Unveiling Spatial and Temporal Dynamics of Plasmon-Enhanced Localized Fields in Metallic Nanoframes through Ultrafast Electron Microscopy.

Plasmonic nanomaterials, particularly noble metal nanoframes (NFs), are important for applications such as catalysis, biosensing, and energy harvesting due to their ability to enhance localized electric fields and atomic efficiency via localized surface plasmon resonance (LSPR). Yet the fundamental structure-function relationships and plasmonic dynamics of the NFS are difficult to study experimentally and thus far rely predominately on computational methodologies, limiting their utilization. This study leverages the capabilities of ultrafast electron microscopy (UEM), specifically photon-induced near-field electron microscopy (PINEM), to probe the light-matter interactions within plasmonic NF structures. The effects of shape, size, and plasmonic coupling of Pt@Au core-shell NFs on spatial and temporal characteristics of plasmon-enhanced localized electric fields are explored. Importantly, time-resolved PINEM analysis reveals that the plasmonic fields around hexagonal NF prisms exhibit a spatially dependent excitation and decay rate, indicating a nuanced interplay between the spatial geometry of the NF and the temporal evolution of the localized electric field. These results and observations uncover nanophotonic energy transfer dynamics in NFs and highlight their potential for applications in biosensing and photocatalysis.

High Temperature, Isothermal Growth Promotes Close Packing and Thermal Stability in DNA-Engineered Colloidal Crystals.

We report a strategy to accelerate the synthesis and increase the crystallinity of colloidal crystals (CCs) engineered with DNA. Specifically, by holding the DNA-modified Au particle building blocks above the Tm of the DNA bonding elements (i.e., free from the particles), but slightly below the Tm of the anticipated CC during the assembly process, crystallinity is increased, and enthalpically favored phases with high degrees of facet registration are observed. We studied the utility of this approach with systems for which the commonly adopted slow-cooling approach yielded primarily amorphous aggregates. In particular, we used it to synthesize high-volume fraction CCs from large (80 nm) anisotropic nanoparticles (cubes and rhombic dodecahedra) with short (<14 nm) DNA designed to restrict the degrees of freedom for the DNA bonds and maintain the anisotropy of the particle building block. Small-angle X-ray scattering and electron microscopy studies show that the crystalline phases synthesized via this method are more thermally stable than their corresponding aggregate phases, likely due to an increased number of DNA-DNA bonds between particles. Crystal size tunability (between 0.5 and 15 µm edge lengths) and epitaxial growth were demonstrated using this strategy by modulating the NaCl concentration in tandem with previously synthesized CC nuclei. Taken together, this isothermal strategy demonstrates how to deliberately crystallize a wide variety of anisotropic colloidal materials and expands the phase space accessible to nanoparticles modified with DNA.

Engineering Anisotropy into Organized Nanoscale Matter.

Programming the organization of discrete building blocks into periodic and quasi-periodic arrays is challenging. Methods for organizing materials are particularly important at the nanoscale, where the time required for organization processes is practically manageable in experiments, and the resulting structures are of interest for applications spanning catalysis, optics, and plasmonics. While the assembly of isotropic nanoscale objects has been extensively studied and described by empirical design rules, recent synthetic advances have allowed anisotropy to be programmed into macroscopic assemblies made from nanoscale building blocks, opening new opportunities to engineer periodic materials and even quasicrystals with unnatural properties. In this review, we define guidelines for leveraging anisotropy of individual building blocks to direct the organization of nanoscale matter. First, the nature and spatial distribution of local interactions are considered and three design rules that guide particle organization are derived. Subsequently, recent examples from the literature are examined in the context of these design rules. Within the discussion of each rule, we delineate the examples according to the dimensionality (0D-3D) of the building blocks. Finally, we use geometric considerations to propose a general inverse design-based construction strategy that will enable the engineering of colloidal crystals with unprecedented structural control.

Non-Centrosymmetric Single Crystalline Biomolecular Nano-Arrays for Responsive Electronics.

Herein, a novel strategy is reported for synthesizing libraries of single crystalline amino acid (AA) nanocrystals with control over size, anisotropy, and polymorphism by leveraging dip-pen nanolithography (DPN) and recrystallization via solvent vapor annealing. The crystals are prepared by first depositing nanoreactors consisting of a solvent with AAs, followed by water vapor-induced recrystallization. This leads to isotropic structures that are non-centrosymmetric with strong piezoelectric (g33 coefficients >1000 mVm N-1), ferroelectric, and non-linear optical properties. However, recrystallizing arrays of isotropic DL-alanine nanodot features with a binary solvent (water and ethanol) leads to arrays of 1D piezoelectric nanorods with their long axis coincident with the polar axis. Moreover, positioning nanoreactors containing AAs (the nanodot features) between micro electrodes leads to capillary formation, making the reactors anisotropic and facilitating piezoelectric nanorod formation between the electrodes. This offers a facile route to device fabrication. These as-fabricated devices respond to ultrasonic stimulation in the form of a piezoelectric response. The technique described herein is significant as it provides a rapid way of investigating non-centrosymmetric nanoscale biocrystals, potentially pivotal for fabricating a new class of stimuli-responsive devices such as sensors, energy harvesters, and stimulators.

DNA-mediated assembly of Au bipyramids into anisotropic light emitting kagome superlattices.

Colloidal crystal engineering with DNA allows one to design diverse superlattices with tunable lattice symmetry, composition, and spacing. Most of these structures follow the complementary contact model, maximizing DNA hybridization on building blocks and producing relatively close-packed lattices. Here, low-symmetry kagome superlattices are assembled from DNA-modified gold bipyramids that can engage only in partial DNA surface matching. The bipyramid dimensions and DNA length can be engineered for two different superlattices with rhombohedral unit cells, including one composed of a periodic stacking of kagome lattices. Enabled by the partial facet alignment, the kagome lattices exhibit lattice distortion, bipyramid twisting, and planar chirality. When conjugated with Cy-5 dyes, the kagome lattices serve as cavities with high-density optical states and large Purcell factors along lateral directions, leading to strong dipole radiation along the z axis and facet-dependent light emission. Such complex optical properties make these materials attractive for lasers, displays, and quantum sensing constructs.

DNA Anchoring Strength Directly Correlates with Spherical Nucleic Acid-Based HPV E7 Cancer Vaccine Potency.

Vaccination for cancers arising from human papillomavirus (HPV) infection holds immense potential, yet clinical success has been elusive. Herein, we describe vaccination studies involving spherical nucleic acids (SNAs) incorporating a CpG adjuvant and a peptide antigen (E711-19) from the HPV-E7 oncoprotein. Administering the vaccine to humanized mice induced immunity-dependent on the oligonucleotide anchor chemistry (cholesterol vs (C12)9). SNAs containing a (C12)9-anchor enhanced IFN-γ production >200-fold, doubled memory CD8+ T-cell formation, and delivered more than twice the amount of oligonucleotide to lymph nodes in vivo compared to a simple admixture. Importantly, the analogous construct with a weaker cholesterol anchor performed similar to admix. Moreover, (C12)9-SNAs activated 50% more dendritic cells and generated T-cells cytotoxic toward an HPV+ cancer cell line, UM-SCC-104, with near 2-fold greater efficiency. These observations highlight the pivotal role of structural design, and specifically oligonucleotide anchoring strength (which correlates with overall construct stability), in developing efficacious therapeutic vaccines.

Proteomimetic Polymers Trigger Potent Antigen-Specific T Cell Responses to Limit Tumor Growth.

Elicitation of effective antitumor immunity following cancer vaccination requires the selective activation of distinct effector cell populations and pathways. Here we report a therapeutic approach for generating potent T cell responses using a modular vaccination platform technology capable of inducing directed immune activation, termed the Protein-like Polymer (PLP). PLPs demonstrate increased proteolytic resistance, high uptake by antigen-presenting cells (APCs), and enhanced payload-specific T cell responses. Key design parameters, namely payload linkage chemistry, degree of polymerization, and side chain composition, were varied to optimize vaccine formulations. Linking antigens to the polymer backbone using an intracellularly cleaved disulfide bond copolymerized with a diluent amount of oligo(ethylene glycol) (OEG) resulted in the highest payload-specific potentiation of antigen immunogenicity, enhancing dendritic cell (DC) activation and antigen-specific T cell responses. Vaccination with PLPs carrying either gp100, E7, or adpgk peptides significantly increased the survival of mice inoculated with B16F10, TC-1, or MC38 tumors, respectively, without the need for adjuvants. B16F10-bearing mice immunized with gp100-carrying PLPs showed increased antitumor CD8+ T cell immunity, suppressed tumor growth, and treatment synergy when paired with two distinct stimulator of interferon gene (STING) agonists. In a human papillomavirus-associated TC-1 model, combination therapy with PLP and 2'3'-cGAMP resulted in 40% of mice completely eliminating implanted tumors while also displaying curative protection from rechallenge, consistent with conferment of lasting immunological memory. Finally, PLPs can be stored long-term in a lyophilized state and are highly tunable, underscoring the unique properties of the platform for use as generalizable cancer vaccines.

Machine Learning-Enabled Image Classification for Automated Electron Microscopy.

Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of "big data" and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

Energy transition needs new materials.

The decreasing cost of electricity worldwide from wind and solar energy, as well as that of end-use technologies such as electric vehicles, reflect substantial progress made toward replacing fossil fuels with alternative energy sources. But a full transition to clean energy can only be realized if numerous challenges are overcome. Many problems can be addressed through the discovery of new materials that improve the efficiency of energy production and consumption; reduce the need for scarce mineral resources; and support the production of green hydrogen, clean ammonia, and carbon-neutral hydrocarbon fuels. However, research and development of new energy materials are not as aggressive as they should be to meet the demands of climate change.

Using Surface Composition and Energy to Control the Formation of Either Tetrahexahedral or Hexoctahedral High-Index Facet Nanostructures.

High-index facet nanoparticles with structurally complex shapes, such as tetrahexahedron (THH) and hexoctahedron (HOH), represent a class of materials that are important for catalysis, and the study of them provides a fundamental understanding of the relationship between surface structures and catalytic properties. However, the high surface energies render them thermodynamically unfavorable compared to low-index facets, thereby making their syntheses challenging. Herein, we report a method to control the shape of high-index facet Cu nanoparticles (either THH with {210} facets or HOH with {421} facets) by tuning the facet surface energy with trace amounts of Te atoms. Density functional theory (DFT) calculations reveal that the density of Te atoms on Cu nanoparticles can change the relative stability of the high-index facets associated with either the THH or HOH structures. By controlling the annealing conditions and the rate of Te dealloying from CuTe nanoparticles, the surface density of Te atoms can be deliberately adjusted, which can be used to force the formation of either THH (higher surface Te density) or HOH (lower surface Te density) nanoparticles.

Reversible strain-promoted DNA polymerization.

Molecular strain can be introduced to influence the outcome of chemical reactions. Once a thermodynamic product is formed, however, reversing the course of a strain-promoted reaction is challenging. Here, a reversible, strain-promoted polymerization in cyclic DNA is reported. The use of nonhybridizing, single-stranded spacers as short as a single nucleotide in length can promote DNA cyclization. Molecular strain is generated by duplexing the spacers, leading to ring opening and subsequent polymerization. Then, removal of the strain-generating duplexers triggers depolymerization and cyclic dimer recovery via enthalpy-driven cyclization and entropy-mediated ring contraction. This reversibility is retained even when a protein is conjugated to the DNA strands, and the architecture of the protein assemblies can be modulated between bivalent and polyvalent states. This work underscores the utility of using DNA not only as a programmable ligand for assembly but also as a route to access restorable bonds, thus providing a molecular basis for DNA-based materials with shape-memory, self-healing, and stimuli-responsive properties.

Multimodal neuro-nanotechnology: Challenging the existing paradigm in glioblastoma therapy.

Integrating multimodal neuro- and nanotechnology-enabled precision immunotherapies with extant systemic immunotherapies may finally provide a significant breakthrough for combatting glioblastoma (GBM). The potency of this approach lies in its ability to train the immune system to efficiently identify and eradicate cancer cells, thereby creating anti-tumor immune memory while minimizing multi-mechanistic immune suppression. A critical aspect of these therapies is the controlled, spatiotemporal delivery of structurally defined nanotherapeutics into the GBM tumor microenvironment (TME). Architectures such as spherical nucleic acids or poly(beta-amino ester)/dendrimer-based nanoparticles have shown promising results in preclinical models due to their multivalency and abilities to activate antigen-presenting cells and prime antigen-specific T cells. These nanostructures also permit systematic variation to optimize their distribution, TME accumulation, cellular uptake, and overall immunostimulatory effects. Delving deeper into the relationships between nanotherapeutic structures and their performance will accelerate nano-drug development and pave the way for the rapid clinical translation of advanced nanomedicines. In addition, the efficacy of nanotechnology-based immunotherapies may be enhanced when integrated with emerging precision surgical techniques, such as laser interstitial thermal therapy, and when combined with systemic immunotherapies, particularly inhibitors of immune-mediated checkpoints and immunosuppressive adenosine signaling. In this perspective, we highlight the potential of emerging treatment modalities, combining advances in biomedical engineering and neurotechnology development with existing immunotherapies to overcome treatment resistance and transform the management of GBM. We conclude with a call to action for researchers to leverage these technologies and accelerate their translation into the clinic.

Sub-Diffraction Correlation of Quantum Emitters and Local Strain Fields in Strain-Engineered WSe2 Monolayers.

Strain-engineering in atomically thin metal dichalcogenides is a useful method for realizing single-photon emitters (SPEs) for quantum technologies. Correlating SPE position with local strain topography is challenging due to localization inaccuracies from the diffraction limit. Currently, SPEs are assumed to be positioned at the highest strained location and are typically identified by randomly screening narrow-linewidth emitters, of which only a few are spectrally pure. In this work, hyperspectral quantum emitter localization microscopy is used to locate 33 SPEs in nanoparticle-strained WSe2 monolayers with sub-diffraction-limit resolution (≈30 nm) and correlate their positions with the underlying strain field via image registration. In this system, spectrally pure emitters are not concentrated at the highest strain location due to spectral contamination; instead, isolable SPEs are distributed away from points of peak strain with an average displacement of 240 nm. These observations point toward a need for a change in the design rules for strain-engineered SPEs and constitute a key step toward realizing next-generation quantum optical architectures.

Space-tiled colloidal crystals from DNA-forced shape-complementary polyhedra pairing.

Generating space-filling arrangements of most discrete polyhedra nanostructures of the same shape is not possible. However, if the appropriate individual building blocks are selected (e.g., cubes), or multiple shapes of the appropriate dimensions are matched (e.g., octahedra and tetrahedra) and their pairing interactions are subsequently forced, space-filled architectures may be possible. With flexible molecular ligands (polyethylene glycol-modified DNA), the shape of a polyhedral nanoparticle can be deliberately altered and used to realize geometries that favor space tessellation. In this work, 10 new colloidal crystals were synthesized from DNA-modified nanocrystal building blocks that differed in shapes and sizes, designed to form space-filling architectures with micron-scale dimensions. The insights and capabilities provided by this new strategy substantially expand the scope of colloidal crystals possible and provide an expanded tool kit for researchers interested in designing metamaterials.

Enhancing Endosomal Escape and Gene Regulation Activity for Spherical Nucleic Acids.

The therapeutic potential of small interfering RNAs (siRNAs) is limited by their poor stability and low cellular uptake. When formulated as spherical nucleic acids (SNAs), siRNAs are resistant to nuclease degradation and enter cells without transfection agents with enhanced activity compared to their linear counterparts; however, the gene silencing activity of SNAs is limited by endosomal entrapment, a problem that impacts many siRNA-based nanoparticle constructs. To increase cytosolic delivery, SNAs are formulated using calcium chloride (CaCl2 ) instead of the conventionally used sodium chloride (NaCl). The divalent calcium (Ca2+ ) ions remain associated with the multivalent SNA and have a higher affinity for SNAs compared to their linear counterparts. Importantly, confocal microscopy studies show a 22% decrease in the accumulation of CaCl2 -salted SNAs within the late endosomes compared to NaCl-salted SNAs, indicating increased cytosolic delivery. Consistent with this finding, CaCl2 -salted SNAs comprised of siRNA and antisense DNA all exhibit enhanced gene silencing activity (up to 20-fold), compared to NaCl-salted SNAs regardless of sequence or cell line (U87-MG and SK-OV-3) studied. Moreover, CaCl2 -salted SNA-based forced intercalation probes show improved cytosolic mRNA detection.

Colloidal quasicrystals engineered with DNA.

In principle, designing and synthesizing almost any class of colloidal crystal is possible. Nonetheless, the deliberate and rational formation of colloidal quasicrystals has been difficult to achieve. Here we describe the assembly of colloidal quasicrystals by exploiting the geometry of nanoscale decahedra and the programmable bonding characteristics of DNA immobilized on their facets. This process is enthalpy-driven, works over a range of particle sizes and DNA lengths, and is made possible by the energetic preference of the system to maximize DNA duplex formation and favour facet alignment, generating local five- and six-coordinated motifs. This class of axial structures is defined by a square-triangle tiling with rhombus defects and successive on-average quasiperiodic layers exhibiting stacking disorder which provides the entropy necessary for thermodynamic stability. Taken together, these results establish an engineering milestone in the deliberate design of programmable matter.

Discovering polyelemental nanostructures with redistributed plasmonic modes through combinatorial synthesis.

Coupling plasmonic and functional materials provides a promising way to generate multifunctional structures. However, finding plasmonic nanomaterials and elucidating the roles of various geometric and dielectric configurations are tedious. This work describes a combinatorial approach to rapidly exploring and identifying plasmonic heteronanomaterials. Symmetry-broken noble/non-noble metal particle heterojunctions (~100 nanometers) were synthesized on multiwindow silicon chips with silicon nitride membranes. The metal types and the interface locations were controlled to establish a nanoparticle library, where the particle morphology and scattering color can be rapidly screened. By correlating structural data with near- and far-field single-particle spectroscopy data, we found that certain low-energy plasmonic modes could be supported across the heterointerface, while others are localized. Furthermore, we found a series of triangular heteronanoplates stabilized by epitaxial Moiré superlattices, which show strong plasmonic responses despite largely comprising a lossy metal (~70 atomic %). These architectures can become the basis for multifunctional and cost-effective plasmonic devices.

Bimolecularly passivated interface enables efficient and stable inverted perovskite solar cells.

Compared with the n-i-p structure, inverted (p-i-n) perovskite solar cells (PSCs) promise increased operating stability, but these photovoltaic cells often exhibit lower power conversion efficiencies (PCEs) because of nonradiative recombination losses, particularly at the perovskite/C60 interface. We passivated surface defects and enabled reflection of minority carriers from the interface into the bulk using two types of functional molecules. We used sulfur-modified methylthio molecules to passivate surface defects and suppress recombination through strong coordination and hydrogen bonding, along with diammonium molecules to repel minority carriers and reduce contact-induced interface recombination achieved through field-effect passivation. This approach led to a fivefold longer carrier lifetime and one-third the photoluminescence quantum yield loss and enabled a certified quasi-steady-state PCE of 25.1% for inverted PSCs with stable operation at 65°C for >2000 hours in ambient air. We also fabricated monolithic all-perovskite tandem solar cells with 28.1% PCE.

Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning.

A bottleneck in high-throughput nanomaterials discovery is the pace at which new materials can be structurally characterized. Although current machine learning (ML) methods show promise for the automated processing of electron diffraction patterns (DPs), they fail in high-throughput experiments where DPs are collected from crystals with random orientations. Inspired by the human decision-making process, a framework for automated crystal system classification from DPs with arbitrary orientations was developed. A convolutional neural network was trained using evidential deep learning, and the predictive uncertainties were quantified and leveraged to fuse multiview predictions. Using vector map representations of DPs, the framework achieves a testing accuracy of 0.94 in the examples considered, is robust to noise, and retains remarkable accuracy using experimental data. This work highlights the ability of ML to be used to accelerate experimental high-throughput materials data analytics.