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Abstract Precise manipulation of nanomaterials has shown great potential in facilitating the fabrication of functional hydrogel nanocomposites in applications such as soft robotics, biomedicine, structural health monitoring, and wearable sensing. Surface acoustic wave (SAW)-based acoustofluidics offers a contactless approach for nanoparticle manipulation. Meanwhile, digital light processing (DLP) has been extensively utilized in the hydrogel printing process due to its high-resolution fabrication capabilities. This study presents an innovative SAW acoustofluidics-assisted DLP system, enabling the patterning of nanoparticles embedded in matrix materials while facilitating programmed light exposure for the controllable photopolymerization of customized hydrogel nanocomposites. Instead of utilizing the acoustic potential field generated by SAWs, we leverage the accompanying electric field due to the piezoelectric effect of the lithium niobate (LiNbO3) substrate to generate electric field, enabling the electric field-driven patterning of multi-walled carbon nanotubes (MWCNTs) Laser Doppler vibrometry confirms the SAW-generated acoustic intensity fields. The analytical simulation together with the scanned data predicted the co-current electric field predicted the distribution of MWCNTs. By applying a programmed light pattern, we successfully fabricated hydrogel nanocomposites in the shape of a VT logo and produced hydrogel nanocomposite sensors. The capabilities of printed hydrogel nanocomposite sensors were demonstrated through beam vibration sensing, proving its potential application in structural health monitoring. The fabricated sensors demonstrated the capability to track finger movements, indicating their potential for wearable sensing applications. In summary, this study offers a unique approach for nanocomposites fabricating multi-material integration and material anisotropy control, thereby facilitating advanced smart material development. Future work will focus on exploring the fabrication of hydrogels containing other types of nanomaterials to enhance material conductivity and achieve other functions, aiming with the goal of developing nanocomposite sensors for applications in soft robotics, biomedicine, structural health monitoring, and wearable sensing. 

Abstract Fast reaction between organic salt and lead iodide always leads to small perovskite crystallites and concentrated defects. Here, polyacrylic acid is blended with organic salt, so as to regulate the crystallization in a two‐step growth method. It is observed that addition of polyacrylic acid retards aggregation and crystallization behavior of the organic salt, and slows down the reaction rate between organic salt and PbI 2 , by which “slow‐release effect” is defined. Such effect improves crystallization of perovskite. X‐ray diffraction study shows that, after addition of 2 m m polyacrylic acid, average crystallite size of perovskite increases from ≈40 to ≈90 nm, meanwhile, grain size increases. Thermal admittance spectroscopy study shows that trap density is reduced by nearly one order (especially for deep energy levels). Due to the improved crystallization and reduced trap density, charge recombination is obviously reduced, while lifetime of charge carriers in perovskite film and devices are prolonged, according to time‐resolved photoluminescence and transient photo‐voltage decay curve tests, respectively. Accordingly, power conversion efficiency of the device is promoted from 19.96 (±0.41)% to 21.84 (±0.25)% (with a champion efficiency of 22.31%), and further elevated to 24.19% after surface modification by octylammonium iodide. 

SnO2 modified mesoporous ZrO2 is used to replace the mesoporous TiO2 layer and serves as a kind of mesoporous electron-transport layer during the low-temperature fabrication of mesoscopic perovskite solar cells that are based on carbon electrode. X-ray/ultraviolet photoelectron spectroscopy studies and electrical test observe that SnO2 modification brought down the work function while increasing the conductivity of the mesoporous ZrO2. Transient photovoltage/photocurrent decay curves, impedance spectroscopy, and photoluminescence mapping show that after the bottom layer of ZrO2 is modified by SnO2, the charge extraction process is accelerated while recombination is retarded. This modification helps to increase the power conversion efficiency from 4.70 (±0.85)% to 10.15 (±0.35)%, along with the optimized efficiency at 13.37% (AM1.5G, 100 mW/cm2) for the low-temperature devices. In addition, the effects of modification layers of SnO2 on the power conversion properties are carefully studied. This study shows that SnO2 modified mesoporous ZrO2 could serve as an efficient electron-transport layer for the low-temperature mesoscopic devices. 

Capsaicin is used to modify SnO 2 quantum dots and then used as an electron-transfer material for perovskite solar cells. After capsaicin modification, the power conversion efficiency of the devices increases from 19.90 (± 0.47)% to 21.87 (± 0.28)% with a champion device of 22.24% (AM 1.5G, 100 mW/cm 2 ). Transient photovoltage and photocurrent decay show that, after the capsaicin doping, the lifetime increases from 21.55 (± 1.54) to 27.63 (± 1.45)  μs, while the charge extraction time reduces from 1.90 (± 0.09) to 1.67 (± 0.06)  μs. Time-resolved photoluminescence and impedance spectrum studies show similar results. The accelerated charge transfer and retarded recombination are due to defect passivation. Space charge limited current study shows that, after modification, the trap density of devices is reduced from 2.24 × 10 15 to 1.28 × 10 15  cm −3 . X-ray photoelectron spectroscopy and theoretical calculation indicate that the reduced trap density is due to the chemical interaction between carbonyl group (from capsaicin) and Sn atom, and that between carbonyl group and Pb atom. 

This study provides a normative theory for how Bayesian causal inference can be implemented in neural circuits. In both cognitive processes such as causal reasoning and perceptual inference such as cue integration, the nervous systems need to choose different models representing the underlying causal structures when making inferences on external stimuli. In multisensory processing, for example, the nervous system has to choose whether to integrate or segregate inputs from different sensory modalities to infer the sensory stimuli, based on whether the inputs are from the same or different sources. Making this choice is a model selection problem requiring the computation of Bayes factor, the ratio of likelihoods between the integration and the segregation models. In this paper, we consider the causal inference in multisensory processing and propose a novel generative model based on neural population code that takes into account both stimulus feature and stimulus reliability in the inference. In the case of circular variables such as heading direction, our normative theory yields an analytical solution for computing the Bayes factor, with a clear geometric interpretation, which can be implemented by simple additive mechanisms with neural population code. Numerical simulation shows that the tunings of the neurons computing Bayes factor are consistent with the "opposite neurons" discovered in dorsal medial superior temporal (MSTd) and the ventral intraparietal (VIP) areas for visual-vestibular processing. This study illuminates a potential neural mechanism for causal inference in the brain. 

Improving efficiency and stability has become an urgent issue in the application of perovskite solar cells (PSCs). Herein, a kind of long‐chain polymer or polymethylmethacrylate (PMMA) is added into the spiro‐OMeTAD matrix to improve the film formation process and hence the device performance. It is observed that, after modification, the spiro‐OMeTAD‐based hole‐transporting layer becomes uniform, continuous, and condensed. Meanwhile, the power conversion efficiency of the devices is upgraded. Compared with the control device, open‐circuit voltage of the modified one (with moderate doping) increases from 1.06 (±0.03) to 1.10 (±0.02) V, fill factor increases from 72.20 (±3.44)% to 75.59 (±3.35)%, and the power conversion efficiency increases from 18.82 (±1.06)% to 20.51 (±0.82)% (highest at 21.78%) under standard test condition (AM 1.5G, 100 mW cm⁻²). Transient photocurrent/photovoltage decay curves, time‐resolved photoluminance, and impedance spectroscopy studies show that the modification could accelerate charge transfer and retard interfacial recombination. In addition, the modification improves device stability. Due to the strengthened barrier against penetration of “H₂O/O₂/Ag,” the efficiency of the unsealed device could retain 91.49% (by average) of the initial one after 100 days storage in the dark [relative humidity = 30(±5)%]. This work shows that long‐chain polymer doping could simultaneously improve efficiency and stability of spiro‐OMeTAD‐based PSCs.