In bulk heterojunction (BHJ) organic solar cells (OSCs) employing perylene diimide (PDI)-based non-fullerene acceptors, excessive intermolecular interactions among PDI units lead to severe aggregation and pronounced donor-acceptor phase separation, both of which critically limit device performance. To address these issues, numerous structurally engineered PDI derivatives have been developed. In particular, twisted multi-PDI architectures designed to suppress intermolecular aggregation have shown improved morphological control; however, such twisted structures are often highly amorphous, which reduces electron-transport efficiency and constrains OSC performance. In this work, we introduce a mixed-acceptor strategy combining a twisted PDI dimer (SF-PDI2) with a planar monomeric PDI (m-PDI) to balance aggregation and morphological uniformity. Ternary blend OSCs consisting of PTB7-Th as the donor and these two PDI acceptors exhibit systematic performance variations depending on their relative ratios. At the optimized composition (SF-PDI2:m-PDI = 90:10 by weight), the device outperforms single-acceptor systems, which is attributed to controlled aggregation arising from the complementary structural features of the two PDI acceptors. This study demonstrates that combining mixed PDI acceptors with similar molecular moieties enables precise control of aggregation, improving both morphology and photovoltaic performance.

Purpose The dependence of the long-time (tortuosity) limit of the extra-cellular diffusivity on the intra-cellular volume fraction is of fundamental importance for microstructure modeling. While such dependencies have been explored for the white matter, the tortuosity limit in gray matter is unknown due to complex cell composition and geometry. Here we rationalize and validate numerically the analytical relation between the extra-cellular diffusivity and intra-cellular fractions of cell bodies (somas) and neurites. Methods The tortuosity relation for extra-cellular diffusivity qualitatively follows from effective medium theory, coarse-grained by diffusion outside somas (spheres) and neurites (cylinders), respectively. This problem is equivalent to finding the overall conductivity in a medium of grains in a matrix, with methodology dating back to the 19th century. We extend the effective medium methodology to populations of impermeable spheres and randomly oriented cylinders with various volume fractions, yielding closed-form expressions corroborated by Monte Carlo simulations. Results We establish the power-law scaling of the extra-cellular diffusivity with the volume fractions of the extra-soma and extra-neurite spaces. We further evaluate the proposed framework using simulations in realistic tissue geometries, and by applying it to in vivo MRI data. Conclusion Theory and simulations relate extra-cellular tortuosity to soma and neurite fractions, thereby offering a diffusion MRI protocol design optimized for in vivo assessment of soma size and soma/neurite fractions within clinical scan times. Such in vivo measurements can be used to study development, aging, and neurodegenerative disorders.

Polarity inversion of conjugated polymers, the switching of electrical polarity with increasing doping level, is considered a promising approach for achieving n-type polymeric materials. Previous studies have attempted to explain this phenomenon, particularly in terms of changes in the band structure at different doping levels. However, polarity inversion has only been observed in a limited number of conjugated polymers, and the reasons why it does not occur universally remain unclear. Herein, the origin of the polymer-specific occurrence of polarity inversion is investigated through a systematic comparative analysis of a series of isoindigo-based conjugated polymers doped with gold(III) chloride (AuCl3). When the concentration of AuCl3 in the polymer film exceeds a certain threshold, an n-type doping pathway involving chlorination of the conjugated backbone emerges, contributing to a transition from p- to n-type behavior. The critical gold atomic density at which inversion occurs is estimated to be similar to 0.4 atoms nm-3. Importantly, the dopant uptake capability of each polymer film depends on its chemical structure; this structural dependency determines whether the dopant concentration in the film can exceed the threshold required for polarity inversion, thereby accounting for the polymer-specific differences in polarity inversion behavior.

PURPOSE:The Soma and Neurite Density Imaging (SANDI) model enables characterization of gray matter (GM) microstructure by estimating soma and neurite signal fractions, but its clinical applicability is limited by the need for multi-shell acquisitions (at least five b-values up to 6000 s/mm2), requiring high-gradient MRI systems. We developed a clinically feasible SANDI model that reduces data requirements and model complexity while preserving sensitivity to cellular-level microstructural features. METHODS:Clinical SANDI incorporates biophysical constraints via fixed intra-neurite diffusivity and a tortuosity relation from effective medium theory to estimate extracellular diffusivity from intracellular volume fractions, reducing the number of free parameters and data requirements. The model was validated using Monte Carlo diffusion simulations in GM-like microenvironments and evaluated in vivo on the ultra-high-gradient 3 T Connectome 2.0 scanner (Gmax = 500 mT/m, five-shell, ∼19 min) and a clinical 3 T system (Gmax = 80 mT/m, two-shell, ∼7 min). Additional experiments across multiple gradient strengths, diffusion times, and sites assessed model robustness. RESULTS:Diffusion simulations showed close agreement (Pearson r = 0.99) between simulated and theoretical extracellular diffusivity across varying intracellular volume fractions. With 500 mT/m gradients, clinical SANDI using two shells demonstrated strong correspondence with five-shell standard SANDI (r = 0.97, intraclass correlation coefficient = 0.94). Across reduced gradient strengths, clinical SANDI preserved cortical intra-soma signal fraction values, whereas standard SANDI exhibited underestimation at gradient strengths below 80 mT/m. CONCLUSION:Clinical SANDI enables reliable cortical GM microstructure estimation on widely available clinical 3T scanners within feasible scan times, facilitating broader translation of advanced diffusion MRI methods for studying aging, neurodegeneration, and neurological disorders.

Characterizing cortical laminar microstructure is essential for understanding human brain function. Leveraging the next-generation Connectome MRI scanner (maximum gradient strength = 500mT/m, slew rate = 600T/m/s), we characterized in vivo cortical laminar cytoarchitecture and myeloarchitecture through cortical depth-dependent analyses of soma and neurite density imaging (SANDI) metrics derived from diffusion MRI, enhanced by a super-resolution technique. SANDI revealed distinct laminar profiles: intra-soma signal fraction f is peaked at ~ 55% cortical depth, while intra-neurite signal fraction f in increased toward deeper layers, consistent with histological patterns. The visual cortex exhibited higher intra-soma signal fraction f is than the motor cortex, particularly in deeper layers. Moreover, intra-soma signal fraction f is correlated positively with cortical curvature in superficial layers and negatively in deeper layers, indicating layer-specific relationships between microstructure and cortical geometry. These findings demonstrate the feasibility of noninvasively mapping cortical laminar architecture, offering a potential surrogate for histology and enabling future studies of normative and pathological brain organization using commercially available high-performance gradient MRI systems.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a key material in solution-processed electronics due to its high electrical conductivity, optical transparency, and aqueous processability. However, its intrinsic water instability critically limits long-term device reliability, causing conductivity loss, swelling, morphological rearrangement, interfacial failure, and even film redispersion. Therefore, enhancing the water stability of PEDOT:PSS films is essential for their practical applications. In this review, water-induced degradation of PEDOT:PSS film is examined through a mechanism-oriented framework that connects molecular interactions, mesoscale structural evolution, and film-level failure. Structural characteristics of PEDOT:PSS in dispersion and solid-film states are first outlined, followed by an analysis of how water interacts with PSS-rich domains, perturbs percolated PEDOT networks, and weakens interfacial cohesion. The principal stabilization strategies, including polar solvent treatments, surfactant incorporation, crosslinking, and chemical modification of PSS, are then systematically discussed. Finally, remaining challenges and future directions for designing highly water-stable PEDOT:PSS films for durable electronic applications are highlighted.

BACKGROUND AND PURPOSE:Neurodegeneration is a key component of clinical disability in multiple sclerosis (MS). However, the underlying mechanism of localized gray matter (GM) atrophy in MS remains unknown. More recently, a network-based etiology has been postulated, which may be associated with clinical progression. The goal of this study was to determine whether GM microstructural abnormalities are organized across an atrophy-prone network. MATERIALS AND METHODS:We leveraged high-gradient diffusion MRI (dMRI) to probe GM mesoscopically by using the SANDI (Soma and Neurite Density Imaging) biophysical modeling approach. The intra-soma signal fraction (fis) was computed, which is a putative biomarker of GM cytoarchitecture. Regions of interest (ROIs) defined by nodes in the Atrophy-based Functional Network (AFN) were used to sample the individual fis map. Group-wise comparisons of the nodal and aggregate fis were assessed using Mann-Whitney U tests, and the multivariate fis (principal component 1; PC1) using independent samples t-tests, with false discovery rate (FDR) correction. Association of PC1 with the Expanded Disability Status Scale (EDSS) score was assessed using partial Spearman's rank-order correlation, controlling for age and sex. The same approach was applied to examine relationships across all nodal pairs. RESULTS:Participants included 38 MS (M/F: 11/27; age: 44 ± 11 years; EDSS: median 2.25, range: 1 - 7.5; disease duration: median 8.5 [IQR: 4.0, 14.0] years) and 35 age- and sex-matched healthy controls (HC; M/F: 15/20, p = 0.32; age: 39 ± 15 years; p = 0.13). fis was decreased in MS for the aggregate average and PC1 of all AFN nodes. Correlation of the EDSS and PC1 further showed that fis decreases as disease severity worsens (ρ = -0.44, p < 0.05). FDR-corrected covariance analysis exhibited medium-to-large effect sizes, with surviving correlations having ρ ≥ 0.39. CONCLUSION:Decreased fis in atrophy-prone GM of MS correlated with disease severity. Further, GM microstructural covariance suggests neuronal loss may relate in part to network effects. Network-based microstructural measures may therefore inform future development of quantitative methods for monitoring disease progression in MS.

Sequential solution doping is one of the most frequently used methods for doping conjugated polymer films. Since the spatial distribution of dopants in doped polymer films significantly influences their electrical properties, elucidating how various material parameters affect the dopant distribution in sequentially solution-doped polymer films is of great importance. This study investigates the effect of crystallinity in conjugated polymer thin films on the spatial distribution of dopants along the out-of-plane direction. The results show that higher crystallinity in polymer films leads to a more non-uniform dopant distribution, with a greater composition of dopants at the film surface compared to the bulk. This phenomenon is attributed to the crystallinity-dependent swellability of polymer films, where films with higher crystallinity exhibit lower swellability, resulting in less efficient dopant diffusion from the surface to the bulk compared to films with lower crystallinity. This study explores how crystallinity in conjugated polymer thin films affects dopant distribution during sequential solution doping, revealing that higher crystallinity results in a more nonuniform distribution, with greater dopant compositions at the surface than in the bulk. This is due to lower swellability, which limits effective dopant diffusion from the surface to the bulk.

The hippocampus, a brain region critical for memory, undergoes significant age-related changes at both the macroscopic and microstructural levels. This study investigates these changes using high-gradient diffusion MRI (dMRI) data analyzed in an unfolded hippocampal space. We applied the Soma and Neurite Density Imaging (SANDI) model to quantify microstructural alterations in 72 cognitively healthy participants aged 19-85 years, scanned on a 3 T Connectome MRI scanner with a maximum gradient strength of 300 mT/m. By combining SANDI with a super-resolution algorithm and the HippUnfold toolbox, we achieved high spatial fidelity in our analysis. We observed significant age-related reductions in soma fraction and soma radius, particularly in the subiculum and dentate gyrus, alongside increases in extracellular diffusivity and extracellular fraction, indicating a decline in cellular density and structural integrity. These microstructural changes occur alongside macroscopic alterations such as reduced hippocampal volume and cortical thickness, decreased gyrification, and increased curvature in specific subfields. The spatial correlations between microstructural and macroscopic metrics across the unfolded hippocampal space are weak, both in their mean values and in how they change with age. Our findings suggest that SANDI metrics provide sensitive and complementary information to traditional structural measures, offering new insights into the microstructural underpinnings of hippocampal aging. This study highlights the potential of advanced dMRI techniques to detect subtle age-related changes in hippocampal microstructure, which may contribute to our understanding of aging and its impact on memory and cognition.

Detecting neuroinflammation and neurodegeneration prior to cortical atrophy and subsequent clinical disability in people with multiple sclerosis (MS) has been challenging due to limited sensitivity on MRI. Our aim was to assess longitudinal changes in cortical cell body and neurite density related to lesion formation and atrophy using high-gradient diffusion MRI. In this longitudinal study, nine people with MS underwent 3 T high-gradient diffusion MRI at baseline and follow-up (median 5 years). Intra-soma, intra-neurite and extra-cellular signal fractions and apparent soma radius were estimated at multiple cortical depths from the pial surface and in normal-appearing, pre-lesional and lesional cortex. At baseline, lower deep gray matter volume was observed in MS relative to age- and sex-matched healthy controls. MS exhibited lower intra-soma fraction compared to HC, especially in deeper layers from the pial surface. At follow-up, cortical volumes decreased in MS, which correlated with lower baseline intra-neurite fraction. Superficial cortical layers showed increased soma radius at rates approximately four times higher than cortical volume loss. Microstructural changes were evident in the cortex at baseline where lesions were subsequently observed. Pre-lesional cortex showed higher intra-neurite fraction than normal-appearing cortex and existing lesions. Our findings provide in vivo evidence that early cortical microstructural changes may be detected by high-gradient diffusion MRI, prior to formation of detectable cortical lesions and cortical volume loss.

In recent years, mapping tissue microstructure in the cortex using high gradient diffusion MRI has received growing attention. The Soma And Neurite Density Imaging (SANDI) explicitly models the soma compartment in the cortex assuming impermeable membranes. As such, it does not account for diffusion time dependence due to water exchange in the estimated microstructural properties, as neurites in gray matter are much less myelinated than in white matter. In this work, we performed a systematic evaluation of an extended SANDI model for in vivo human cortical microstructural mapping that accounts for water exchange effects between the neurite and extracellular compartments using the anisotropic Kärger model. We refer to this model as in vivo SANDIX, adapting the nomenclature from previous publications. As in the original SANDI model, the soma compartment is modeled as an impermeable sphere due to the much smaller surface-to-volume ratio compared to the neurite compartment. A Monte Carlo simulation study was performed to examine the sensitivity of the in vivo SANDIX model to sphere radii, compartment fractions, and water exchange times. The simulation results indicate that the proposed in vivo SANDIX framework can account for the water exchange effect and provide measures of intra-soma and intra-neurite signal fractions without spurious time-dependence in estimated parameters, whereas the measured water exchange times need to be interpreted with caution. The model was then applied to in vivo diffusion MRI data acquired in 13 healthy adults on the 3-Tesla Connectome MRI scanner equipped with 300 mT/m gradients. The in vivo results exhibited patterns that were consistent with corresponding anatomical characteristics in both cortex and white matter. In particular, the estimated water exchange times in gray and white matter were distinct and differentiated between the two tissue types. Our results show the SANDIX approach applied to high-gradient diffusion MRI data achieves cortical microstructure mapping of the in vivo human brain with the evaluation of water exchange effects. This approach potentially provides a more appropriate description of in vivo cortical microstructure for improving data interpretation in future neurobiological studies.

AbstractA novel additive method to boost the Seebeck coefficient of doped conjugated polymers without a significant loss in electrical conductivity is demonstrated. Perovskite (CsPbBr3) quantum dots (QDs) passivated by ligands with long alkyl chains are mixed with a conjugated polymer in a solution phase to form polymer‐QD blend films. Solution sequential doping of the blend film with AuCl3 solution not only doped the conjugated polymer but also decomposed the QDs, resulting in a doped conjugated polymer film embedded with separated ions dissociated from the QDs. For the doped polymer‐molten QD blend films with the optimal QD content, it is found that a greatly enhanced Seebeck coefficient is achieved compared to that of the doped polymer film without QDs, while the doping level and electrical conductivity are not significantly reduced by the QD incorporation. Consequently, the power factor is enhanced, reaching a remarkably high value of up to 401.9 µW m−1 K−2 (≈155% increase with the QDs). The applicability of this method to a variety of conjugated polymers is also demonstrated. The enhancement in the Seebeck coefficient is attributed to ion‐induced local variations in the polymer work function, which generates an internal energy barrier for charge transport and causes an energy filtering effect.

Surface halide vacancies are prevalent on lead halide perovskite (LHP) quantum dots (QDs) due to their intrinsically low formation energy, and they serve as dominant non-radiative recombination centers that degrade optoelectronic performance. While ligand exchange has been commonly used to mitigate these surface defects, the influence of multidentate ligand geometry on binding interactions with QD surfaces remains largely unexplored. In this study, we demonstrate that controlling the spatial configuration of bidentate phosphine ligands by adjusting the length of the alkyl bridge connecting the phosphorus atoms can achieve better lattice matching to the CsPbI3 QD surface and thereby enhance ligand-surface binding strength. By comparing DPPM and DPPP, which possess distinct P-P separations, we show that the lattice-matched ligand DPPP exhibits stronger binding affinity due to improved steric compatibility with the QD lattice. As a result, DPPP-treated QDs exhibit significantly higher photoluminescence quantum yield and lower trap density than their DPPM-treated counterparts. Photodiodes incorporating DPPP-passivated QDs achieve enhanced responsivity and reduced dark current, reaching a specific detectivity of 5.67 × 1012 Jones. These findings highlight the critical role of ligand-lattice geometric matching in improving interfacial coordination and device performance, offering a new molecular design strategy for high-performance LHP QD-based optoelectronics.

Axon diameter and myelin thickness affect the conduction velocity of action potentials in the nervous system. Imaging them non-invasively with MRI-based methods is, thus, valuable for studying brain microstructure and function. Electron microscopy studies suggest that axon diameter and myelin thickness are closely related to each other. However, the relationship between MRI-based estimates of these microstructural measures, known to be relative indices, has not been investigated across the brain mainly due to methodological limitations. In recent years, studies using ultra-high-gradient strength diffusion MRI (dMRI) have demonstrated improved estimation of axon diameter index across white-matter (WM) tracts in the human brain, making such investigations feasible. In this study, we aim to investigate relationships between tissue microstructure properties across white-matter tracts, as estimated with MRI-based methods. We collected dMRI with ultra-high-gradient strength and multi-echo spin-echo MRI on ex vivo macaque and human brain samples on a preclinical scanner. From these data, we estimated axon diameter index, intra-axonal signal fraction, myelin water fraction (MWF), and aggregate g-ratio and investigated their correlations. We found that the correlations between axon diameter index and other microstructural imaging parameters were weak but consistent across WM tracts in samples estimated with sufficient signal-to-noise ratio. In well-myelinated regions, tissue voxels with larger axon diameter indices were associated with lower packing density, lower MWF, and a tendency of higher g-ratio. We also found that intra-axonal signal fractions and MWF were not consistently correlated when assessed in different samples. Overall, the findings suggest that MRI-based axon geometry and myelination measures can provide complementary information about fiber morphology, and the relationships between these measures agree with prior electron microscopy studies in smaller field of views. Combining these advanced measures to characterize tissue morphology may help differentiate tissue changes during disease processes such as demyelination versus axonal damage. The regional variations and relationships of microstructural measures in control samples as reported in this study may serve as a point of reference for investigating such tissue changes in disease.

This comprehensive review provides an in-depth examination of recent advances in thermoelectric (TE) materials based on conjugated polymers (CPs), emphasizing strategies aimed at enhancing their performance for energy harvesting applications. CP-based TE materials have garnered significant interest due to their inherently low thermal conductivity, mechanical flexibility, lightweight nature, and the easy tunability of molecular structures. Despite these advantages, their commercialization remains limited by challenges such as modest TE performance and insufficient long-term stability. This review explores key progress in molecular design, structural engineering, and doping strategies that have led to notable improvements in critical parameters such as electrical conductivity, Seebeck coefficient, and power factor, collectively enhancing the TE figure of merit (ZT). In addition, the article traces the historical development of CP-based flexible TE generators for wearable and portable electronics, underscoring the importance of bridging the gap between material TE properties, mechanical properties, and device realization.

Despite significant recent advancements in highly functional organic semiconductors (OSCs), the n-type OSCs reported to date lag behind their p-type counterparts in terms of long-term environmental stability. As an alternative approach to n-type materials, a few p-type polymers have been shown to undergo dramatic transitions in their charge carrier polarity to n-type through transition metal-incorporated Lewis acid doping. Although the concept of polarity switching is promising, its unclear chemical origin-particularly from a materials science perspective-limits its potential as an n-type counterpart. In this work, the chemical and structural mechanisms underlying the p-to-n polarity switching in a heavily doped conjugated polymer are elucidated. Using gold(III) chloride-doped indacenodithiophene-co-benzothiadiazole (IDTBT) as a model system, doping-induced thin-film structural changes are investigated. Quantitative X-ray photoelectron spectroscopy analysis of doped IDTBT films provides direct evidence of oxidation state changes in Au and Cl ions and confirms the covalent chlorination of the polymer backbone, establishing a direct correlation between the chemical doping mechanism and polarity switching. Finally, leveraging this polarity switching behavior, a p-n homojunction organic diode is demonstrated with a rectification ratio of 104-105, highlighting the versatility and potential of this excessively p-doped n-type OSC system for tailoring charge transport properties.

Defining the connectome, the complete matrix of structural connections between the nervous system nodes, is a challenge for human systems neuroscience due to the range of scales that must be bridged. Here we report the design of the Connectome 2.0 human magnetic resonance imaging (MRI) scanner to perform connectomics at the mesoscopic and microscopic scales with strong gradients for in vivo human imaging. We construct a 3-layer head-only gradient coil optimized to minimize peripheral nerve stimulation while achieving a gradient strength of 500 mT m−1 and a slew rate of 600 T m−1 s−1, corresponding to a 5-fold greater gradient performance than state-of-the-art research gradient systems, including the original Connectome (Connectome 1.0) scanner. We find that gains in sensitivity of up to two times were achieved by integrating a 72-channel in vivo head coil and a 64-channel ex vivo whole-brain radiofrequency coil with built-in field monitoring for data fidelity. We demonstrate mapping of fine white matter pathways and inferences of cellular and axonal size and morphology approaching the single-micron level, with at least a 30

Monitoring crops' biotic and abiotic responses through sensors is crucial for conserving resources and maintaining crop production. Existing sensors often have technical limitations, measuring only specific parameters with limited reliability and spatial or temporal resolution. Wearable sensing systems are emerging as viable alternatives for plant health monitoring. These systems employ flexible materials attached to the plant body to detect nonchemical (mechanical and optical) and chemical parameters, including transpiration, plant growth, and volatile organic compounds, alongside microclimate factors like surface temperature and humidity. In smart farming, data from real-time monitoring using these sensors, integrated with Internet of Things technologies, can enhance crop production efficiency by supporting growth environment optimization and pest and disease management. This study examines the core components of wearable standalone systems, such as sensors, circuits, and power sources, and reviews their specific sensing targets and operational principles. It further discusses wearable sensors for plant physiology and metabolite monitoring, affordability, and machine learning techniques for analyzing multimodal sensor data. By summarizing these aspects, this study aims to advance the understanding and development of wearable sensing systems for sustainable agriculture.

Background:Choroid plexus (ChP) has gained attention as a potential biomarker in neurodegenerative diseases, yet its segmentation remains challenging. Gadolinium-based contrast-enhanced MRI (CE-MRI) is the reference standard, as non-contrast MRI images lack sufficient contrast. However, gadolinium deposition, risk of nephrogenic system fibrosis in renally impaired patients, and patient discomfort limit its repeated administration. Purpose:To develop deep learning-based synthetic-contrast-enhanced MRI (SynCE-MRI) using T1-weighted images to improve ChP visualization and evaluate its ability to detect morphological changes in Parkinsonian syndromes. Materials and methods:This retrospective study included 265 (mean age = 65.7 ± 7.00 years, males/females: 120/145) consecutive patients in the internal cohort (174 with Parkinson's disease [PD], 46 with essential tremor, and 45 with atypical Parkinsonian disorder [APD]) who underwent T1W and CE-MRI at 3T from Asan Medical Center (June 2021-December 2023), and an external cohort of 58 (mean age = 60.7 ± 7.8 years, males/females: 40/18) patients (29/29 PD/APD) from Pusan National University, Yangsan Hospital (April 2011-December 2014). Nested-UNet was used for SynCE-MRI synthesis from T1W images. The 3D-UNet ChP segmentation model was trained by CE-MRI and tested using SynCE-MRI. Kruskal-Wallis and Bonferroni-corrected Mann-Whitney U tests assessed image synthesis, segmentation, and ChP morphometry (P < .05). Results:SynCE-MRI achieved high-fidelity images with peak signal-to-noise ratio (PSNR) 35.37 ± 1.32 and structural similarity index measure (SSIM) 0.970 ±0.0054. Segmentation accuracy for SynCE-MRI (dice score = 0.803 ± 0.029, 95% CI: 0.797-0.810) significantly outperformed manual (dice score = 0.59 ± 0.057, 95% CI: 0.578-0.603; P < .001) and automated (dice score = 0.489 ± 0.049, 95% CI: 0.479-0.500; P < .001) T1W-based segmentations. SynCE-MRI-based ChP volumes closely matched CE-MRI (mean absolute-volume difference [MAVD] = 6.7%; ICC = 0.88, 95% CI: 0.82-0.92). SynCE-MRI revealed significantly larger ChP volumes in APD versus PD using internal cohort (APD: 2.69 ± 0.39 mL, 95% CI: 2.54-2.84 vs PD: 2.43 ± 0.47 mL, 95% CI: 2.25-2.52; P = .04) and external cohort (APD: 2.81 ± 0.48 mL, 95% CI: 2.60-3.02 vs PD: 2.52 ± 0.45 mL, 95% CI: 2.36-2.69; P = .03). Conclusion:SynCE-MRI accurately replicates CE-MRI for ChP imaging and morphometry, outperforms T1W imaging in segmentation, and detects ChP enlargement in APD versus PD across internal and external cohorts, consistent with CE-MRI findings.

The role of polymer side chains in dopant diffusion during solution sequential doping is systematically investigated using poly(3–2-methyl-2-hexylcarboxylate)thiophene (P3ET), a polythiophene derivative with thermocleavable side chains. Two types of polymer films, P3ET with intact side chains and side-chain-free P3ET-COOH obtained by thermovleavage, are subjected to sequential treatment with an acetonitrile solution of the benchmark molecular dopant 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) and compared. Spectroscopic and microstructural analyses reveal that although comparable total amounts of F4TCNQ are incorporated into both films, their spatial distribution and aggregation behavior differ markedly. In P3ET-COOH, F4TCNQ is strongly concentrated and crystallized on the film surface, whereas in P3ET it is less concentrated and only weakly crystallized. The difference is attributed to restricted F4TCNQ diffusion in the P3ET-COOH film, arising from the absence of side chains and minimized swelling. These findings highlight the critical role of polymer side chains in enabling efficient and uniform doping of conjugated polymers via solution sequential doping.