Coherent photoexcitation of entangled triplet pair states.

The functional properties of organic semiconductors are defined by the interplay between optically bright and dark states. Organic devices require rapid conversion between these bright and dark manifolds for maximum efficiency, and one way to achieve this is through multiexciton generation (S1→1TT). The dark state 1TT is typically generated from bright S1 after optical excitation; however, the mechanistic details are hotly debated. Here we report a 1TT generation pathway in which it can be coherently photoexcited, without any involvement of bright S1. Using <10-fs transient absorption spectroscopy and pumping sub-resonantly, 1TT is directly generated from the ground state. Applying this method to a range of pentacene dimers and thin films of various aggregation types, we determine the critical material properties that enable this forbidden pathway. Through a strikingly simple technique, this result opens the door for new mechanistic insights into 1TT and other dark states in organic materials.

Elucidating Singlet-Fission-Born Multiexciton Dynamics via Molecular Engineering: A Dilution Principle Extended to Quintet Triplet Pair.

Multiexciton in singlet exciton fission represents a critical quantum state with significant implications for both solar cell applications and quantum information science. Two distinct fields of interest explore contrasting phenomena associated with the geminate triplet pair: one focusing on the persistence of long-lived correlation and the other emphasizing efficient decorrelation. Despite the pivotal nature of multiexciton processes, a comprehensive understanding of their dependence on the structural and spin properties of materials is currently lacking in experimental realizations. To address this gap in knowledge, molecular engineering was employed to modify the TIPS-tetracene structures, enabling an investigation of the structure-property relationships in spin-related multiexciton processes. In lieu of the time-resolved electron paramagnetic resonance technique, two time-resolved magneto-optical spectroscopies were implemented for quantitative analysis of spin-dependent multiexciton dynamics. The utilization of absorption and fluorescence signals as complementary optical readouts, in the presence of a magnetic field, provided crucial insights into geminate triplet pair dynamics. These insights encompassed the duration of multiexciton correlation and the involvement of the spin state in multiexciton decorrelation. Furthermore, simulations based on our kinetic models suggested a role for quintet dilution in multiexciton dynamics, surpassing the singlet dilution principle established by the Merrifield model. The integration of intricate model structures and time-resolved magneto-optical spectroscopies served to explicitly elucidate the interplay between structural and spin properties in multiexciton processes. This comprehensive approach not only contributes to the fundamental understanding of these processes but also aligns with and reinforces previous experimental studies of solid states and theoretical assessments.

Necking Reduction at Low Temperature in Aspect Ratio Etching of SiO2 at CF4/H2/Ar Plasma.

This study investigated the effect of temperature on the aspect-ratio etching of SiO2 in CF4/H2/Ar plasma using patterned samples of a 200 nm trench in a low-temperature reactive-ion etching system. Lower temperatures resulted in higher etch rates and aspect ratios for SiO2. However, the plasma property was constant with the chuck temperature, indicated by the line intensity ratio from optical emission spectroscopy monitoring of the plasma. The variables obtained from the characterization of the etched profile for the 200 nm trench after etching were analyzed as a function of temperature. A reduction in the necking ratio affected the etch rate and aspect ratio of SiO2. The etching mechanism of the aspect ratio etching of SiO2 was discussed based on the results of the surface composition at necking via energy-dispersive X-ray spectroscopy with temperature. The results suggested that the neutral species reaching the etch front of SiO2 had a low sticking coefficient. The bowing ratio decreased with lowering temperature, indicating the presence of directional ions during etching. Therefore, a lower temperature for the aspect ratio etching of SiO2 could achieve a faster etch rate and a higher aspect ratio of SiO2 via the reduction of necking than higher temperatures.

Anthracene derivatives with strong spin-orbit coupling and efficient high-lying reverse intersystem crossing beyond the El-Sayed rule.

The attention to materials with hot exciton channel and triplet-triplet fusion (TTF) mediated high-lying reverse intersystem crossing (hRISC) has been raised for their ability to convert non-emissive 'dark' triplets into radiative singlet excitons. This spin conversion process results in high exciton utilization efficiency (EUE) that exceeds the theoretical limits. Notably, it is known that such spin conversion processes from the high-lying excited triplet to the singlet state are facilitated by the orthogonal orbital transition effect governed by the El-Sayed's rule. In this study, an anthracene derivative with indenoquinoline substituent 7,7-dimethyl-9-(10-(4-(naphthalen-1-yl)phenyl)anthracen-9-yl)-7H-indeno[1,2-f]quinoline (2MIQ-NPA) was synthesized and analyzed to investigate whether the hRISC process occurs in these molecules, even when the El-Sayed's rule is not followed. The hRISC channels of the emitter were fully unraveled through DFT calculations and experiments, which were quantitatively subdivided using transient electroluminescence measurements. The results showed that 2MIQ-NPA, which does not follow the El-Sayed's rule and has a relatively strong spin-orbit coupling matrix element of 0.116 cm-1 between the high-lying triplet state of T4 and the lowest singlet state of S1, effectively converted triplet excitons into singlet excitons with an EUE of 64.3%, contributed by a direct hot exciton channel of 19.2% and a TTF-mediated hot exciton channel of 15.1%. Despite the low outcoupling efficiency, the non-doped device with 2MIQ-NPA achieved an excellent device performance with an external quantum efficiency of 7.0%.

Controlling Intramolecular Singlet Fission Dynamics via Torsional Modulation of Through-Bond versus Through-Space Couplings.

Covalent dimers, particularly pentacenes, are the dominant platform for developing a mechanistic understanding of intramolecular singlet fission (iSF). Numerous studies have demonstrated that a photoexcited singlet state in these structures can rapidly and efficiently undergo exciton multiplication to form a correlated pair of triplets within a single molecule, with potential applications from photovoltaics to quantum information science. One of the most significant barriers limiting such dimers is the fast recombination of the triplet pair, which prevents spatial separation and the formation of long-lived triplet states. There is an ever-growing need to develop general synthetic strategies to control the evolution of triplets following iSF and enhance their lifetime. Here, we rationally tune the dihedral angle and interchromophore separation between pairs of pentacenes in a systematic series of bridging units to facilitate triplet separation. Through a combination of transient optical and spin-resonance techniques, we demonstrate that torsion within the linker provides a simple synthetic handle to tune the fine balance between through-bond and through-space interchromophore couplings that steer iSF. We show that the full iSF pathway from femtosecond to microsecond timescales is tuned through the static coupling set by molecular design and structural fluctuations that can be biased through steric control. Our approach highlights a straightforward design principle to generate paramagnetic spin pair states with higher yields.

Superatom-in-Superatom Nanoclusters: Synthesis, Structure, and Photoluminescence.

We report a new strategy in which a thiolate-protected Ag25 nanocluster can be doped with open d-shell group 8 (Ru, Os) and 9 (Ir) metals by forming metal hydride (RuH2 , OsH2 , IrH) superatoms with a closed d-shell. Structural analyses using various experimental and theoretical methods revealed that the Ag25 nanoclusters were co-doped with the open d-shell metal and hydride species to produce superatom-in-superatom nanoclusters, establishing a novel superatom doping phenomenon for open d-shell metals. The synthesized superatom-in-superatom nanoclusters exhibited dopant-dependent photoluminescence (PL) properties. Comparative PL lifetime studies of the Ag25 nanoclusters doped with 8-10 group metals revealed that both radiative and nonradiative processes were significantly dependent on the dopant. The former is strongly correlated with the electron affinity of the metal dopant, whereas the latter is governed predominantly by the kernel structure changed upon the doping of the metal hydride(s).

Progressive Contextual Aggregation Empowered by Pixel-wise Confidence Scoring for Image Inpainting.

Image inpainting methods leverage the similarity of adjacent pixels to create alternative content. However, as the invisible region becomes larger, the pixels completed in the deeper hole are difficult to infer from the surrounding pixel signal, which is more prone to visual artifacts. To help fill this void, we adopt an alternative progressive hole-filling scheme that hierarchically fills the corrupted region in the feature and image spaces. This technique allows us to utilize reliable contextual information of the surrounding pixels, even for large hole samples, and then gradually complete the details as the resolution increases. For a more realistic representation of the completed region, we devise a pixel-wise dense detector. By distinguishing each pixel as whether it is a masked region or not, and passing the gradient to all resolutions, the generator further enhances the potential quality of the compositing. Furthermore, the completed images at different resolutions are then merged using a proposed structure transfer module (STM) that incorporates fine-grained local and coarse-grained global interactions. In this new mechanism, each completed image at the different resolutions attends its closest composition at fine granularity adjacent image and thus can capture the global continuity by interacting both short- and long-range dependencies. By comparing our solutions qualitatively and quantitatively with state-of-the-art methods, we conclude that our model exhibits a significantly improved visual quality, even in the case of large holes.

Neural Network Models for Driving Control of Indoor Autonomous Vehicles in Mobile Edge Computing.

Mobile edge computing has been proposed as a solution for solving the latency problem of traditional cloud computing. In particular, mobile edge computing is needed in areas such as autonomous driving, which requires large amounts of data to be processed without latency for safety. Indoor autonomous driving is attracting attention as one of the mobile edge computing services. Furthermore, it relies on its sensors for location recognition because indoor autonomous driving cannot use a GPS device, as is the case with outdoor driving. However, while the autonomous vehicle is being driven, the real-time processing of external events and the correction of errors are required for safety. Furthermore, an efficient autonomous driving system is required because it is a mobile environment with resource constraints. This study proposes neural network models as a machine-learning method for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the range data measured with the LiDAR sensor. We designed six neural network models to be evaluated according to the number of input data points. In addition, we made an autonomous vehicle based on the Raspberry Pi for driving and learning and an indoor circular driving track for collecting data and performance evaluation. Finally, we evaluated six neural network models in terms of confusion matrix, response time, battery consumption, and driving command accuracy. In addition, when neural network learning was applied, the effect of the number of inputs was confirmed in the usage of resources. The result will influence the choice of an appropriate neural network model for an indoor autonomous vehicle.

From Human Pose Similarity Metric to 3D Human Pose Estimator: Temporal Propagating LSTM Networks.

Predicting a 3D pose directly from a monocular image is a challenging problem. Most pose estimation methods proposed in recent years have shown 'quantitatively' good results (below  âˆ¼ 50mm). However, these methods remain 'perceptually' flawed because their performance is only measured via a simple distance metric. Although this fact is well understood, the reliance on 'quantitative' information implies that the development of 3D pose estimation methods has been slowed down. To address this issue, we first propose a perceptual Pose SIMilarity (PSIM) metric, by assuming that human perception (HP) is highly adapted to extracting structural information from a given signal. Second, we present a perceptually robust 3D pose estimation framework: Temporal Propagating Long Short-Term Memory networks (TP-LSTMs). Toward this, we analyze the information-theory-based spatio-temporal posture correlations, including joint interdependency, temporal consistency, and HP. The experimental results clearly show that the proposed PSIM metric achieves a superior correlation with users' subjective opinions than conventional pose metrics. Furthermore, we demonstrate the significant quantitative and perceptual performance improvements of TP-LSTMs compared to existing state-of-the-art methods.

Single-Image 3-D Reconstruction: Rethinking Point Cloud Deformation.

Single-image 3-D reconstruction has long been a challenging problem. Recent deep learning approaches have been introduced to this 3-D area, but the ability to generate point clouds still remains limited due to inefficient and expensive 3-D representations, the dependency between the output and the number of model parameters, or the lack of a suitable computing operation. In this article, we present a novel deep-learning-based method to reconstruct a point cloud of an object from a single still image. The proposed method can be decomposed into two steps: feature fusion and deformation. The first step extracts both global and point-specific shape features from a 2-D object image, and then injects them into a randomly generated point cloud. In the second step, which is deformation, we introduce a new layer termed as GraphX that considers the interrelationship between points like common graph convolutions but operates on unordered sets. The framework can be applicable to realistic image data with background as we optionally learn a mask branch to segment objects from input images. To complement the quality of point clouds, we further propose an objective function to control the point uniformity. In addition, we introduce different variants of GraphX that cover from best performance to best memory budget. Moreover, the proposed model can generate an arbitrary-sized point cloud, which is the first deep method to do so. Extensive experiments demonstrate that we outperform the existing models and set a new height for different performance metrics in single-image 3-D reconstruction.

Parallel triplet formation pathways in a singlet fission material.

Harvesting long-lived free triplets in high yields by utilizing organic singlet fission materials can be the cornerstone for increasing photovoltaic efficiencies potentially. However, except for polyacenes, which are the most studied systems in the singlet fission field, spin-entangled correlated triplet pairs and free triplets born through singlet fission are relatively poorly characterized. By utilizing transient absorption and photoluminescence spectroscopy in supramolecular aggregate thin films consisting of Hamilton-receptor-substituted diketopyrrolopyrrole derivatives, we show that photoexcitation gives rise to the formation of spin-0 correlated triplet pair 1(TT) from the lower Frenkel exciton state. The existence of 1(TT) is proved through faint Herzberg-Teller emission that is enabled by vibronic coupling and correlated with an artifact-free triplet-state photoinduced absorption in the near-infrared. Surprisingly, transient electron paramagnetic resonance reveals that long-lived triplets are produced through classical intersystem crossing instead of 1(TT) dissociation, with the two pathways in competition. Moreover, comparison of the triplet-formation dynamics in J-like and H-like thin films with the same energetics reveals that spin-orbit coupling mediated intersystem crossing persists in both. However, 1(TT) only forms in the J-like film, pinpointing the huge impact of intermolecular coupling geometry on singlet fission dynamics.

Ultrafast Symmetry-Breaking Charge Separation in a Perylene Bisimide Dimer Enabled by Vibronic Coupling and Breakdown of Adiabaticity.

Perylene bisimides (PBIs) have received great attention in their applicability to optoelectronics. Especially, symmetry-breaking charge separation (SB-CS) in PBIs has been investigated to mimic the efficient light capturing and charge generation in natural light-harvesting systems. However, unlike ultrafast CS dynamics in donor-acceptor heterojunction materials, ultrafast SB-CS in a stacked homodimer has still been challenging due to excimer formation in the absence of rigidifying surroundings such as a special pair in the natural systems. Herein, we present the detailed mechanism of ultrafast photoinduced SB-CS occurring in a 1,7-bis(N-pyrrolidinyl) PBI dimer within a cyclophane. Through narrow-band and broad-band transient absorption spectroscopy, we demonstrate that ultrafast SB-CS in the dimer is enabled by the combination of (1) vibrationally coherent charge-transfer resonance-enhanced excimer formation and (2) breakdown of adiabaticity (formation of SB-CS diabats) in the excimer state via structural and solvent fluctuation. Quantum chemical calculations also underpin that the participation of strong electron-donating substituents in overall vibrational modes plays a crucial role in triggering the ultrafast SB-CS. Therefore, our work provides an alternative route to facilitate ultrafast SB-CS in PBIs and thereby establishes a novel strategy for the design of optoelectronic materials.

Gel Chromatography for Separation of Single-Walled Carbon Nanotubes.

Carbon nanotubes (CNTs), having either metallic or semiconducting properties depending on their chirality, are advanced materials that can be used for different devices and materials (e.g., fuel cells, transistors, solar cells, reinforced materials, and medical materials) due to their excellent electrical conductivity, mechanical strength, and thermal conductivity. Single-walled CNTs (SWNTs) have received special attention due to their outstanding electrical and optical properties; however, the inability to selectively synthesize specific types of CNTs has been a major obstacle for their commercialization. Therefore, researchers have studied different methods for the separation of SWNTs based on their electrical and optical properties. Gel chromatography methods enable the large-scale separation of metallic/semiconducting (m/s) SWNTs and single-chirality SWNTs with specific bandgaps. The core principle of gel chromatography-based SWNT separation is the interaction between the SWNTs and gels, which depends on the unique electrical properties of the former. Controlled pore glass, silica gel, agarose-based gel, and allyl dextran-based gel have been exploited as mediums for gel chromatography. In this paper, the interaction between SWNTs and gels and the different gel chromatography-based SWNT separation technologies are introduced. This paper can serve as a reference for researchers who plan to separate SWNTs with gel chromatography.

Synthesis and Characterizations of 5,5'-Bibenzo[rst]pentaphene with Axial Chirality and Symmetry-Breaking Charge Transfer.

Exploration of novel biaryls consisting of two polycyclic aromatic hydrocarbon (PAH) units can be an important strategy toward further developments of organic materials with unique properties. In this study, 5,5'-bibenzo[rst]pentaphene (BBPP) with two benzo[rst]pentaphene (BPP) units is synthesized in an efficient and versatile approach, and its structure is unambiguously elucidated by X-ray crystallography. BBPP exhibits axial chirality, and the (M)- and (P)-enantiomers are resolved by chiral high-performance liquid chromatography and studied by circular dichroism spectroscopy. These enantiomers have a relatively high isomerization barrier of 43.6 kcal mol-1 calculated by density functional theory. The monomer BPP and dimer BBPP are characterized by UV-vis absorption and fluorescence spectroscopy, cyclic voltammetry, and femtosecond transient absorption spectroscopy. The results indicate that both BPP and BBPP fluoresce from a formally dark S1 electronic state that is enabled by Herzberg-Teller intensity borrowing from a neighboring bright S2 state. While BPP exhibits a relatively low photoluminescence quantum yield (PLQY), BBPP exhibits a significantly enhanced PLQY due to a greater S2 intensity borrowing. Moreover, symmetry-breaking charge transfer in BBPP is demonstrated by spectroscopic investigations in solvents of different polarity. This suggests high potential for singlet fission in such π-extended biaryls through appropriate molecular design.

Real-time Observation of Structural Dynamics Triggering Excimer Formation in a Perylene Bisimide Folda-dimer by Ultrafast Time-Domain Raman Spectroscopy.

In π-conjugated organic photovoltaic materials, an excimer state has been generally regarded as a trap state which hinders efficient excitation energy transport. But despite wide investigations of the excimer for overcoming the undesirable energy loss, the understanding of the relationship between the structure of the excimer in stacked organic compounds and its properties remains elusive. Here, we present the landscape of structural dynamics from the excimer formation to its relaxation in a co-facially stacked archetypical perylene bisimide folda-dimer using ultrafast time-domain Raman spectroscopy. We directly captured vibrational snapshots illustrating the ultrafast structural evolution triggering the excimer formation along the interchromophore coordinate on the complex excited-state potential surfaces and following evolution into a relaxed excimer state. Not only does this work showcase the ultrafast structural dynamics necessary for the excimer formation and control of excimer characteristics but also provides important criteria for designing the π-conjugated organic molecules.

A Deep Motion Sickness Predictor Induced by Visual Stimuli in Virtual Reality.

In a virtual reality (VR) environment, where visual stimuli predominate over other stimuli, the user experiences cybersickness because the balance of the body collapses due to self-motion. Accordingly, the VR experience is accompanied by unavoidable sickness referred to as visually induced motion sickness (VIMS). In this article, our primary purpose is to simultaneously estimate the VIMS score by referring to the content and calculate the temporally induced VIMS sensitivity. To seek our goals, we propose a novel architecture composed of two consecutive networks: 1) neurological representation and 2) spatiotemporal representation. In the first stage, the network imitates and learns the neurological mechanism of motion sickness. In the second stage, the significant feature of the spatial and temporal domains is expressed over the generated frames. After the training procedure, our model can calculate VIMS sensitivity for each frame of the VR content by using the weakly supervised approach for unannotated temporal VIMS scores. Furthermore, we release a massive VR content database. In the experiments, the proposed framework demonstrates excellent performance for VIMS score prediction compared with existing methods, including feature engineering and deep learning-based approaches. Furthermore, we propose a way to visualize the cognitive response to visual stimuli and demonstrate that the induced sickness tends to be activated in a similar tendency, as done in clinical studies.

Gray Ramus Communicans Nerve Block for Acute Pain Control in Vertebral Compression Fracture.

Background and Objectives: The current options for acute pain control of vertebral compression fracture include hard brace, vertebroplasty, early surgery, and analgesic injection. We hypothesize that the gray ramus communicans nerve block (GRNB) controls the acute pain experienced during vertebral compression fractures. This study assessed the time course of pain control after injection and evaluated the risk factors affecting pain control failure. Materials and methods: Sixty-three patients (24 male, 66.19 ± 15.17 y) with a thoracolumbar vertebral fracture at the T10-L5 spine, who presented to our hospital from November 2018 to October 2019, were included in this retrospective cohort study. GRNB was performed within 1 week of the trauma. The patients were followed up on days 3, 14, 30, 90, and 180 and assessed with the serial visual analog scale (VAS, resting and motion), Oswestry Low Back Disability (ODI) questionnaire, and Roland-Morris Disability Questionnaire (RDQ). The failure group was defined by the need for an additional block or cement injection after a single GRNB. The failure group's risk factors, such as body mass index, initial thoracolumbar injury classification and severity score, Kummel's disease, age, bone marrow density (BMD), and underlying disease, were analyzed. Results: The motion VAS score improved from preoperative to three months post-procedure, but the resting VAS was affected by the procedure for only three days. The quality of life index improved at postoperative six months. A lower BMD was the only risk that affected treatment failure in the logistic regression analysis (p = 0.0038). Conclusion: The effect of GRNB was maintained even at three months after trauma based on motion VAS results. The only risk factor identified for GRNB failure was lower BMD.

Silicon Oxide Etching Process of NF3 and F3NO Plasmas with a Residual Gas Analyzer.

The use of NF3 is significantly increasing every year. However, NF3 is a greenhouse gas with a very high global warming potential. Therefore, the development of a material to replace NF3 is required. F3NO is considered a potential replacement to NF3. In this study, the characteristics and cleaning performance of the F3NO plasma to replace the greenhouse gas NF3 were examined. Etching of SiO2 thin films was performed, the DC offset of the plasma of both gases (i.e., NF3 and F3NO) was analyzed, and a residual gas analysis was performed. Based on the analysis results, the characteristics of the F3NO plasma were studied, and the SiO2 etch rates of the NF3 and F3NO plasmas were compared. The results show that the etch rates of the two gases have a difference of 95% on average, and therefore, the cleaning performance of the F3NO plasma was demonstrated, and the potential benefit of replacing NF3 with F3NO was confirmed.

If we build it, they will come: Caregiver decision to use an accessible outpatient psychiatric service for children and adolescents in Nigeria.

OBJECTIVE: If child and adolescent psychiatric (CAP) services were accessible in lower-middle-income countries (LMIC) such as Nigeria, what individual and socio-cultural factors would influence caregivers' willingness to use these services when they are needed? METHODS: To address this question, we conducted structured interviews with a stratified random sampling of 442 adult caregivers of children aged 5 to 19-years who lived within 10 km of an established CAP outpatient service in Ibadan, Nigeria. RESULTS: Based on structural equation modeling, our cross-sectional findings indicated that caregivers were generally willing to use the accessible outpatient CAP service for a narrow range of overtly disruptive and developmentally atypical child behavior. However, their decisions were not influenced by their recognition of child and adolescent mental health (CAMH) conditions, competing life stressors, caregiver wellness, nor stigma as we had initially hypothesized. Rather caregivers pragmatically considered a range of approaches to address CAMH concerns. Post-hoc hypotheses confirmed that caregivers' beliefs about etiology and treatment effectiveness for CAMH conditions shaped their help-seeking decisions and stigmatization of CAP services. Specifically, caregivers who attributed CAMH conditions to physical causes regarded biomedical interventions as the most effective treatment while spiritual interventions were deemed to be the least effective. CONCLUSIONS: Taken together our results suggested that caregivers were receptive and willing to use outpatient psychiatric services for their children. However, their beliefs about the etiology and treatment effectiveness of CAMH conditions shaped how they intended to engage the services. These findings underscored the importance of scaling up a broader spectrum of accessible complementary CAMH intervention and prevention services in Nigeria that extend beyond indigenous or biomedical models. In doing so caregivers will come.

Simulator for Interactive and Effective Organization of Things in Edge Cluster Computing.

Edge computing is intended to process events that occur at the endpoint of the Internet of Things (IoT) network quickly and intelligently. Edge regions must be organized effectively to facilitate cooperation so that the intention of edge computing can be realized. However, inevitably, many human and material resources are required in the process of arranging things in the edge area to confirm the appropriateness of the thing operation. To address this problem, we proposed a simulator that created a virtual space for edge computing and provided an interactive role and effective organization for edge things. The proposed simulator was aimed at Raspberry Pi as the physical hardware target. To prove the accuracy of the proposed simulator, the similarity between the proposed simulator and the physical target Raspberry Pi was evaluated based on three metrics while executing several applications. In the experiment, several edge-computing service applications were performed in various cluster architecture types formed by the proposed simulator. To support effective resource usage and fast real-time response for edge computing, the proposed simulator identified a suitable number of things in forming the edge cluster.