The investigation into highly efficient heptazine-based polymeric photocatalysts for visible light-driven solar fuel synthesis

Artificial photosynthesis has been regarded as a promising method to generate fuels in a much greener way by utilising inexhaustible solar energy via water splitting and CO2 conversion. Polymeric semiconductors have been recently identified as promising photocatalysts due to their comparatively low cost and ease modification of the electronic structure. However, the majority only respond to a limited wavelength region ( 420 nm), leading to a 10.3% apparent quantum yield (λ = 420 nm). Both theoretical calculations and spectroscopies have attributed such superior performance to enhanced charge separation and narrow bandgap. Such new polymer was then coupled with an inorganic photocatalyst to construct a Z-scheme system, which successfully splits water into both H2 and O2 in a stoichiometry ratio. Further, an efficient strategy was demonstrated to stepwise tailor the bandgap of polymeric photocatalysts from 2.7 to 1.9 eV by carefully manipulating the O/N linker/terminal atoms in the heptazine chains. These polymers work stably and efficiently for both H2 and O2 evolution (420 nm < λ < 710 nm), exhibiting nearly 20 times higher activity compared to g-C3N4 with high AQYs under visible light irradiation. Experimental and theoretical results have attributed the narrowed band gap and enhanced charge separation to the oxygen incorporation into the linker/terminal position. Based on this success, a more challenging multi-electron photochemical process of visible light-driven CO2 reduction in water was investigated using junctions consisting of the novel polymers and two kinds of carbon quantum dots (CQD) cocatalysts. The novel CQD was synthesised via a microwave-assisted method while the other CQD fabricated via sonication of glucose was reported as reduction cocatalysts (redCQD). In CO2 reduction reactions, the novel CQD/polymer junctions selectively produce methanol and O2 while the redCQD/polymer junction generates CO only. Ultrafast spectroscopies revealed that novel CQD works as a hole acceptor in the junctions, different from the redCQD as an electron acceptor. Electrons reach the surface of polymers to reduce CO2 to produce methanol while holes accumulate on CQD to oxidise water. Microwave-assisted CQD shows more favourable water adsorption instead of methanol adsorption compared with polymers, thus facilitating methanol production instead of CO. Therefore, the function of CQD is a key reason for such high selectivity

Insight on Reaction Pathways of Photocatalytic CO2 Conversion

Photocatalytic CO2 conversion to value-added chemicals is a promising solution to mitigate the current energy and environmental issues but is a challenging process. The main obstacles include the inertness of CO2 molecule, the sluggish multi-electron process, the unfavorable thermodynamics, and the selectivity control to preferable products. Furthermore, the lack of fundamental understanding of the reaction pathways accounts for the very moderate performance in the field. Therefore, in this Perspective, we attempt to discuss the possible reaction mechanisms toward all C1 and C2 value-added products, taking into account the experimental evidence and theoretical calculation on the surface adsorption, proton and electron transfer, and products desorption. Finally, the remaining challenges in the field, including mechanistic understanding, reactor design, economic consideration, and potential solutions, are critically discussed by us

Electronic Noise of a Single Skyrmion

To enable the practical use of skyrmion-based devices, it is essential to achieve a balance between energy efficiency and thermal stability, while also ensuring reliable electrical detection against noise. Understanding how a skyrmion interacts with material disorder and external perturbations is thus essential. Here we investigate the electronic noise of a single skyrmion under the influence of thermal fluctuations and spin currents in a magnetic thin film. We detect the thermally induced noise with a 1/f signature in the strong pinning regime but a random telegraph noise in the intermediate pinning regime. Both the thermally dominated and current-induced telegraph-like signals are detected in the weak pinning regime. Our results provide a comprehensive electronic noise picture of a single skyrmion, demonstrating the potential of noise fluctuation as a valuable tool for characterizing the pinning condition of a skyrmion. These insights could also aid in the development of low-noise and reliable skyrmion-based devices

New modeling of the Vostok ice flow line and implication for the glaciological chronology of the Vostok ice core

International audienceWe have used new spaceborne (elevation) and airborne (ice thickness) data to constrain a 2D1/2 model of snow accumulation and ice flow along the Ridge B‐Vostok station ice flow line (East Antarctica). We show that new evaluations of the ice flow line geometry (from the surface elevation), ice thickness (from low‐frequency radar data), and basal melting and sliding change significantly the chronology of the Vostok ice core. This new Vostok dating model reconciles orbital and glaciological timescales and is in good agreement with the Dome Fuji glaciological timescale. At the same time, the new model shows significantly older ages than the previous GT4 timescale for the last glacial part, being thus in better agreement with the GRIP and GISP2 chronologies

DDC-PIM: Efficient Algorithm/Architecture Co-design for Doubling Data Capacity of SRAM-based Processing-In-Memory

Processing-in-memory (PIM), as a novel computing paradigm, provides significant performance benefits from the aspect of effective data movement reduction. SRAM-based PIM has been demonstrated as one of the most promising candidates due to its endurance and compatibility. However, the integration density of SRAM-based PIM is much lower than other non-volatile memory-based ones, due to its inherent 6T structure for storing a single bit. Within comparable area constraints, SRAM-based PIM exhibits notably lower capacity. Thus, aiming to unleash its capacity potential, we propose DDC-PIM, an efficient algorithm/architecture co-design methodology that effectively doubles the equivalent data capacity. At the algorithmic level, we propose a filter-wise complementary correlation (FCC) algorithm to obtain a bitwise complementary pair. At the architecture level, we exploit the intrinsic cross-coupled structure of 6T SRAM to store the bitwise complementary pair in their complementary states ($Q/\overline{Q}$), thereby maximizing the data capacity of each SRAM cell. The dual-broadcast input structure and reconfigurable unit support both depthwise and pointwise convolution, adhering to the requirements of various neural networks. Evaluation results show that DDC-PIM yields about $2.84\times$ speedup on MobileNetV2 and $2.69\times$ on EfficientNet-B0 with negligible accuracy loss compared with PIM baseline implementation. Compared with state-of-the-art SRAM-based PIM macros, DDC-PIM achieves up to $8.41\times$ and $2.75\times$ improvement in weight density and area efficiency, respectively.Comment: 14 pages, to be published in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD

Bandgap engineering of organic semiconductors for highly efficient photocatalytic water splitting

The bandgap engineering of semiconductors, in particular low‐cost organic/polymeric photocatalysts could directly influence their behavior in visible photon harvesting. However, an effective and rational pathway to stepwise change of the bandgap of an organic/polymeric photocatalyst is still very challenging. An efficient strategy is demonstrated to tailor the bandgap from 2.7 eV to 1.9 eV of organic photocatalysts by carefully manipulating the linker/terminal atoms in the chains via innovatively designed polymerization. These polymers work in a stable and efficient manner for both H2 and O2 evolution at ambient conditions (420 nm < λ < 710 nm), exhibiting up to 18 times higher hydrogen evolution rate (HER) than a reference photocatalyst g‐C3N4 and leading to high apparent quantum yields (AQYs) of 8.6%/2.5% at 420/500 nm, respectively. For the oxygen evolution rate (OER), the optimal polymer shows 19 times higher activity compared to g‐C3N4 with excellent AQYs of 4.3%/1.0% at 420/500 nm. Both theoretical modeling and spectroscopic results indicate that such remarkable enhancement is due to the increased light harvesting and improved charge separation. This strategy thus paves a novel avenue to fabricate highly efficient organic/polymeric photocatalysts with precisely tunable operation windows and enhanced charge separation

Data-Adaptive Wavelets and Multi-Scale Singular Spectrum Analysis

Using multi-scale ideas from wavelet analysis, we extend singular-spectrum analysis (SSA) to the study of nonstationary time series of length $N$ whose intermittency can give rise to the divergence of their variance. SSA relies on the construction of the lag-covariance matrix C on M lagged copies of the time series over a fixed window width W to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components; here W = M Dt, with Dt the time step. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M <= W <= N. Multi-scale SSA varies W, while keeping a fixed W/M ratio, and uses the eigenvectors of the corresponding lag-covariance matrix C_M as a data-adaptive wavelets; successive eigenvectors of C_M correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's covariance matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic and geophysical time series. A real application is to the Southern Oscillation index (SOI) monthly values for 1933-1996. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 4 and 3 years supports the Devil's staircase scenario for the El Nino/Southern Oscillation phenomenon.Comment: 24 pages, 19 figure