From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis.

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics-including plasmonics, metamaterials, and metasurfaces-enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

The role of the plasmon in interfacial charge transfer.

The lack of a detailed mechanistic understanding for plasmon-mediated charge transfer at metal-semiconductor interfaces severely limits the design of efficient photovoltaic and photocatalytic devices. A major remaining question is the relative contribution from indirect transfer of hot electrons generated by plasmon decay in the metal to the semiconductor compared to direct metal-to-semiconductor interfacial charge transfer. Here, we demonstrate an overall electron transfer efficiency of 44 ± 3% from gold nanorods to titanium oxide shells when excited on resonance. We prove that half of it originates from direct interfacial charge transfer mediated specifically by exciting the plasmon. We are able to distinguish between direct and indirect pathways through multimodal frequency-resolved approach measuring the homogeneous plasmon linewidth by single-particle scattering spectroscopy and time-resolved transient absorption spectroscopy with variable pump wavelengths. Our results signify that the direct plasmon-induced charge transfer pathway is a promising way to improve hot carrier extraction efficiency by circumventing metal intrinsic decay that results mainly in nonspecific heating.

Very-large-scale-integrated high quality factor nanoantenna pixels.

Metasurfaces precisely control the amplitude, polarization and phase of light, with applications spanning imaging, sensing, modulation and computing. Three crucial performance metrics of metasurfaces and their constituent resonators are the quality factor (Q factor), mode volume (Vm) and ability to control far-field radiation. Often, resonators face a trade-off between these parameters: a reduction in Vm leads to an equivalent reduction in Q, albeit with more control over radiation. Here we demonstrate that this perceived compromise is not inevitable: high quality factor, subwavelength Vm and controlled dipole-like radiation can be achieved simultaneously. We design high quality factor, very-large-scale-integrated silicon nanoantenna pixels (VINPix) that combine guided mode resonance waveguides with photonic crystal cavities. With optimized nanoantennas, we achieve Q factors exceeding 1,500 with Vm less than 0.1 ( λ / n air ) 3 . Each nanoantenna is individually addressable by free-space light and exhibits dipole-like scattering to the far-field. Resonator densities exceeding a million nanoantennas per cm2 can be achieved. As a proof-of-concept application, we show spectrometer-free, spatially localized, refractive-index sensing, and fabrication of an 8 mm × 8 mm VINPix array. Our platform provides a foundation for compact, densely multiplexed devices such as spatial light modulators, computational spectrometers and in situ environmental sensors.

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen's antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

Spectroscopy in Nanoscopic Cavities: Models and Recent Experiments.

The ability of nanophotonic cavities to confine and store light to nanoscale dimensions has important implications for enhancing molecular, excitonic, phononic, and plasmonic optical responses. Spectroscopic signatures of processes that are ordinarily exceedingly weak such as pure absorption and Raman scattering have been brought to the single-particle limit of detection, while new emergent polaritonic states of optical matter have been realized through coupling material and photonic cavity degrees of freedom across a wide range of experimentally accessible interaction strengths. In this review, we discuss both optical and electron beam spectroscopies of cavity-coupled material systems in weak, strong, and ultrastrong coupling regimes, providing a theoretical basis for understanding the physics inherent to each while highlighting recent experimental advances and exciting future directions.

Highly confined epsilon-near-zero and surface phonon polaritons in SrTiO3 membranes.

Recent theoretical studies have suggested that transition metal perovskite oxide membranes can enable surface phonon polaritons in the infrared range with low loss and much stronger subwavelength confinement than bulk crystals. Such modes, however, have not been experimentally observed so far. Here, using a combination of far-field Fourier-transform infrared (FTIR) spectroscopy and near-field synchrotron infrared nanospectroscopy (SINS) imaging, we study the phonon polaritons in a 100 nm thick freestanding crystalline membrane of SrTiO3 transferred on metallic and dielectric substrates. We observe a symmetric-antisymmetric mode splitting giving rise to epsilon-near-zero and Berreman modes as well as highly confined (by a factor of 10) propagating phonon polaritons, both of which result from the deep-subwavelength thickness of the membranes. Theoretical modeling based on the analytical finite-dipole model and numerical finite-difference methods fully corroborate the experimental results. Our work reveals the potential of oxide membranes as a promising platform for infrared photonics and polaritonics.

Toward "super-scintillation" with nanomaterials and nanophotonics.

Following the discovery of X-rays, scintillators are commonly used as high-energy radiation sensors in diagnostic medical imaging, high-energy physics, astrophysics, environmental radiation monitoring, and security inspections. Conventional scintillators face intrinsic limitations including a low extraction efficiency of scintillated light and a low emission rate, leading to efficiencies that are less than 10 % for commercial scintillators. Overcoming these limitations will require new materials including scintillating nanomaterials ("nanoscintillators"), as well as new photonic approaches that increase the efficiency of the scintillation process, increase the emission rate of materials, and control the directivity of the scintillated light. In this perspective, we describe emerging nanoscintillating materials and three nanophotonic platforms: (i) plasmonic nanoresonators, (ii) photonic crystals, and (iii) high-Q metasurfaces that could enable high performance scintillators. We further discuss how a combination of nanoscintillators and photonic structures can yield a "super scintillator" enabling ultimate spatio-temporal resolution while enabling a significant boost in the extracted scintillation emission.

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution.

The development of many quantum optical technologies depends on the availability of single quantum emitters with near-perfect coherence. Systematic improvement is limited by a lack of understanding of the microscopic energy flow at the single-emitter level and ultrafast timescales. Here we utilize a combination of fluorescence correlation spectroscopy and ultrafast spectroscopy to capture the sample-averaged dynamics of defects with single-particle sensitivity. We employ this approach to study heterogeneous emitters in two-dimensional hexagonal boron nitride. From milliseconds to nanoseconds, the translational, shelving, rotational and antibunching features are disentangled in time, which quantifies the normalized two-photon emission quantum yield. Leveraging the femtosecond resolution of this technique, we visualize electron-phonon coupling and discover the acceleration of polaronic formation on multi-electron excitation. Corroborated with theory, this translates to the photon fidelity characterization of cascaded emission efficiency and decoherence time. Our work provides a framework for ultrafast spectroscopy in heterogeneous emitters, opening new avenues of extreme-scale characterization for quantum applications.

Unraveling sources of emission heterogeneity in Silicon Vacancy color centers with cryo-cathodoluminescence microscopy.

Diamond color centers have proven to be versatile quantum emitters and exquisite sensors of stress, temperature, electric and magnetic fields, and biochemical processes. Among color centers, the silicon-vacancy (SiV[Formula: see text]) defect exhibits high brightness, minimal phonon coupling, narrow optical linewidths, and high degrees of photon indistinguishability. Yet the creation of reliable and scalable SiV[Formula: see text]-based color centers has been hampered by heterogeneous emission, theorized to originate from surface imperfections, crystal lattice strain, defect symmetry, or other lattice impurities. Here, we advance high-resolution cryo-electron microscopy combined with cathodoluminescence spectroscopy and 4D scanning transmission electron microscopy (STEM) to elucidate the structural sources of heterogeneity in SiV[Formula: see text] emission from nanodiamond with sub-nanometer-scale resolution. Our diamond nanoparticles are grown directly on TEM membranes from molecular-level seedings, representing the natural formation conditions of color centers in diamond. We show that individual subcrystallites within a single nanodiamond exhibit distinct zero-phonon line (ZPL) energies and differences in brightness that can vary by 0.1 meV in energy and over 70% in brightness. These changes are correlated with the atomic-scale lattice structure. We find that ZPL blue-shifts result from tensile strain, while ZPL red shifts are due to compressive strain. We also find that distinct crystallites host distinct densities of SiV[Formula: see text] emitters and that grain boundaries impact SiV[Formula: see text] emission significantly. Finally, we interrogate nanodiamonds as small as 40 nm in diameter and show that these diamonds exhibit no spatial change to their ZPL energy. Our work provides a foundation for atomic-scale structure-emission correlation, e.g., of single atomic defects in a range of quantum and two-dimensional materials.

Tuning the Chiral Growth of Plasmonic Bipyramids via the Wavelength and Polarization of Light.

Circularly polarized light (CPL) is a versatile tool to prepare chiral nanostructures, but the mechanism for inducing enantioselectivity is not well understood. This work shows that the energy and polarization of visible photons can initiate photodeposition at different sites on plasmonic nanocrystals. Here, CPL on achiral gold bipyramids (AuBPs) creates hot holes that oxidatively deposit PbO2 asymmetrically. We show for the first time that the location of PbO2 photodeposition and hence optical dissymmetry depends on the CPL wavelength. Specifically, 488 and 532 nm CPL induce PbO2 growth in the middle of AuBPs, whereas 660 nm CPL induces PbO2 growth at the tips. Our observations show that wavelength-dependent plasmonic field distributions are more important than surface lightning rod effects in localizing plasmon-mediated photochemistry. The largest optical dissymmetry occurs at excitation wavelengths between the transverse and longitudinal resonances of the AuBPs because higher-order modes are required to induce chiral electric fields.

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths annually and 10 million new cases reported each year. The causative organism, Mycobacterium tuberculosis (Mtb) can take nearly 40 days to culture, a required step to determine the pathogen's antibiotic susceptibility. Both rapid identification of Mtb and rapid antibiotic susceptibility testing (AST) are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the MtB complex strain Bacillus Calmette Guerin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin and amikacin, as well as a pan susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and in patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all 5 BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5000. We show how this instrument and our machine learning model enables combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy.

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material's detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure-function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials' intrinsic atomic and near atomic-length scale. We conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

The carotenoid redshift: Physical basis and implications for visual signaling.

Carotenoid pigments are the basis for much red, orange, and yellow coloration in nature and central to visual signaling. However, as pigment concentration increases, carotenoid signals not only darken and become more saturated but they also redshift; for example, orange pigments can look red at higher concentration. This occurs because light experiences exponential attenuation, and carotenoid-based signals have spectrally asymmetric reflectance in the visible range. Adding pigment disproportionately affects the high-absorbance regions of the reflectance spectra, which redshifts the perceived hue. This carotenoid redshift is substantial and perceivable by animal observers. In addition, beyond pigment concentration, anything that increases the path length of light through pigment causes this redshift (including optical nano- and microstructures). For example, male Ramphocelus tanagers appear redder than females, despite the same population and concentration of carotenoids, due to microstructures that enhance light-pigment interaction. This mechanism of carotenoid redshift has sensory and evolutionary consequences for honest signaling in that structures that redshift carotenoid ornaments may decrease signal honesty. More generally, nearly all colorful signals vary in hue, saturation, and brightness as light-pigment interactions change, due to spectrally asymmetrical reflectance within the visible range of the relevant species. Therefore, the three attributes of color need to be considered together in studies of honest visual signaling.

Progress and Prospects in Optical Ultrafast Microscopy in the Visible Spectral Region: Transient Absorption and Two-Dimensional Microscopy.

Ultrafast optical microscopy, generally employed by incorporating ultrafast laser pulses into microscopes, can provide spatially resolved mechanistic insight into scientific problems ranging from hot carrier dynamics to biological imaging. This Review discusses the progress in different ultrafast microscopy techniques, with a focus on transient absorption and two-dimensional microscopy. We review the underlying principles of these techniques and discuss their respective advantages and applicability to different scientific questions. We also examine in detail how instrument parameters such as sensitivity, laser power, and temporal and spatial resolution must be addressed. Finally, we comment on future developments and emerging opportunities in the field of ultrafast microscopy.

Rapid genetic screening with high quality factor metasurfaces.

Genetic analysis methods are foundational to advancing personalized medicine, accelerating disease diagnostics, and monitoring the health of organisms and ecosystems. Current nucleic acid technologies such as polymerase chain reaction (PCR) and next-generation sequencing (NGS) rely on sample amplification and can suffer from inhibition. Here, we introduce a label-free genetic screening platform based on high quality (high-Q) factor silicon nanoantennas functionalized with nucleic acid fragments. Each high-Q nanoantenna exhibits average resonant quality factors of 2,200 in physiological buffer. We quantitatively detect two gene fragments, SARS-CoV-2 envelope (E) and open reading frame 1b (ORF1b), with high-specificity via DNA hybridization. We also demonstrate femtomolar sensitivity in buffer and nanomolar sensitivity in spiked nasopharyngeal eluates within 5 minutes. Nanoantennas are patterned at densities of 160,000 devices per cm2, enabling future work on highly-multiplexed detection. Combined with advances in complex sample processing, our work provides a foundation for rapid, compact, and amplification-free molecular assays.

Controlling Valley-Specific Light Emission from Monolayer MoS2 with Achiral Dielectric Metasurfaces.

Excitons in two-dimensional transition metal dichalcogenides have a valley degree of freedom that can be optically manipulated for quantum information processing. Here, we integrate MoS2 monolayers with achiral silicon disk array metasurfaces to enhance and control valley-specific absorption and emission. Through the coupling to the metasurface electric and magnetic Mie modes, the intensity and lifetime of the emission of neutral excitons, trions, and defect bound excitons can be enhanced and shortened, respectively, while the spectral shape can be modified. Additionally, the degree of polarization (DOP) of exciton and trion emission from the valley can be symmetrically enhanced at 100 K. The DOP increase is attributed to both the metasurface-enhanced chiral absorption of light and the metasurface-enhanced exciton emission from the Purcell effect. Combining Si-compatible photonic design with large-scale 2D materials integration, our work makes an important step toward on-chip valleytronic applications approaching room-temperature operation.

Combining Acoustic Bioprinting with AI-Assisted Raman Spectroscopy for High-Throughput Identification of Bacteria in Blood.

Identifying pathogens in complex samples such as blood, urine, and wastewater is critical to detect infection and inform optimal treatment. Surface-enhanced Raman spectroscopy (SERS) and machine learning (ML) can distinguish among multiple pathogen species, but processing complex fluid samples to sensitively and specifically detect pathogens remains an outstanding challenge. Here, we develop an acoustic bioprinter to digitize samples into millions of droplets, each containing just a few cells, which are identified with SERS and ML. We demonstrate rapid printing of 2 pL droplets from solutions containing S. epidermidis, E. coli, and blood; when they are mixed with gold nanorods (GNRs), SERS enhancements of up to 1500× are achieved.We then train a ML model and achieve ≥99% classification accuracy from cellularly pure samples and ≥87% accuracy from cellularly mixed samples. We also obtain ≥90% accuracy from droplets with pathogen:blood cell ratios <1. Our combined bioprinting and SERS platform could accelerate rapid, sensitive pathogen detection in clinical, environmental, and industrial settings.

LiH formation and its impact on Li batteries revealed by cryogenic electron microscopy.

Little is known about how evolved hydrogen affects the cycling of Li batteries. Hypotheses include the formation of LiH in the solid-electrolyte interphase (SEI) and dendritic growth of LiH. Here, we discover that LiH formation in Li batteries likely follows a different pathway: Hydrogen evolved during cycling reacts to nucleate and grow LiH within already deposited Li metal, consuming active Li. We provide the evidence that LiH formed in Li batteries electrically isolates active Li from the current collector that degrades battery capacity. We detect the coexistence of Li metal and LiH also on graphite and silicon anodes, showing that LiH forms in most Li battery anode chemistries. Last, we find that LiH has its own SEI layer that is chemically and structurally distinct from the SEI on Li metal. Our results highlight the formation mechanism and chemical origins of LiH, providing critical insight into how to prevent its formation.

Universal Narrowband Wavefront Shaping with High Quality Factor Meta-Reflect-Arrays.

Optical metasurfaces offer unprecedented flexibility in light wave manipulation but suffer weak resonant enhancement. Tackling this problem, we experimentally unveil a new phase gradient metasurface platform made entirely from individually addressable high quality factor (high-Q) silicon meta-atoms. Composed of pairs of nearly identical nanoblocks, these meta-atoms support dipolar-guided-mode resonances that, due to the controlled suppression of radiation loss, serve as highly sensitive phase pixels when placed above a mirror. A key novelty of this platform lies in the vanishingly small structural perturbations needed to produce universal phase fronts. Having fabricated elements with Q-factor ∼380 and spaced by λ/1.2, we achieve strong beam steering, up to 59% efficient, to angles 32.3°, 25.3°, and 20.9°, with variations in nanoantenna volume fractions across the metasurfaces of ≤2.6%, instead of >50% required by traditional versions. Aside from extreme sensitivity, the metasurfaces exhibit near-field intensity enhancement over 1000×. Taken together, these properties represent an exciting prospect for dynamic and nonlinear wave shaping.

Mechanism for plasmon-generated solvated electrons.

Solvated electrons are powerful reducing agents capable of driving some of the most energetically expensive reduction reactions. Their generation under mild and sustainable conditions remains challenging though. Using near-ultraviolet irradiation under low-intensity one-photon conditions coupled with electrochemical and optical detection, we show that the yield of solvated electrons in water is increased more than 10 times for nanoparticle-decorated electrodes compared to smooth silver electrodes. Based on the simulations of electric fields and hot carrier distributions, we determine that hot electrons generated by plasmons are injected into water to form solvated electrons. Both yield enhancement and hot carrier production spectrally follow the plasmonic near-field. The ability to enhance solvated electron yields in a controlled manner by tailoring nanoparticle plasmons opens up a promising strategy for exploiting solvated electrons in chemical reactions.