene plane  is much lower than that of strong acid salts (yellow region). Additionally, the Hirshfeld charge of the Y-shaped base is much more negative for weak acid salts  than for strong acid salts . This difference is clearly due to the difference between the base atoms  of the Y-shaped adsorbent; a –CO2 base is more negatively charged than a –SO2 or –NO2 base. This means that the original bonding nature between the alkali ion and the base molecule is retained in the case of weak acid salts, but the alkali atom ion is more strongly bonded to the graphene edge in the case of strong acid salts  with just a few minutes of sonication. The process requires only common chemicals such as carbonate and acetate, which are cheap and environmentally friendly. Moreover, the process is simple (milling and washing) and scalable; thus the new mechanochemical route proposed here will be a key technology for mass production and effective usage of attractive nanomaterials.We have found a new mechanochemical reaction for the production of high-quality soluble graphene, whereby the activated carbon radicals induced by fragmentation react with organic salts in a pathway for edge-functionalization. In general, salt is used to precipitate a stable colloid by weakening the electrical repulsion of the colloid d = 500 mm) was used for modification by planetary ball milling . In most cases, seven steel balls with a diameter of 20 mm were placed in an 80 ml container. The rotation speed was controlled at 500 rpm. The milled powder was washed several times until the water pH became neutral. The washed samples were dried overnight and were ground in a mortar to obtain fine powder. Typically, 0.3 g of the powder was added into 100 ml of a solvent and probe-sonication  was conducted to exfoliate the powder. The obtained dispersion was poured into a 50 ml centrifugation tube. The dispersion was centrifuged  at 1500 rpm for 30 min. The top half of the dispersion was carefully extracted using a pipette and stored for use. The characterization methods are all described in detail in the ESI.†Natural graphite (Sigma-Aldrich, There are no conflicts to declare.NA-001-C9NA00463G-s001


The current development of clean and high efficiency energy sources such as solar or wind energy sources has to be supported by the design and fabrication of energy storage systems. Electrochemical capacitors (or supercapacitors (SCs)) are promising devices for energy storage thanks to their highly efficient power management and possible small size. However, in comparison to commercial batteries, SCs do not have very high energy densities that significantly limit their applications. The value of energy density directly depends on the capacitance of full SCs and their cell voltage. Thus, an increase of SCs electrode specific capacitance together with the use of the wide potential window electrolyte can result in high performance SCs. Conductive polymer polyaniline (PANI) as well as carbonaceous materials graphene (G) or reduced graphene oxide (RGO) have been widely studied for usage in electrodes of SCs. Although pristine PANI electrodes have shown low cycling stability and graphene sheets can have low specific capacitance due to agglomeration during their preparation without a spacer, their synergetic effect can lead to high electrochemical properties of G/PANI composites. This review points out the best results for G/PANI composite in comparison to that of pristine PANI or graphene (or RGO). Various factors, such as the ratio between graphene and PANI, oxidants, time, and the temperature of chemical oxidative polymerization, which have been determined to influence the morphology, capacitance, cycling stability, etc. of the composite electrode materials measured in three-electrode system are discussed. Consequently, we provide an in-depth summary on diverse promising approaches of significant breakthroughs in recent years and provide strategies to choose suitable electrodes based on PANI and graphene. The current energy demands of humankind are continuously growing due to the increase of the number of portable electronic devices and electric vehicles. New technologies for energy generation from light (as solar cells), heat (as thermoelectric generators), or mechanical stimuli (as eolic/wind power generators) have appeared. At the same time, effective energy storage devices are still needed. Light, thin, eco-friendly, and flexible energy storage systems are also essential for portable and flexible electronic devices needs. Thus, high-efficiency electrochemical energy-storage devices, particularly supercapacitors (SCs), are receiving intensive interest due to their high power density and rate performance as well as their long cycling life ,2,3. In 2/g . M. M48]. MOver 44% growth of cycling stability from 43.3% after 3000 cycles for pristine PANI to 87.4% after 5000 cycles at 5 A/g for the composite with 65 wt% N-doped graphene (NG) prepared by HT method with ethylenediamine (EDA) see d was repKe et al. reported that only 5 wt% of amino-triazine (AT) functional reduced graphene oxide (ATRGO) were enough to change the cycling stability from 47% after 1500 cycles at 100 mV/s for pristine PANI to 89% for ATRGO/PANI . Moreove2/g to 58 m2/g ..70]. Max2) that presented cycling stability increase up to 56.5% after 4000 cycles at 500 mV/s in comparison to 35% for pristine PANI  a a2 was s2 . . 120]. AHowever, Yan et al. also studied the mixture of electrodes based on RGO, CNT, and aniline, and reported the capacitance of 1035 F/g at 1 mV/s as can be seen in Thus, the addition of various metal oxides or hydroxides leads to an increase in specific capacity. However, with such an increase, there may be a change in the energy storage mechanism from the EDLC to the battery-type. So, the use of metal oxides and especially hydroxides should be carefully implemented and studied. At the same time, composites of graphene with PANI and with CNT additive present no battery-type but rather a strong capacitive/pseudocapacitive behaviour.3) and power density (in W/cm3), as well as the cycling stability, are known to be among the main characteristic parameters of SC for their commercial application. Therefore, the goal of SC research is to achieve high energy density at high power density, although in the major part of the available publications these values are rarely presented (often being substituted by specific energy and power). SC specific energy (E in Wh/kg) and specific power (P in W/kg) can be calculated by using the following expressions:totalC and single el.C are the measured capacitance of full SC and that of single electrode, respectively, ∆V is the operating voltage window, Δt is the discharge time in hours. Thus, although the values of capacitance are very important for the SC performance, the electrolyte voltage window plays also a major role for the enhancement of specific energy as well as specific power.The energy density  or liquid such as H2SO4, Na2SO4 or tetraacetylammonium-tetrafluoroborate-acetonitrile (Et4NBF4-AN) with different potential windows up to 2 V. In some articles mentioned above, two equal RGO/PANI electrodes were assembled to further investigate the electrochemical performance of symmetric supercapacitors. Summarizing the results, 4NBF4-AN electrolyte with the highest potential window [According to l window . In all l window  or even l window  or 10 A/l window .In the current review, recent advances in the synthesis, design and properties of graphene/PANI composites as electrode materials for supercapacitors were presented. Using different preparation conditions, ratios between components, methods, etc., the obtained composites show higher cycling stability than that of pristine PANI and higher specific capacitance than that of pristine graphene-related materials. However, a large variation of the different key factors such as time of the polymerization, types of oxidants, acids, and the ratio between the components can significantly change the morphology/mass loading/electrochemical performance of G/PANI composites. Therefore, the optimized synthesis conditions further enhance the cycling stability as well as the specific capacitive performances of G/PANI electrodes. 2SO4. At the same time, the specific capacitance can be enhanced by the polymerization time optimisation that, in turn, strongly depends on the ratio between aniline and graphene. Also, an increase of APS content during the process can significantly increase mass loading as well as areal specific capacitance.In addition, no strong direct dependency was found between concentrations of PANI and graphene since their composite structure includes oxidizing agents such as APS and acids such as HCl or HMoreover, we also stressed that due to the difference in the presentation view of the published results, the comparison of the specific capacitance values of G/PANI composites could be incorrect. At the same time, it is obvious that cycling stability of PANI always significantly increased with the addition of graphene and that the specific capacitance of graphene-related materials grew in composites with PANI. To analyse the time (speed) of the charge/discharge process, which is the one of the main differences between the supercapacitors and batteries as well as between the shape of CV and GCD;To test the cycling stability for longer periods of time , which is important for practical applications;To develop/improve new methods for preparation of the porous materials on an industrial scale.In addition, it is possible to propose the following topics for further investigations: Moreover, it must be understandable by the researchers that depending on the ratio in the composite between graphene and PANI, cycling stability will be more important for the composites with amount of PANI > 51 wt% (since its specific capacity is obviously higher than that for graphene); and the specific capacitance will be expected to increase if the concentration of graphene in the composite is higher than 51 wt% . Thus, articles with comparative data between the initial materials and the final composites are undoubtedly valuable for scientists.In addition, it is necessary to study and explain the charging mechanism of graphene/PANI composites as single electrodes before formation of the full device since the development and combination of capacitive or pseudocapacitive electrodes with the battery-type materials will result in hybrid device with perspective electrochemical performance in comparison to typical EDLC supercapacitors. It will also be important to study the graphene/PANI composite in various electrolytes, particularly in those for Na, K, and Mg-ion instead of Li-ion batteries.In conclusion, graphene/PANI composites can be used as a basis for high-performance supercapacitors. However, more studies and tests in the future must be carried out in a systematic manner to obtain high-performance electrode materials and, respectively, supercapacitors for a wide range of applications.


Among people who inject drugs (PWID), obtaining syringes via syringe services programs (SSPs) and pharmacies reduces injection sharing practices associated with hepatitis C virus (HCV). Whether indirect use of SSPs via secondary exchange confers a similar benefit remains unknown, particularly in rural settings. We compared HCV serostatus and injection sharing practices by primary syringe source among a sample of rural PWID.Data are from a cross-sectional study of adults who use drugs recruited from eleven rural counties in New Hampshire, Vermont, and Massachusetts using respondent-driven sampling (2018–2019). Study staff performed HCV antibody testing. An audio computer-assisted self-interview assessed sociodemographic characteristics, past 30-day injection practices, and past 30-day primary syringe source. Primary syringe source was classified as direct SSP, pharmacy, indirect SSP (secondary exchange), or “other” . Mixed effects modified Poisson models assessed the association of primary syringe source with HCV seroprevalence and injection sharing practices.Among 397 PWID, the most common primary syringe source was “other” (33%), then pharmacies (27%), SSPs (22%), and secondary exchange (18%). In multivariable models, compared with those obtaining most syringes from “other” sources, those obtaining most syringes from pharmacies had a lower HCV seroprevalence ; however, the upper bound of the 95% CI was close to 1.0. Compared with those obtaining most syringes from other sources, PWID obtaining most syringes directly from SSPs or pharmacies were less likely to report borrowing used syringes , borrowing used injection equipment , and backloading . Potential inverse associations between obtaining most syringes via secondary exchange and injection sharing practices did not reach the threshold for statistical significance.PWID in rural New England largely relied on informal syringe sources . Those obtaining most syringes from an SSP or pharmacy were less likely to share injection equipment/syringes and had a lower HCV seroprevalence, which suggests using these sources reduces the risk of new HCV infections or serves as proxy for past injection behavior.The online version contains supplementary material available at 10.1186/s13722-022-00358-7. The opioid crisis in the United States has fueled a surge in injection drug use and new hepatitis C virus (HCV) infections. Between 2010 and 2019, the number of new HCV infections in the U.S. increased by 387% . In ruraIn most states, syringe services programs (SSPs) and the nonprescription sale of syringes in pharmacies serve as important interventions to reduce transmission of bloodborne pathogens –9. StudiPeople who use SSPs commonly extend the indirect reach of these programs through secondary syringe exchange, a practice whereby an individual obtains syringes from an SSP and distributes them to others in their social network . SecondaUsing data from the Drug Injection Surveillance and Care Enhancement for Rural Northern New England (DISCERNNE) study, we examined the association of primary syringe source  with HCV serostatus. A secondary goal was to examine the relationship between primary syringe sources and three injection sharing practices: borrowing used syringes, borrowing used injection equipment, and backloading.Data for this investigation were collected as part of the DISCERNNE study, a multi-site, mixed-methods cross-sectional study conducted in 11 rural counties along the Connecticut River Valley in New Hampshire (NH), Vermont (VT), and Massachusetts (MA). The overall goal of DISCERNNE was to characterize the risk environment and epidemiology of overdose and injection-mediated infectious diseases among rural PWID. Further study details and findings from the DISCERNNE study have been published elsewhere –21.Participants were eligible for DISCERNNE if they: (1) were 18 years or older, (2) spent most of the last 30 days living in the study area, (3) used opioids “to get high”  or injected any drug in the last 30 days, and (4) were able to provide written informed consent. We recruited participants at 11 study sites that were chosen after consulting local public health officials, service providers, and harm reduction experts. Study staff recruited participants between May 2018 and October 2019 using respondent-driven sampling (RDS), a chain referral sampling method used to recruit difficult-to-reach populations , 23. StaParticipants completed a 90-min audio computer-assisted self-interview (ACASI) on touch-screen laptops. The use of ACASI has been shown to enhance perceived confidentiality and increase accurate reporting of sensitive behaviors, including substance use , 25. TheWe assessed participants’ primary syringe source with the question: “During the last 30 days, where have you gotten most of your syringes or needles?” Response options included (1) a “syringe or needle exchange program, in person” , (2) “from someone else who got them from a syringe or needle exchange program” , (3) a “pharmacy”, or (4) some other syringe source . In our primary analysis, “other” sources served as the reference category. To directly compare those obtaining most syringes from pharmacies with those obtaining most syringes from SSPs on both primary and secondary outcomes, we conducted a supplementary analysis using SSP as the referent category.The primary outcome of interest was HCV serostatus. Participants were considered HCV seropositive if they had a positive rapid HCV antibody test. HCV-RNA testing was not performed. Secondary outcomes included the following past 30-day injection sharing practices: borrowing used syringes (using a syringe known to have been used by someone else), borrowing other used injection equipment , and backloading .We selected several potentially confounding variables using the disjunctive cause criterion, which proposes that sufficient control for confounding can be achieved by adjusting for variables that cause the exposure, outcome, or both, and excluding variables known to be instrumental variables , 28. InfWe compared participant characteristics, HCV serostatus, and injection sharing practices for those obtaining most syringes directly from SSPs, indirectly through SSPs, from pharmacies, or from other sources using chi-square tests and ANOVA for discrete and continuous variables, respectively. Descriptive statistics were not weighted to account for RDS, and therefore should not be interpreted as population-based estimates. We used multivariable mixed effects modified Poisson regressions to model the relationship between primary syringe source and our primary and secondary outcomes. Mixed effects models accounted for the lack of independence among participants within study sites with a random intercept for study site. Modified Poisson models allow for the direct estimation of prevalence ratios for common binary outcomes , 37. We Participants in the analytic sample were predominantly male (58%), White (93%), injected heroin in the past 30 days (92%), and reported injecting drugs at least daily (59%) in the past 30 days Table . AlthougWith respect to primary syringe source in the past 30 days, 22% reported obtaining most of their syringes directly from an SSP (direct SSP), 27% from a pharmacy, and 18% from someone else who got them from an SSP (indirect SSP). The remaining 33% of participants reported obtaining most of their syringes in the past 30 days from other sources. Among these PWID, primary syringe sources included friends and acquaintances (56%), a drug dealer or street syringe seller (25%), a spouse, partner, or family member (16%), and finding them (3%). A majority of PWID who reported obtaining most syringes directly from SSPs (76%) used no other syringe source; similarly, 86% of those who obtained most syringes from a pharmacy used no other source, and 61% of those who obtained most syringes indirectly from SSPs used no other source. Among those who obtained most syringes from “other” sources, 22% obtained syringes from SSPs (directly or indirectly) or a pharmacy at least once in the past 30 days.Those obtaining most syringes from “other” sources were more likely to be female than those getting most syringes directly from SSPs, at pharmacies, or indirectly from SSPs Table . Three qIn the final mixed effects modified Poisson adjusted model for HCV seroprevalence Table , compareIn the final multivariable adjusted models for injection sharing practices Table , compareWe performed a sensitivity analysis using an alternative model building approach (bivariate screening). The results from this approach were not appreciably different from our initial results, with no change in the overall conclusions  was much higher than that reported in previous studies among urban PWID (1.4–4.3%) [Secondary syringe exchange was relatively common in our sample of rural PWID. It is difficult to compare the prevalence of secondary exchange in our study with that of previous studies since those engaging in secondary exchange were defined differently across studies. However, the proportion of PWID in our study who .4–4.3%) , 38. Urb.4–4.3%) , as they.4–4.3%) . Scarcit.4–4.3%) , recent .4–4.3%) . Given tAlthough indirect use of SSPs was not associated with HCV seroprevalence, pharmacy use and direct SSP use were modestly correlated with lower HCV seroprevalence compared with using “other” syringe sources. Rural PWID who obtained most of their syringes from a pharmacy had a 15% lower prevalence of HCV antibodies compared with those who obtained most syringes from other sources; however, the upper bound of the 95% confidence interval was very close to 1.0, which suggests our findings may also be compatible with no significant difference. Previous reviews and meta-analyses have found inconsistent evidence that pharmacy syringe sales or SSPs reduce HCV incidence or prevalence , 42–44. Consistent with a large body of research in urban settings , 42, 43,most syringes in the past 30 days from someone else who got them from an SSP. In contrast, the Chicago study defined their group of “mixed/secondary exchangers” as PWID who, in the past 6 months, obtained at least some needles indirectly from an SSP through other persons [Although the associations observed between acquiring most syringes through secondary exchange (vs. other sources) and each of the injection sharing practices were in the anticipated direction, these associations were weak and imprecise. These results differ from two previous studies conducted in three urban U.S. cities, which observed stronger associations between indirect SSP use and injection sharing practices , 38. Sev persons . Only 5%Nevertheless, our findings should not be interpreted to mean that secondary syringe exchange should be discouraged in rural settings. First, strong evidence supports that secondary exchange increases the number of people served by SSPs by reaching PWID who are unable or unwilling to attend an SSP in person. In previous U.S. studies in urban settings, PWID who participated in secondary exchange reported fear of exposure, fear of police harassment, and inconvenient SSP locations and hours as major barriers to attending SSPs , 39. SecThis study has several limitations. First, the data are cross-sectional, which precludes statements about causality. Second, as previously mentioned, the study did not include HCV-RNA testing, so our seroprevalence data cannot differentiate between incident, prevalent, or resolved infection. The relatively high HCV seroprevalence (73%) in our sample suggests many of these cases may have developed long before we measured participants’ primary syringe source, and perhaps even before SSPs or nonprescription pharmacy syringe sales were available in the study area. Therefore, the modest and non-significant associations across primary syringe sources do not necessarily mean that those currently obtaining syringes from SSPs and pharmacies will not be less likely to develop a new HCV infection in the future. Given SSP and pharmacy use were negatively associated with injection sharing practices, we may have observed stronger protective associations between these syringe sources and HCV had we been able to focus on incident infections. Future research among rural PWID should include HCV-RNA testing to better assess the relationship between syringe source and HCV infection. Third, given the sample size, the analysis had limited power to detect differences in associations across the primary syringe source groups. Fourth, the self-reported data for primary syringe source creates the potential for social desirability bias. Previous research suggests, however, the use of ACASI may diminish socially desirable responses to sensitive questions .Our measure of participants’ primary syringe source over the past 30 days is also subject to misclassification. For instance, although we classified friends, spouses, relatives and street sellers as “other” syringe sources, it is possible the PWID in our sample did not know the original source of the syringes obtained from others. If many of these syringes originally came from SSPs, then we have underestimated the number of individuals acquiring syringes indirectly via SSPs in our sample. However, from the perspective of risk perception, a participant truly not knowing the original source of their syringe remains distinct from a participant knowing a peer is giving them a sterile syringe that was obtained from an SSP. In the former scenario, the participant is assuming greater risk of infection than the participant who knowingly obtains most syringes via secondary exchange.Finally, although we used RDS for recruitment, because several key assumptions were not met, we did not use RDS weights , 55. TheSecondary syringe exchange is a common practice among PWID in the rural northeastern U.S. However, indirect SSP use was not associated with HCV seroprevalence and only weakly associated with injection sharing practices. Further research is needed to determine whether existing syringe exchange networks can be leveraged to deliver peer-based harm reduction interventions to rural PWID. Finally, these findings reaffirm the important role SSPs and pharmacies play in reducing injection sharing practices, and suggest their benefits might extend to reducing the risk of future HCV infections.Additional file 1: Table S1. Associations between primary syringe source and injection sharing practices, with direct SSP as the reference group. Table S2. Associations between primary syringe source and HCV seroprevalence using an alternative model building approach (bivariate screening). Table S3. Associations between primary syringe source and injection sharing practices using an alternative model building approach (bivariate screening). Table S4. Syringe sources used at least once in the past 30 days by primary syringe source (past 30 days). Table S5. Frequency of participants whose primary syringe source was their only source in the past 30 days. Table S6. Sensitivity analysis - Associations of syringe source with HCV serostatus and injection sharing practices using alternative categories for syringe source.