Organic Cocrystal Alloys: From Three Primary Colors to Continuously Tunable Emission and Applications on Optical Waveguides and Displays.

Multicolor luminescence of organic fluorescent materials is an essential part of lighting and optical communication. However, the conventional construction of a multicolor luminescence system based on integrating multiple organic fluorescent materials of a single emission band remains complicated and to be improved. Herein, organic alloys (OAs) capable of full-color emission are synthesized based on charge transfer (CT) cocrystals. By adjusting the molar ratio of electron donors, the emission color of the OAs can be conveniently and continuously regulated in a wide visible range from blue (CIE: 0.187, 0.277), to green (CIE: 0.301, 0.550), and to red (CIE: 0.561, 0.435). The OAs show analogous 1D morphology with smooth surface, allowing for full-color waveguides with low optical-loss coefficient. Impressively, full-color optical displays are easily achieved through the OAs system with continuous emission, which shows promising applications in the field of optical display and promotes the development of organic photonics.

The Importance of Sintering-Induced Grain Boundaries in Copper Catalysis to Improve Carbon-Carbon Coupling.

Syngas conversion serves as a gas-to-liquid technology to produce liquid fuels and valuable chemicals from coal, natural gas, or biomass. During syngas conversion, sintering is known to deactivate the catalyst owing to the loss of active surface area. However, the growth of nanoparticles might induce the formation of new active sites such as grain boundaries (GBs) which perform differently from the original nanoparticles. Herein, we reported a unique Cu-based catalyst, Cu nanoparticles with in situ generated GBs confined in zeolite Y (denoted as activated Cu/Y), which exhibited a high selectivity for C5+ hydrocarbons (65.3 C%) during syngas conversion. Such high selectivity for long-chain products distinguished activated Cu/Y from typical copper-based catalysts which mainly catalyze methanol synthesis. This unique performance was attributed to the GBs, while the zeolite assisted the stabilization through spatial confinement. Specifically, the GBs enabled H-assisted dissociation of CO and subsequent hydrogenation into CHx*. CHx* species not only serve as the initiator but also directly polymerize on Cu GBs, known as the carbide mechanism. Meanwhile, the synergy of GBs and their vicinal low-index facets led to the CO insertion where non-dissociative adsorbed CO on low-index facets migrated to GBs and inserted into the metal-alkyl bond for the chain growth.

Realization of Single-Phase White-Light-Emitting Materials with Time-Evolution Ultralong Room-Temperature Phosphorescence by Coordination Assemblies.

Two Cd-based supramolecular coordination polymers, [Cd3(CzIP)3(DMF)2] (1) and [Cd2(CzIP)2(DMF)4] (2), were synthesized by using 5-(carbazol-9-yl) isophthalate (CzIP) as ligands. These two compounds exhibit multiple luminescence emissions; apart from fluorescence, time- and temperature-dependent ultralong phosphorescence (RTP) were also achieved under room conditions. Significantly, compound 1 has a long-lived afterglow of 0.93 s at 545 nm under ambient conditions. Compound 2 shows nearly pure white-light emission with CIE coordinates of (0.33, 0.33) via the dual emission of fluorescence and phosphorescence. It has come to our attention that it is the first example of a luminescent coordination polymer with single-phase white-light emission and color-evolution RTP. In addition, the long-lived RTP materials can be used in time-dependent anticounterfeiting and white-light-emitting diodes. Experimental and singlet and triplet state calculations indicate that both C-H···π interaction and inter- and intramolecular charge transfer interactions could be beneficial to the emission of ultralong RTP.

Oxalierpenes A and B, Unusual Indole-Diterpenoid Derivatives with Antiviral Activity from a Marine-Derived Strain of the Fungus Penicillium oxalicum.

Oxalierpenes A and B (1 and 2), two unusual indole-diterpenoid derivatives, were obtained from the marine-derived fungus Penicillium oxalicum. The absolute configurations of 1 and 2 were elucidated by calculated TDDFT ECD and DP4plus methods. Oxalierpene A (1) represents the first indole-diterpenoid derivative with a five-membered ring of 4-hydroxy-5,5-dimethyldihydrofuran-3-one as a side chain. Oxalierpene B (2) has a unique 6/5/6/5/5/6/6/5/5 ring system. Compounds 1 and 2 showed antiviral activity against the H1N1 virus and respiratory syncytial virus (RSV), with IC50 values ranging from 2.8 to 9.4 µM.

Intercalating Organic Hybrid Cadmium Antimony Sulfide Nanoparticles into Graphene Oxide Nanosheets for Electrochemical Lithium Storage.

Inorganic metal sulfides have received extensive investigation as anode materials in lithium-ion batteries (LIBs). However, applications of crystalline organic hybrid metal sulfides as anode materials in LIBs are quite rare. In addition, combining the nanoparticles of crystalline organic hybrid metal sulfides with conductive materials is expected to enhance the electrochemical lithium storage performance. Nevertheless, due to the difficulty of harvesting the nanoparticles of crystalline organic hybrid metal sulfides, this approach has never been tried to date. Herein, nanoparticles of a crystalline organic hybrid cadmium antimony sulfide (1,4-DABH2)Cd2Sb2S6 (DCAS) were prepared by a top-down method, including the procedures of solvothermal synthesis, ball milling, and ultrasonic pulverization. Thereafter, the nanoparticles of DCAS with sizes of ∼500 nm were intercalated into graphene oxide nanosheets through a freeze-drying treatment and a DCAS@GO composite was obtained. Compared with the reported Sb2S3- and CdS-based composites, the DCAS@GO composite exhibited superior electrochemical Li+ ion storage performance, including a high capacity of 1075.6 mAh g-1 at 100 mA g-1 and exceptional rate tolerances (646.8 mAh g-1 at 5000 mA g-1). In addition, DCAS@GO can provide a high capacity of 705.6 mAh g-1 after 500 cycles at 1000 mA g-1. Our research offers a viable approach for preparing the nanoparticles of crystalline organic hybrid metal sulfides and proves that intercalating organic hybrid metal sulfide nanoparticles into GO nanosheets can efficiently boost the electrochemical Li+ ion storage performance.

Facet sensitivity of iron carbides in Fischer-Tropsch synthesis.

Fischer-Tropsch synthesis (FTS) is a structure-sensitive reaction of which performance is strongly related to the active phase, particle size, and exposed facets. Compared with the full-pledged investigation on the active phase and particle size, the facet effect has been limited to theoretical studies or single-crystal surfaces, lacking experimental reports of practical catalysts, especially for Fe-based catalysts. Herein, we demonstrate the facet sensitivity of iron carbides in FTS. As the prerequisite, {202} and {112} facets of χ-Fe5C2 are fabricated as the outer shell through the conformal reconstruction of Fe3O4 nanocubes and octahedra, as the inner cores, respectively. During FTS, the activity and stability are highly sensitive to the exposed facet of iron carbides, whereas the facet sensitivity is not prominent for the chain growth. According to mechanistic studies, {202} χ-Fe5C2 surfaces follow hydrogen-assisted CO dissociation which lowers the activation energy compared with the direct CO dissociation over {112} surfaces, affording the high FTS activity.

Screening parameters for diagnosing primary aldosteronism in patients with moderate to severe obstructive sleep apnea hypopnea syndrome and resistant hypertension.

Background: Patients with obstructive sleep apnea hypopnea syndrome (OSAHS) combined with resistant hypertension (RH) have a high risk of developing primary aldosteronism (PA). This study investigated the aldosterone-renin ratio (ARR), plasma aldosterone concentration (PAC), and plasma renin activity (PRA) to determine the optimal cutoff values for PA diagnosis in patients with OSAHS combined with RH. Methods: Patients diagnosed with moderate and severe OSAHS combined with RH were recruited from the inpatient clinic of the Department of Endocrinology at Ji'an Central Hospital between October 2020 and April 2023. The included patients were divided into PA and no-PA groups. Diagnostic accuracy measures were calculated for each group, and receiver operating characteristic (ROC) curves were generated. Results: A total of 241 patients were included, of which 103 had positive ARR screening results in the diagnostic accuracy analysis and 66 were diagnosed with PA. PAC and ARR showed moderate predictive capacity for PA, with area under the curve (AUC) values of 0.66 [95% confidence interval (CI): 0.55-0.77] and 0.72 (95% CI: 0.63-0.82), respectively, while PRA exhibited a limited predictive capacity (AUC = 0.51, 95% CI: 0.40-0.63). Using 45 as the optimal cutoff value for ARR, the sensitivity was 86% and the specificity was 52%. The optimal cutoff value for PAC was 17, with a sensitivity of 78% and a specificity of 55%. Notably, in patients with severe OSAHS, ARR at screening demonstrated significant predictive value for PA, with an AUC of 0.84 (95% CI: 0.72-0.96), a sensitivity of 85%, and a specificity of 76%. Conversely, in patients with moderate OSAHS, only ARR demonstrated significant predictive value for PA diagnosis, while PAC did not demonstrate notable diagnostic value. Conclusion: ARR and PAC are initial screening tools for PA, facilitating early detection, particularly in low-resource settings. In patients with OSAHS and RH, the ARR and PAC thresholds for PA diagnosis may require more stringent adjustment.

Sparse Bayesian extreme learning machine for multi-classification.

Extreme learning machine (ELM) has become a popular topic in machine learning in recent years. ELM is a new kind of single-hidden layer feedforward neural network with an extremely low computational cost. ELM, however, has two evident drawbacks: 1) the output weights solved by Moore-Penrose generalized inverse is a least squares minimization issue, which easily suffers from overfitting and 2) the accuracy of ELM is drastically sensitive to the number of hidden neurons so that a large model is usually generated. This brief presents a sparse Bayesian approach for learning the output weights of ELM in classification. The new model, called Sparse Bayesian ELM (SBELM), can resolve these two drawbacks by estimating the marginal likelihood of network outputs and automatically pruning most of the redundant hidden neurons during learning phase, which results in an accurate and compact model. The proposed SBELM is evaluated on wide types of benchmark classification problems, which verifies that the accuracy of SBELM model is relatively insensitive to the number of hidden neurons; and hence a much more compact model is always produced as compared with other state-of-the-art neural network classifiers.