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Additive engineering has emerged as a promising strategy to address the inherent instability challenges of perovskite solar cells (PSCs) in the pursuit of commercial viability. However, achieving multifunctionality using a singular additive remains a considerable challenge. In this study, a novel comb-like multifunctional perfluoroalkyl-g-polyethylenimmonium iodide (FPEI·HI) as additives to the PbI2 precursor solution to facilitate the formation of high-quality and water-resistant perovskite films is presented. FPEI·HI establishes robust interactions with both formamidinium iodide (FAI) and PbI2, mediated by hydrogen bonding and Lewis acid-base interactions. These interactions play a pivotal role in simultaneously passivating negative and positive charged defects within the perovskite structure. Furthermore, the inclusion of perfluoroalkyl chains serves as resilience against moisture intrusion. As a consequence of these effects, a notably high device efficiency of 24.29% is achieved, demonstrating comprehensive improvement in various photovoltaic parameters compared to the control device (22.51%). Notably, unencapsulated devices exhibit remarkable stability in high-humidity environments, retaining 90% of their initial efficiency even after 2500 h of storage. This work underscores the efficacy of FPEI·HI as a critical enabler for enhancing the stability and efficiency of perovskite solar cells, marking a significant stride toward their commercialization.
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Albeit the undesirable attributes of NiOx, such as low conductivity, unmanageable defects, and redox reactions occurring at the perovskite/NiOx interface, which impede the progress in inverted perovskite solar cells (i-PSCs), it is the most favorable choice of technology for industrialization of PSCs. In this study, we propose a novel Ni vacancy defect modulate approach to leverage the conformal growth and surface self-limiting reaction characteristics of the atomic layer deposition (ALD)-fabricated NiOx by varying the O2 plasma injection time (tOE) to induce self-doping. Consequently, NiOx thin films with enhanced conductivity, an appropriate Ni3+/Ni2+ ratio, stable surface states, and ultrathinness are realized as hole-transporting layers (HTLs) in p-i-n PSCs. As a result of these improvements, ALD-NiOx-based devices exhibit the highest power conversion efficiency (PCE) of 19.86% and a fill factor (FF) of 81.86%. Notably, the optimal interfacial defects effectively suppressed the severe reaction between the perovskite and NiOx. This suppression is evidenced by the lowest decay rate observed in a harsh environment, lasting for 500 consecutive hours. The proposed approach introduces the possibility of a hierarchical distribution of defects and offers feasibility for the fabrication of large-area, uniform, and high-quality films.
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Enzymatically derived selenium-enriched peptides from Cardamine violifolia (CV) can serve as valuable selenium supplements. However, the industrial application of free enzyme is impeded by its limited stability and reusability. Herein, this study explores the application of co-immobilized enzymes (Alcalase and Dispase) on amino resin for hydrolyzing CV proteins to produce selenium-enriched peptides. The successful enzyme immobilization was confirmed through scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and Fourier-transform infrared spectroscopy (FTIR). Co-immobilized enzyme at a mass ratio of 5:1 (Alcalase/Dispase) exhibited the smallest pore size (7.065 nm) and highest activity (41 U/mg), resulting in a high degree of hydrolysis of CV protein (27.2%), which was obviously higher than the case of using free enzymes (20.7%) or immobilized Alcalase (25.8%). In addition, after a month of storage, the co-immobilized enzyme still retained a viability level of 41.93%, showing fairly good stability. Encouragingly, the selenium-enriched peptides from co-immobilized enzyme hydrolysis exhibited uniform distribution of selenium forms, complete amino acid fractions and homogeneous distribution of molecular weight, confirming the practicality of using co-immobilized enzymes for CV protein hydrolysis.
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The reconstruction of Cu catalysts during electrochemical reduction of CO2 is a widely known but poorly understood phenomenon. Herein, we examine the structural evolution of Cu nanocubes under CO2 reduction reaction and its relevant reaction conditions using identical location transmission electron microscopy, cyclic voltammetry, in situ X-ray absorption fine structure spectroscopy and ab initio molecular dynamics simulation. Our results suggest that Cu catalysts reconstruct via a hitherto unexplored yet critical pathway - alkali cation-induced cathodic corrosion, when the electrode potential is more negative than an onset value (e.g., -0.4 VRHE when using 0.1 M KHCO3). Having alkali cations in the electrolyte is critical for such a process. Consequently, Cu catalysts will inevitably undergo surface reconstructions during a typical process of CO2 reduction reaction, resulting in dynamic catalyst morphologies. While having these reconstructions does not necessarily preclude stable electrocatalytic reactions, they will indeed prohibit long-term selectivity and activity enhancement by controlling the morphology of Cu pre-catalysts. Alternatively, by operating Cu catalysts at less negative potentials in the CO electrochemical reduction, we show that Cu nanocubes can provide a much more stable selectivity advantage over spherical Cu nanoparticles.
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Di(2-ethylhexyl)phthalate (DEHP) is commonly released from plastics in aqueous environment, which can disrupt endocrine system and cause adverse effects on public health. There is a pressing need to highly sensitive detect DEHP. Herein, a near-infrared (NIR) light-driven lab-on-paper cathodic photoelectrochemical aptasensing platform integrated with AgInS2/Cu2O/FeOOH photocathode and "Y"-like ternary conjugated DNA nanostructure-mediated "ON-OFF" catalytic switching of hemin monomer-to-dimer was established for ultrasensitive DEHP detection. Profiting from the collaborative roles of the effective photosensitization of NIR-response AgInS2 and the fast hole extraction of FeOOH, the NIR light-activated AgInS2/Cu2O/FeOOH photocathode generated a markedly enhanced photocathodic signal. The dual hemin-labelled "Y"-like ternary conjugated DNA nanostructures made the hemin monomers separated in space and they maintained highly active to catalyze in situ generation of electron acceptors (O2). The hemin monomers were relocated in close proximity with the help of target-induced allosteric change of DNA nanostructures, which could spontaneously dimerize into catalytically inactive hemin dimers and fail to mediate electron acceptors generation, resulting in a decreased photocathodic signal. Therefore, the ultrasensitive DEHP detection was realized with a linear response range of 1 pM-500 nM and a detection limit of 0.39 pM. This work rendered a promising prototype to construct powerful paper-based photocathodic aptasensing system for sensitive and accurate screening of DEHP in aqueous environment.
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Cobre , Dietilexilftalato , Técnicas Eletroquímicas , Eletrodos , Raios Infravermelhos , Processos Fotoquímicos , Cobre/química , Técnicas Eletroquímicas/métodos , Dietilexilftalato/química , Dietilexilftalato/análise , Aptâmeros de Nucleotídeos/química , Técnicas Biossensoriais/métodos , Papel , Prata/química , Limite de Detecção , Índio/química , Poluentes Químicos da Água/análise , Poluentes Químicos da Água/químicaRESUMO
The efficacy of electron transport layers (ETLs) is pivotal for optimizing the device performance of perovskite photovoltaic applications. However, colloidal dispersions of SnO2 are prone to aggregation and possess structural defects, such as terminal-hydroxyls (OHT) and oxygen vacancies (VOs), which can degrade the quality of ETLs, impede charge extraction and transport, and affect the nucleation and growth processes of the perovskite layer. In this study, the Sb(OH)4 - ions hydrolyzed from SbCl3 in colloidal dispersion can bind to defect sites and effectively stabilize the SnO2 nanocrystals are demonstrated. Upon oxidative annealing, a Sb2O5@SnO2 composite film is formed, in which the Sb2O5 not only mitigates the aforementioned defects but also broadens the energy range of unoccupied states through its dispersed conduction band. The increased electron affinity (EA) facilitates more efficient capture of photoexcited electrons from the perovskite layer, thus augmenting electron extraction and minimizing electron-hole recombination. As a result, a significant improvement in power conversion efficiency (PCE) from 22.60% to 24.54% is achieved, with an open circuit voltage (VOC) of up to 1.195 V, along with excellent stability of unsealed devices under various conditions. This study provides valuable insights for the understanding and design of ETLs in perovskite photovoltaic applications.
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INTRODUCTION: Osteoarthritis (OA) is a devastating whole-joint disease affecting a large population worldwide; the role of lipid dysregulation in OA and mechanisms underlying targeted therapy effect of lipid-lowering metformin on OA remains poorly defined. OBJECTIVES: To investigate the effects of lipid dysregulation on OA progression and to explore lipid dysregulation-targeting OA treatment of metformin. METHODS: RNA-Seq data, biochemical, and histochemical assays in human and murine OA cartilage as well as primary chondrocytes were utilized to determine lipid dysregulation. Effects of metformin, a potent lipid-lowering medication, on ACSL4 expression and chondrocyte metabolism were determined. Further molecular experiments, including RT-qPCR, western blotting, flow cytometry, and immunofluorescence staining, were performed to investigate underlying mechanisms. Mice with intra-articular injection of metformin were utilized to determine the effects on ACLT-induced OA progression. RESULTS: ACSL4 and 4-HNE expressions were elevated in human and ACLT-induced mouse OA cartilage and IL-1ß-treated chondrocytes (P < 0.05). Ferrostatin-1 largely rescued IL-1ß-induced MDA, lipid peroxidation, and ferroptotic mitochondrial morphology (P < 0.05). Metformin decreased the levels of OA-related genes (P < 0.05) and increased the levels of p-AMPK and p-ACC in IL-1ß-treated chondrocytes. Intra-articular injection of metformin alleviated ACLT-induced OA lesions in mice, and reverted the percentage of chondrocytes positive for MMP13, Col2a1, ACSL4 and 4-HNE in ACLT mice (P < 0.05). Ferroptotic chondrocytes promoted the recruitment and chemotaxis of RAW264.7 cells via CCL2, which was blocked by metformin in vitro (P < 0.05). CONCLUSION: We establish a critical role of polyunsaturated fatty acids metabolic process in OA cartilage degradation and define metformin as a potential OA treatment. Metformin reshapes lipid availability and ameliorates chondrocyte ferroptosis sensitivity via the AMPK/ACC pathway. In the future, gene-edited animals and extensive omics technologies will be utilized to reveal detailed lipids' involvement in cartilage lesions.
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Drought and floods seriously affect agriculture across the world. It is of great importance to lower down the agricultural vulnerability to disasters to build climate-resilient agriculture. The paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought and floods in the world in the period 2003-2019. Research results show that (1) the agricultural vulnerability to drought and floods is at a low level across the globe owning to the dual effects of decreasing exposure and increasing adaptability; (2) the northern parts of United States, northeastern parts of China, and the border between Russia and Kazakhstan are identified as most vulnerable areas to drought and floods; and (3) spatio-temporal mismatch of precipitation is the main factor to cause floods and drought while better adaption is beneficial to minimize the adverse effects of disasters. Based on analysis on the drivers and spatial patterns of drought and floods risk in all dimensions, tailored measures and policies are put forwards to make adaptive strategies of agriculture to climate change.
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Agricultura , Mudança Climática , Secas , Inundações , Desastres , China , Análise Espaço-TemporalRESUMO
The specific and excellent properties of the low-dimensional nanomaterials have made them promising building blocks to be integrated into microelectromechanical systems with high performances. Here, we present a new microheater chip for in situ TEM, in which a cross-stacked superaligned carbon nanotube (CNT) film resistor is located on a suspended SiNx membrane via van der Waals (vdW) interactions. The CNT microheater has a fast high-temperature response and low power consumption, thanks to the micro/nanostructure of the CNT materials. Moreover, the membrane bulging amplitude is significantly reduced to only â¼100 nm at 800 °C for the vdW interaction between the CNTs and the SiNx membrane. An in situ observation of the Sn melting process is successfully conducted with the assistance of a customized flexible temperature control system. The uniform wafer-scaled CNT films enable a high level of consistency and cost-effective mass production of such chips. The as-developed in situ chips, as well as the related techniques, hold great promise in nanoscience, materials science, and electrochemistry.
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Tuning the interfacial Schottky barrier with van der Waals (vdW) contacts is an important solution for two-dimensional (2D) electronics. Here we report that the interlayer dipoles of 2D vdW superlattices (vdWSLs) can be used to engineer vdW contacts to 2D semiconductors. A bipolar WSe2 with Ba6Ta11S28 (BTS) vdW contact was employed to exhibit this strategy. Strong interlayer dipoles can be formed due to charge transfer between the Ba3TaS5 and TaS2 layers. Mechanical exfoliation breaks the superlattice and produces two distinguished surfaces with TaS2 and Ba3TaS5 terminations. The surfaces thus have opposite surface dipoles and consequently different work functions. Therefore, all the devices fall into two categories in accordance with the rectifying direction, which were verified by electrical measurements and scanning photocurrent microscopy. The growing vdWSL family along with the addition surface dipoles enables prospective vdW contact designs and have practical application in nanoelectronics and nano optoelectronics.
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Despite the remarkable progress of perovskite solar cells (PSCs), challenges remain in terms of finding effective and viable strategies to enhance their long-term stability while maintaining high efficiency. In this study, a new insulating and hydrophobic fluorinated polyimide (FPI: 6FDA-6FAPB) was used as the interface layer between the perovskite layer and the hole transport layer (HTL) in PSCs. The functional groups of FPI play a pivotal role in passivating interface defects within the device. Due to its high work function, FPI demonstrates field-effect passivation (FEP) capabilities as an interface layer, effectively mitigating non-radiative recombination at the interface. Notably, the FPI insulating interface layer does not impede carrier transmission at the interface, which is attributed to the presence of hole tunneling effects. The optimized PSCs achieve an outstanding power conversion efficiency (PCE) of 24.61 % and demonstrate excellent stability, showcasing the efficacy of FPI in enhancing device performance and reliability.
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In recent years, researchers have become focused on the relationship between lipids and bone metabolism balance. Moreover, many diseases related to lipid metabolism disorders, such as nonalcoholic fatty liver disease, atherosclerosis, obesity, and menopause, are associated with osteoporotic phenotypes. It has been clinically observed in humans that these lipid metabolism disorders promote changes in osteoporosis-related indicators bone mineral density and bone mass. Furthermore, similar osteoporotic phenotype changes were observed in high-fat and high-cholesterol-induced animal models. Abnormal lipid metabolism (such as increased oxidized lipids and elevated plasma cholesterol) affects bone microenvironment homeostasis via cross-organ communication, promoting differentiation of mesenchymal stem cells to adipocytes, and inhibiting commitment towards osteoblasts. Moreover, disturbances in lipid metabolism affect the bone metabolism balance by promoting the secretion of cytokines such as receptor activator of nuclear factor-kappa B ligand by osteoblasts and stimulating the differentiation of osteoclasts. Conclusively, this review addresses the possible link between lipid metabolism disorders and osteoporosis and elucidates the potential modulatory mechanisms and signaling pathways by which lipid metabolism affects bone metabolism balance. We also summarize the possible approaches and prospects of intervening lipid metabolism for osteoporosis treatment.
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2,2',7,7'-Tetrakis(N,N-di-p-methoxyphenyl)-amine-9,9'-spirobifluorene (Spiro-OMeTAD) represents the state-of-the-art hole-transporting material (HTM) in n-i-p perovskite solar cells (PSCs). However, its susceptibility to stability issues has been a long-standing concern. In this study, we embark on a comprehensive exploration of the untapped potential within the family of spiro-type HTMs using an innovative anisotropic regulation strategy. Diverging from conventional approaches that can only modify spirobifluorene with single functional group, this approach allows us to independently tailor the two orthogonal components of the spiro-skeleton at the molecular level. The newly designed HTM, SF-MPA-MCz, features enhanced thermal stability, precise energy level alignment, superior film morphology, and optimized interfacial properties when compared to Spiro-OMeTAD, which contribute to a remarkable power conversion efficiency (PCE) of 24.53% for PSCs employing SF-MPA-MCz with substantially improved thermal stability and operational stability. Note that the optimal concentration for SF-MPA-MCz solution is only 30 mg/ml, significantly lower than Spiro-OMeTAD (>70 mg/ml), which could remarkably reduce the cost especially for large-area processing in future commercialization. This work presents a promising avenue for the versatile design of multifunctional HTMs, offering a blueprint for achieving efficient and stable PSCs.
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This review paper aims to serve as a comprehensive guide and instructional resource for researchers seeking to effectively implement language models in medical imaging research. First, we presented the fundamental principles and evolution of language models, dedicating particular attention to large language models. We then reviewed the current literature on how language models are being used to improve medical imaging, emphasizing a range of applications such as image captioning, report generation, report classification, findings extraction, visual question response systems, interpretable diagnosis and so on. Notably, the capabilities of ChatGPT were spotlighted for researchers to explore its further applications. Furthermore, we covered the advantageous impacts of accurate and efficient language models in medical imaging analysis, such as the enhancement of clinical workflow efficiency, reduction of diagnostic errors, and assistance of clinicians in providing timely and accurate diagnoses. Overall, our goal is to have better integration of language models with medical imaging, thereby inspiring new ideas and innovations. It is our aspiration that this review can serve as a useful resource for researchers in this field, stimulating continued investigative and innovative pursuits of the application of language models in medical imaging.
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Diagnóstico por Imagem , Diagnóstico por Imagem/métodos , Humanos , Idioma , Processamento de Imagem Assistida por Computador/métodosRESUMO
BACKGROUND: Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer-related death. Gleason score (GS) is the primary driver of PCa risk-stratification and medical decision-making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non-invasive method to further characterize PCa, providing additional anatomical and functional information. Meanwhile, the diagnostic power of MRI is limited by qualitative or, at best, semi-quantitative interpretation criteria, leading to inter-reader variability. PURPOSES: Computer-aided diagnosis employing quantitative MRI analysis has yielded promising results in non-invasive prediction of GS. However, convolutional neural networks (CNNs) do not implicitly impose a frame of reference to the objects. Thus, CNNs do not encode the positional information properly, limiting method robustness against simple image variations such as flipping, scaling, or rotation. Capsule network (CapsNet) has been proposed to address this limitation and achieves promising results in this domain. In this study, we develop a 3D Efficient CapsNet to stratify GS-derived PCa risk using T2-weighted (T2W) MRI images. METHODS: In our method, we used 3D CNN modules to extract spatial features and primary capsule layers to encode vector features. We then propose to integrate fully-connected capsule layers (FC Caps) to create a deeper hierarchy for PCa grading prediction. FC Caps comprises a secondary capsule layer which routes active primary capsules and a final capsule layer which outputs PCa risk. To account for data imbalance, we propose a novel dynamic weighted margin loss. We evaluate our method on a public PCa T2W MRI dataset from the Cancer Imaging Archive containing data from 976 patients. RESULTS: Two groups of experiments were performed: (1) we first identified high-risk disease by classifying low + medium risk versus high risk; (2) we then stratified disease in one-versus-one fashion: low versus high risk, medium versus high risk, and low versus medium risk. Five-fold cross validation was performed. Our model achieved an area under receiver operating characteristic curve (AUC) of 0.83 and 0.64 F1-score for low versus high grade, 0.79 AUC and 0.75 F1-score for low + medium versus high grade, 0.75 AUC and 0.69 F1-score for medium versus high grade and 0.59 AUC and 0.57 F1-score for low versus medium grade. Our method outperformed state-of-the-art radiomics-based classification and deep learning methods with the highest metrics for each experiment. Our divide-and-conquer strategy achieved weighted Cohen's Kappa score of 0.41, suggesting moderate agreement with ground truth PCa risks. CONCLUSIONS: In this study, we proposed a novel 3D Efficient CapsNet for PCa risk stratification and demonstrated its feasibility. This developed tool provided a non-invasive approach to assess PCa risk from T2W MR images, which might have potential to personalize the treatment of PCa and reduce the number of unnecessary biopsies.
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Imageamento por Ressonância Magnética , Redes Neurais de Computação , Neoplasias da Próstata , Masculino , Neoplasias da Próstata/diagnóstico por imagem , Humanos , Imageamento Tridimensional/métodosRESUMO
Raman spectroscopy is widely applied in identifying local structures in materials, but the interpretation of Raman spectra is non-trivial. An accurate computational database of reference spectra calculated with a consistent level of theory can significantly aid in interpreting measured Raman spectra. Here, we present a database of Raman spectra of inorganic compounds calculated with accurate hybrid functionals in density functional theory. Raman spectra were obtained by calculating dynamical matrices and polarizability tensors for structures from the Inorganic Crystal Structure Database. The calculated Raman spectra and other phonon properties (e.g., infrared spectra) are stored in a MongoDB database publicly shared through a web application. We assess the accuracy of our Raman calculations by statistically comparing ~80 calculated spectra with an existing experimental Raman database. To date, the database contains 161 compounds and is continuously growing as we add more materials computed with our automated workflow.
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Di(2-ethylhexyl)phthalate (DEHP), as an environmental endocrine disruptor, has adverse effects on eco-environments and health. Thus, it is crucial to highly sensitive on-site detect DEHP. Herein, a double-enzyme active MnO2@BSA mediated dual-modality photoelectrochemical (PEC)/colorimetric aptasensing platform with the cascaded sensitization structures of ZnIn2S4 and TiO2 as signal generators was engineered for rapid and ultrasensitive detection of DEHP using an all-in-one lab-on-paper analytical device. Benefitting from cascaded sensitization effect, the ZnIn2S4/TiO2 photosensitive structures-assembled polypyrrole paper electrode gave an enhanced photocurrent signal. The MnO2@BSA nanoparticles (NPs) with peroxidase-mimic and oxidase-mimic double-enzymatic activity induced multiple signal quenching effects and catalyzed color development. Specifically, the MnO2@BSA NPs acted as peroxidase mimetics to generate catalytic precipitates, which not only obstructed interfacial electron transfer but also served as electron acceptors to accept photogenerated electrons. Besides, the steric hindrance effect from MnO2@BSA NPs-loaded branchy polymeric DNA duplex structures further decreased photocurrent signal. The target recycling reaction caused the detachment of MnO2@BSA NPs to increase PEC signal, realizing the ultrasensitive detection of DEHP with a low detection limit of 27 fM. Ingeniously, the freed MnO2@BSA NPs flowed to colorimetric zone with the aid of fluid channels and acted as oxidase mimetics to induce color intensity enhancement, resulting in the rapid visual detection of DEHP. This work provided a prospective paradigm to develop field-based paper analytical tool for DEHP detection in aqueous environment.
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Dietilexilftalato , Polímeros , Compostos de Manganês , Estudos Prospectivos , Óxidos , Pirróis , Peroxidase , Peroxidases , CorantesRESUMO
Ultraviolet-induced degradation has emerged as a critical stability concern impeding the widespread adoption of perovskite solar cells (PSCs), particularly in the context of phase-unstable wide-band gap perovskite films. This study introduces a novel approach by employing a fully aromatic carbazole-based self-assembled monolayer, denoted as (4-(3,6-dimethoxy-9H-carbazol-9-yl)phenyl)phosphonic acid (MeO-PhPACz), as a hole-selective layer (HSL) in inverted wide-band gap PSCs. Incorporating a conjugated linker plays a pivotal role in promoting the formation of a dense and highly ordered HSL on substrates, facilitating subsequent perovskite interfacial interactions, and fostering the growth of uniform perovskite films. The high-quality film could effectively suppress interfacial non-radiative recombination, improving hole extraction/transport efficiency. Through these advancements, the optimized wide-band gap PSCs, featuring a band gap of 1.68â eV, attain an impressive power conversion efficiency (PCE) of 21.10 %. Remarkably, MeO-PhPACz demonstrates inherent UV resistance and heightened UV absorption capabilities, substantially improving UV resistance for the targeted PSCs. This characteristic holds significance for the feasibility of large-scale outdoor applications.
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BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone image registration, ultimately reducing patient radiation dose and setup uncertainty. In this work, we propose a MRI-to-CT transformer-based improved denoising diffusion probabilistic model (MC-IDDPM) to translate MRI into high-quality sCT to facilitate radiation treatment planning. METHODS: MC-IDDPM implements diffusion processes with a shifted-window transformer network to generate sCT from MRI. The proposed model consists of two processes: a forward process, which involves adding Gaussian noise to real CT scans to create noisy images, and a reverse process, in which a shifted-window transformer V-net (Swin-Vnet) denoises the noisy CT scans conditioned on the MRI from the same patient to produce noise-free CT scans. With an optimally trained Swin-Vnet, the reverse diffusion process was used to generate noise-free sCT scans matching MRI anatomy. We evaluated the proposed method by generating sCT from MRI on an institutional brain dataset and an institutional prostate dataset. Quantitative evaluations were conducted using several metrics, including Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), Multi-scale Structure Similarity Index (SSIM), and Normalized Cross Correlation (NCC). Dosimetry analyses were also performed, including comparisons of mean dose and target dose coverages for 95% and 99%. RESULTS: MC-IDDPM generated brain sCTs with state-of-the-art quantitative results with MAE 48.825 ± 21.491 HU, PSNR 26.491 ± 2.814 dB, SSIM 0.947 ± 0.032, and NCC 0.976 ± 0.019. For the prostate dataset: MAE 55.124 ± 9.414 HU, PSNR 28.708 ± 2.112 dB, SSIM 0.878 ± 0.040, and NCC 0.940 ± 0.039. MC-IDDPM demonstrates a statistically significant improvement (with p < 0.05) in most metrics when compared to competing networks, for both brain and prostate synthetic CT. Dosimetry analyses indicated that the target dose coverage differences by using CT and sCT were within ± 0.34%. CONCLUSIONS: We have developed and validated a novel approach for generating CT images from routine MRIs using a transformer-based improved DDPM. This model effectively captures the complex relationship between CT and MRI images, allowing for robust and high-quality synthetic CT images to be generated in a matter of minutes. This approach has the potential to greatly simplify the treatment planning process for radiation therapy by eliminating the need for additional CT scans, reducing the amount of time patients spend in treatment planning, and enhancing the accuracy of treatment delivery.