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Encoding Microreactors with Droplet Chains in Microfluidics

Droplet-based high throughput biomolecular screening and combinatorial synthesis entail a viable indexing strategy to be developed for the identification of each micro-reactor. Here, we propose a novel indexing scheme based on the generation of droplet sequences on demand to form unique encoding droplet chains in fluidic networks. These codes are represented by multiunit and multilevel droplets packages, with each code unit possessing several distinct signal levels, potentially allowing large encoding capacity. For proof of concept, we use magnetic nanoparticles as the encoding material and a giant magnetoresistance (GMR) sensor-based active sorting system supplemented with an optical detector to generate and decode the sequence of one exemplar sample droplet reactor and a 4-unit quaternary magnetic code. The indexing capacity offered by 4-unit multilevel codes with this indexing strategy is estimated to exceed 104, which holds great promise for large-scale droplet-based screening and synthesis.

sources and filters are required. The combination of optical and magnetic codes, though bearing the advantages of boosting the encoding capacity, is still at the expense of the cost and complexity of the whole system. 19 Furthermore, a key drawback of current droplet encoding strategy is that the encoding materials are typically loaded with samples in the same droplets, which may cause undesirable interference to the analyses of cell behaviors for drug screening due to the different concentrations of coencapsulated encoding materials. There is also a possibility of nanocrystals to be synthesized being contaminated by the unwanted encoding materials. Under such circumstances, it is crucial to separating samples and encoding materials. A solution is by using a droplet neighboring to a sample-containing droplet as a code, as shown in Figure 1a. This approach is promising to overcome the drawbacks of conventional encoding strategy without the concern of altering the initial composition of the samples. So far, such a position-encoding strategy was demonstrated by passively producing alternating sample-containing and fluorescent dye-containing droplets with a pair of T-junctions fabricated in microfluidic channels. 22 However, this method offers little flexibility to adjust the number of droplets near the sample droplets. Hence, the current encoding capacity of single code with multiple levels ( Figure 1b) and multiunit code with two levels ( Figure 1c) is still limited for encoding in a single droplet.
Here, we put forth the concept of multiunit multilevel codes (Figure 1d) potentially allowing to achieve a large indexing capacity without worrying the alteration of initial compositions of samples. In this concept, unique sequences of droplets are created on demand in microfluidic networks as codes, of which each elementary droplet unit exhibits a distinct signal level. We demonstrate 4-unit quaternary codes which could potentially offer a capacity of 256, which are 64 times larger than that of single-unit codes with the same number of intensity levels applied by scaling up the encoding capacity without scaling up the device.
For proof-of-concept demonstration, we use ferrofluid magnetic nanoparticles (MNPs) as encoding materials to be encapsulated in droplets (Figure 1e). A modular fluidic code generation system is established and armed with a magnetic field sensor and electro-magnetic valves. We operate the device to create a sequence of reaction droplets encoded by 4-unit quaternary codes. The droplet reactors are then decoded using the magnetic detector. To demonstrate the potential of the encoding strategy for multiplexed assays and synthesis, we exemplarily load fluorescent dyes (green color) in droplets between the encoding droplet sequences to mimic the products to be analyzed/synthesized in reaction droplets. In this way, the reaction products can be monitored by optically observing the fluorescence. By combining the intensity levels, the limit of the indexing capacity offered by the 4-unit codes using the setup is explored to reach 38416, which is sufficient to perform the indexing task for producing large size compound libraries for drug screening.

Results and Discussions
Concept of droplet-based positional encoding Our concept of multiunit multilevel positional encoding for droplet fluidics is based on an active droplet selection strategy, which can be realized by a fluidic system with an encoded signal detector, valves and a rigorous droplet selection algorithm. A code is embodied by a chain of droplets consisting of multiple units exhibiting differentiable signal levels. Each droplet unit is physically isolated out of an initial droplet chain produced from the upstream of a fluidic network, while the number of the units forming the code and the encoded signal levels of individual units are pre-defined by a computer program. This functionality is relying upon the active switch of a 3-way valve, one way connected to the up-stream channel, the others connected to down-stream channels diverting selected individual droplet units for sample indexing and remaining droplet units for recycling. The mechanical activation of the valve is controlled by a feedback from the signal detector which analyses the signal of each interrogated droplet. Right after generating a desired code, a droplet reactor to be indexed is inserted behind the code for indexing. In practice, such a concept could be applicable in a variety of detectors and encoding signals combinations including optical detectors and fluorescent signals, magnetic detectors and magnetic field signals. Figure 1: (a) Encoding droplet reactors with a neighboring droplet code. A code is denoted by a star shape and a droplet reactor is denoted by a filled circle. Schematics of (b) a single unit code with multiple levels, (c) multiunit codes with two levels, and (d) multiunit code with multiple levels. (e) Schematic of the operation principle of code creation and verification in fluidics. The selection and detection of the signals of an initial sequence and the verification of created codes are conducted with GMR sensors. The entirety of a magnetic code and a reaction droplet is detected by a GMR sensor sensing system and a high-speed camera fitted to a far-field microscope, respectively. Black and gray star symbols indicate droplets with high and low concentrations of MNPs. Green circles indicate fluorescein droplets.

Generation of multiunit multilevel droplet codes
To prove the above concept, we choose GMR sensors as signal detectors. The GMR sensors are a type of magnetic field sensors that is capable of detecting very low magnetic fields down to a few tens of micro-Tesla. 23 Ferrofluid superparamagnetic nanoparticles are used as the encoding material of droplet codes. The kind of magnetic nanoparticles, when loaded in droplets and magnetized by an external magnetic field, can generate quantifiable magnetic field patterns that can be resolved by a GMR sensor. 24,25 We chose PTFE tubes with inner diameters of a few hundred micrometers to build the fluidic networks. By connecting these tubes with pre-formed T-junctions, modular systems can be set up with ease. The millifluidic system enables to generate droplets with volumes ranging from a few picoliters to nanoliters. 26 providing a wide range of droplet volumes for diverse applications to cell culturing and materials synthesis. We built a fluidic platform encompassing all the above features to flow through to enable the functionalities of code generation, code verification and sample indexing (details of the system is shown in Figure S2).
A code is embodied by a unique sequence of droplet units and each unit should produce well-differentiable signals. Binary codes based on two discrete signal levels have been ubiquitous in nowadays information society in computing and telecommunications. Realization for binary codes is rather straightforward to follow, 27 that is, by using two T-junctions to produce droplets encapsulating distinct amounts of magnetic nanoparticles ( Figure S3). The droplets produced from upstream can be merged into a single channel to form an initial sequence which afterwards passes across a GMR sensor for detection. The spacing between droplets is controlled by adding spacer oils to avoid potential overlap in the signal patterns of neighboring droplets so that they will not affect the resolution. The volume of droplets may influence the signal levels when the size of droplets is smaller than the size of magnetic sensors. 26 Under such a circumstance, the sensor is sensitive to both the volume of droplets and the concentrations of encapsulated magnetic particles. Hence, in current work, different concentrations of magnetic nanoparticles are explored to create distinct signal levels. We operate with droplets produced with volumes sufficient to cover the whole sensing area of the sensor so that the signal level is insensitive to the volume of droplets. Code units can be selected from the initial droplets sequence, where each droplet provides either high (pink-shaded region) or low level (green-shaded region) of magnetic signals to represent logic '1' and '0', respectively. The combination of a certain number of '1' and '0' gives binary codes and different combinations represent different decimal numbers. For example, in 4-unit binary codes, '0000', '0001', '0010', '0011',..., '1111' represent decimal numbers 0, 1, 2, 3,..., 15, respectively. Naturally, 4-unit binary codes offer an indexing capacity of 16, which is, however, not sufficient to cater for the indexing requirement in large compound libraries.
One way to expand the indexing capacity is to increase the distinguishable magnetic signal levels. For example, 4-unit quaternary codes offer an indexing capacity of 256, which is 16 times of that of the 4-unit binary codes and comparable with that offered by state-ofthe-art multicolor optical encoding strategy. For this, we periodically adjust the flow rates of magnetic nanoparticles and water loaded in a droplet by using only one T-junction ( Figure   S4). With this method, a concentration gradient of magnetic nanoparticles can be loaded in droplets and hence a gradient of magnetic encoding signals can be generated (Figure 2a The detection result is manifested in the form of several units of magnetic signal peaks that shows a certain pattern representing a decimal number followed by an optical signal peak produced by the fluorescence. Such a signal sequence reveals that both the codes and the presence of reaction product in the droplet reactor.

Exploring a large library of codes
To explore the limit of indexing capacity offered using this setup and materials, a statistical analysis is performed on the magnetic signals from droplets of 9 different concentrations The number of codes is determined by the detection limit of the magnetic sensor. Still, the capacity could be extended even without changing the setup by using simple optical The velocity of droplets does not influence the signal level as long as the shape of droplets does not change, but it affects the signal width. However, droplets may deform at a high flow velocity exceeding a certain threshold due to a high shear stress. Under such a circumstance, the signal level can drop due to the shrinking of the dimensions of droplets perpendicular to the travel direction of droplets, leading to less effective magnetic stray fields collected by the sensor. In our previous study, 28 we found that when a droplet shrinks in the lateral direction by a strong magnetic force, the sensor area exposed to the droplet decreases, which is the same as the situation when they are stretched by high shear stress at a high flow velocity.
The voltage signal follows a scaling rule for a constant ferrofluid concentration: where S is the sensor area exposed to ferrofluid droplets. Hence, with a constant fluctuation of concentration ∆C, the fluctuation of voltage signal ∆V decreases with the decrease of S.
Furthermore, droplets encapsulating the highest concentration of ferrofluid (Ferrotec EMG 700, commercial stock concentration: 75 mg/mL) determines the whole signal range (V S ), which decreases with the exposed sensor area S. As the number of resolvable different signal levels (N ) is determined by V S /∆V . In this respect, two scenarios can apply: (i) When ∆V is larger than the limit of detection of the sensor, the number of distinct signal levels that can be generated is not changed because both V S and ∆V decrease proportionally.
(ii) When ∆V is smaller than the limit of detection of the sensor, the noise of detection dominates over the signal change caused by the fluctuation of the concentration of ferrofluid.
In this case, the number of distinct signal levels will decrease accordingly. However, in this scenario, solidifying droplets into solid particles would mitigate this effect. This requires the production of droplets with volumes smaller than the channel cross section to avoid channel clogging and using ferrofluid blended with photosensitive polymers that can be crosslinked by UV illumination. 29

Conclusions
Droplet microfluidic devices are promising platforms for large-scale biological assays and combinatorial synthesis. The capability to identify each droplet reactor is crucial towards the realization of high-throughput biological assays, custom multistep synthesis in a fully automated way. We have reported a multiunit multilevel positional encoding strategy to encode droplet reactors, with each droplet unit possessing several distinct signal levels. For the proof-of-concept demonstration, a millifluidics platform armed with an encoding functionality and a synergistic optical and magnetic detection system was built up and a sequence of a reaction droplet encoded using a 4-unit quaternary code was created and decoded using the devices.
The capacity limit using the setup and materials was investigated. Using only magnetic signals, 12 distinguishable magnetic levels in one code unit can be achieved, therefore the indexing capacity of 4-unit codes can reach 20736. By further adding optical signal as an encoding dimension, the indexing capacity of codes can reach around 38416. The proposed encoding strategy is advantageous in terms of its potential to encoding a large number of encoding capacity without scaling up the system compared with other current encoding methods such as multi-colour encoding. The positional encoding method is also beneficial for droplet-based screening that excludes the possibility of sample contamination due to the presence of encoding materials in the same reactors. We anticipate that if the sensitivity and resolution of the magnetic sensor can be further improved or the concentration and the magnetic moments of magnetic nanoparticles can be increased, more distinguishable signal levels will be available. Encoding capacity exceeding 10 6 , which is of the scale of the size of some large compound libraries, is expected to be achieved.

Experimental
The measurement platform

Creation of droplets
The droplet generator module ( Figure S2a) was assembled from: the pulse free syringe pumps

Optical detection module
A microscope (Zeiss, Scope. A1) equipped with a high-speed camera (Photron, Fastcam SA3, black and white imaging) was used as the optical detection module ( Figure S2b). An objective lens with 5x magnification was applied. The microscope was operated in bright-field mode while detecting magnetic droplets. When the fluorescent light needs to be collected, the microscope was operated with a fluorescence filter. The analog output from the camera was transferred to the computer. A LabView program was used to extract the center pixel grayscale of the live camera image. The grayscale ranges from 0 to 255, with 0 as pure dark and 255 as pure bright. When a dark object passes the detection spot, the grayscale of the image decreases; when a luminescent object passes the detection spot, the grayscale increases. Therefore, when the dark ferrofluid droplets passed the probe light spot, the grayscale of the center pixel decreased. As a consequence, rectangular-shape peaks ( Figure   S2b, Inset 2) formed when a train of droplets passes by.

Magnetic detection module
The magnetic detection was realized with a GMR sensor. The layer stack of the GMR Therefore, a strategy is taken to enhance the magnetic stray fields to be detected. As the ferrofluid employed for present study is a suspension of magnetic colloidal nanoparticles in water, it does not retain magnetization without applying external magnetic field. Thus, an external field should be applied to achieve a net magnetization of the ferrofluid. In addition, the external magnetic field can be simultaneously used to bias the sensor to the sensitive region. Based on these considerations, a permanent magnet (AlNiCo 500, type A1560, IBSMagnet, length: 60 mm, diameter: 15 mm) was placed below the GMR sensor.
The position of the permanent magnet was adjusted to achieve detectable stray field from MNPs droplets and to bias the GMR sensor to the most sensitive region.
The GMR sensor was connected with 3 trimmers (Bourns, 3006P-1-102LF) to realize a Wheatstone bridge geometry ( Figure S2c). The measured differential output voltage from the bridge scales with the change of external magnetic field. 27 By balancing the bridge, the background voltage across the bridge can be minimized so that the measuring sensitivity can be enhanced.
A lock-in amplifier (AMETEK, Model 7230) was used to amplify the voltage across the bridge and reduce the noise. The whole bridge circuit was also powered by the lock-in using a constant AC voltage of 0.2 V. The modulation frequency and the time constant were set as 1 kHz and 100 ms, respectively. The line filter is set to filter 50 Hz and 100 Hz noise.
The analog output from the lock-in was converted to digital data through a data acquisition box (NI, USB-6009). A LabView program was used to visualize and analyze the digital data. The characteristic peaks ( Figure S2c, Inset 3) formed when a train of droplets pass by.
The peak amplitude and width were determined instantly by the LabView program. This information was used as a feedback for automatically triggering the switch of a 3-way valve, relying on which droplets of interest were sorted into the codes container ( Figure S2d).

Sorting module
The sorting function was realized by switching the 3-way valve ( Figure S2d Generation of the initial sequence for quaternary codes Figure S4a and Table 1 show the schematic of the fluidic circuit and the flow rate program that were used to generate the initial sequence for quaternary codes. The generated train of droplets presented a regular signal pattern, with 160 s as a period and in each period the signal level first increase and then decrease ( Figure S4b). The sensitivity of the lock-in was set to 10 µV.

Supporting Information Available
The following files are available free of charge.
The Supporting Information file contains further details on the experimental setup, the formation of binary codes and the envisioned application example. The Supporting Information is provided as a single PDF file.