Ultrafast Nonvolatile Ionic Liquids-Based Supercapacitors with Al Foam-Enhanced Carbon Electrode.

The ultrafast frequency response supercapacitor is a promising candidate for alternating current line filtering. We report the fabrication of a special structured ionic liquid-based supercapacitor with an ultrafast response of only 1.5 ms. The three-dimensional aluminum (Al) foam in situ coated with carbon layer (∼500 nm) serves as the novel, highly efficient electrode-current collector. The high porosity (95%) of Al foam allows the rapid ion diffusion and the as-obtained Al/C interface with atomic-level mixing allows the fast electron transfer, two crucial factors for ultrafast response. Hence, it possesses an excellent specific mass capacitance of 68 mF g-1 at 120 Hz, as well as an ultrahigh rate of up to 3000 V s -1. The supercapacitors exhibit frequency modulation performance in the range of 20 kHz to 16 MHz. They exhibit the similar even better alternating current filtering performance, as compared to the commercial aluminum electrolytic capacitors, detected at 10 Hz, 60 Hz, 100 Hz and 1 M Hz. These results suggest that, although ILs have high viscosity and low ion mobility, the IL-based supercapacitor has a great potential to be used as a device for alternating current line filtering, as well as providing nonvolatile and nonflammability safety.

Semi-automatic lymphoma detection and segmentation using fully conditional random fields.

The detection and delineation of the lymphoma volume are a critical step for its treatment and its outcome prediction. Positron Emission Tomography (PET) is widely used for lymphoma detection. Two common types of approaches can be distinguished for lymphoma detection and segmentation in PET. The first one is ROI dependent which needs a ROI defined by physicians. The second one is based on machine learning methods which need a large learning database. However, such a large standard database is quite rare in medical field. Considering these problems, we propose a new approach that combines PET (metabolic information) with CT (anatomical information). Our approach is semi-automatic, it consists of three steps. First, an anatomical multi-atlas segmentation is applied on CT to locate and remove the organs having physiologic hypermetabolism in PET. Then, CRFs (Conditional Random Fields) detect and segment a set of possible lymphoma volumes in PET. The conditional probabilities used in CRFs are usually estimated by a learning step. In this work, we propose to estimate them in an unsupervised way. The final step is to visualize the detected lymphoma volumes and select the real ones by simply clicking on them. The false detection is low thanks to the first step. Our method is tested on 11 patients. The rate of good detection of lymphoma is 100%. The average of Dice indexes for measuring the lymphoma segmentation performance is 84.4% compared to the manual lymphoma segmentation. Comparing with other methods in terms of Dice index shows the best performance of our method.

Highly electroconductive mesoporous graphene nanofibers and their capacitance performance at 4 V.

We report the fabrication of one-dimensional highly electroconductive mesoporous graphene nanofibers (GNFs) by a chemical vapor deposition method using MgCO3·3H2O fibers as the template. The growth of such a unique structure underwent the first in situ decomposition of MgCO3·3H2O fibers to porous MgO fibers, followed by the deposition of carbon on the MgO surface, the removal of MgO by acidic washing, and the final self-assembly of wet graphene from single to double layer in drying process. GNFs exhibited good structural stability, high surface area, mesopores in large amount, and electrical conductivity 3 times that of carbon nanotube aggregates. It, used as an electrode in a 4 V supercapacitor, exhibited high energy density in a wide range of high power density and excellent cycling stability. The short diffusion distance for ions of ionic liquids electrolyte to the surface of GNFs yielded high surface utilization efficiency and a capacitance up to 15 µF/cm(2), higher than single-walled carbon nanotubes.

Raising the performance of a 4 V supercapacitor based on an EMIBF4-single walled carbon nanotube nanofluid electrolyte.

Addition of a single walled carbon nanotube in ionic liquids of EMIBF4 produced a nanofluid with increased ionic conductivity. It, as the electrolyte, allowed the increase of the capacitance, energy density and cycling stability of a supercapacitor operated at 4 V.

Highly deformation-tolerant carbon nanotube sponges as supercapacitor electrodes.

Developing flexible and deformable supercapacitor electrodes based on porous materials is of high interest in energy related fields. Here, we show that carbon nanotube sponges, consisting of highly porous conductive networks, can serve as compressible and deformation-tolerant supercapacitor electrodes in aqueous or organic electrolytes. In aqueous electrolytes, the sponges maintain a similar specific capacitance (>90% of the original value) under a predefined compressive strain of 50% (corresponding to a volume reduction of 50%), and retain more than 70% of the original capacitance under 80% strain while the volume normalized capacitance increases by 3-fold. The sponge electrode maintains a stable performance after 1000 large strain compression cycles. A coin-shaped cell assembled with these sponges shows excellent stability over 15,000 charging cycles with negligible degradation after 500 cycles. Our results indicate that carbon nanotube sponges have the potential to fabricate deformable supercapacitor electrodes with stable performance.