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Optical scattering poses a significant challenge to high-resolution microscopy within deep tissue. To accurately predict the performance of various microscopy techniques in thick samples, we present a computational model that efficiently solves Maxwell’s equation in highly scattering media. This toolkit simulates the deterioration of the laser beam point spread function (PSF) without making a paraxial approximation, enabling accurate modeling of high-numerical-aperture (NA) objective lenses commonly employed in experiments. Moreover, this framework is applicable to a broad range of scanning microscopy techniques including confocal microscopy, stimulated emission depletion (STED) microscopy, and ground-state depletion microscopy. Notably, the proposed method requires only readily obtainable macroscopic tissue parameters. As a practical demonstration, we investigate the performance of Laguerre–Gaussian (LG) versus Hermite–Gaussian (HG) depletion beams in STED microscopy. 

Abstract Printable and wearable plant sensors offer an approach for collecting critical environmental data at high spatial resolution to understand plant conditions and aid land management practices. Here, screen printed capacitive devices that can measure relative humidity (RH) directly at the plant‐environment interface, are demonstrated in an ultra‐thin (<6 µm) form factor. Using screen printing and a temporary tattoo transfer process, a simple technique is established to: 1) enclose printed electronic features between two layers of ethyl cellulose (EtC), 2) mount printed microparticle carbon‐based electronics onto a variety of plant structures, and 3) dramatically increase the capacitance and sensitivity for humidity sensors when compared to unencapsulated devices. This sandwich tattoo capacitor (STC) platform exhibits an RH sensitivity up to 1000 pF/%RH and stability while mounted to living plant leaves over several days. Electrochemical impedance spectroscopy (EIS) validates the formation of electric double layers within the EtC films that encapsulate the printed electrodes providing tunable capacitance values based on the ionic concentration of the device transfer fluid. 

3D‐printed polymer blends with programmable mechanical and compositional heterogeneity were fabricated using grayscale digital light processing by spatially modulating the intensity of light during printing and swelling the resulting part with a second monomer. A rubbery poly(ethylene glycol) diacrylate functionally graded print is variably swollen with acrylamide monomer as a function of crosslinking density. Following a secondary polymerization, a 3D‐printed functionally graded blend with regions of varying composition and stiffness was formed. A deterministic model for polymer conversion informs printing conditions to correspond with predicted material properties based upon local volume fractions of the two materials. Upon the secondary polymerization, two networks are present within the printed structure including glassy and rubbery regions. The compressive moduli of local regions within prints ranges from 76 to 200 MPa and measured moduli of the structures agree with predicted values acquired using finite element analysis. A lattice structure with prescribed local stiffness printed using grayscale exposures deforms differentially when compressed. Advantageously, local dimensional deformations caused by the removal of the unreacted printing monomer are eliminated due to the introduction of the second polymer. This method provides predictive control over local mechanical properties and high shape precision while maintaining the simplicity of vat photopolymerization. 

Abstract A rapid and facile approach to predictably control integration between two materials with divergent properties is introduced. Programmed integration between photopolymerizable soft and stiff hydrogels is investigated due to their promise in applications such as tissue engineering where heterogeneous properties are often desired. The spatial control afforded by grayscale 3D printing is leveraged to define regions at the interface that permit diffusive transport of a second material in‐filled into the 3D printed part. The printing parameters (i.e., effective exposure dose) for the resin are correlated directly to mesh size to achieve controlled diffusion. Applying this information to grayscale exposures leads to a range of distances over which integration is achieved with high fidelity. A prescribed finite distance of integration between soft and stiff hydrogels leads to a 33% increase in strain to failure under tensile testing and eliminates failure at the interface. The feasibility of this approach is demonstrated in a layer‐by‐layer 3D printed part fabricated by stereolithography, which is subsequently infilled with a soft hydrogel containing osteoblastic cells. In summary, this approach holds promise for applications where integration of multiple materials and living cells is needed by allowing precise control over integration and reducing mechanical failure at contrasting material interfaces. 

Abstract Implantable electrophoretic drug delivery devices have shown promise for applications ranging from treating pathologies such as epilepsy and cancer to regulating plant physiology. Upon applying a voltage, the devices electrophoretically transport charged drug molecules across an ion‐conducting membrane out to the local implanted area. This solvent‐flow‐free “dry” delivery enables controlled drug release with minimal pressure increase at the outlet. However, a major challenge these devices face is limiting drug leakage in their idle state. Here, a method of reducing passive drug leakage through the choice of the drug co‐ion is presented. By switching acetylcholine's associated co‐ion from chloride to carboxylate co‐ions as well as sulfopropyl acrylate‐based polyanions, steady‐state drug leakage rate is reduced up to sevenfold with minimal effect on the active drug delivery rate. Numerical simulations further illustrate the potential of this method and offer guidance for new material systems to suppress passive drug leakage in electrophoretic drug delivery devices. 

Abstract Low‐cost biosensors that can rapidly and widely monitor plant nutritional levels will be critical for better understanding plant health and improving precision agriculture decision making. In this work, fully printed ion‐selective organic electrochemical transistors (OECTs) that can detect macronutrient concentrations in whole plant sap are described. Potassium, the most concentrated cation in the majority of plants, is selected as the target analyte as it plays a critical role in plant growth and development. The ion sensors demonstrate high current (170 µA dec⁻¹) and voltage (99 mV dec⁻¹) sensitivity, and a low limit of detection (10 × 10⁻⁶ m). These OECT biosensors can be used to determine potassium concentration in raw sap and sap‐like aqueous environments demonstrating a log‐linear response within the expected physiological range of cations in plants. The performance of these printed devices enables their use in high‐throughput plant health monitoring in agricultural and ecological applications.