Ruddlesden-Popper 2D Perovskite-MoS2 Hybrid Heterojunction Photocathodes for Efficient and Scalable Photo-Rechargeable Li-Ion Batteries.

Photo-rechargeable batteries (PRBs) can provide a compact solution to power autonomous smart devices located at remote sites that cannot be connected with the grid. The study reports the Ruddlesden-Popper (RP) metal halide perovskite (MHP) and molybdenum disulfide (MoS2) hybrid heterojunction-based photocathodes for Li-ion photo-rechargeable battery (Li-PRB) applications. Hybrid Lithium-ion batteries (LIBs) have demonstrated an average discharge specific capacity of 144.46 and 129.17 mAhg-1 for 50 cycles when operating at 176 and 294 mAg-1, respectively compared to the pristine LIBs which have shown specific capacity of 37.48 and 25.60 mAhg-1 under similar conditions. Hybrid Li-PRB has achieved an average dark discharge specific capacities of 128.66 mAhg-1 (capacity retention: 96.56%) which enhanced to 180.67 mAhg-1 under illumination (capacity retention: 97.39%; photo-enhancement: 40.42%) at 64 mAg-1. Excellent performance of hybrid Li-PRB is attributed to the formation of type-II heterojunction that leads to improved crystallinity and film morphology. The PRB has demonstrated a high photo conversion and storage efficiency (PC-SE) of 0.52% under standard 1 Sun illumination, which outperforms other previously reported MHP based LIBs and PRBs. This work provides a novel approach of harnessing the potential of MHPs for PRBs and offers new avenues for MHP photocathodes for various applications beyond PRBs.

Classification Framework for Medical Diagnosis of Brain Tumor with an Effective Hybrid Transfer Learning Model.

Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require caution, and even the smallest error in diagnosis can have negative repercussions. Medical errors in brain tumor diagnosis are common and frequently result in higher patient mortality rates. Magnetic resonance imaging (MRI) is widely used for tumor evaluation and detection. However, MRI generates large amounts of data, making manual segmentation difficult and laborious work, limiting the use of accurate measurements in clinical practice. As a result, automated and dependable segmentation methods are required. Automatic segmentation and early detection of brain tumors are difficult tasks in computer vision due to their high spatial and structural variability. Therefore, early diagnosis or detection and treatment are critical. Various traditional Machine learning (ML) techniques have been used to detect various types of brain tumors. The main issue with these models is that the features were manually extracted. To address the aforementioned insightful issues, this paper presents a hybrid deep transfer learning (GN-AlexNet) model of BT tri-classification (pituitary, meningioma, and glioma). The proposed model combines GoogleNet architecture with the AlexNet model by removing the five layers of GoogleNet and adding ten layers of the AlexNet model, which extracts features and classifies them automatically. On the same CE-MRI dataset, the proposed model was compared to transfer learning techniques (VGG-16, AlexNet, SqeezNet, ResNet, and MobileNet-V2) and ML/DL. The proposed model outperformed the current methods in terms of accuracy and sensitivity (accuracy of 99.51% and sensitivity of 98.90%).

A Novel Hybrid Deep Learning Model for Metastatic Cancer Detection.

Cancer has been found as a heterogeneous disease with various subtypes and aims to destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis the distinct type of cancer since they may help cancer survivors with treatment in the early stage. It must also divide cancer patients into high- and low-risk groups. While realizing efficient detection of cancer is frequently a time-taking and exhausting task with the high possibility of pathologist errors and previous studies employed data mining and machine learning (ML) techniques to identify cancer, these strategies rely on handcrafted feature extraction techniques that result in incorrect classification. On the contrary, deep learning (DL) is robust in feature extraction and has recently been widely used for classification and detection purposes. This research implemented a novel hybrid AlexNet-gated recurrent unit (AlexNet-GRU) model for the lymph node (LN) breast cancer detection and classification. We have used a well-known Kaggle (PCam) data set to classify LN cancer samples. This study is tested and compared among three models: convolutional neural network GRU (CNN-GRU), CNN long short-term memory (CNN-LSTM), and the proposed AlexNet-GRU. The experimental results indicated that the performance metrics accuracy, precision, sensitivity, and specificity (99.50%, 98.10%, 98.90%, and 97.50) of the proposed model can reduce the pathologist errors that occur during the diagnosis process of incorrect classification and significantly better performance than CNN-GRU and CNN-LSTM models. The proposed model is compared with other recent ML/DL algorithms to analyze the model's efficiency, which reveals that the proposed AlexNet-GRU model is computationally efficient. Also, the proposed model presents its superiority over state-of-the-art methods for LN breast cancer detection and classification.

Ruddlesden-Popper 2D perovskites of type (C6H9C2H4NH3)2(CH3NH3)n-1PbnI3n+1 (n = 1-4) for optoelectronic applications.

Ruddlesden-Popper (RP) phase metal halide organo perovskites are being extensively studied due to their quasi-two dimensional (2D) nature which makes them an excellent material for several optoelectronic device applications such as solar cells, photo-detectors, light emitting diodes (LEDs), lasers etc. While most of reports show use of linear carbon chain based organic moiety, such as n-Butylamine, as organic spacer in RP perovskite crystal structure, here we report a new series of quasi 2D perovskites with a ring type cyclic carbon group as organic spacer forming RP perovskite of type (CH)2(MA)n-1PbnI3n+1; CH = 2-(1-Cyclohexenyl)ethylamine; MA = Methylamine). This work highlights the synthesis, structural, thermal, optical and optoelectronic characterizations for the new RP perovskite series n = 1-4. The demonstrated RP perovskite of type for n = 1-4 have shown formation of highly crystalline thin films with alternate stacking of organic and inorganic layers, where the order of PbI6 octahedron layering are controlled by n-value, and shown uniform direct bandgap tunable from 2.51 eV (n = 1) to 1.92 eV (n = 4). The PL lifetime measurements supported the fact that lifetime of charge carriers increase with n-value of RP perovskites [154 ps (n = 1) to 336 ps (n = 4)]. Thermogravimetric analysis (TGA) showed highly stable nature of reported RP perovskites with linear increase in phase transition temperatures from 257 °C (n = 1) to 270 °C (n = 4). Scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDAX) are used to investigate the surface morphology and elemental compositions of thin films. In addition, the photodetectors fabricated for the series using (CH)2(MA)n-1PbnI3n+1 RP perovskite as active absorbing layer and without any charge transport layers, shown sharp photocurrent response from 17 nA/cm2 for n = 1 to 70 nA/cm2 for n = 4, under zero bias and low power illumination conditions (470 nm LED, 1.5 mW/cm2). Furthermore, for lowest bandgap RP perovskite n = 4, (CH)2MA3Pb4I13 the photodetector showed maximum photocurrent density of ~ 508 nA/cm2 at 3 V under similar illumination condition, thus giving fairly large responsivity (46.65 mA/W). Our investigations show that 2-(1-Cyclohexenyl)ethylamine based RP perovskites can be potential solution processed semiconducting materials for optoelectronic applications such as photo-detectors, solar cells, LEDs, photobatteries etc.

Assessing the reliability and degradation of 10-35 years field-aged PV modules.

The objective of this study was to conduct a reliability analysis on photovoltaic (PV) modules from the oldest PV installation site in Pakistan. Four sets of modules; Type A & B (30 years old), Type C (10 years old), and Type D (35 years old) were identified for this analysis. It has been observed that modules have shown degradation after working for a good number of years in the field. Comparing with nameplate data (available for Type B & C only), a drop of 28.68% and 2.99 percentage points (pp) was observed in the output power (Pmax) and efficiency (Eff.) respectively for Type B, while a drop of 22.21% and 4.05 pp was observed in Pmax and Eff. respectively for Type C. A greater drop in ISC and Pmax was observed in Type B, which is attributed to severe browning of EVA in them. While the greater drop in Pmax, in case of Type C, is attributed to the poor quality of materials used. Amongst the different defects observed, the junction box defects which include cracking and embrittlement, etc., and backsheet defects which include discoloration, delamination and cracking, etc. were found in all four types of modules. Other defects include browning of EVA, observed in Type B and D, and corrosion of frame and electrical wires, found in Type A, B, and D. This first-ever study will provide valuable information in understanding the degradation mechanism and henceforth, improving the long term reliability of PV modules in the humid-subtropical conditions of Pakistan.

Lanthanide-doped inorganic nanoparticles turn molecular triplet excitons bright.

The generation, control and transfer of triplet excitons in molecular and hybrid systems is of great interest owing to their long lifetime and diffusion length in both solid-state and solution phase systems, and to their applications in light emission1, optoelectronics2,3, photon frequency conversion4,5 and photocatalysis6,7. Molecular triplet excitons (bound electron-hole pairs) are 'dark states' because of the forbidden nature of the direct optical transition between the spin-zero ground state and the spin-one triplet levels8. Hence, triplet dynamics are conventionally controlled through heavy-metal-based spin-orbit coupling9-11 or tuning of the singlet-triplet energy splitting12,13 via molecular design. Both these methods place constraints on the range of properties that can be modified and the molecular structures that can be used. Here we demonstrate that it is possible to control triplet dynamics by coupling organic molecules to lanthanide-doped inorganic insulating nanoparticles. This allows the classically forbidden transitions from the ground-state singlet to excited-state triplets to gain oscillator strength, enabling triplets to be directly generated on molecules via photon absorption. Photogenerated singlet excitons can be converted to triplet excitons on sub-10-picosecond timescales with unity efficiency by intersystem crossing. Triplet exciton states of the molecules can undergo energy transfer to the lanthanide ions with unity efficiency, which allows us to achieve luminescent harvesting of the dark triplet excitons. Furthermore, we demonstrate that the triplet excitons generated in the lanthanide nanoparticle-molecule hybrid systems by near-infrared photoexcitation can undergo efficient upconversion via a lanthanide-triplet excitation fusion process: this process enables endothermic upconversion and allows efficient upconversion from near-infrared to visible frequencies in the solid state. These results provide a new way to control triplet excitons, which is essential for many fields of optoelectronic and biomedical research.

Hydrothermal Coating of Patterned Carbon Nanotube Forest for Structured Lithium-Ion Battery Electrodes.

Controlling the arrangement and interface of nanoparticles is essential to achieve good transfer of charge, heat, or mechanical load. This is particularly challenging in systems requiring hybrid nanoparticle mixtures such as combinations of organic and inorganic materials. This work presents a process to coat vertically aligned carbon nanotube (CNT) forests with metal oxide nanoparticles using microwave-assisted hydrothermal synthesis. Hydrothermal processes normally damage delicate CNT forests, which is addressed here by a combination of lithographic patterning, transfer printing, and reduction of the synthesis time. This process is applied for the fabrication of structured Li-ion battery (LIB) electrodes where the aligned CNTs provide a straight electron transport path through the electrode and the hydrothermal coating process is used to coat the CNTs with conversion anode materials for LIBs. These nanoparticles are anchored on the surface of the CNTs and batteries fabricated following this process show a fourfold longer cyclability. Finally, this process is used to create thick electrodes (350 µm) with a gravimetric capacity of over 900 mAh g-1 .

Triple-Cation-Based Perovskite Photocathodes with AZO Protective Layer for Hydrogen Production Applications.

Metal halide perovskites are actively pursued as photoelectrodes to drive solar fuel synthesis. However, currently, these photocathodes suffer from limited stability in water, which hampers their practical application. Here, we report a high-performance solution-processable photocathode composed of cesium formamidinium methylammonium triple-cation lead halide perovskite protected by an Al-doped ZnO (AZO) layer combined with a Field's metal encapsulation. Careful selection of charge transport layers resulted in an improvement in photocurrent, fill factor, device stability and reproducibility. The dead pixels count reduced from 25 to 6% for the devices with an AZO layer, and in photocathodes with an AZO layer the photocurrent density increased by almost 20% to 14.3 mA cm-2. In addition, we observed a 5-fold increase in the device lifetime for photocathodes with AZO, which reached up to 18 h before complete failure. Finally, the photocathodes are fabricated using low-cost and scalable methods, which have promise to become compatible with standard solution-based processes.

Strongly coloured thiocyanate frameworks with perovskite-analogue structures.

We report the first examples of thiocyanate-based analogues of the cyanide Prussian blue compounds, MIII[Bi(SCN)6], M = Fe, Cr, Sc. These compounds adopt the primitive cubic pcu topology and show strict cation order. Optical absorption measurements show these compounds have band gaps within the visible and near IR region, suggesting that they may be useful for applications where light harvesting is key, such as photocatalysis. We also show that Cr[Bi(SCN)6] can reversibly uptake water into its framework structure pointing towards the possibility of using these frameworks for host/guest chemistry.

Opal-like Multicolor Appearance of Self-Assembled Photonic Array.

Molecular self-assembly of short peptide building blocks leads to the formation of various material architectures that may possess unique physical properties. Recent studies had confirmed the key role of biaromaticity in peptide self-assembly, with the diphenylalanine (FF) structural family as an archetypal model. Another significant direction in the molecular engineering of peptide building blocks is the use of fluorenylmethoxycarbonyl (Fmoc) modification, which promotes the assembly process and may result in nanostructures with distinctive features and macroscopic hydrogel with supramolecular features and nanoscale order. Here, we explored the self-assembly of the protected, noncoded fluorenylmethoxycarbonyl-ß,ß-diphenyl-Ala-OH (Fmoc-Dip) amino acid. This process results in the formation of elongated needle-like crystals with notable aromatic continuity. By altering the assembly conditions, arrays of spherical particles were formed that exhibit strong light scattering. These arrays display vivid coloration, strongly resembling the appearance of opal gemstones. However, unlike the Rayleigh scattering effect produced by the arrangement of opal, the described optical phenomenon is attributed to Mie scattering. Moreover, by controlling the solution evaporation rate, i.e., the assembly kinetics, we were able to manipulate the resulting coloration. This work demonstrates a bottom-up approach, utilizing self-assembly of a protected amino acid minimal building block, to create arrays of organic, light-scattering colorful surfaces.

Reduced graphene oxide (rGO) based wideband optical sensor and the role of Temperature, Defect States and Quantum Efficiency.

We report a facile and cost-effective approach to develop self-standing reduced Graphene Oxide (rGO) film based optical sensor and its low-temperature performance analysis where midgap defect states play a key role in tuning the crucial sensor parameters. Graphite oxide (GO) is produced by modified Hummers' method and reduced thermally at 250 °C for 1 h in Argon atmosphere to obtain rGO. Self-standing rGO film is prepared via vacuum filtration. The developed film is characterized by HRTEM, FESEM, Raman, and XRD techniques. The developed sensor exhibits highest sensitivity towards 635 nm illumination wavelength, irrespective of the operating temperature. For a given excitation wavelength, photoresponse study at low temperature (123K-303K) reveals inverse relationship between sensitivity and operating temperature. Highest sensitivity of 49.2% is obtained at 123 K for 635 nm laser at power density of 1.4 mW/mm2. Unlike sensitivity, response- and recovery-time demonstrate directly proportional dependence with operating temperature. Power dependent studies establish linear relation between power-density and sensitivity, and a safe limit beyond which sample heating prolongs the recovery time. Wavelength-dependent studies shows that proposed sensor can efficiently operate from visible to near NIR region. To the best of our knowledge such rGO based optical sensor performance at low temperature had not been reported earlier.

Photo-Rechargeable Organo-Halide Perovskite Batteries.

Emerging autonomous electronic devices require increasingly compact energy generation and storage solutions. Merging these two functionalities in a single device would significantly increase their volumetric performance, however this is challenging due to material and manufacturing incompatibilities between energy harvesting and storage materials. Here we demonstrate that organic-inorganic hybrid perovskites can both generate and store energy in a rechargeable device termed a photobattery. This photobattery relies on highly photoactive two-dimensional lead halide perovskites to simultaneously achieve photocharging and Li-ion storage. Integrating these functionalities provides simple autonomous power solutions while retaining capacities of up to 100 mAh/g and efficiencies similar to electrodes using a mixture of batteries and solar materials.

Real-Time Observation of Exciton-Phonon Coupling Dynamics in Self-Assembled Hybrid Perovskite Quantum Wells.

Self-assembled hybrid perovskite quantum wells have attracted attention due to their tunable emission properties, ease of fabrication, and device integration. However, the dynamics of excitons in these materials, especially how they couple to phonons, remains an open question. Here, we investigate two widely used materials, namely, butylammonium lead iodide (CH3(CH2)3NH3)2PbI4 and hexylammonium lead iodide (CH3(CH2)5NH3)2PbI4, both of which exhibit broad photoluminescence tails at room temperature. We performed femtosecond vibrational spectroscopy to obtain a real-time picture of the exciton-phonon interaction and directly identified the vibrational modes that couple to excitons. We show that the choice of the organic cation controls which vibrational modes the exciton couples to. In butylammonium lead iodide, excitons dominantly couple to a 100 cm-1 phonon mode, whereas in hexylammonium lead iodide, excitons interact with phonons with frequencies of 88 and 137 cm-1. Using the determined optical phonon energies, we analyzed photoluminescence broadening mechanisms. At low temperatures (<100 K), the broadening is due to acoustic phonon scattering, whereas at high temperatures, LO phonon-exciton coupling is the dominant mechanism. Our results help explain the broad photoluminescence line shape observed in hybrid perovskite quantum wells and provide insights into the mechanism of exciton-phonon coupling in these materials.

Flexible Batteries: Hierarchical Assemblies of Carbon Nanotubes for Ultraflexible Li-Ion Batteries (Adv. Mater. 31/2016).

An advanced battery architecture composed of 3D carbon nanotube (CNT) current collectors is used to mitigate stresses in flexible batteries. On Page 6705, C. George, M. De Volder, and co-workers describe the fabrication process and characteristics of this new generation of ultraflexible batteries, which show high rate and cyclablility. These batteries may find applications in the powering of flexible displays and logics.

Hierarchical Assemblies of Carbon Nanotubes for Ultraflexible Li-Ion Batteries.

The flexible batteries that are needed to power flexible circuits and displays remain challenging, despite considerable progress in the fabrication of such devices. Here, it is shown that flexible batteries can be fabricated using arrays of carbon nanotube microstructures, which decouple stress from the energy-storage material. It is found that this battery architecture imparts exceptional flexibility (radius ≈ 300 µm), high rate (20 A g(-1) ), and excellent cycling stability.

Strong Photocurrent from Two-Dimensional Excitons in Solution-Processed Stacked Perovskite Semiconductor Sheets.

Room-temperature photocurrent measurements in two-dimensional (2D) inorganic-organic perovskite devices reveal that excitons strongly contribute to the photocurrents despite possessing binding energies over 10 times larger than the thermal energies. The p-type (C6H9C2H4NH3)2PbI4 liberates photocarriers at metallic Schottky aluminum contacts, but incorporating electron- and hole-transport layers enhances the extracted photocurrents by 100-fold. A further 10-fold gain is found when TiO2 nanoparticles are directly integrated into the perovskite layers, although the 2D exciton semiconducting layers are not significantly disrupted. These results show that strong excitonic materials may be useful as photovoltaic materials despite high exciton binding energies and suggest mechanisms to better understand the photovoltaic properties of the related three-dimensional perovskites.

Blue-Green Color Tunable Solution Processable Organolead Chloride-Bromide Mixed Halide Perovskites for Optoelectronic Applications.

Solution-processed organo-lead halide perovskites are produced with sharp, color-pure electroluminescence that can be tuned from blue to green region of visible spectrum (425-570 nm). This was accomplished by controlling the halide composition of CH3NH3Pb(BrxCl1-x)3 [0 ≤ x ≤ 1] perovskites. The bandgap and lattice parameters change monotonically with composition. The films possess remarkably sharp band edges and a clean bandgap, with a single optically active phase. These chloride-bromide perovskites can potentially be used in optoelectronic devices like solar cells and light emitting diodes (LEDs). Here we demonstrate high color-purity, tunable LEDs with narrow emission full width at half maxima (FWHM) and low turn on voltages using thin-films of these perovskite materials, including a blue CH3NH3PbCl3 perovskite LED with a narrow emission FWHM of 5 nm.

In situ intercalation dynamics in inorganic-organic layered perovskite thin films.

The properties of layered inorganic semiconductors can be manipulated by the insertion of foreign molecular species via a process known as intercalation. In the present study, we investigate the phenomenon of organic moiety (R-NH3I) intercalation in layered metal-halide (PbI2)-based inorganic semiconductors, leading to the formation of inorganic-organic (IO) perovskites [(R-NH3)2PbI4]. During this intercalation strong resonant exciton optical transitions are created, enabling study of the dynamics of this process. Simultaneous in situ photoluminescence (PL) and transmission measurements are used to track the structural and exciton evolution. On the basis of the experimental observations, a model is proposed which explains the process of IO perovskite formation during intercalation of the organic moiety through the inorganic semiconductor layers. The interplay between precursor film thickness and organic solution concentration/solvent highlights the role of van der Waals interactions between the layers, as well as the need for maintaining stoichiometry during intercalation. Nucleation and growth occurring during intercalation matches a Johnson-Mehl-Avrami-Kolmogorov model, with results fitting both ideal and nonideal cases.