Decoding early stress signaling waves in living plants using nanosensor multiplexing

Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.

Single-Molecule Methane Sensing Using Palladium-Functionalized nIR Fluorescent Single-Walled Carbon Nanotubes

There has been considerable interest in detecting atmospheric and process-associated methane (CH4) at low concentrations due to its potency as a greenhouse gas. Nanosensor technology, particularly fluorescent single-walled carbon nanotube (SWCNT) arrays, is promising for such applications because of their chemical sensitivities at single-molecule detection limits. However, the methodologies for connecting the stochastic molecular fluctuations from gas impingement on such sensors require further development. In this work, we synthesize Pd-conjugated ss(GT)15-DNA-wrapped SWCNTas near-infrared (nIR) fluorescent, single-molecule sensors of CH4. The complexes are characterized using X-ray photoelectron spectroscopy (XPS) and spectrophotometry, demonstrating spectral changes between the Pd2+ and Pd0 oxidation states. The nIR fluctuations generated upon exposure from 8 to 26 ppb of CH4 were separated into high- and low-frequency components. Aggregating the low-frequency components for an array of sensors showed the most consistent levels of detection with a limit of 0.7 ppb. These results advance the hardware and computational methods necessary to apply this approach to the challenge of environmental methane sensing.

In Silico Investigation of the Clinical Translatability of Competitive Clearance Glucose-Responsive Insulins

The glucose-responsive insulin (GRI) MK-2640 from Merck was a pioneer in its class to enter the clinical stage, having demonstrated promising responsiveness in in vitro and preclinical studies via a novel competitive clearance mechanism (CCM). The smaller pharmacokinetic response in humans motivates the development of new predictive, computational tools that can improve the design of therapeutics such as GRIs. Herein, we develop and use a new computational model, IM3PACT, based on the intersection of human and animal model glucoregulatory systems, to investigate the clinical translatability of CCM GRIs based on existing preclinical and clinical data of MK-2640 and regular human insulin (RHI). Simulated multi-glycemic clamps not only validated the earlier hypothesis of insufficient glucose-responsive clearance capacity in humans but also uncovered an equally important mismatch between the in vivo competitiveness profile and the physiological glycemic range, which was not observed in animals. Removing the inter-species gap increases the glucose-dependent GRI clearance from 13.0% to beyond 20% for humans and up to 33.3% when both factors were corrected. The intrinsic clearance rate, potency, and distribution volume did not apparently compromise the translation. The analysis also confirms a responsive pharmacokinetics local to the liver. By scanning a large design space for CCM GRIs, we found that the mannose receptor physiology in humans remains limiting even for the most optimally designed candidate. Overall, we show that this computational approach is able to extract quantitative and mechanistic information of value from a posteriori analysis of preclinical and clinical data to assist future therapeutic discovery and development.

Rational Design and Efficacy of Glucose-Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models

Glucose-responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose-mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose-responsive particles, and 3) glucose-responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose-responsive systems, providing a useful approach for future GRI development.

Wearable sensors for monitoring marine environments and their inhabitants

Human societies depend on marine ecosystems, but their degradation continues. Toward mitigating this decline, new and more effective ways to precisely measure the status and condition of marine environments are needed alongside existing rebuilding strategies. Here, we provide an overview of how sensors and wearable technology developed for humans could be adapted to improve marine monitoring. We describe barriers that have slowed the transition of this technology from land to sea, update on the developments in sensors to advance ocean observation and advocate for more widespread use of wearables on marine organisms in the wild and in aquaculture. We propose that large-scale use of wearables could facilitate the concept of an 'internet of marine life' that might contribute to a more robust and effective observation system for the oceans and commercial aquaculture operations. These observations may aid in rationalizing strategies toward conservation and restoration of marine communities and habitats.

Colloidal robotics

Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.

Single-Crystal 2D Covalent Organic Frameworks for Plant Biotechnology

Molecules chemically synthesized as periodic two-dimensional (2D) frameworks via covalent bonds can form some of the highest-surface area and -charge density particles possible. There is significant potential for applications such as nanocarriers in life sciences if biocompatibility can be achieved; however, significant synthetic challenges remain in avoiding kinetic traps from disordered linking during 2D polymerization of compatible monomers, resulting in isotropic polycrystals without a long-range order. Here, we establish thermodynamic control over dynamic control on the 2D polymerization process of biocompatible imine monomers by minimizing the surface energy of nuclei. As a result, polycrystal, mesocrystal, and single-crystal 2D covalent organic frameworks (COFs) are obtained. We achieve COF single crystals by exfoliation and minification methods, forming high-surface area nanoflakes that can be dispersed in aqueous medium with biocompatible cationic polymers. We find that these 2D COF nanoflakes with high surface area are excellent plant cell nanocarriers that can load bioactive cargos, such as the plant hormone abscisic acid (ABA) via electrostatic attraction, and deliver them into the cytoplasm of intact living plants, traversing through the cell wall and cell membrane due to their 2D geometry. This synthetic route to high-surface area COF nanoflakes has promise for life science applications including plant biotechnology.

Design of Biodegradable, Climate-Specific Packaging Materials That Sense Food Spoilage and Extend Shelf Life

The AgriFood systems in tropical climates are under strain due to a rapid increase in human population and extreme environmental conditions that limit the efficacy of packaging technologies to extend food shelf life and guarantee food safety. To address these challenges, we rationally designed biodegradable packaging materials that sense spoilage and prevent molding. We nanofabricated the interface of 2D covalent organic frameworks (COFs) to reinforce silk fibroin (SF) and obtain biodegradable membranes with augmented mechanical properties and that displayed an immediate colorimetric response (within 1 s) to food spoilage, using packaged poultry as an example. Loading COF with antimicrobial hexanal also mitigated biotic spoilage in high-temperature and -humidity conditions, resulting in a four-order of magnitude decrease in the total amount of mold growth in soybeans packaged in silk-COF, when compared to cling film (i.e., polyethylene). Together, the integration of sensing, structural reinforcement, and antimicrobial agent delivery within a biodegradable nanocomposite framework defines climate-specific packaging materials that can decrease food waste and enhance food safety.

In-Vivo fluorescent nanosensor implants based on hydrogel-encapsulation: investigating the inflammation and the foreign-body response

Nanotechnology-enabled sensors or nanosensors are emerging as promising new tools for various in-vivo life science applications such as biosensing, components of delivery systems, and probes for spatial bioimaging. However, as with a wide range of synthetic biomaterials, tissue responses have been observed depending on cell types and various nanocomponent properties. The tissue response is critical for determining the acute and long term health of the organism and the functional lifetime of the material in-vivo. While nanomaterial properties can contribute significantly to the tissue response, it may be possible to circumvent adverse reactions by formulation of the encapsulation vehicle. In this study, five formulations of poly (ethylene glycol) diacrylate (PEGDA) hydrogel-encapsulated fluorescent nanosensors were implanted into SKH-1E mice, and the inflammatory responses were tracked in order to determine the favorable design rules for hydrogel encapsulation and minimization of such responses. Hydrogels with higher crosslinking density were found to allow faster resolution of acute inflammation. Five different immunocompromised mice lines were utilized for comparison across different inflammatory cell populations and responses. Degradation products of the gels were also characterized. Finally, the importance of the tissue response in determining functional lifetime was demonstrated by measuring the time-dependent nanosensor deactivation following implantation into animal models.

Investigations of Vacancy-Assisted Selective Detection of NO2 Molecules in Vertically Aligned SnS2

Two important methods for enhancing gas sensing performance are vacancy/defect and interlayer engineering. Tin sulfide (SnS₂) has recently attracted much attention for sensing of the NO₂ gas due to its active surface sites and tunable electronic structure. Herein, SnS₂ has been synthesized by the chemical vapor deposition (CVD) method followed by nitrogen plasma treatment with different exposure times for fast detection of NO₂ molecules. Plasma treatment created a substantial number of surface vacancies on SnS₂ flakes, which were controlled by the exposure period to modify the surface of flakes. After 12 min of nitrogen plasma treatment, SnS₂ nanoflakes show considerable improvement in NO₂ sensing characteristics, including a high sensing response of ∼264% toward 100 ppm NO₂ at 120°C. The enhancement in the relative response of the sensor is due to the electronic interaction between NO₂ molecules and the S vacancies on the surface of SnS₂. Density functional theory (DFT) computations indicate that the S-vacancy defects on the surface dominate the effective NO₂ detection and the NO₂ adsorption mechanism transition from physisorption to chemisorption. Adsorption kinetics of the NO₂ gas over SnS₂ nanoflake-based chemiresistor sensors were studied using the Lee and Strano model [ Langmuir 2005, 21(11), 5192-5196]. The irreversible rate of the reaction for various NO₂ concentrations exposed to the gas sensor is extracted using this model, which also appropriately describes the response curves. The forward rate constant of the irreversible gas sensor increased with the increase of the N₂ plasma treatment time and reached the maximum in the 12 min plasma-treated sample. Through defect engineering, this research may open up new vistas for the design and synthesis of 2D materials with enhanced sensing properties.

Fluids and Electrolytes under Confinement in Single-Digit Nanopores

Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Existing theories often fail to predict the exotic effects observed in the narrowest of such pores, called single-digit nanopores (SDNs), which have diameters or conduit widths of less than 10 nm, and have only recently become accessible for experimental measurements. What SDNs reveal has been surprising, including a rapidly increasing number of examples such as extraordinarily fast water transport, distorted fluid-phase boundaries, strong ion-correlation and quantum effects, and dielectric anomalies that are not observed in larger pores. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies at the water-energy nexus, from new membranes for precise separations and water purification to new gas permeable materials for water electrolyzers and energy-storage devices. SDNs also present unique opportunities to achieve ultrasensitive and selective chemical sensing at the single-ion and single-molecule limit. In this review article, we summarize the progress on nanofluidics of SDNs, with a focus on the confinement effects that arise in these extremely narrow nanopores. The recent development of precision model systems, transformative experimental tools, and multiscale theories that have played enabling roles in advancing this frontier are reviewed. We also identify new knowledge gaps in our understanding of nanofluidic transport and provide an outlook for the future challenges and opportunities at this rapidly advancing frontier.

Near-Infrared Fluorescent Carbon Nanotube Sensors for the Plant Hormone Family Gibberellins

Gibberellins (GAs) are a class of phytohormones, important for plant growth, and very difficult to distinguish because of their similarity in chemical structures. Herein, we develop the first nanosensors for GAs by designing and engineering polymer-wrapped single-walled carbon nanotubes (SWNTs) with unique corona phases that selectively bind to bioactive GAs, GA₃ and GA₄, triggering near-infrared (NIR) fluorescence intensity changes. Using a new coupled Raman/NIR fluorimeter that enables self-referencing of nanosensor NIR fluorescence with its Raman G-band, we demonstrated detection of cellular GA in Arabidopsis, lettuce, and basil roots. The nanosensors reported increased endogenous GA levels in transgenic Arabidopsis mutants that overexpress GA and in emerging lateral roots. Our approach allows rapid spatiotemporal detection of GA across species. The reversible sensor captured the decreasing GA levels in salt-treated lettuce roots, which correlated remarkably with fresh weight changes. This work demonstrates the potential for nanosensors to solve longstanding problems in plant biotechnology.

Observation and Isochoric Thermodynamic Analysis of Partially Water-Filled 1.32 and 1.45 nm Diameter Carbon Nanotubes

Recent measurements of fluids under extreme confinement, including water within narrow carbon nanotubes, exhibit marked deviations from continuum theoretical descriptions. In this work, we generate precise carbon nanotube replicates that are filled with water, closed from external mass transfer, and studied over a wide temperature range by Raman spectroscopy. We study segments that are empty, partially filled, and completely filled with condensed water from -80 to 120 °C. Partially filled, nanodroplet states contain submicron vapor-like and liquid-like domains and are analyzed using a Clausius-Clapeyron-type model, yielding heats of condensation of water inside closed 1.32 nm diameter carbon nanotubes (3.32 ± 0.10 kJ/mol and 3.72 ± 0.11 kJ/mol) and 1.45 nm diameter carbon nanotubes (3.50 ± 0.07 kJ/mol) that are lower than the bulk enthalpy of vaporization and closer to the bulk enthalpy of fusion. Favored partial filling fractions are calculated, highlighting the effect of subnanometer changes in confining diameter on fluid properties and suggesting the promise of molecular engineering of nanoconfined liquid/vapor interfaces for water treatment or membrane distillation.

Molecular Recognition and In Vivo Detection of Temozolomide and 5-Aminoimidazole-4-carboxamide for Glioblastoma Using Near-Infrared Fluorescent Carbon Nanotube Sensors

There is a pressing need for sensors and assays to monitor chemotherapeutic activity within the human body in real time to optimize drug dosimetry parameters such as timing, quantity, and frequency in an effort to maximize efficacy while minimizing deleterious cytotoxicity. Herein, we develop near-infrared fluorescent nanosensors based on single walled carbon nanotubes for the chemotherapeutic Temozolomide (TMZ) and its metabolite 5-aminoimidazole-4-carboxamide using Corona Phase Molecular Recognition as a synthetic molecular recognition technique. The resulting nanoparticle sensors are able to monitor drug activity in real-time even under in vivo conditions. Sensors can be engineered to be biocompatible by encapsulation in poly(ethylene glycol) diacrylate hydrogels. Selective detection of TMZ was demonstrated using U-87 MG human glioblastoma cells and SKH-1E mice with detection limits below 30 μM. As sensor implants, we show that such systems can provide spatiotemporal therapeutic information in vivo, as a valuable tool for pharmacokinetic evaluation. Sensor implants are also evaluated using intact porcine brain tissue implanted 2.1 cm below the cranium and monitored using a recently developed Wavelength-Induced Frequency Filtering technique. Additionally, we show that by taking the measurement of spatial and temporal analyte concentrations within each hydrogel implant, the direction of therapeutic flux can be resolved. In all, these types of sensors enable the real time detection of chemotherapeutic concentration, flux, directional transport, and metabolic activity, providing crucial information regarding therapeutic effectiveness.

Discretized hexagonal boron nitride quantum emitters and their chemical interconversion

Quantum emitters in two-dimensional hexagonal boron nitride (hBN) are of significant interest because of their unique photophysical properties, such as single-photon emission at room temperature, and promising applications in quantum computing and communications. The photoemission from hBN defects covers a wide range of emission energies but identifying and modulating the properties of specific emitters remain challenging due to uncontrolled formation of hBN defects. In this study, more than 2000 spectra are collected consisting of single, isolated zero-phonon lines (ZPLs) between 1.59 and 2.25 eV from diverse sample types. Most of ZPLs are organized into seven discretized emission energies. All emitters exhibit a range of lifetimes from 1 to 6 ns, and phonon sidebands offset by the dominant lattice phonon in hBN near 1370 cm^-1. Two chemical processing schemes are developed based on water and boric acid etching that generate or preferentially interconvert specific emitters, respectively. The identification and chemical interconversion of these discretized emitters should significantly advance the understanding of solid-state chemistry and photophysics of hBN quantum emission.

Emergent microrobotic oscillators via asymmetry-induced order

Spontaneous oscillations on the order of several hertz are the drivers of many crucial processes in nature. From bacterial swimming to mammal gaits, converting static energy inputs into slowly oscillating power is key to the autonomy of organisms across scales. However, the fabrication of slow micrometre-scale oscillators remains a major roadblock towards fully-autonomous microrobots. Here, we study a low-frequency oscillator that emerges from a collective of active microparticles at the air-liquid interface of a hydrogen peroxide drop. Their interactions transduce ambient chemical energy into periodic mechanical motion and on-board electrical currents. Surprisingly, these oscillations persist at larger ensemble sizes only when a particle with modified reactivity is added to intentionally break permutation symmetry. We explain such emergent order through the discovery of a thermodynamic mechanism for asymmetry-induced order. The on-board power harvested from the stabilised oscillations enables the use of electronic components, which we demonstrate by cyclically and synchronously driving a microrobotic arm. This work highlights a new strategy for achieving low-frequency oscillations at the microscale, paving the way for future microrobotic autonomy.

Spontaneous low-frequency oscillations, which are a feature of biological systems, are challenging to engineer into microrobotic systems. The authors discover a mechanism for asymmetry-induced order and realise electrical and mechanical oscillations in a particle collective to power a microrobotic arm.

Gas Separations using Nanoporous Atomically Thin Membranes: Recent Theoretical, Simulation, and Experimental Advances

Porous graphene and other atomically thin 2D materials are regarded as highly promising membrane materials for high-performance gas separations due to their atomic thickness, large-scale synthesizability, excellent mechanical strength, and chemical stability. When these atomically thin materials contain a high areal density of gas-sieving nanoscale pores, they can exhibit both high gas permeances and high selectivities, which is beneficial for reducing the cost of gas-separation processes. Here, recent modeling and experimental advances in nanoporous atomically thin membranes for gas separations is discussed. The major challenges involved, including controlling pore size distributions, scaling up the membrane area, and matching theory with experimental results, are also highlighted. Finally, important future directions are proposed for real gas-separation applications of nanoporous atomically thin membranes.

Universal Kinetic Mechanism Describing CO2 Photoreductive Yield and Selectivity for Semiconducting Nanoparticle Photocatalysts

Photocatalytic conversion of CO₂ to generate high-value and renewable chemical fuels and feedstock presents a sustainable and renewable alternative to fossil fuels and petrochemicals. Currently, there is a dearth of kinetic understanding to inform better catalyst design, especially at uniform reaction conditions across diverse catalytic species. In this work, we investigate 12 active, stable, and unique but common nanoparticle photocatalysts for CO₂ reduction at room temperature and low partial pressure in aqueous phase: TiO₂, SnO₂, and SiC deposited with silver, gold, and platinum. Our analysis reveals a single consistent chemical kinetic mechanism, which accurately describes the yield and selectivity of all single-carbon containing (C1) products obtained in spite of the diverse catalysts employed. Formaldehyde is predicted as the first product in the reaction network and we report, to the best of our knowledge, the highest selectivity to date toward formaldehyde during CO₂ photoreduction when compared against all other C1 products (∼80%) albeit at low CO₂ conversion (<0.5 μmol g_cat^-1 h^-1, <16.8 nmol m^-2 h^-1). Further, we observe a volcano-like relationship between the electron-transfer rate of a given photocatalyst for CO₂ reduction and the net rate at which reduced products are produced in the reaction mixture taking into account unfavorable product oxidation. We establish an empirical upper limit for the maximum rate of production of CO₂ reduction products for any nanoparticle photocatalyst in the absence of a hole-scavenging agent. These results form the basis for the design and optimization of the next generation of highly efficiency and active photocatalysts for CO₂ reduction.

Biological Impacts of Reduced Graphene Oxide Affected by Protein Corona Formation

Applications of reduced graphene oxide (rGO) in many different areas have been gradually increasing owing to its unique physicochemical characteristics, demanding more understanding of their biological impacts. Herein, we assessed the toxicological effects of rGO in mammary epithelial cells. Because the as-synthesized rGO was dissolved in sodium cholate to maintain a stable aqueous dispersion, we hypothesize that changing the cholate concentration in the dispersion may alter the surface property of rGO and subsequently affect its cellular toxicity. Thus, four types of rGO were prepared and compared: rGO dispersed in 4 and 2 mg/mL sodium cholate, labeled as rGO and concentrated-rGO (c-rGO), respectively, and rGO and c-rGO coated with a protein corona through 1 h incubation in culture media, correspondingly named pro-rGO and pro-c-rGO. Notably, c-rGO and pro-c-rGO exhibited higher toxicity than rGO and pro-rGO and also caused higher reactive oxygen species production, more lipid membrane peroxidation, and more significant disruption of mitochondrial-based ATP synthesis. In all toxicological assessments, pro-c-rGO induced more severe adverse impacts than c-rGO. Further examination of the material surface, protein adsorption, and cellular uptake showed that the surface of c-rGO was coated with a lower content of surfactant and adsorbed more proteins, which may result in the higher cellular uptake observed with pro-c-rGO than pro-rGO. Several proteins involved in cellular redox mediation were also more enriched in pro-c-rGO. These results support the strong correlation between dispersant coating and corona formation and their subsequent cellular impacts. Future studies in this direction could reveal a deeper understanding of the correlation and the specific cellular pathways involved and help gain knowledge on how the toxicity of rGO could be modulated through surface modification, guiding the sustainable applications of rGO.

A wavelength-induced frequency filtering method for fluorescent nanosensors in vivo

Fluorescent nanosensors hold the potential to revolutionize life sciences and medicine. However, their adaptation and translation into the in vivo environment is fundamentally hampered by unfavourable tissue scattering and intrinsic autofluorescence. Here we develop wavelength-induced frequency filtering (WIFF) whereby the fluorescence excitation wavelength is modulated across the absorption peak of a nanosensor, allowing the emission signal to be separated from the autofluorescence background, increasing the desired signal relative to noise, and internally referencing it to protect against artefacts. Using highly scattering phantom tissues, an SKH1-E mouse model and other complex tissue types, we show that WIFF improves the nanosensor signal-to-noise ratio across the visible and near-infrared spectra up to 52-fold. This improvement enables the ability to track fluorescent carbon nanotube sensor responses to riboflavin, ascorbic acid, hydrogen peroxide and a chemotherapeutic drug metabolite for depths up to 5.5 ± 0.1 cm when excited at 730 nm and emitting between 1,100 and 1,300 nm, even allowing the monitoring of riboflavin diffusion in thick tissue. As an application, nanosensors aided by WIFF detect the chemotherapeutic activity of temozolomide transcranially at 2.4 ± 0.1 cm through the porcine brain without the use of fibre optic or cranial window insertion. The ability of nanosensors to monitor previously inaccessible in vivo environments will be important for life-sciences research, therapeutics and medical diagnostics.

Size Selective Corona Interactions from Self-Assembled Rosette and Single-Walled Carbon Nanotubes

Nanoparticle corona phases, especially those surrounding anisotropic particles, are central to determining their catalytic, molecular recognition, and interfacial properties. It remains a longstanding challenge to chemically synthesize and control such phases at the nanoparticle surface. In this work, the supramolecular chemistry of rosette nanotubes (RNTs), well-defined hierarchically self-assembled nanostructures formed from heteroaromatic bicyclic bases, is used to create molecularly precise and continuous corona phases on single-walled carbon nanotubes (SWCNTs). These RNT-SWCNT (RS) complexes exhibit the lowest solvent-exposed surface area (147.8 ± 60 m^-1 ) measured to date due to its regular structure. Through Raman spectroscopy, molecular-scale control of the free volume is also observed between the two annular structures and the effects of confined water. SWCNT photoluminescence (PL) within the RNT is also modulated considerably as a function of their diameter and chirality, especially for the (11, 1) species, where a PL increase compared to other species can be attributed to their chiral angle and the RNT's inward facing electron densities. In summary, RNT chemistry is extended to the problem of chemically defining both the exterior and interior corona interfaces of an encapsulated particle, thereby opening the door to precision control of core-shell nanoparticle interfaces.

Irreversible synthesis of an ultrastrong two-dimensional polymeric material

Polymers that extend covalently in two dimensions have attracted recent attention^1,2 as a means of combining the mechanical strength and in-plane energy conduction of conventional two-dimensional (2D) materials^3,4 with the low densities, synthetic processability and organic composition of their one-dimensional counterparts. Efforts so far have proven successful in forms that do not allow full realization of these properties, such as polymerization at flat interfaces^5,6 or fixation of monomers in immobilized lattices^7-9. Another frequently employed synthetic approach is to introduce microscopic reversibility, at the cost of bond stability, to achieve 2D crystals after extensive error correction^10,11. Here we demonstrate a homogenous 2D irreversible polycondensation that results in a covalently bonded 2D polymeric material that is chemically stable and highly processable. Further processing yields highly oriented, free-standing films that have a 2D elastic modulus and yield strength of 12.7 ± 3.8 gigapascals and 488 ± 57 megapascals, respectively. This synthetic route provides opportunities for 2D materials in applications ranging from composite structures to barrier coating materials.

Thermally fluctuating, semiflexible sheets in simple shear flow

We perform Brownian dynamics simulations of semiflexible colloidal sheets with hydrodynamic interactions and thermal fluctuations in shear flow. As a function of the ratio of bending rigidity to shear energy (a dimensionless quantity we denote S) and the ratio of bending rigidity to thermal energy, we observe a dynamical transition from stochastic flipping to crumpling and continuous tumbling. This dynamical transition is broadened by thermal fluctuations, and the value of S at which it occurs is consistent with the onset of chaotic dynamics found for athermal sheets. The effects of different dynamical conformations on rheological properties such as viscosity and normal stress differences are also quantified. Namely, the viscosity in a dilute dispersion of sheets is found to decrease with increasing shear rate (shear-thinning) up until the dynamical crumpling transition, at which point it increases again (shear-thickening), and non-zero first normal stress differences are found that exhibit a local maximum with respect to temperature at large S (small shear rate). These results shed light on the dynamical behavior of fluctuating 2D materials dispersed in fluids and should greatly inform the design of associated solution processing methods.

Approximate Corona Phase Hamiltonian for Individual Cylindrical Nanoparticle-Polymer Interactions

Nanoparticle surfaces, such as cylindrical nanowires and carbon nanotubes, are commonly coated with adsorbed polymer corona phases to impart solution stabilization and to control molecular interactions. These adsorbed polymer molecules (biological or otherwise), also known as the corona phase, are critical to engineering particle and molecular interactions. However, the prediction of its structure and the corresponding properties remains an unresolved problem in polymer physics. In this work, we construct a Hamiltonian describing the adsorption of an otherwise linear polymer to the surface of a cylindrical nanorod in the form of an integral equation summing up the energetic contributions corresponding to polymer bending, confinement, solvation, and electrostatics. We introduce an approximate functional that allows for the solution of the minimum energy configuration in the strongly bound limit. The functional is shown to predict the pitch and surface area of observed helical corona phases in the literature based on the surface binding energy and persistence length alone. This approximate functional also predicts and quantitatively describes the recently observed ionic strength-mediated phase transitions of charged polymer corona at carbon nanotube surfaces. The Hamiltonian and the approximate functional provide the first theoretical link between the polymer's mechanical and chemical properties and the resulting adsorbed phase configuration and therefore should find widespread utility in predicting corona phase structures around anisotropic nanoparticles.

High Thermal Effusivity Nanocarbon Materials for Resonant Thermal Energy Harvesting

Carbon nanomaterials have extraordinary thermal properties, such as high conductivity and stability. Nanocarbon combined with phase change materials (PCMs) can yield exceptionally high thermal effusivity composites optimal for thermal energy harvesting. The progress in synthesis and processing of high effusivity materials, and their application in resonant energy harvesting from temperature variations is reviewed.

Antibody-Free Rapid Detection of SARS-CoV-2 Proteins Using Corona Phase Molecular Recognition to Accelerate Development Time

To develop better analytical approaches for future global pandemics, it is widely recognized that sensing materials are necessary that enable molecular recognition and sensor assay development on a much faster scale than currently possible. Previously developed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) point-of-care devices are based on the specific molecular recognition using subunit protein antibodies and protein receptors that selectively capture the viral proteins. However, these necessarily involve complex and lengthy development and processing times and are notoriously prone to a loss of biological activity upon sensor immobilization and device interfacing, potentially limiting their use in applications at scale. Here, we report a synthetic strategy for nanoparticle corona interfaces that enables the molecular recognition of SARS-CoV-2 proteins without any antibody and receptor design. Our nanosensor constructs consist of poly(ethylene glycol) (PEG)─phospholipid heteropolymers adsorbed onto near-infrared (nIR) fluorescent single-walled carbon nanotubes (SWCNTs) that recognize the nucleocapsid (N) and spike (S) protein of SARS-CoV-2 using unique three-dimensional (3D) nanosensor interfaces. This results in rapid and label-free nIR fluorescence detection. This antibody-free nanosensor shows up to 50% sensor responses within 5 min of viral protein injections with limit of detection (LOD) values of 48 fM and 350 pM for N and S proteins, respectively. Finally, we demonstrate instrumentation based on a fiber-optic platform that interfaces the advantages of antibody-free molecular recognition and biofluid compatibility in human saliva conditions.

Direct Chemical Vapor Deposition Synthesis of Porous Single-Layer Graphene Membranes with High Gas Permeances and Selectivities

Single-layer graphene containing molecular-sized in-plane pores is regarded as a promising membrane material for high-performance gas separations due to its atomic thickness and low gas transport resistance. However, typical etching-based pore generation methods cannot decouple pore nucleation and pore growth, resulting in a trade-off between high areal pore density and high selectivity. In contrast, intrinsic pores in graphene formed during chemical vapor deposition are not created by etching. Therefore, intrinsically porous graphene can exhibit high pore density while maintaining its gas selectivity. In this work, the density of intrinsic graphene pores is systematically controlled for the first time, while appropriate pore sizes for gas sieving are precisely maintained. As a result, single-layer graphene membranes with the highest H₂ /CH₄ separation performances recorded to date (H₂ permeance > 4000 GPU and H₂ /CH₄ selectivity > 2000) are fabricated by manipulating growth temperature, precursor concentration, and non-covalent decoration of the graphene surface. Moreover, it is identified that nanoscale molecular fouling of the graphene surface during gas separation where graphene pores are partially blocked by hydrocarbon contaminants under experimental conditions, controls both selectivity and temperature dependent permeance. Overall, the direct synthesis of porous single-layer graphene exploits its tremendous potential as high-performance gas-sieving membranes.

Biotransformations and cytotoxicity of eleven graphene and inorganic two-dimensional nanomaterials using simulated digestions coupled with a triculture in vitro model of the human gastrointestinal epithelium

Background

Engineered nanomaterials (ENMs) have already made their way into myriad applications and products across multiple industries. However, the potential health risks of exposure to ENMs remain poorly understood. This is particularly true for the emerging class of ENMs know as 2-dimensional nanomaterials (2DNMs), with a thickness of one or a few layers of atoms arranged in a planar structure.

Methods

The present study assesses the biotransformations and in vitro cytotoxicity in the gastrointestinal tract of 11 2DNMs, namely graphene, graphene oxide (GO), partially reduced graphene oxide (prGO), reduced graphene oxide (rGO), hexagonal boron nitride (h-BN), molybdenum disulphide (MoS2), and tungsten disulphide (WS2). The evaluated pristine materials were either readily dispersed in water or dispersed with the use of a surfactant (Na-cholate or PF108). Materials dispersed in a fasting food model (FFM, water) were subjected to simulated 3-phase (oral, gastric, and small intestinal) digestion to replicate the biotransformations that would occur in the GIT after ingestion. A triculture model of small intestinal epithelium was used to assess the effects of the digested products (digestas) on epithelial layer integrity, cytotoxicity, viability, oxidative stress, and initiation of apoptosis.

Results

Physicochemical characterization of the 2DNMs in FFM dispersions and in small intestinal digestas revealed significant agglomeration by all materials during digestion, most prominently by graphene, which was likely caused by interactions with digestive proteins. Also, MoS2 had dissolved by ~75% by the end of simulated digestion. Other than a low but statistically significant increase in cytotoxicity observed with all inorganic materials and graphene dispersed in PF108, no adverse effects were observed in the exposed tricultures.

Conclusions

Our results suggest that occasional ingestion of small quantities of 2DNMs may not be highly cytotoxic in a physiologically relevant in vitro model of the intestinal epithelium. Still, their inflammatory or genotoxic potential after short- or long-term ingestion remains unclear and needs to be studied in future in vitro and in vivo studies. These would include studies of effects on co-ingested nutrient digestion and absorption, which have been documented for numerous ingested ENMs, as well as effects on the gut microbiome, which can have important health implications.

Augmenting the living plant mesophyll into a photonic capacitor

Living plants provide an opportunity to rethink the design and fabrication of devices ordinarily produced from plastic and circuit boards and ultimately disposed of as waste. The spongy mesophyll is a high -surface area composition of parenchyma cells that supports gas and liquid exchange through stomata pores within the surface of most leaves. Here, we investigate the mesophyll of living plants as biocompatible substrates for the photonic display of thin nanophosphorescent films for photonic applications. Size-sorted, silica-coated 650 ± 290 -nm strontium aluminate nanoparticles are infused into five diverse plant species with conformal display of 2-μm films on the mesophyll enabling photoemission of up to 4.8 × 10¹³ photons/second. Chlorophyll measurements over 9 days and functional testing over 2 weeks at 2016 excitation/emission cycles confirm biocompatibility. This work establishes methods to transform living plants into photonic substrates for applications in plant-based reflectance devices, signaling, and the augmentation of plant-based lighting.

Nanosensor Chemical Cytometry for Characterizing the Efflux Heterogeneity of Nitric Oxide from Macrophages

Macrophages are a critical part of the human immune response, and their collective heterogeneity is implicated in disease progression and prevention. A nondestructive, label-free tool does not currently exist for profiling the dynamic, antigenic responses of single macrophages in a collection to correlate with specific molecular expression and correlated biophysical properties at the cellular level, despite the potential for diagnosis and therapeutics. Herein, we develop a nanosensor chemical cytometry (NCC) that can profile the heterogeneity of inducible nitric oxide synthase (iNOS) responses from macrophage populations. By integrating a near-infrared (nIR) fluorescent nanosensor array and collagen layer with microfluidics, the cellular lensing effect of the macrophage was utilized to characterize both nitric oxide (NO) efflux and refractive index (RI) changes at a single-cell level. Using a parallel, multichannel approach, distinct iNOS heterogeneities of macrophages can be monitored at an attomolar (10^-18 mol) sensitivity in a nondestructive and real-time manner with a throughput of exceeding the 200 cells/frame. We demonstrate that estimated mean NO efflux rates of macrophage populations are elevated from 342 (σ = 199) to 464 (σ = 206) attomol/cell·hr with a 3% larger increase in the heterogeneity, and estimated RI of macrophage decrease from 1.366 (σ = 0.015) to 1.359 (σ = 0.009) with trimodal subpopulations under lipopolysaccharide (LPS) activation. These measured values are also in good agreement with Griess assay results and previously reported measurements. This work provides an efficient strategy for single-cell analysis of macrophage populations for cellular manufacturing and biopharmaceutical engineering.

Transcutaneous Measurement of Essential Vitamins Using Near-Infrared Fluorescent Single-Walled Carbon Nanotube Sensors

Vitamins such as riboflavin and ascorbic acid are frequently utilized in a range of biomedical applications as drug delivery targets, fluidic tracers, and pharmaceutical excipients. Sensing these biochemicals in the human body has the potential to significantly advance medical research and clinical applications. In this work, a nanosensor platform consisting of single-walled carbon nanotubes (SWCNTs) with nanoparticle corona phases engineered to allow for the selective molecular recognition of ascorbic acid and riboflavin, is developed. The study provides a methodological framework for the implementation of colloidal SWCNT nanosensors in an intraperitoneal SKH1-E murine model by addressing complications arising from tissue absorption and scattering, mechanical perturbations, as well as sensor diffusion and interactions with the biological environment. Nanosensors are encapsulated in a polyethylene glycol diacrylate hydrogel and a diffusion model is utilized to validate analyte transport and sensor responses to local concentrations at the boundary. Results are found to be reproducible and stable after exposure to 10% mouse serum even after three days of in vivo implantation. A geometrical encoding scheme is used to reference sensor pairs, correcting for in vivo optical and mechanical artifacts, resulting in an order of magnitude improvement of p-value from 0.084 to 0.003 during analyte sensing.

A virucidal face mask based on the reverse-flow reactor concept for thermal inactivation of SARS-CoV-2

While facial coverings reduce the spread of SARS-CoV-2 by viral filtration, masks capable of viral inactivation by heating can provide a complementary method to limit transmission. Inspired by reverse-flow chemical reactors, we introduce a new virucidal face mask concept driven by the oscillatory flow of human breath. The governing heat and mass transport equations are solved to evaluate virus and CO₂ transport. Given limits imposed by the kinetics of SARS-CoV-2 thermal inactivation, human breath, safety, and comfort, heated masks may inactivate SARS-CoV-2 to medical-grade sterility. We detail one design, with a volume of 300 ml at 90°C that achieves a 3-log reduction in viral load with minimal impedance within the mask mesh, with partition coefficient around 2. This is the first quantitative analysis of virucidal thermal inactivation within a protective face mask, and addresses a pressing need for new approaches for personal protective equipment during a global pandemic.

SynCells: A 60 × 60 μm2 Electronic Platform with Remote Actuation for Sensing Applications in Constrained Environments

Autonomous electronic microsystems smaller than the diameter of a human hair (<100 μm) are promising for sensing in confined spaces such as microfluidic channels or the human body. However, they are difficult to implement due to fabrication challenges and limited power budget. Here we present a 60 × 60 μm electronic microsystem platform, or SynCell, that overcomes these issues by leveraging the integration capabilities of two-dimensional material circuits and the low power consumption of passive germanium timers, memory-like chemical sensors, and magnetic pads. In a proof-of-concept experiment, we magnetically positioned SynCells in a microfluidic channel to detect putrescine. After we extracted them from the channel, we successfully read out the timer and sensor signal, the latter of which can be amplified by an onboard transistor circuit. The concepts developed here will be applicable to microsystems targeting a variety of applications from microfluidic sensing to biomedical research.

Cellular lensing and near infrared fluorescent nanosensor arrays to enable chemical efflux cytometry

Nanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry.

Chemical kinetic mechanisms and scaling of two-dimensional polymers via irreversible solution-phase reactions

Two-dimensional (2D) polymers are extended networks of multi-functional repeating units that are covalently linked together but confined to a single plane. The past decade has witnessed a surge in interest and effort toward producing and utilizing 2D polymers. However, facile synthesis schemes suitable for mass production are yet to be realized. In addition, unifying theories to describe the 2D polymerization process, such as those for linear polymers, have not yet been established. Herein, we perform a chemical kinetic simulation to study the recent synthesis of 2D polymers in homogeneous solution with irreversible chemistry. We show that reaction sites for polymerization in 2D always scale unfavorably compared to 3D, growing as molecular weight to the 1/2 power vs 2/3 power for 3D. However, certain mechanisms can effectively suppress out-of-plane defect formation and subsequent 3D growth. We consider two such mechanisms, which we call bond-planarity and templated autocatalysis. In the first, although single bonds can easily rotate out-of-plane to render polymerization in 3D, some double-bond linkages prefer a planar configuration. In the second mechanism, stacked 2D plates may act as van der Waals templates for each other to enhance growth, which leads to an autocatalysis. When linkage reactions possess a 1000:1 selectivity (γ) for staying in plane vs rotating, solution-synthesized 2D polymers can have comparable size and yield with those synthesized from confined polymerization on a surface. Autocatalysis could achieve similar effects when self-templating accelerates 2D growth by a factor β of 10⁶. A combined strategy relaxes the requirement of both mechanisms by over one order of magnitude. We map the dependence of molecular weight and yield for the 2D polymer on the reaction parameters, allowing experimental results to be used to estimate β and γ. Our calculations show for the first time from theory the feasibility of producing two-dimensional polymers from irreversible polymerization in solution.

Buckling, crumpling, and tumbling of semiflexible sheets in simple shear flow

As 2D materials such as graphene, transition metal dichalcogenides, and 2D polymers become more prevalent, solution processing and colloidal-state properties are being exploited to create advanced and functional materials. However, our understanding of the fundamental behavior of 2D sheets and membranes in fluid flow is still lacking. In this work, we perform numerical simulations of athermal semiflexible sheets with hydrodynamic interactions in shear flow. For sheets initially oriented near the flow-vorticity plane, we find buckling instabilities of different mode numbers that vary with bending stiffness and can be understood with a quasi-static model of elasticity. For different initial orientations, chaotic tumbling trajectories are observed. Notably, we find that sheets fold or crumple before tumbling but do not stretch again upon applying greater shear.

Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion

A central ambition of the robotics field has been to increasingly miniaturize such systems, with perhaps the ultimate achievement being the synthetic microbe or cell sized machine. To this end, we have introduced and demonstrated prototypes of what we call colloidal state machines (CSMs) as particulate devices capable of integrating sensing, memory, and energy harvesting as well as other functions onto a single particle. One technique that we have introduced for creating CSMs based on 2D materials such as graphene or monolayer MoS₂ is "autoperforation", where the nanometer-scale film is fractured around a designed strain field to produce structured particles upon liftoff. While CSMs have been demonstrated with functions such as memory, sensing, and energy harvesting, the property of locomotion has not yet been demonstrated. In this work, we introduce an inversion moulding technique compatible with autoperforation that allows for the patterning of an external catalytic surface that enables locomotion in an accompanying fuel bath. Optimal processing conditions for electroplating a catalytic Pt layer to one side of an autoperforated CSM are elucidated. The self-driven propulsion of the resulting Janus CSM in H₂O₂ is studied, including the average velocity, as a function of fluid surface tension and H₂O₂ concentration in the bath. Since machines have to encode for a specific task, this work summarizes efforts to create a microfluidic testbed that allows for CSM designs to be evaluated for the ultimate purpose of navigation through complex fluidic networks, such as the human circulatory system. We introduce two CSM designs that mimic aspects of human immunity to solve search and recruitment tasks in such environments. These results advance CSM design concepts closer to promising applications in medicine and other areas.

Diameter Dependence of Water Filling in Lithographically Segmented Isolated Carbon Nanotubes

Although the structure and properties of water under conditions of extreme confinement are fundamentally important for a variety of applications, they remain poorly understood, especially for dimensions less than 2 nm. This problem is confounded by the difficulty in controlling surface roughness and dimensionality in fabricated nanochannels, contributing to a dearth of experimental platforms capable of carrying out the necessary precision measurements. In this work, we utilize an experimental platform based on the interior of lithographically segmented, isolated single-walled carbon nanotubes to study water under extreme nanoscale confinement. This platform generates multiple copies of nanotubes with identical chirality, of diameters from 0.8 to 2.5 nm and lengths spanning 6 to 160 μm, that can be studied individually in real time before and after opening, exposure to water, and subsequent water filling. We demonstrate that, under controlled conditions, the diameter-dependent blue shift of the Raman radial breathing mode (RBM) between 1 and 8 cm^-1 measures an increase in the interior mechanical modulus associated with liquid water filling, with no response from exterior water exposure. The observed RBM shift with filling demonstrates a non-monotonic trend with diameter, supporting the assignment of a minimum of 1.81 ± 0.09 cm^-1 at 0.93 ± 0.08 nm with a nearly linear increase at larger diameters. We find that a simple hard-sphere model of water in the confined nanotube interior describes key features of the diameter-dependent modulus change of the carbon nanotube and supports previous observations in the literature. Longer segments of 160 μm show partial filling from their ends, consistent with pore clogging. These devices provide an opportunity to study fluid behavior under extreme confinement with high precision and repeatability.

Predicting Gas Separation through Graphene Nanopore Ensembles with Realistic Pore Size Distributions

The development of nanoporous single-layer graphene membranes for gas separation has prompted increasing theoretical investigations of gas transport through graphene nanopores. However, computer simulations and theories that predict gas permeances through individual graphene nanopores are not suitable to describe experimental results, because a realistic graphene membrane contains a large number of nanopores of diverse sizes and shapes. With this need in mind, here, we generate nanopore ensembles in silico by etching carbon atoms away from pristine graphene with different etching times, using a kinetic Monte Carlo algorithm developed by our group for the isomer cataloging problem of graphene nanopores. The permeances of H₂, CO₂, and CH₄ through each nanopore in the ensembles are predicted using transition state theory based on classical all-atomistic force fields. Our findings show that the total gas permeance through a nanopore ensemble is dominated by a small fraction of large nanopores with low energy barriers of pore crossing. We also quantitatively predict the increase of the gas permeances and the decrease of the selectivities between the gases as functions of the etching time of graphene. Furthermore, by fitting the theoretically predicted selectivities to the experimental ones reported in the literature, we show that nanopores in graphene effectively expand as the temperature of permeation measurement increases. We propose that this nanopore "expansion" is due to the desorption of contaminants that partially clog the graphene nanopores. In general, our study highlights the effects of the pore size and shape distributions of a graphene nanopore ensemble on its gas separation properties and calls into attention the potential effect of pore-clogging contamination in experiments.

Plant Nanobionic Sensors for Arsenic Detection

Arsenic is a highly toxic heavy-metal pollutant which poses a significant health risk to humans and other ecosystems. In this work, the natural ability of wild-type plants to pre-concentrate and extract arsenic from the belowground environment is exploited to engineer plant nanobionic sensors for real-time arsenic detection. Near-infrared fluorescent nanosensors are specifically designed for sensitive and selective detection of arsenite. These optical nanosensors are embedded in plant tissues to non-destructively access and monitor the internal dynamics of arsenic taken up by the plants via the roots. The integration of optical nanosensors with living plants enables the conversion of plants into self-powered autosamplers of arsenic from their environment. Arsenite detection is demonstrated with three different plant species as nanobionic sensors. Based on an experimentally validated kinetic model, the nanobionic sensor could detect 0.6 and 0.2 ppb levels of arsenic after 7 and 14 days respectively by exploiting the natural ability of Pteris cretica ferns to hyperaccumulate and tolerate exceptionally high level of arsenic. The sensor readout could also be interfaced with portable electronics at a standoff distance, potentially enabling applications in environmental monitoring and agronomic research.

Species-independent analytical tools for next-generation agriculture

Innovative approaches are urgently required to alleviate the growing pressure on agriculture to meet the rising demand for food. A key challenge for plant biology is to bridge the notable knowledge gap between our detailed understanding of model plants grown under laboratory conditions and the agriculturally important crops cultivated in fields or production facilities. This Perspective highlights the recent development of new analytical tools that are rapid and non-destructive and provide tissue-, cell- or organelle-specific information on living plants in real time, with the potential to extend across multiple species in field applications. We evaluate the utility of engineered plant nanosensors and portable Raman spectroscopy to detect biotic and abiotic stresses, monitor plant hormonal signalling as well as characterize the soil, phytobiome and crop health in a non- or minimally invasive manner. We propose leveraging these tools to bridge the aforementioned fundamental gap with new synthesis and integration of expertise from plant biology, engineering and data science. Lastly, we assess the economic potential and discuss implementation strategies that will ensure the acceptance and successful integration of these modern tools in future farming practices in traditional as well as urban agriculture.

Implantable Nanosensors for Human Steroid Hormone Sensing In Vivo Using a Self-Templating Corona Phase Molecular Recognition

Dynamic measurements of steroid hormones in vivo are critical, but steroid sensing is currently limited by the availability of specific molecular recognition elements due to the chemical similarity of these hormones. In this work, a new, self-templating synthetic approach is applied using corona phase molecular recognition (CoPhMoRe) targeting the steroid family of molecules to produce near infrared fluorescent, implantable sensors. A key limitation of CoPhMoRe has been its reliance on library generation for sensor screening. This problem is addressed with a self-templating strategy of polymer design, using the examples of progesterone and cortisol sensing based on a styrene and acrylic acid copolymer library augmented with an acrylated steroid. The pendant steroid attached to the corona backbone is shown to self-template the phase, providing a unique CoPhMoRE design strategy with high efficacy. The resulting sensors exhibit excellent stability and reversibility upon repeated analyte cycling. It is shown that molecular recognition using such constructs is viable even in vivo after sensor implantation into a murine model by employing a poly (ethylene glycol) diacrylate (PEGDA) hydrogel and porous cellulose interface to limit nonspecific absorption. The results demonstrate that CoPhMoRe templating is sufficiently robust to enable a new class of continuous, in vivo biosensors.

Denatured M13 Bacteriophage-Templated Perovskite Solar Cells Exhibiting High Efficiency

The M13 bacteriophage, a nature-inspired environmentally friendly biomaterial, is used as a perovskite crystal growth template and a grain boundary passivator in perovskite solar cells. The amino groups and carboxyl groups of amino acids on the M13 bacteriophage surface function as Lewis bases, interacting with the perovskite materials. The M13 bacteriophage-added perovskite films show a larger grain size and reduced trap-sites compared with the reference perovskite films. In addition, the existence of the M13 bacteriophage induces light scattering effect, which enhances the light absorption particularly in the long-wavelength region around 825 nm. Both the passivation effect of the M13 bacteriophage coordinating to the perovskite defect sites and the light scattering effect intensify when the M13 virus-added perovskite precursor solution is heated at 90 °C prior to the film formation. Heating the solution denatures the M13 bacteriophage by breaking their inter- and intra-molecular bondings. The denatured M13 bacteriophage-added perovskite solar cells exhibit an efficiency of 20.1% while the reference devices give an efficiency of 17.8%. The great improvement in efficiency comes from all of the three photovoltaic parameters, namely short-circuit current, open-circuit voltage, and fill factor, which correspond to the perovskite grain size, trap-site passivation, and charge transport, respectively.

A Fiber Optic Interface Coupled to Nanosensors: Applications to Protein Aggregation and Organic Molecule Quantification

Fluorescent nanosensors hold promise to address analytical challenges in the biopharmaceutical industry. The monitoring of therapeutic protein critical quality attributes such as aggregation is a long-standing challenge requiring low detection limits and multiplexing of different product parameters. However, general approaches for interfacing nanosensors to the biopharmaceutical process remain minimally explored to date. Herein, we design and fabricate a integrated fiber optic nanosensor element, measuring sensitivity, response time, and stability for applications to the rapid process monitoring. The fiber optic-nanosensor interface, or optode, consists of label-free nIR fluorescent single-walled carbon nanotube transducers embedded within a protective yet porous hydrogel attached to the end of the fiber waveguide. The optode platform is shown to be capable of differentiating the aggregation status of human immunoglobulin G, reporting the relative fraction of monomers and dimer aggregates with sizes 5.6 and 9.6 nm, respectively, in under 5 min of analysis time. We introduce a lab-on-fiber design with potential for at-line monitoring with integration of 3D-printed miniaturized sensor tips having high mechanical flexibility. A parallel measurement of fluctuations in laser excitation allows for intensity normalization and significantly lower noise level (3.7 times improved) when using lower quality lasers, improving the cost effectiveness of the platform. As an application, we demonstrate the capability of the fully integrated lab-on-fiber system to rapidly monitor various bioanalytes including serotonin, norepinephrine, adrenaline, and hydrogen peroxide, in addition to proteins and their aggregation states. These results in total constitute an effective form factor for nanosensor-based transducers for applications in industrial process monitoring.

Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin

Despite considerable progress, development of glucose-responsive insulins (GRIs) still largely depends on empirical knowledge and tedious experimentation-especially on rodents. To assist the rational design and clinical translation of the therapeutic, we present a Pharmacokinetic Algorithm Mapping GRI Efficacies in Rodents and Humans (PAMERAH) built upon our previous human model. PAMERAH constitutes a framework for predicting the therapeutic efficacy of a GRI candidate from its user-specified mechanism of action, kinetics, and dosage, which we show is accurate when checked against data from experiments and literature. Results from simulated glucose clamps also agree quantitatively with recent GRI publications. We demonstrate that the model can be used to explore the vast number of permutations constituting the GRI parameter space and thereby identify the optimal design ranges that yield desired performance. A design guide aside, PAMERAH more importantly can facilitate GRI's clinical translation by connecting each candidate's efficacies in rats, mice, and humans. The resultant mapping helps to find GRIs that appear promising in rodents but underperform in humans (i.e., false positives). Conversely, it also allows for the discovery of optimal human GRI dynamics not captured by experiments on a rodent population (false negatives). We condense such information onto a "translatability grid" as a straightforward, visual guide for GRI development.

Highly Ordered Two-Dimensional MoS2 Archimedean Scroll Bragg Reflectors as Chromatically Adaptive Fibers

Nanostructured fibers provide a basis for a unique class of multifunctional textiles, composites, and membrane applications, including those capable of chromatic modulating because of their high aspect ratio, surface area, and processing capability. Here in, we utilize two-dimensional (2D) materials including molybdenum disulfide (MoS₂) and hexagonal boron nitride (hBN) to generate single layer Archimedean scroll fibers, possessing cross sections formed from a single 2D molecular layer. Chemical vapor deposited (CVD) monolayer MoS₂ (0.29-0.33% in volume) and 226-259 nm-thick poly(methyl methacrylate) (PMMA) were used to create Bragg reflector fibers, exploiting the anisotropic function, exhibiting reflection at 630-709 nm, and verifying the highly ordered nanoinclusions. The Bragg reflectors show a memory response to heating and cooling, which switches the reflection wavelength from 629 to 698 nm. We simulate the reflection and transmission spectra of MoS₂/PMMA and MoS₂/polydimethylsiloxane layered composites to provide the design of scroll fiber composites using the transfer matrix methods. Moreover, we demonstrate the incorporation of a few-layer CVD hBN into the scroll fiber composite that emits photons at 576 nm. The highly oriented layered structures extend the capability of the fiber nanocomposites to take advantage of anisotropic optical, electrical, and thermal properties unique to 2D materials.

Synthesis and Physicochemical Transformations of Size-Sorted Graphene Oxide during Simulated Digestion and Its Toxicological Assessment against an In Vitro Model of the Human Intestinal Epithelium

In the last decade, along with the increasing use of graphene oxide (GO) in various applications, there is also considerable interest in understanding its effects on human health. Only a few experimental approaches can simulate common routes of exposure, such as ingestion, due to the inherent complexity of the digestive tract. This study presents the synthesis of size-sorted GO of sub-micrometer- or micrometer-sized lateral dimensions, its physicochemical transformations across mouth, gastric, and small intestinal simulated digestions, and its toxicological assessment against a physiologically relevant, in vitro cellular model of the human intestinal epithelium. Results from real-time characterization of the simulated digestas of the gastrointestinal tract using multi-angle laser diffraction and field-emission scanning electron microscopy show that GO agglomerates in the gastric and small intestinal phase. Extensive morphological changes, such as folding, are also observed on GO following simulated digestion. Furthermore, X-ray photoelectron spectroscopy reveals that GO presents covalently bound N-containing groups on its surface. It is shown that the GO employed in this study undergoes reduction. Toxicological assessment of the GO small intestinal digesta over 24 h does not point to acute cytotoxicity, and examination of the intestinal epithelium under electron microscopy does not reveal histological alterations. Both sub-micrometer- and micrometer-sized GO variants elicit a 20% statistically significant increase in reactive oxygen species generation compared to the untreated control after a 6 h exposure.

Real-time detection of wound-induced H2O2 signalling waves in plants with optical nanosensors

Decoding wound signalling in plants is critical for understanding various aspects of plant sciences, from pest resistance to secondary metabolite and phytohormone biosynthesis. The plant defence responses are known to primarily involve NADPH-oxidase-mediated H₂O₂ and Ca²⁺ signalling pathways, which propagate across long distances through the plant vasculature and tissues. Using non-destructive optical nanosensors, we find that the H₂O₂ concentration profile post-wounding follows a logistic waveform for six plant species: lettuce (Lactuca sativa), arugula (Eruca sativa), spinach (Spinacia oleracea), strawberry blite (Blitum capitatum), sorrel (Rumex acetosa) and Arabidopsis thaliana, ranked in order of wave speed from 0.44 to 3.10 cm min^-1. The H₂O₂ wave tracks the concomitant surface potential wave measured electrochemically. We show that the plant RbohD glutamate-receptor-like channels (GLR3.3 and GLR3.6) are all critical to the propagation of the wound-induced H₂O₂ wave. Our findings highlight the utility of a new type of nanosensor probe that is species-independent and capable of real-time, spatial and temporal biochemical measurements in plants.