Unlike traditional photoluminescence (PL), mechanoluminescence (ML) achieved under mechanical excitation demonstrates unique characteristics such as high penetrability, spatial resolution, and signal-to-background ratio (SBR) for bioimaging applications. However, bioimaging with organic mechanoluminescent materials remains challenging because of the shallow penetration depth of ML with short emission wavelengths and the absence of a suitable mechanical force to generate ML in vivo. To resolve these issues, the present paper reports the achievement of ultrasound (US)-excited fluorescence and phosphorescence from purely organic luminogens for the first time with emission wavelengths extending to the red/NIR region, with the penetrability of the US-excited emission being considerably higher than that of PL. Consequently, US-excited subcutaneous phosphorescence imaging can be achieved using a mechanoluminescent-luminogen-based capsule device with a quantified intensity of 9.15 ± 1.32 × 104 p s-1 cm-2 sr-1 and an SBR of 24. Moreover, the US-excited emission can be adequately tuned using the packing modes of the conjugated skeletons, dipole orientation of mechanoluminescent luminogens, and strength and direction of intermolecular interactions. Overall, this study innovatively expands the kind of excitation sources and the emission wavelengths of organic mechanoluminescent materials, paving the way for practical biological applications based on US-excited emission.

Amyloid-beta (Aβ42) aggregates are characteristic Alzheimer\'s disease signatures, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational \"wobble\" of Nile blue (NB) molecules transiently binding to Aβ42 fibrils. We correlate fibril architectures measured by SMOLM with their growth and decay over the course of 5 to 20 min visualized by single-molecule localization microscopy (SMLM). We discover that stable Aβ42 fibrils tend to be well-ordered and signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order and disorder are signatures of growing and decaying fibrils, respectively. We also observe SMLM-invisible fibril remodeling, including steady growth and decay patterns that conserve β-sheet organization. SMOLM reveals that increased fibril architectural heterogeneity is correlated with dynamic remodeling and that large-scale fibril remodeling tends to originate from strongly heterogeneous local regions.

Amyloid-beta (Aβ42) aggregates are characteristic signatures of Alzheimer\'s disease, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational \"wobble\" of Nile blue (NB) molecules transiently binding to Aβ42 fibrils. We quantify correlations between fibril architectures, measured by SMOLM, and their growth and decay visualized by single-molecule localization microscopy (SMLM). We discover that stable Aβ42 fibrils tend to be well-ordered, signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order and disorder are signatures of growing and decaying Aβ42 fibrils, respectively. We also observe SMLM-invisible fibril remodeling, including steady growth and decay patterns that conserve β-sheet organization. SMOLM reveals that increased heterogeneity in fibril architectures is correlated with more dynamic remodeling and that large-scale fibril remodeling tends to originate from local regions that exhibit strong heterogeneity.

Defect engineering is promising to tailor the physical properties of 2D semiconductors for function-oriented electronics and optoelectronics. Compared with the extensively studied 2D binary materials, the origin of defects and their influence on physical properties of 2D ternary semiconductors are not clarified. Here, the effect of defects on the electronic structure and optical properties of few-layer hexagonal Znln2 S4 is thoroughly studied via versatile spectroscopic tools in combination with theoretical calculations. It is demonstrated that the Zn-In antistructural defects induce the formation of a series of donor and acceptor energy levels and sulfur vacancies induce donor energy levels, leading to rich recombination paths for defect emission and extrinsic absorption. Impressively, the emission of donor-acceptor pair in Znln2 S4 can be significantly tailored by electrostatic gating due to efficient tunability of Fermi level (Ef ). Furthermore, the layer-dependent dipole orientation of defect emission in Znln2 S4 is directly revealed by back focal plane imagining, where it presents obviously in-plane dipole orientation within a dozen-layer thickness of Znln2 S4 . These unique features of defects in Znln2 S4 including extrinsic absorption, rich recombination paths, gate tunability, and in-plane dipole orientation are definitely a benefit to the advanced orientation-functional optoelectronic applications.

We determine precise nanoscale information about the morphologies of several organic thin film structures using Fourier plane imaging microscopy (FIM). We used FIM microscopy to detect the orientation of molecular transition dipole moments from an extremely low density of luminescent dye molecules, which we call \"morphology sensors\". The orientation of the sensor molecules is driven by the local film structure and thus can be used to determine details of the host morphology without influencing it. We use symmetric planar phosphorescent dye molecules as the sensors that are deposited into the bulk of organic film hosts during the growth. We demonstrate morphological mapping with a depth resolution to a few Ångstroms that is limited by the ability to determine thickness during deposition, along with an in-plane resolution limited by optical diffraction. Furthermore, we monitor morphological changes arising from thermal annealing of metastable organic films that are commonly employed in photonic devices.

Fluorescence polarization microscopy (FPM) analyzes both intensity and orientation of fluorescence dipole, and reflects the structural specificity of target molecules. It has become an important tool for studying protein organization, orientational order, and structural changes in cells. However, suffering from optical diffraction limit, conventional FPM has low orientation resolution and observation accuracy, as the polarization information is averaged by multiple fluorescent molecules within a diffraction-limited volume. Recently, novel super-resolution FPMs have been developed to break the diffraction barrier. In this review, we will introduce the recent progress to achieve sub-diffraction determination of dipole orientation. Biological applications, based on polarization analysis of fluorescence dipole, are also summarized, with focus on chromophore-target molecule interaction and molecular organization.

Determining the anatomical source of brain activity non-invasively measured from EEG or MEG sensors is challenging. In order to simplify the source localization problem, many techniques introduce the assumption that current sources lie on the cortical surface. Another common assumption is that this current flow is orthogonal to the cortical surface, thereby approximating the orientation of cortical columns. However, it is not clear which cortical surface to use to define the current source locations, and normal vectors computed from a single cortical surface may not be the best approximation to the orientation of cortical columns. We compared three different surface location priors and five different approaches for estimating dipole vector orientation, both in simulations and visual and motor evoked MEG responses. We show that models with source locations on the white matter surface and using methods based on establishing correspondences between white matter and pial cortical surfaces dramatically outperform models with source locations on the pial or combined pial/white surfaces and which use methods based on the geometry of a single cortical surface in fitting evoked visual and motor responses. These methods can be easily implemented and adopted in most M/EEG analysis pipelines, with the potential to significantly improve source localization of evoked responses.

In the family of III-VI monochalcogenides M2X2 (M = gallium, indium; X = sulfur, selenide, etc.), the interlayer interaction and the electronic band edges share the contribution of the same chalcogenide atomic orbits. This makes quantum confinement and interlayer interaction play a subtle role in two-dimensional (2D) monochalcogenides crystals. In this report, we study the direction-resolved photoluminescence of 2D Ga2Se2 at various thicknesses. We observe that the in-plane dipole radiation survives, but out-of-plane dipole radiation fades at 2D limits.

We proposed and showed strongly orientation-controlled Förster resonance energy transfer (FRET) to highly anisotropic CdSe nanoplatelets (NPLs). For this purpose, we developed a liquid-air interface self-assembly technique specific to depositing a complete monolayer of NPLs only in a single desired orientation, either fully stacked (edge-up) or fully nonstacked (face-down), with near-unity surface coverage and across large areas over 20 cm2. These NPL monolayers were employed as acceptors in an energy transfer working model system to pair with CdZnS/ZnS core/shell quantum dots (QDs) as donors. We found the resulting energy transfer from the QDs to be significantly accelerated (by up to 50%) to the edge-up NPL monolayer compared to the face-down one. We revealed that this acceleration of FRET is accounted for by the enhancement of the dipole-dipole interaction factor between a QD-NPL pair (increased from 1/3 to 5/6) as well as the closer packing of NPLs with stacking. Also systematically studying the distance-dependence of FRET between QDs and NPL monolayers via varying their separation (d) with a dielectric spacer, we found out that the FRET rate scales with d-4 regardless of the specific NPL orientation. Our FRET model, which is based on the original Förster theory, computes the FRET efficiencies in excellent agreement with our experimental results and explains well the enhancement of FRET to NPLs with stacking. These findings indicate that the geometrical orientation of NPLs and thereby their dipole interaction strength can be exploited as an additional degree of freedom to control and tune the energy transfer rate.

In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.