Short Filter Research Articles

Effect of Different Sizes and Heights on the Removal Efficiency of Composite Clay Filter for Gold Mine Site Wastewater Remediation

Wastewater from mining-related activities contains toxic elements that require remediation, and most available wastewater filters have inconsistent flow rates and removal efficiency due to their thickness. This study, therefore, examined the effect of height and size on the flow rate and removal efficiency of a clay composite filter for wastewater remediation. The developed clay filter and its composites were characterized using various techniques such as X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). The XRF analysis showed that the clay contained 91.38% major minerals, including iron oxide (Fe2O3), aluminum oxide (Al2O3), and silica (SiO2), which could enhance the filtration process. Additionally, FTIR revealed that both the clay and the filter are rich in functional groups, including kaolinite and illite, which could promote the filtration process. Further analysis showed that the filters had an average adsorption rate of 87.32%, an average flow rate of 0.891 L/hr, and an average removal efficiency of 99.6%. An increase in the height of a small-diameter filter resulted in a 0.21% increase in removal efficiency, while for larger diameters, the removal efficiency decreased by 0.11%. Conversely, increasing the diameter of a short filter increased the efficiency by 0.25%, while for taller filters, the removal efficiency decreased by 0.07%. Therefore, this work demonstrated that both height and diameter have noticeable effects on flow rate: as height increases, flow rate decreases, and as diameter increases, flow rate increases. The filter's efficiency is somewhat affected by both height and diameter, with a small increase in efficiency noted at greater heights and a slight decrease in efficiency noted at larger diameters.

Long-Range Imaging of Alpha Emitters Using Radioluminescence in Open Environments: Daytime and Night-Time Applications.

Alpha emitters like plutonium pose severe health risks when ingested, damaging DNA and potentially causing cancer. Traditional detection methods require proximity within millimeters of the contamination source, presenting safety risks and operational inefficiencies. Long-range detection through alpha radioluminescence (RL) offers a promising alternative. However, most of the previous experiments have been carried out under controlled conditions that preclude the overwhelming effect of ambient light. This study demonstrates the successful detection of a 3 MBq alpha emitter in an open environment using a compact alpha camera. This camera incorporates a deep-cooled CCD and a low f-number lens system designed to minimize the blue shift effects of filters. Night-time imaging was achieved with a dual-filter system using a sandwich filter assembly centered at 337 nm and 343 nm for capturing alpha RL and subtracting background light, respectively. At night, the alpha source was detected from 1 m away within one minute, and the lowest detection limit can be calculated as 75 kBq. The system was also evaluated under simulated urban lighting conditions. For daytime imaging, a stack of tilted 276 nm short pass filters minimized sunlight interference, enabling the detection of the alpha source at 70 cm within 10 min under indirect sunlight. This research highlights the viability of long-range optical detection of alpha emitters for environmental monitoring in real-world settings.

Penggunaan Media Sosial dalam Meningkatkan Penjualan Melalui Aplikasi TikTok: Studi Kasus pada Industri E-Commerce

Abstract: Social media is one form of developing information technology and social media users can share various information through various platforms such as TikTok. TikTok has proven to be an effective platform in promotion and marketing strategies, increasing public awareness and business revenue. Features such as short videos, filters, and creative ads allow users to reach a wide audience. However, it is also necessary to be aware of negative impacts such as gadget addiction and controversial content. Strategies to increase TikTok's effectiveness include engaging content, collaboration with influencers, use of hashtags, and ads such as Top View Ads and Brand Takeover. With the right approach, TikTok can be a very effective promotional tool to increase sales and consumer interaction in e-commerce.

Kalman Filter Using a Third-Order Tensorial Decomposition of the Impulse Response

For system identification problems associated with long-length impulse responses, the recently developed decomposition-based technique that relies on a third-order tensor (TOT) framework represents a reliable choice. It is based on a combination of three shorter filters, which merge their estimates in tandem with the Kronecker product. In this way, the global impulse response is modeled in a more efficient manner, with a significantly reduced parameter space (i.e., fewer coefficients). In this paper, we further develop a Kalman filter based on the TOT decomposition method. As compared to the recently designed recursive least-squares (RLS) counterpart, the proposed Kalman filter achieves superior performance in terms of the main criteria (e.g., tracking and accuracy). In addition, it significantly outperforms the conventional Kalman filter, while also having a lower computational complexity. Simulation results obtained in the context of echo cancellation support the theoretical framework and the related advantages.

Role of Vena Cava Filter in the Prophylaxis and Treatment of Venous Thromboembolism in Injured Adult Patients: A Systematic Review, Meta-Analysis, and Practice Management Guideline from the Eastern Association for the Surgery of Trauma [RETRACTED

Injured patients are at an increased risk of developing deep vein thrombosis (DVT) and pulmonary embolism (PE). Inferior vena cava (IVC) filters have been used in injured patients to prevent venous thromboembolism (VTE), but current evidence-based guidelines are lacking. Questions regarding IVC filter use in injured patients with clearly defined Population(s), Intervention(s), Comparison(s), and appropriately selected Outcomes (PICO) were formulated. The study sought to understand the evidence behind use of ultra short term IVC filters and use of IVC filters in injured patients with and without known VTE who are unable to receive therapeutic anticoagulation and chemoprophylaxis, respectively. A literature search and review was conducted, followed by meta-analysis. The quality of evidence was assessed per Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. There were twenty-one studies that were analyzed. Three studies were randomized controlled trials (RCTs), three were observational studies, and fifteen studies were retrospective studies. In injured patients without known acute VTE who cannot receive chemoprophylaxis, we recommend against placement of an IVC filter due to associated higher rate of mortality, DVT, PE, and length of stay. The quality of evidence was assessed to be low. In injured patients with known DVT who cannot receive chemoprophylaxis we conditionally recommend against placement of an IVC filter. The quality of evidence was assessed to be very low. No recommendations can be made with respect to placement of ultra short term IVC filters based upon available data. IVC filters should not be placed routinely for prophylaxis in injured adult patients without known VTE who cannot receive chemoprophylaxis. The taskforce conditionally recommends against the placement of IVC filter in injured adult patients with known DVT who cannot receive chemoprophylaxis. Guideline; Systematic review/meta-analysis, level IV.

A hybrid TCN-GRU model for classifying human activities using smartphone inertial signals.

Recognising human activities using smart devices has led to countless inventions in various domains like healthcare, security, sports, etc. Sensor-based human activity recognition (HAR), especially smartphone-based HAR, has become popular among the research community due to lightweight computation and user privacy protection. Deep learning models are the most preferred solutions in developing smartphone-based HAR as they can automatically capture salient and distinctive features from input signals and classify them into respective activity classes. However, in most cases, the architecture of these models needs to be deep and complex for better classification performance. Furthermore, training these models requires extensive computational resources. Hence, this research proposes a hybrid lightweight model that integrates an enhanced Temporal Convolutional Network (TCN) with Gated Recurrent Unit (GRU) layers for salient spatiotemporal feature extraction without tedious manual feature extraction. Essentially, dilations are incorporated into each convolutional kernel in the TCN-GRU model to extend the kernel's field of view without imposing additional model parameters. Moreover, fewer short filters are applied for each convolutional layer to alleviate excess parameters. Despite reducing computational cost, the proposed model utilises dilations, residual connections, and GRU layers for longer-term time dependency modelling by retaining longer implicit features of the input inertial sequences throughout training to provide sufficient information for future prediction. The performance of the TCN-GRU model is verified on two benchmark smartphone-based HAR databases, i.e., UCI HAR and UniMiB SHAR. The model attains promising accuracy in recognising human activities with 97.25% on UCI HAR and 93.51% on UniMiB SHAR. Since the current study exclusively works on the inertial signals captured by smartphones, future studies will explore the generalisation of the proposed TCN-GRU across diverse datasets, including various sensor types, to ensure its adaptability across different applications.

Co-current filtrate flow in TFF perfusion processes: Decoupling transmembrane pressure from crossflow to improve product sieving.

Hollow fiber-based membrane filtration has emerged as the dominant technology for cell retention in perfusion processes yet significant challenges in alleviating filter fouling remain unsolved. In this work, the benefits of co-current filtrate flow applied to a tangential flow filtration (TFF) module to reduce or even completely remove Starling recirculation caused by the axial pressure drop within the module was studied by pressure characterization experiments and perfusion cell culture runs. Additionally, a novel concept to achieve alternating Starling flow within unidirectional TFF was investigated. Pressure profiles demonstrated that precise flow control can be achieved with both lab-scale and manufacturing-scale filters. TFF systems with co-current flow showed up to 40% higher product sieving compared to standard TFF. The decoupling of transmembrane pressure from crossflow velocity and filter characteristics in co-current TFF alleviates common challenges for hollow fiber-based systems such as limited crossflow rates and relatively short filter module lengths, both of which are currently used to avoid extensive pressure drop along the filtration module. Therefore, co-current filtrate flow in unidirectional TFF systems represents an interesting and scalable alternative to standard TFF or alternating TFF operation with additional possibilities to control Starling recirculation flow.

Voltage-gated sodium channels (Na<sub>V</sub>) in GtoPdb v.2023.1

Sodium channels are voltage-gated sodium-selective ion channels present in the membrane of most excitable cells. Sodium channels comprise of one pore-forming α subunit, which may be associated with either one or two β subunits [179]. α-Subunits consist of four homologous domains (I-IV), each containing six transmembrane segments (S1-S6) and a pore-forming loop. The positively charged fourth transmembrane segment (S4) acts as a voltage sensor and is involved in channel gating. The crystal structure of the bacterial NavAb channel has revealed a number of novel structural features compared to earlier potassium channel structures including a short selectivity filter with ion selectivity determined by interactions with glutamate side chains [278]. Interestingly, the pore region is penetrated by fatty acyl chains that extend into the central cavity which may allow the entry of small, hydrophobic pore-blocking drugs [278]. Auxiliary β1, β2, β3 and β4 subunits consist of a large extracellular N-terminal domain, a single transmembrane segment and a shorter cytoplasmic domain.The nomenclature for sodium channels was proposed by Goldin et al., (2000) [146] and approved by the NC-IUPHAR Subcommittee on sodium channels (Catterall et al., 2005, [53]).

Astronomical time scale of the lower Miocene depositional sequences (Aquitanian-Burdigalian) in the Jambour Field, northern Iraq

The Miocene succession is considered one of the major shallow hydrocarbon reservoirs in Iraq. It consists primarily of lagoonal evaporites and carbonate alternations, with many barren intervals and non-diagnostic fauna. An astronomical time scale (ATS) was established in two wells in Jambour Field, Kurdistan, using high-resolution cyclostratigraphic analysis of GR data for the first time in Iraq to determine the absolute age of the Miocene sequences and their boundaries. Sixteen unique carbonate and evaporite facies types were discovered and classified into five facies associations, from the mid-outer ramp to the peritidal carbonate and evaporite ramps. The most significant of these implies that, after astro-climatic frequencies, sea-level change was the dominant regulator of lower Miocene deposition. The difference in GR and facies type is mostly due to third eustatic sequences, which describe a rich series of long and short-period eccentricities in orbitally defined terms. The eustatic sea-level variations of the third-order sequences correlate with the sedimentary noise model applied over the tuned GR. A sharp sediment accumulation rate (SAR) was caused by an abrupt shift in the depositional environment, as demonstrated by the applied eCOCO within the lower Aquitanian part of the Dhiban Formation; consequently, each well was split into two datasets. The SAR ranges from 3.1 to 1.97 cm/kyr in the Ja46 well and 2.3 to 3.3 in the Ja49 well. The MTM spectral analysis of the four datasets revealed the eccentricity cycles' dominance with a high degree of confidence level. The present study employs high-resolution ATS using tuning of the GR with the new merged short and long eccentricity cycle filter output method, which is supported by previous strontium isotope studies and compared to the La 2004 astronomical solution. According to the ATS, the Aquitanian-Burdigalian sequences range from 5.08 myr at Ja46 Well to 4.66 myr at Ja49 Well. The tuning output indicated the presence of two hiatuses, the first in the Dhiban Formation with a time gap of about 0.21 and 0.3 myr in the Ja46 and Ja49 wells, respectively, and the second at the top of the Jeribe Formation with a time gap of about 0.34 myr in the Ja49 well. This pause corresponds to a significant sea-level drop in the Arabian Platform Basin at 21.4–21.0 and 18.5 Ma.

Joint Online Estimation of Early and Late Residual Echo PSD for Residual Echo Suppression

In hands-free telephony and other distant-talking applications, an acoustic echo cancellation system is typically required, where a short adaptive filter is often used in practice to achieve fast convergence at low computational cost. This may result in late residual echo (LRE) remaining due to under-modeling of the echo path and early residual echo (ERE) due to filter misalignment. Both residual echo components can be suppressed using a postfilter in the subband domain, which requires accurate estimates of the power spectral density (PSD) of the ERE and LRE components. State-of-the-art methods estimate the ERE and LRE PSDs independently of each other, where the ERE PSD is estimated by simply multiplying the loudspeaker PSD with a frequency-dependent scalar and the LRE PSD is estimated using a recursive estimator based on frequency-dependent reverberation scaling and decay parameters. In this paper, we propose to extend the ERE PSD estimator from a scalar to a moving average filter on the loudspeaker PSD. In addition, we propose a signal-based method to jointly estimate all model parameters for the ERE and LRE PSD estimators in online mode, and derive two gradient-descent-based algorithms to simultaneously update the model parameters by minimizing the mean squared log error. The proposed method is compared with state-of-the-art methods in terms of estimation accuracy of the model parameters as well as the residual echo PSDs. Simulation results using both artificially generated as well as measured impulse responses show that the proposed method outperforms state-of-the-art methods for all considered scenarios.

Rectangular Orthogonal Digital Filter Banks Based on Extended Gaussian Functions

Rectangular orthogonal digital filter banks (ODFBs) based on square-root-raised-cosine (SRRC) functions are widely utilised to realise flexible and elastic multi-channel aggregations for fixed and mobile networks. However, long digital filter lengths are required to minimize digital filtering-associated signal distortions. In this paper, based on the extended Gaussian function (EGF), a novel rectangular ODFB with excellent robustness against the short digital filter length-induced truncation effect is proposed. Optimum digital filter parameters of the EGF-based ODFBs are identified and verified in multi-channel hybrid OFDM-digital filter multiple access (DFMA) PONs based on intensity modulation and direct detection (IMDD). By making use of the identified optimum digital filter parameters, extensive comparisons of digital filter characteristics and corresponding multi-channel upstream PON performances are made between the EGF-based ODFBs and the SRRC-based ODFBs. It is shown that to achieve a similar aggregated upstream signal transmission capacity, the EGF-based ODFB reduces the digital filter DSP complexity by a factor of 4. For a digital filter length as short as 8, in comparison with the SRRC-based ODFB, the EGF-based ODFB introduces >1.5 dB (>0.8 dB) improvements in upstream receiver sensitivity for 5-bits (8-bits) DACs/ADCs, increases the aggregated upstream signal transmission capacity by >5.5%, enlarges the ONU launch power dynamic range by >2.5 dB and improves the frequency offset tolerance by a factor of >1.5. In addition, the EGF-based ODFB also enhances upstream performance robustness against ONU symbol timing offsets.

NGIA: A novel Greedy Incremental Alignment based algorithm for gene sequence clustering

Gene sequence clustering is very basic and important in computational biology and bioinformatics for the study of phylogenetic relationships and gene function prediction, etc. With the rapid growth of the amount of biological data (gene/protein sequences), gene sequence clustering algorithms face more challenges in low precision and efficiency. The growing redundant sequences in gene sequence databases usually contribute to the increasing memory and computing demand for most clustering methods. For example, the original greedy incremental alignment-based (GIA) clustering algorithm obtains high precision clustering results, but with very poor efficiency. Efficient greedy incremental clustering algorithms have been developed with a cost of precision reduction, which usually trade clustering precision off for speed improvement. Algorithms with a better balance between precision and speed are needed. This paper proposes a novel Greedy Incremental Alignment-based algorithm called nGIA for gene clustering with high efficiency and precision. nGIA consists of a pre-filter, a modified short word filter, a new data packing strategy, a modified greedy incremental method, and is parallelized via GPU. The experimental evaluations on four independent datasets show that the proposed tool can cluster datasets with high precisions of 99.99%. Compared with the results of CD-HIT, Vsearch, and Uclust, nGIA is on average 13.6x, 6.2x, and 1.7x faster. In addition, we have developed a multi-node version to handle large data sets. The strong scalability test shows that the multi-node version of nGIA can scale up to 32 threads with a 31% parallel efficiency. The software is available at https://github.com/SIAT-HPCC/gene-sequence-clustering.

Structures of a mammalian TRPM8 in closed state

Transient receptor potential melastatin 8 (TRPM8) channel is a Ca2+-permeable non-selective cation channel that acts as the primary cold sensor in humans. TRPM8 is also activated by ligands such as menthol, icilin, and phosphatidylinositol 4,5-bisphosphate (PIP2), and desensitized by Ca2+. Here we have determined electron cryo-microscopy structures of mouse TRPM8 in the absence of ligand, and in the presence of Ca2+ and icilin at 2.5–3.2 Å resolution. The ligand-free state TRPM8 structure represents the full-length structure of mammalian TRPM8 channels with a canonical S4-S5 linker and the clearly resolved selectivity filter and outer pore loop. TRPM8 has a short but wide selectivity filter which may account for its permeability to hydrated Ca2+. Ca2+ and icilin bind in the cytosolic-facing cavity of the voltage-sensing-like domain of TRPM8 but induce little conformational change. All the ligand-bound TRPM8 structures adopt the same closed conformation as the ligand-free structure. This study reveals the overall architecture of mouse TRPM8 and the structural basis for its ligand recognition.

Comparative study of estimating the Curie point depth and heat flow using potential magnetic data

Abstract The estimation of the Curie point depth (CPD) and heat flow (HF) from magnetic data is useful for geothermal and tectonic studies. However, the methodology of estimating these values is still controversial as numerous studies have used different types of transformed magnetic data. Most studies utilize the total magnetic intensity (TMI) or the reduced to the pole (RTP) data, and since shallow magnetic bodies may affect the final CPD values, low-pass (LP) wavelength filtering has also been used to estimate the CPD. In this study, the two-dimensional radially averaged spectral analysis was applied to the land-based magnetic data from the Sinai Peninsula. TMI and RTP data were both analyzed, using different LP filtered wavelengths, and the final CPD and HF values were compared. The cut-off wavelength parameter was selected in terms of the geologic complexity. The results show that the estimated CPD values are well correlated regardless of whether the magnetic data were either TMI or RTP. The RTP data produced a spatial shift in the CPD smaller than the window size being used. Additionally, the centroid method is primarily dependent on the wavenumber, which varied slightly on applying the RTP. There were slight differences in the estimated CPDs when a short LP filter (e.g., 20 km) was applied, whereas increasing the wavelength (e.g., 40 km) caused the CPD values to increase exceeding the plausible depth limits, and the associated spatial trends varied when compared to the other methods. In areas where the basement rocks were shallow or exposed, a LP filter can be applied with short cut-off wavelength. The estimated CPDs were discussed in the context of seismicity data, gravity-based Moho depths, and HF measurements.

Spatial and long–short temporal attention correlation filters for visual tracking

Discriminative correlation filter is one of the quick and effective ways for studying visual tracking. However, discriminative correlation filter-based methods still suffer from many challenging questions caused by environmental interferences, such as spatial boundary effect, temporal filter degradation, and tracking drift. A novel appearance optimisation model, named spatial and long–short temporal attention model, has been proposed based on a new spatial regularisation term and a long–short temporal regularisation term for learning the correlation filter to localise the target. On the one hand, our proposed method can improve the classical spatial regularisation term with a new weight matrix to alleviate the spatial boundary effect. On the other hand, two new temporal regularisation terms are designed: a short temporal regularisation term and a long temporal regularisation term. The short temporal regularisation term can enlarge the inner connections of the current frame and all foregoing frames to improve the tracking performances, and the long temporal regularisation term can address the influence of occlusion by using the similarity between the initial filter and the current one. Extensive experiments on various benchmarks illustrate that our proposed tracker performs favourably against several related popular trackers.

Produced oily water treatment efficiency by polyester fiber deep bed filter (phase two: Extended filter length and long duration)

The petroleum industry generates a massive amount of oily water discharge from oil/water separators.Oily water will cause a major environmental risk if not treated before discharge. The challenge is to propose a suitable low-maintenance cheap treatment method.This study represents a second phase of testing polyester fibers as deep bed filtration media to treat produced oily water. The previous first phase study investigated the efficiency of the polyester fiber by conducting short-duration filtration tests using 40 cm polyester fiber filters.Two suggestions from the first phase study can be deduced: to optimize the oil removal efficiency of polyester fiber filters in long-duration field processes. Use either a large number of short filters with low flow capacity or less number of long filters with high flow capacity. The two methods were employed and tested separately in this study.The results of both methods clearly showed the ability of the polyester fiber deep bed filters to produce high-quality brine of less than 5 ppm oil concentration. The polyester fibers filter was proven to be a competitor with the existing materials used in the industry.

Effects of sampling rate and noise filter processing on repeatability assessment in UHPLC with ultraviolet detection based on the ISO 11843-7.

The present study examines whether short measurement time and noise filter processing in an ultra-high-performance liquid chromatography with ultraviolet detection (UHPLC-UV) contribute to limitations for repeatability assessment based on the ISO 11843 part 7 (ISO 11843-7), which can stochastically provide a measurement standard deviation (SD) caused by baseline noise (SB). In this study, ergosterol was used as an example in UHPLC-UV analysis. From the results of power spectrum analysis of baseline noise, 1024 consecutive digital data points provided a suitable SB. Thus, it was found that an SB can be obtained from about 1min of baseline when a chromatogram was recorded at sampling rate of 20pointss-1 in the present UHPLC-UV system. The relative SDs (RSDs) of the peak area obtained by the ISO 11843-7 were within 95% of the confidential intervals of the RSDs obtained by repetitive measurements, indicating the ISO 11843-7 is applicable to estimate repeatability in a UHPLC-UV system. In a similar way, we found that the RSD of the peak area obtained from a chromatogram with noise filter processing in UHPLC-UV could also be estimated by the ISO 11843-7. In conclusion, we experimentally demonstrate that short measurement time and noise filter processing are not limitations for repeatability assessment based on the ISO 11843-7.

Identification of Room Acoustic Impulse Responses via Kronecker Product Decompositions

The identification of room acoustic impulse responses represents a challenging problem in the framework of many important applications related to the acoustic environment, like echo cancellation, noise reduction, and microphone arrays, among others. In this context, the main issues are related to the long length of such impulse responses and their time-variant nature. These raise significant difficulties in terms of the convergence rate, computational complexity, and accuracy of the solution. Recently, a decomposition-based approach was developed for the identification of low-rank systems, which can also be applied (to some extent) for the identification of acoustic impulse responses. This approach exploits the nearest Kronecker product decomposition of the impulse response and solves a high-dimension system identification problem using a combination of low-dimension solutions (provided by shorter filters), thus gaining in terms of both performance and complexity. Nevertheless, it does not consider the intrinsic nature of the room acoustic impulse responses, which contain specific components (e.g., early reflections and late reverberation) that can be very different in nature. In this paper, we propose an improved decomposition-based method (via the Kronecker product) that takes into account these specific components and processes them separately, in order to better exploit their important low-rank features. Following this approach, an iterative Wiener filter is firstly developed, followed by a recursive least-squares (RLS) algorithm designed in the same framework. Both solutions outperform the conventional benchmarks, i.e., the conventional Wiener filter and the RLS algorithm, respectively. Moreover, they achieve superior performances as compared to the recently developed versions based on the nearest Kronecker product decomposition, also owning lower computational complexities than their previous counterparts. Simulations are performed in the framework of acoustic echo cancellation and the obtained results support the performance features of the proposed algorithms.

Filter Optimization for MFTN-OQAM Systems

In this paper, a novel and effective method for designing the pulse shaping filter for multicarrier faster-than-Nyquist with offset quadrature amplitude modulation (MFTN-OQAM) systems is proposed. The connection between the signal-to-interference ratio (SIR) and the filter coefficients is first established. Then, for a desired overall compression level taking into account compressions in both frequency and time domains, a simple convergence search is suggested to jointly find the optimal values of time and frequency compression factors as well as the filter coefficients to maximize the SIR under a spectrum localization constraint. The obtained results show that higher SIRs, and consequently better bit error rates, can be achieved by the proposed filters over the Martin filter that is commonly used in the filter-bank multicarrier OQAM (FBMC-OQAM) systems (i.e., without time or frequency compression). Moreover, when applying our method to FBMC-OQAM systems, the obtained results show that the original Martin filter is suboptimal as shorter filters are found having the same SIR, which translates to lower implementation cost and latency.

High-Performance Near-Infrared Photodetectors Based on the Synergy Effect of Short Wavelength Light Filter and Long Wavelength Response of a Perovskite/Polymer Hybrid Structure.

Near-infrared photodetectors (NIR-PDs) are widely used in communications, biomedical imaging, and national defense. Here we report a new strategy to prepare a short wavelength light filter based NIR-PDs by introducing an interface layer between the perovskite layer and the polymer layer to achieve the selective passage of carriers. Through the synergistic effect of the perovskite and the interface layer, the short wavelength light component in the signal spectrum is effectively filtered out. The organic polymer layer with a bulk heterojunction structure is applied to realize the absorption and conversion of near-infrared light. The prepared device achieves a maximum external quantum efficiency of 83.7% without bias, a high specific detectivity of 1.52 × 1013 Jones, an NIR responsivity of 0.577A/W, and a short response time of 1.73/0.97 μs within the detection range from 770 to 900 nm. All these properties show great advantages compared with other perovskite/polymer hybrid NIR photodetectors that have been reported. This innovative strategy provides a new way to prepare high-performance near-infrared photodetectors.