We designed highly efficient porphyrin sensitizers with two phenyl groups at meso-positions of the macrocycle bearing two ortho-substituted long alkoxyl chains for dye-sensitized solar cells; the ortho-substituted devices exhibit significantly enhanced photovoltaic performances with the best porphyrin, LD14, showing J(SC) = 19.167 mA cm(-2), V(OC) = 0.736 V, FF = 0.711, and overall power conversion efficiency η = 10.17%.

Novel zinc porphyrins with 1-4 π-conjugated phenylethylnyl (PE) units (labeled PE1-PE4) as a link of controlled length were synthesized for fundamental tests and applications as a dye-sensitized solar cell (DSSC). The UV-visible spectra of the solution samples show clear absorption patterns of the PE groups in a region 300-400 nm, consistent with results calculated with density-functional theory. Cyclic voltammograms of PE1-PE4 in tetrahydrofuran show similar electrochemical potentials for each compound. Femtosecond fluorescence up-conversion of solution samples and of porphyrin-sensitized TiO 2 films was measured with excitation at 420 or 430 nm and emission at 460, 470, 620, and 680 nm. When these porphyrins were fabricated into DSSC devices, the efficiency of power conversion of these devices decreased systematically with increasing length of the link: 2.5 ( 0.2% (PE1), 2.0 ( 0.1% (PE2), 0.78 ( 0.09% (PE3), 0.25 ( 0.02% (PE4). This great photovoltaic degradation from PE1 to PE4 is not interpretable according to the rate of electron injection independent of length; other factors, including electron transfer from the semiconductor back to the porphyrin cation or the electrolyte, must be considered to account for the observed dependence of photovoltaic performance on length.

Zinc porphyrins in a series bearing a phenylethynyl, naphthalenylethynyl, anthracenylethynyl, phenanthrenylethynyl or pyrenylethynyl substituent, denoted LD1, LD2, LD3a, LD3p or LD4, respectively, were prepared as photosensitizers for dye-sensitized solar cells. The overall efficiencies of the corresponding devices show a trend LD4 > LD3p > LD2 > LD3a > LD1. Significantly, LD4 features J SC /mA cm À2 ¼ 19.627, V OC /V ¼ 0.711, and FF ¼ 0.721, giving an efficiency h ¼ 10.06% of power conversion. This value is superior to that of a N719-based solar cell fabricated under similar experimental conditions. The remarkable performance of the LD4 cell is rationalized to be due to the broader and more red-shifted spectral feature that makes the IPCE spectrum to cover broadly across the entire visible region, 400-800 nm.

A series of acene-modified zinc porphyrins (benzene to pentacene, denoted as LAC-1 to LAC-5) were prepared to study their absorption spectra, electrochemical properties, and photovoltaic properties. For the absorption spectral changes in THF, porphyrin B bands are red-shifted and broadened from 449 to 501 nm for LAC-1 to LAC-3, showing the effect of additional π-conjugation. In contrast, the B bands of LAC-4 and LAC-5 are blue-shifted. In addition, the tetracenyl group of LAC-4 gives rise to absorption bands in between B and Q bands. On the other hand, the Q bands of LAC-1 to LAC-5 are systematically broadened and red-shifted from 629 to 751 nm. By comparison, the absorption bands of LAC porphyrins on TiO2 films are broadened and slightly shifted. Fluorescence emission maxima of LAC porphyrins in THF are also systematically red-shifted from LAC-1 to LAC-5. Cyclic voltammetry experiments in THF/TBAP show that the first reductions are systematically positive-shifted from −1.16 to −0.85 V vs SCE for LAC-1 to LAC-5, indicating the effect of increasing π-conjugation. As for the performance of DSSCs using LAC porphyrins, the overall efficiencies are LAC-1 (2.95%), LAC-2 (3.31%), LAC-3 (5.44%), LAC-4 (2.82%), and LAC-5 (0.10%). Overall efficiency of a LAC-3-sensitized solar cell is nearly twice of that of a LAC-1-sensitized solar cell and is about 81% overall efficiency of N719-sensitized solar cells under the same experimental conditions. The conversion efficiency of incident photons to current (IPCE) experiments shows that the broadened absorption bands of LAC-3 effectively minimizes the gap between B and Q bands, contributing to the improved DSSC performance. The very poor performance of LAC-5 is suggested to be caused by rapid nonradiative relaxation of the molecule in the singlet excited state.

This paper studies the coordinated beamforming design problem for the multiple-input single-output (MISO) interference channel, assuming only channel distribution information (CDI) at the transmitters. Under a given requirement on the rate outage probability for receivers, we aim to maximize the system utility (e.g., the weighted sum rate, weighted geometric mean rate, and the weighed harmonic mean rate) subject to the rate outage constraints and individual power constraints. The outage constraints, however, lead to a complicated, nonconvex structure for the considered beamforming design problem and make the optimization problem difficult to handle. Although this nonconvex optimization problem can be solved in an exhaustive search manner, this brute-force approach is only feasible when the number of transmitter-receiver pairs is small. For a system with a large number of transmitter-receiver pairs, computationally efficient alternatives are necessary. The focus of this paper is hence on the design of such efficient approximation methods. In particular, by employing semidefinite relaxation (SDR) and first-order approximation techniques, we propose an efficient successive convex approximation (SCA) algorithm that provides high-quality approximate beamforming solutions via solving a sequence of convex approximation problems. The solution thus obtained is further shown to be a stationary point for the SDR of the original outage constrained beamforming design problem. Furthermore, we propose a distributed SCA algorithm where each transmitter optimizes its own beamformer using local CDI and information obtained from limited message exchange with the other transmitters. Our simulation results demonstrate that the proposed SCA algorithm and its distributed counterpart indeed converge, and near-optimal performance can be achieved for all the considered system utilities.

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non-small cell lung cancer (nScLc) is one of the most common lung cancers worldwide. Accurate prognostic stratification of NSCLC can become an important clinical reference when designing therapeutic strategies for cancer patients. With this clinical application in mind, we developed a deep neural network (Dnn) combining heterogeneous data sources of gene expression and clinical data to accurately predict the overall survival of nScLc patients. Based on microarray data from a cohort set (614 patients), seven well-known NSCLC biomarkers were used to group patients into biomarker-and biomarker+ subgroups. then, by using a systems biology approach, prognosis relevance values (pRV) were then calculated to select eight additional novel prognostic gene biomarkers. finally, the combined 15 biomarkers along with clinical data were then used to develop an integrative DNN via bimodal learning to predict the 5-year survival status of NSCLC patients with tremendously high accuracy (AUC: 0.8163, accuracy: 75.44%). Using the capability of deep learning, we believe that our prediction can be a promising index that helps oncologists and physicians develop personalized therapy and build the foundation of precision medicine in the future.Lung cancer is the worldwide leading cause of cancer-related mortality, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all lung cancer patients 1 . The most common NSCLC subtypes are adenocarcinoma (ADC), squamous cell carcinoma (SQC), and large cell carcinoma. Although the overall 5-year survival rate of patients diagnosed with stage I ADC was 63%, nearly 35% of patients relapsed after surgery with a poor prognosis 2 . Adjuvant treatments have been considered ideal for ADC patients with the highest risk of recurrence or death to increase survival rates 3 . Therefore, prognostic stratification is crucial for categorizing patients to help doctors make decisions on therapeutic strategies.Recently, researchers have developed predictive methods based on gene expression profiles to classify lung cancer patients with distinct clinical outcomes, including relapse and overall survival 4 . Previous studies have shown the importance of biomarkers for NSCLC, such as EPCAM, HIF1A, PKM, PTK7, ALCAM, CADM1, and SLC2A1, which were used as a single biomarker for predicting prognostic condition or metastasis 5-11 . However, cancer is a systemic disease with complicated and illusive mechanisms that often involves multiple genes and cross-talk between pathways. Therefore, extending our understanding of NSCLC via the single gene biomarkers by studying the interactions between genes is essential for more accurate prognostic prediction.Machine learning algorithms are powerful tools that apply input features (biomarkers) to capture the complicated interdependencies between these features to accurately predict clinical outcomes 12 . In addition, predicting cancer prognosis can be improved by appropriately modeling the interactions between biomarkers compared with the single biomarker approach ...

Phenylethynyl-substituted porphyrin (PE1) sensitizers bearing a nitro, cyano, methoxy, or dimethylamino phenylethynyl substituent were prepared to examine the electron-donating or -withdrawing effects of dyes on the photovoltaic performance of the corresponding dye-sensitized solar cells. The overall efficiencies of power conversion of the devices show a systematic trend Me 2 N-PE1 > MeO-PE1 > CN-PE1 > NO 2 -PE1, for which Me 2 N-PE1 has a device performance about 90% of that of a N719-sensitized solar cell under the same experimental conditions. The superior performance of Me 2 N-PE1 is attributed to the effective electron-donating property of the dye that exhibits broadened and red-shifted spectral features. According to frontier orbitals based on DFT calculations, the electrons are effectively injected from the dye to TiO 2 for Me 2 N-PE1 and MeO-PE1 upon excitation, but that driving force reverses for NO 2 -PE1. Electrochemical tests indicate that both LUMO and HOMO levels show a systematic trend Me 2 N-PE1 > MeO-PE1 > CN-PE1 > NO 2 -PE1, consistent with the trend of variation of the short-circuit currents in this series of sensitizers.