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Pneumatically-actuated soft robots have advantages over traditional rigid robots in many applications. In particular, their flexible bodies and gentle air-powered movements make them more suitable for use around humans and other objects that could be injured or damaged by traditional robots. However, existing systems for controlling soft robots currently require dedicated electromechanical hardware (usually solenoid valves) to maintain the actuation state (expanded or contracted) of each independent actuator. When combined with power, computation, and sensing components, this control hardware adds considerable cost, size, and power demands to the robot, thereby limiting the feasibility of soft robots in many important application areas. In this work, we introduce a pneumatic memory that uses air (not electricity) to set and maintain the states of large numbers of soft robotic actuators without dedicated electromechanical hardware. These pneumatic logic circuits use normally-closed microfluidic valves as transistor-like elements; this enables our circuits to support more complex computational functions than those built from normally-open valves. We demonstrate an eight-bit nonvolatile random-access pneumatic memory (RAM) that can maintain the states of multiple actuators, control both individual actuators and multiple actuators simultaneously using a pneumatic version of time division multiplexing (TDM), and set actuators to any intermediate position using a pneumatic version of analog-to-digital conversion. We perform proof-of-concept experimental testing of our pneumatic RAM by using it to control soft robotic hands playing individual notes, chords, and songs on a piano keyboard. By dramatically reducing the amount of hardware required to control multiple independent actuators in pneumatic soft robots, our pneumatic RAM can accelerate the spread of soft robotic technologies to a wide range of important application areas.

Counterfeit or substandard medicines adversely affect the health of millions of people and cost an estimated $200 billion USD annually. Their burden is greatest in developing countries, where the World Health Organization estimates that one in ten medical products are fake. In this work, I describe a simple addition to the existing drug manufacturing process that imparts an edible universally unique physical identifier to each pill, tablet, capsule, caplet, etc. This technique uses nonpareils (also called sprinkles and “hundreds and thousands”), tiny inexpensive multicolor candy spheres that are normally added to other candies or desserts as decorations. If nonpareils are applied at random to a pill immediately after manufacture, the specific pattern they form is unlikely to ever be repeated by random chance; this means that the pattern (or “CandyCode”) can be used to uniquely identify the pill and distinguish it from all other pills. By taking a photograph of each CandyCoded pill after manufacture and recording the location and color of each nonpareil, a manufacturer can construct a database containing the CandyCodes of all known-authentic pills they produce. A consumer can then simply use a cellphone to photograph a pill and transfer its image to the manufacturer’s server, which determines whether the pill’s CandyCode matches a known-good CandyCode in their database (meaning that the pill is authentic) or does not have a match in the database (in which case the consumer is warned that the pill may be counterfeit and should not be consumed). To demonstrate the feasibility of using random particles as universal identifiers, I performed a series of experiments using both real CandyCodes (on commercially produced chocolate candies) and simulated CandyCodes (generated by software). I also developed a simple method for converting a CandyCode photo to a set of strings for convenient storage and retrieval in a database. Even after subjecting CandyCodes to rough handling to simulate shipping conditions, the CandyCodes were still easily verifiable using a cellphone camera. A manufacturer could produce at least 10 17 CandyCoded pills—41 million for each person on Earth—and still be able to uniquely identify each CandyCode. By providing universally-unique IDs that are easy to manufacture but hard to counterfeit, require no alteration of the existing drug formulation and minimal alteration of the manufacturing process, and need only a cameraphone for verification, CandyCodes could play an important role in the fight against fraud in pharmaceuticals and many other products.

Sorting cells by their type is an important capability in biological research and medical diagnostics. However, most cell sorting techniques rely on labels or tags, which may have limited availability and specificity. Sorting different cell types by their different physical properties is an attractive alternative to labels because all cells intrinsically have these physical properties. But some physical properties, like cell size, vary significantly from cell to cell within a cell type; this makes it difficult to identify and sort cells based on their sizes alone. In this work we continuously sort different cells types by their density, a physical property with much lower cell-to-cell variation within a cell type (and therefore greater potential to discriminate different cell types) than other physical properties. We accomplish this using a 3D-printed microfluidic chip containing a horizontal flowing micron-scale density gradient. As cells flow through the chip, Earth's gravity makes each cell move vertically to the point where the cell's density matches the surrounding fluid's density. When the horizontal channel then splits, cells with different densities are routed to different outlets. As a proof of concept, we use our density sorter chip to sort polymer microbeads by their material (polyethylene and polystyrene) and blood cells by their type (white blood cells and red blood cells). The chip enriches the fraction of white blood cells in a blood sample from 0.1% (in whole blood) to nearly 98% (in the output of the chip), a 1000x enrichment. Any researcher with access to a 3D printer can easily replicate our density sorter chip and use it in their own research using the design files provided as online Supporting Information. Additionally, researchers can simulate the performance of a density sorter chip in their own applications using the Python-based simulation software that accompanies this work. The simplicity, resolution, and throughput of this technique make it suitable for isolating even rare cell types in complex biological samples, in a wide variety of different research and clinical applications.

We present a method for direct non-optical quantification of dry mass, dry density and water mass of single living cells in suspension. Dry mass and dry density are obtained simultaneously by measuring a cell's buoyant mass sequentially in an H2O-based fluid and a D2O-based fluid. Rapid exchange of intracellular H2O for D2O renders the cell's water content neutrally buoyant in both measurements, and thus the paired measurements yield the mass and density of the cell's dry material alone. Utilizing this same property of rapid water exchange, we also demonstrate the quantification of intracellular water mass. In a population of E. coli, we paired these measurements to estimate the percent dry weight by mass and volume. We then focused on cellular dry density - the average density of all cellular biomolecules, weighted by their relative abundances. Given that densities vary across biomolecule types (RNA, DNA, protein), we investigated whether we could detect changes in biomolecular composition in bacteria, fungi, and mammalian cells. In E. coli, and S. cerevisiae, dry density increases from stationary to exponential phase, consistent with previously known increases in the RNA/protein ratio from up-regulated ribosome production. For mammalian cells, changes in growth conditions cause substantial shifts in dry density, suggesting concurrent changes in the protein, nucleic acid and lipid content of the cell.

We have used a microfluidic mass sensor to measure the density of single living cells. By weighing each cell in two fluids of different densities, our technique measures the single-cell mass, volume, and density of approximately 500 cells per hour with a density precision of 0.001 g mL⁻¹. We observe that the intrinsic cell-to-cell variation in density is nearly 100-fold smaller than the mass or volume variation. As a result, we can measure changes in cell density indicative of cellular processes that would be otherwise undetectable by mass or volume measurements. Here, we demonstrate this with four examples: identifying Plasmodium falciparum malaria-infected erythrocytes in a culture, distinguishing transfused blood cells from a patient's own blood, identifying irreversibly sickled cells in a sickle cell patient, and identifying leukemia cells in the early stages of responding to a drug treatment. These demonstrations suggest that the ability to measure single-cell density will provide valuable insights into cell state for a wide range of biological processes.

Microfluidics researchers are increasingly using computer simulation in many different aspects of their research. However, these simulations are often computationally intensive: simulating the behavior of a simple microfluidic chip can take hours to complete on typical computing hardware, and even powerful workstations can lack the computational capabilities needed to simulate more complex chips. This slows the development of new microfluidic chips for new applications. To address this issue, we present a microfluidic simulation method that can simulate the behavior of fluids and particles in some typical microfluidic chips instantaneously (in around one second). Our method decomposes the chip into its primary components: channels and intersections. The behavior of fluid in each channel is determined by leveraging analogies with electronic circuits, and the behavior of fluid and particles in each intersection is determined by querying a database containing nearly 100,000 pre-simulated channel intersections. While constructing this database takes a nontrivial amount of computation time, once built, this database can be queried to determine the behavior of fluids and particles in a given intersection in a fraction of a second. Using this approach, the behavior of a microfluidic chip can be simulated in just one second on a standard laptop computer, without any noticeable degradation in the accuracy of the simulation. While our current technique has some constraints on the designs of the chips it can simulate (namely, T- or cross-shaped intersections, 90 degree channel turns, a fixed channel width, fluid flow rates between 0 and 2 cm/s, and particles with diameters between 1 and 20 microns), we provide several strategies for increasing the range of possible chip designs that can be simulated using our technique. As a proof of concept, we show that our simulation method can instantaneously simulate the paths followed by particles in both simple and complex microfluidic chips, with results that are essentially indistinguishable from simulations that took hours or even days to complete using conventional approaches.

A microfluidic device containing a suspended microchannel resonator capable of measuring the mass of microscopic objects with femtogram resolution allows determination of bacteria, yeast and mammalian cell growth rates in less than one cell cycle by repeated measurement of the buoyant mass of single growing cells. We used a suspended microchannel resonator (SMR) combined with picoliter-scale microfluidic control to measure buoyant mass and determine the 'instantaneous' growth rates of individual cells. The SMR measures mass with femtogram precision, allowing rapid determination of the growth rate in a fraction of a complete cell cycle. We found that for individual cells of Bacillus subtilis , Escherichia coli , Saccharomyces cerevisiae and mouse lymphoblasts, heavier cells grew faster than lighter cells.

The overwhelming majority of research on wild bumble bees has focused on the social colony stage. Nest‐founding queens in the early season are difficult to study because incipient nests are challenging to find in the wild and the foundress queen flight period is very short relative to the entire nesting period. As a result, natural history information on foundress queens is exceedingly rare. New methodological approaches are needed to adequately study this elusive life stage. We trap‐nested wild queen bumble bees in artificial nest boxes in Gothic, Colorado and used a custom‐built radio frequency identification (RFID) system to continuously record queen foraging activity (inferred from entering and exiting the nest) for the majority of their spring flight periods. Foundress queens made frequent, short foraging trips, which tended to increase in duration over the course of the flight period. All queens who produced adult workers ceased foraging within approximately 1 week after workers emerged in the nest. We observed frequent nest failure among foundress queens: Fewer than one quarter of queens who laid eggs in nest boxes went on to produce reproductive gynes at the end of the season. We also report nest characteristics and curious phenomena we observed, including conspecific nest invasion and queens remaining outside the nest overnight. We present this trap‐nesting and subsequent RFID tracking method as a valuable, albeit resource‐intensive, path forward for uncovering new information about the elusive, incipient life stage of wild bumble bees. Using a trap‐nesting and RFID tracking methodology, we report wild bumble bee queen foraging into and out of the nest as well as success rates of foundress queens. Queens made frequent, short foraging trips and ceased foraging shortly after workers emerged in the nest. Fewer than one quarter of queens observed in our study succeeded in producing reproductive queens (gynes) at the end of the season.

Measuring the temperature of a sample is a fundamental need in many biological and chemical processes. When the volume of the sample is on the microliter or nanoliter scale (e.g., cells, microorganisms, precious samples, or samples in microfluidic devices), accurate measurement of the sample temperature becomes challenging. In this work, we demonstrate a technique for accurately determining the temperature of microliter volumes using a simple 3D-printed microfluidic chip. We accomplish this by first filling \"microfluidic thermometer\" channels on the chip with substances with precisely known freezing/melting points. We then use a thermoelectric cooler to create a stable and linear temperature gradient along these channels within a measurement region on the chip. A custom software tool (available as online Supporting Information) is then used to find the locations of solid-liquid interfaces in the thermometer channels; these locations have known temperatures equal to the freezing/melting points of the substances in the channels. The software then uses the locations of these interfaces to calculate the temperature at any desired point within the measurement region. Using this approach, the temperature of any microliter-scale on-chip sample can be measured with an uncertainty of about a quarter of a degree Celsius. As a proof-of-concept, we use this technique to measure the unknown freezing point of a 50 microliter volume of solution and demonstrate its feasibility on a 400 nanoliter sample. Additionally, this technique can be used to measure the temperature of any on-chip sample, not just near-zero-Celsius freezing points. We demonstrate this by using an oil that solidifies near room temperature (coconut oil) in a microfluidic thermometer to measure on-chip temperatures well above zero Celsius. By providing a low-cost and simple way to accurately measure temperatures in small volumes, this technique should find applications in both research and educational laboratories.

Most microfluidic chips utilize off-chip hardware (syringe pumps, computer-controlled solenoid valves, pressure regulators, etc.) to control fluid flow on-chip. This expensive, bulky, and power-consuming hardware severely limits the utility of microfluidic instruments in resource-limited or point-of-care contexts, where the cost, size, and power consumption of the instrument must be limited. In this work, we present a technique for on-chip fluid control that requires no off-chip hardware. We accomplish this by using inert compounds to change the density of one fluid in the chip. If one fluid is made 2% more dense than a second fluid, when the fluids flow together under laminar flow the interface between the fluids quickly reorients to be orthogonal to Earth's gravitational force. If the channel containing the fluids then splits into two channels, the amount of each fluid flowing into each channel is precisely determined by the angle of the channels relative to gravity. Thus, any fluid can be routed in any direction and mixed in any desired ratio on-chip simply by holding the chip at a certain angle. This approach allows for sophisticated control of on-chip fluids with no off-chip control hardware, significantly reducing the cost of microfluidic instruments in point-of-care or resource-limited settings.