Indefinite and bidirectional near-infrared nanocrystal photoswitching.

Materials whose luminescence can be switched by optical stimulation drive technologies ranging from superresolution imaging1-4, nanophotonics5, and optical data storage6,7, to targeted pharmacology, optogenetics, and chemical reactivity8. These photoswitchable probes, including organic fluorophores and proteins, can be prone to photodegradation and often operate in the ultraviolet or visible spectral regions. Colloidal inorganic nanoparticles6,9 can offer improved stability, but the ability to switch emission bidirectionally, particularly with near-infrared (NIR) light, has not, to our knowledge, been reported in such systems. Here, we present two-way, NIR photoswitching of avalanching nanoparticles (ANPs), showing full optical control of upconverted emission using phototriggers in the NIR-I and NIR-II spectral regions useful for subsurface imaging. Employing single-step photodarkening10-13 and photobrightening12,14-16, we demonstrate indefinite photoswitching of individual nanoparticles (more than 1,000 cycles over 7 h) in ambient or aqueous conditions without measurable photodegradation. Critical steps of the photoswitching mechanism are elucidated by modelling and by measuring the photon avalanche properties of single ANPs in both bright and dark states. Unlimited, reversible photoswitching of ANPs enables indefinitely rewritable two-dimensional and three-dimensional multilevel optical patterning of ANPs, as well as optical nanoscopy with sub-Å localization superresolution that allows us to distinguish individual ANPs within tightly packed clusters.

Giant nonlinear optical responses from photon-avalanching nanoparticles.

Avalanche phenomena use steeply nonlinear dynamics to generate disproportionately large responses from small perturbations, and are found in a multitude of events and materials1. Photon avalanching enables technologies such as optical phase-conjugate imaging2, infrared quantum counting3 and efficient upconverted lasing4-6. However, the photon-avalanching mechanism underlying these optical applications has been observed only in bulk materials and aggregates6,7, limiting its utility and impact. Here we report the realization of photon avalanching at room temperature in single nanostructures-small, Tm3+-doped upconverting nanocrystals-and demonstrate their use in super-resolution imaging in near-infrared spectral windows of maximal biological transparency. Avalanching nanoparticles (ANPs) can be pumped by continuous-wave lasers, and exhibit all of the defining features of photon avalanching, including clear excitation-power thresholds, exceptionally long rise time at threshold, and a dominant excited-state absorption that is more than 10,000 times larger than ground-state absorption. Beyond the avalanching threshold, ANP emission scales nonlinearly with the 26th power of the pump intensity, owing to induced positive optical feedback in each nanocrystal. This enables the experimental realization of photon-avalanche single-beam super-resolution imaging7 with sub-70-nanometre spatial resolution, achieved by using only simple scanning confocal microscopy and without any computational analysis. Pairing their steep nonlinearity with existing super-resolution techniques and computational methods8-10, ANPs enable imaging with higher resolution and at excitation intensities about 100 times lower than other probes. The low photon-avalanching threshold and excellent photostability of ANPs also suggest their utility in a diverse array of applications, including sub-wavelength imaging7,11,12 and optical and environmental sensing13-15.

Helical van der Waals crystals with discretized Eshelby twist.

The ability to manipulate the twisting topology of van der Waals structures offers a new degree of freedom through which to tailor their electrical and optical properties. The twist angle strongly affects the electronic states, excitons and phonons of the twisted structures through interlayer coupling, giving rise to exotic optical, electric and spintronic behaviours1-5. In twisted bilayer graphene, at certain twist angles, long-range periodicity associated with moiré patterns introduces flat electronic bands and highly localized electronic states, resulting in Mott insulating behaviour and superconductivity3,4. Theoretical studies suggest that these twist-induced phenomena are common to layered materials such as transition-metal dichalcogenides and black phosphorus6,7. Twisted van der Waals structures are usually created using a transfer-stacking method, but this method cannot be used for materials with relatively strong interlayer binding. Facile bottom-up growth methods could provide an alternative means to create twisted van der Waals structures. Here we demonstrate that the Eshelby twist, which is associated with a screw dislocation (a chiral topological defect), can drive the formation of such structures on scales ranging from the nanoscale to the mesoscale. In the synthesis, axial screw dislocations are first introduced into nanowires growing along the stacking direction, yielding van der Waals nanostructures with continuous twisting in which the total twist rates are defined by the radii of the nanowires. Further radial growth of those twisted nanowires that are attached to the substrate leads to an increase in elastic energy, as the total twist rate is fixed by the substrate. The stored elastic energy can be reduced by accommodating the fixed twist rate in a series of discrete jumps. This yields mesoscale twisting structures consisting of a helical assembly of nanoplates demarcated by atomically sharp interfaces with a range of twist angles. We further show that the twisting topology can be tailored by controlling the radial size of the structure.

Ligand-Assisted Direct Lithography of Upconverting and Avalanching Nanoparticles for Nonlinear Photonics.

Upconverting nanoparticles (UCNPs) exhibit unique nonlinear optical properties that can be harnessed in microscopy, sensing, and photonics. However, forming high-resolution nano- and micropatterns of UCNPs with large packing fractions is still challenging. Additionally, there is limited understanding of how nanoparticle patterning chemistries are affected by the particle size. Here, we explore direct patterning chemistries for 6-18 nm Tm3+-, Yb3+/Tm3+-, and Yb3+/Er3+-based UCNPs using ligands that form either new ionic linkages or covalent bonds between UCNPs under ultraviolet (UV), electron-beam (e-beam), and near-infrared (NIR) exposure. We study the effect of UCNP size on these patterning approaches and find that 6 nm UCNPs can be patterned with compact ionic-based ligands. In contrast, patterning larger UCNPs requires long-chain, cross-linkable ligands that provide sufficient interparticle spacing to prevent irreversible aggregation upon film casting. Compared to approaches that use a cross-linkable liquid monomer, our patterning method limits the cross-linking reaction to the ligands bound on UCNPs deposited as a thin film. This highly localized photo-/electron-initiated chemistry enables the fabrication of densely packed UCNP patterns with high resolutions (∼1 µm with UV and NIR exposure; <100 nm with e-beam). Our upconversion NIR lithography approach demonstrates the potential to use inexpensive continuous-wave lasers for high-resolution 2D and 3D lithography of colloidal materials. The deposited UCNP patterns retain their upconverting, avalanching, and photoswitching behaviors, which can be exploited in patterned optical devices for next-generation UCNP applications.

Accelerating the Design of Multishell Upconverting Nanoparticles through Bayesian Optimization.

The photon upconverting properties of lanthanide-doped nanoparticles drive their applications in imaging, optoelectronics, and additive manufacturing. To maximize their brightness, these upconverting nanoparticles (UCNPs) are often synthesized as core/shell heterostructures. However, the large numbers of compositional and structural parameters in multishell heterostructures make optimizing optical properties challenging. Here, we demonstrate the use of Bayesian optimization (BO) to learn the structure and design rules for multishell UCNPs with bright ultraviolet and violet emission. We leverage an automated workflow that iteratively recommends candidate UCNP structures and then simulates their emission spectra using kinetic Monte Carlo. Yb3+/Er3+- and Yb3+/Er3+/Tm3+-codoped UCNP nanostructures optimized with this BO workflow achieve 10- and 110-fold brighter emission within 22 and 40 iterations, respectively. This workflow can be expanded to structures with higher compositional and structural complexity, accelerating the discovery of novel UCNPs while domain-specific knowledge is being developed.

Triplet-Induced Singlet Oxygen Photobleaches Near-Infrared Dye-Sensitized Upconversion Nanosystems.

The rapid photobleaching of near-infrared (NIR) dye-sensitized upconversion nanosystems is one of the crucial problems that has blocked their technological applications. Uncovering the photophysical and photochemical pathways of NIR dyes would help to elucidate the photobleaching mechanism and thereby improve the photostability of the system. Here we investigate the triplet dynamics of NIR dyes and their interaction with triplet oxygen in the typically investigated IR806-sensitized upconversion nanoparticle (UCNP) nanosystem. Low-temperature fluorescence at 77 K provides direct proof of the generation of singlet oxygen (1O2) under 808 nm laser irradiation. Mass spectrometry indicates that all three double bonds in the structure of IR806 can be broken in the photochemical process. Coupling IR806 to the surface of UCNPs can accelerate its triplet dynamics, thus producing more 1O2 to photocleave IR806. Importantly, we find that the addition of ß-carotene can scavenge the generated 1O2, thereby providing a simple method to effectively inhibit photobleaching.

A Generalized Approach to Photon Avalanche Upconversion in Luminescent Nanocrystals.

Photon avalanching nanoparticles (ANPs) exhibit extremely nonlinear upconverted emission valuable for subdiffraction imaging, nanoscale sensing, and optical computing. Avalanching has been demonstrated with Tm3+-, Pr3+-, or Nd3+-doped nanocrystals, but their emission is limited to a few wavelengths and materials. Here, we utilize Gd3+-assisted energy migration to tune the emission wavelengths of Tm3+-sensitized ANPs and generate highly nonlinear emission from Eu3+, Tb3+, Ho3+, and Er3+ ions. The upconversion intensities of these spectrally discrete ANPs scale with nonlinearity factor s = 10-17 under 1064 nm excitation at power densities as low as 7 kW cm-2. This strategy for imprinting avalanche behavior on remote emitters can be extended to fluorophores adjacent to ANPs, as we demonstrate with CdS/CdSe/CdS core/shell/shell quantum dots. ANPs with rationally designed energy transfer networks provide the means to transform conventional linear emitters into a highly nonlinear ones, expanding the use of photon avalanching in biological, chemical, and photonic applications.

Scientific Machine Learning of 2D Perovskite Nanosheet Formation.

We apply a scientific machine learning (ML) framework to aid the prediction and understanding of nanomaterial formation processes via a joint spectral-kinetic model. We apply this framework to study the nucleation and growth of two-dimensional (2D) perovskite nanosheets. Colloidal nanomaterials have size-dependent optical properties and can be observed in situ, all of which make them a good model for understanding the complex processes of nucleation, growth, and phase transformation of 2D perovskites. Our results demonstrate that this model nanomaterial can form through two processes at the nanoscale: either via a layer-by-layer chemical exfoliation process from lead bromide nanocrystals or via direct nucleation from precursors. We utilize a phenomenological kinetic analysis to study the exfoliation process and scientific machine learning to study the direct nucleation and growth and discuss the circumstances under which it is more appropriate to use phenomenological or more complex machine learning models. Data for both analysis techniques are collected through in situ spectroscopy in a stopped flow chamber, incorporating over 500,000 spectra taken under more than 100 different conditions. More broadly, our research shows that the ability to utilize and integrate traditional kinetics and machine learning methods will greatly assist in the understanding of complex chemical systems.

Tuning Phonon Energies in Lanthanide-doped Potassium Lead Halide Nanocrystals for Enhanced Nonlinearity and Upconversion.

Optical applications of lanthanide-doped nanoparticles require materials with low phonon energies to minimize nonradiative relaxation and promote nonlinear processes like upconversion. Heavy halide hosts offer low phonon energies but are challenging to synthesize as nanocrystals. Here, we demonstrate the size-controlled synthesis of low-phonon-energy KPb2 X5 (X=Cl, Br) nanoparticles and the ability to tune nanocrystal phonon energies as low as 128 cm-1 . KPb2 Cl5 nanoparticles are moisture resistant and can be efficiently doped with lighter lanthanides. The low phonon energies of KPb2 X5 nanoparticles promote upconversion luminescence from higher lanthanide excited states and enable highly nonlinear, avalanche-like emission from KPb2 Cl5 : Nd3+ nanoparticles. The realization of nanoparticles with tunable, ultra-low phonon energies facilitates the discovery of nanomaterials with phonon-dependent properties, precisely engineered for applications in nanoscale imaging, sensing, luminescence thermometry and energy conversion.

Dynamics of Polymer Nanocapsule Buckling and Collapse Revealed by In Situ Liquid-Phase TEM.

Nanocapsules are hollow nanoscale shells that have applications in drug delivery, batteries, self-healing materials, and as model systems for naturally occurring shell geometries. In many applications, nanocapsules are designed to release their cargo as they buckle and collapse, but the details of this transient buckling process have not been directly observed. Here, we use in situ liquid-phase transmission electron microscopy to record the electron-irradiation-induced buckling in spherical 60-187 nm polymer capsules with ∼3.5 nm walls. We observe in real time the release of aqueous cargo from these nanocapsules and their buckling into morphologies with single or multiple indentations. The in situ buckling of nanoscale capsules is compared to ex situ measurements of collapsed and micrometer-sized capsules and to Monte Carlo (MC) simulations. The shape and dynamics of the collapsing nanocapsules are consistent with MC simulations, which reveal that the excessive wrinkling of nanocapsules with ultrathin walls results from their large Föppl-von Kármán numbers around 105. Our experiments suggest design rules for nanocapsules with the desired buckling response based on parameters such as capsule radius, wall thickness, and collapse rate.

Active meta-learning for predicting and selecting perovskite crystallization experiments.

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. In this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion.

Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the rank-score characteristic function and cognitive diversity measure. One example is to combine diverse machine learning models to achieve better prediction quality. In this work, we apply CFA to the synthesis of metal halide perovskites containing organic ammonium cations via inverse temperature crystallization. Using a data set generated by high-throughput experimentation, four individual models (support vector machines, random forests, weighted logistic classifier, and gradient boosted trees) were developed. We characterize each of these scoring systems and explore 66 possible combinations of the models. When measured by the precision on predicting crystal formation, the majority of the combination models improves the individual model results. The best combination models outperform the best individual models by 3.9 percentage points in precision. In addition to improving prediction quality, we demonstrate how the fusion models can be used to identify mislabeled input data and address issues of data quality. In particular, we identify example cases where all single models and all fusion models do not give the correct prediction. Experimental replication of these syntheses reveals that these compositions are sensitive to modest temperature variations across the different locations of the heating element that can hinder or enhance the crystallization process. In summary, we demonstrate that model fusion using CFA can not only identify a previously unconsidered influence on reaction outcome but also be used as a form of quality control for high-throughput experimentation.

Elucidating the Weakly Reversible Cs-Pb-Br Perovskite Nanocrystal Reaction Network with High-Throughput Maps and Transformations.

Advances in automation and data analytics can aid exploration of the complex chemistry of nanoparticles. Lead halide perovskite colloidal nanocrystals provide an interesting proving ground: there are reports of many different phases and transformations, which has made it hard to form a coherent conceptual framework for their controlled formation through traditional methods. In this work, we systematically explore the portion of Cs-Pb-Br synthesis space in which many optically distinguishable species are formed using high-throughput robotic synthesis to understand their formation reactions. We deploy an automated method that allows us to determine the relative amount of absorbance that can be attributed to each species in order to create maps of the synthetic space. These in turn facilitate improved understanding of the interplay between kinetic and thermodynamic factors that underlie which combination of species are likely to be prevalent under a given set of conditions. Based on these maps, we test potential transformation routes between perovskite nanocrystals of different shapes and phases. We find that shape is determined kinetically, but many reactions between different phases show equilibrium behavior. We demonstrate a dynamic equilibrium between complexes, monolayers, and nanocrystals of lead bromide, with substantial impact on the reaction outcomes. This allows us to construct a chemical reaction network that qualitatively explains our results as well as previous reports and can serve as a guide for those seeking to prepare a particular composition and shape.

Ultralow-threshold, continuous-wave upconverting lasing from subwavelength plasmons.

Miniaturized lasers are an emerging platform for generating coherent light for quantum photonics, in vivo cellular imaging, solid-state lighting and fast three-dimensional sensing in smartphones1-3. Continuous-wave lasing at room temperature is critical for integration with opto-electronic devices and optimal modulation of optical interactions4,5. Plasmonic nanocavities integrated with gain can generate coherent light at subwavelength scales6-9, beyond the diffraction limit that constrains mode volumes in dielectric cavities such as semiconducting nanowires10,11. However, insufficient gain with respect to losses and thermal instabilities in nanocavities has limited all nanoscale lasers to pulsed pump sources and/or low-temperature operation6-9,12-15. Here, we show continuous-wave upconverting lasing at room temperature with record-low thresholds and high photostability from subwavelength plasmons. We achieve selective, single-mode lasing from Yb3+/Er3+-co-doped upconverting nanoparticles conformally coated on Ag nanopillar arrays that support a single, sharp lattice plasmon cavity mode and greater than wavelength λ/20 field confinement in the vertical dimension. The intense electromagnetic near-fields localized in the vicinity of the nanopillars result in a threshold of 70 W cm-2, orders of magnitude lower than other small lasers. Our plasmon-nanoarray upconverting lasers provide directional, ultra-stable output at visible frequencies under near-infrared pumping, even after six hours of constant operation, which offers prospects in previously unrealizable applications of coherent nanoscale light.

MoS2 Liquid Cell Electron Microscopy Through Clean and Fast Polymer-Free MoS2 Transfer.

Two dimensional (2D) materials have found various applications because of their unique physical properties. For example, graphene has been used as the electron transparent membrane for liquid cell transmission electron microscopy (TEM) due to its high mechanical strength and flexibility, single-atom thickness, chemical inertness, etc. Here, we report using 2D MoS2 as a functional substrate as well as the membrane window for liquid cell TEM, which is enabled by our facile and polymer-free MoS2 transfer process. This provides the opportunity to investigate the growth of Pt nanocrystals on MoS2 substrates, which elucidates the formation mechanisms of such heterostructured 2D materials. We find that Pt nanocrystals formed in MoS2 liquid cells have a strong tendency to align their crystal lattice with that of MoS2, suggesting a van der Waals epitaxial relationship. Importantly, we can study its impact on the kinetics of the nanocrystal formation. The development of MoS2 liquid cells will allow further study of various liquid phenomena on MoS2, and the polymer-free MoS2 transfer process will be implemented in a wide range of applications.

The Making and Breaking of Lead-Free Double Perovskite Nanocrystals of Cesium Silver-Bismuth Halide Compositions.

Replacing lead in halide perovskites is of great interest due to concerns about stability and toxicity. Recently, lead free double perovskites in which the unit cell is doubled and two divalent lead cations are substituted by a combination of mono- and trivalent cations have been synthesized as bulk single crystals and as thin films. Here, we study stability and optical properties of all-inorganic cesium silver(I) bismuth(III) chloride and bromide nanocrystals with the double perovskite crystal structure. The cube-shaped nanocrystals are monodisperse in size with typical side lengths of 8 to 15 nm. The absorption spectrum of the nanocrystals presents a sharp peak, which we assign to a direct bismuth s-p transition and not to a quantum confined excitonic transition. Using this spectroscopic handle combined with high-resolution transmission electron microscopy (TEM) based elemental analysis, we conduct stoichiometric studies at the single nanocrystal level as well as decomposition assays in solution and observe that Ag+ diffusion and coalescence is one of the pathways by which this material degrades. Drying the nanocrystals leads to self-assembly into ordered nanocrystal solids, and these exhibit less degradation than nanocrystals in solution. Our results demonstrate that Cs2AgBiX6 (X = Cl, Br) nanocrystals are a useful model system to study structure-function relationships in the search for stable nontoxic halide perovskites.

Dynamics of Nanoscale Dendrite Formation in Solution Growth Revealed Through in Situ Liquid Cell Electron Microscopy.

Formation mechanisms of dendrite structures have been extensively explored theoretically, and many theoretical predictions have been validated for micro- or macroscale dendrites. However, it is challenging to determine whether classical dendrite growth theories are applicable at the nanoscale due to the lack of detailed information on the nanodendrite growth dynamics. Here, we study iron oxide nanodendrite formation using liquid cell transmission electron microscopy (TEM). We observe "seaweed"-like iron oxide nanodendrites growing predominantly in two dimensions on the membrane of a liquid cell. By tracking the trajectories of their morphology development with high spatial and temporal resolution, it is possible to explore the relationship between the tip curvature and growth rate, tip splitting mechanisms, and the effects of precursor diffusion and depletion on the morphology evolution. We show that the growth of iron oxide nanodendrites is remarkably consistent with the existing theoretical predictions on dendritic morphology evolution during growth, despite occurring at the nanoscale.

Photostable and efficient upconverting nanocrystal-based chemical sensors.

Chemical sensing in living systems demands optical sensors that are bright, stable, and sensitive to the rapid dynamics of chemical signaling. Lanthanide-doped upconverting nanoparticles (UCNPs) efficiently convert near infrared (NIR) light to higher energy emission and allow biological systems to be imaged with no measurable background or photobleaching, and with reduced scatter for subsurface experiments. Despite their advantages as imaging probes, UCNPs have little innate chemical sensing ability and require pairing with organic fluorophores to act as biosensors, although the design of stable UCNP-fluorophore hybrids with efficient upconverted energy transfer (UET) has remained a challenge. Here, we report Yb3+- and Er3+-doped UCNP-fluorophore conjugates with UET efficiencies up to 88%, and photostabilities 100-fold greater by UET excitation than those of the free fluorophores under direct excitation. Despite adding distance between Er3+ donors and organic acceptors, thin inert shells significantly enhance overall emission without compromising UET efficiency. This can be explained by the large increase in quantum yield of Er3+ donors at the core/shell interface and the large number of fluorophore acceptors at the surface. Sensors excited by UET show increases in photostability well beyond those reported for other methods for increasing the longevity of organic fluorophores, and those covalently attached to UCNP surface polymers show greater chemical stability than those directly coordinated to the nanocrystal surface. By conjugating other fluorescent chemosensors to UCNPs, these hybrids may be extended to a series of NIR-responsive biosensors for quantifying the dynamic chemical populations critical for cell signaling.

Direct Evidence for Coupled Surface and Concentration Quenching Dynamics in Lanthanide-Doped Nanocrystals.

Luminescence quenching at high dopant concentrations generally limits the dopant concentration to less than 1-5 mol% in lanthanide-doped materials, and this remains a major obstacle in designing materials with enhanced efficiency/brightness. In this work, we provide direct evidence that the major quenching process at high dopant concentrations is the energy migration to the surface (i.e., surface quenching) as opposed to the common misconception of cross-relaxation between dopant ions. We show that after an inert epitaxial shell growth, erbium (Er3+) concentrations as high as 100 mol% in NaY(Er)F4/NaLuF4 core/shell nanocrystals enhance the emission intensity of both upconversion and downshifted luminescence across different excitation wavelengths (980, 800, and 658 nm), with negligible concentration quenching effects. Our results highlight the strong coupling of concentration and surface quenching effects in colloidal lanthanide-doped nanocrystals, and that inert epitaxial shell growth can overcome concentration quenching. These fundamental insights into the photophysical processes in heavily doped nanocrystals will give rise to enhanced properties not previously thought possible with compositions optimized in bulk.

Multifunctional Magnetic and Upconverting Nanobeads as Dual Modal Imaging Tools.

We report the fabrication of aqueous multimodal imaging nanocomposites based on superparamagnetic nanoparticles (MNPs) and two different sizes of photoluminescent upconverting nanoparticles (UCNPs). The controlled and simultaneous incorporation of both types of nanoparticles (NPs) was obtained by controlling the solvent composition and the addition rate of the destabilizing solvent. The magnetic properties of the MNPs remained unaltered after their encapsulation into the polymeric beads as shown by the T2 relaxivity measurements. The UCNPs maintain photoluminescent properties even when embedded with the MNPs into the polymer bead. Moreover, the light emitted by the magnetic and upconverting nanobeads (MUCNBs) under NIR excitation (λexc = 980 nm) was clearly observed through different thicknesses of agarose gel or through a mouse skin layer. The comparison with magnetic and luminescent nanobeads based on red-emitting quantum dots (QDs) demonstrated that while the QD-based beads show significant autofluorescence background from the skin, the signal obtained by the MUCNBs allows a decrease in this background. In summary, these results indicate that MUCNBs are good magnetic and optical probes for in vivo multimodal imaging sensors.