A review on novel activation strategy on carbonaceous materials with special morphology/texture for electrochemical storage

Various novel carbonaceous materials including carbon nanotubes,nano-onions,carbon microspheres,graphene nanosheets,and carbon microfibers with unique properties,such as tunable surface area and pore size,high chemical stability,cost-effective and facile preparation,have attracted enormous interest for many applications.Also essential,the activation processes play a critical role to achieve these valuable properties.In this review,we provide a thorough analysis of the emerging nano-and microscopic carbon species with special morphology/textures and currently available types of chemical activation agents,and novel activation strategy to enhance electrochemical performance of activated carbon material in electrical energy storage devices including supercapacitor and alkaline ions batteries.A particular emphasis is set on recent advance in activated carbon materials with special morphology/textures for supercapacitors and sodium ion batteries.

Nondestructive monitoring of annealing and chemical-mechanical planarization behavior using ellipsometry and deep learning

The Cu-flling process in through-silicon via(TSV-Cu)is a key technology for chip stacking and three-dimensional vertical packaging.During this process,defects resulting from chemical-mechanical planarization(CMP)and annealing severely affect the reliability of the chips.Traditional methods of defect characterization are destructive and cumbersome.In this study,a new defect inspection method was developed using Mueller matrix spectroscopic ellipsometry.TSV-Cu with a 3-μm-diameter and 8-μm-deep Cu filling showed three typical types of characteristics:overdishing(defect-OD),protrusion(defect-P),and defect-free.The process dimension for each defect was 13 nm.First,the three typical defects caused by CMP and annealing were investigated.With single-channel deep learning and a Mueller matrix element(MME),the TSV-Cu defect types could be distinguished with an accuracy rate of 99.94%.Next,seven effective MMEs were used as independent channels in the artificial neural network to quantify the height variation in the Cu flling in the z-direction.The accuracy rate was 98.92%after training,and the recognition accuracy reached 1 nm.The proposed approach rapidly and nondestructively evaluates the annealing bonding performance of CMP processes,which can improve the reliability of high-density integration.

Application of ion-in-conjugation molecules in resistive memories and gas sensors: The role of conjugation

Ion-in-conjugation(IIC) materials are eme rging as an important class of organic electronic materials with wide applications in energy storage,resistive memories and gas sensors.Many IIC materials were designed and investigated,however the role of conjugation in IIC materials’ performance is yet investigated.Here we designed two molecules obtained by condensation of 4-butylaniline and oxocarbon acid.Squaric acid derivatives squaraine named SA-Bu and a croconamide named CA-Bu which only differ in their oxocarbon cores.While employing SA-Bu and CA-Bu as resistive memory and gas sensory materials,SA-Bu has attained promising performance in ternary memo ry and detection of NO_(2) as low as 10 parts-per-billion whereas CA-Bu show mainly binary memory behavior and negligible NO_(2) response.Theoretical calculations reveal that conjugation of CA-Bu was distorted by the increased steric hindrance,frustrating the charge transport and suppressing the conductivity.Our work demonstrates that the conjugation plays a crucial role in ion-in-materials promoting ternary RRAM devices and highperformance gas sensors manufacture.