Self-Driven Perovskite/Organic Quasi-Tandem Photodetectors Operating in Both Narrowband and Broadband Regimes.

Dual-band photodetectors (PDs) have attracted extensive research attention due to their great potential for diverse and refreshing application scenarios in full-color imaging, optical communication, and imaging detection. Here, a self-driven dual-band PD without filters and other auxiliary equipment to achieve a narrowband response in Mode 1 and a broadband response in Mode 2 was designed based on carrier-selective transmission narrowing (CSTN). The polymer material poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA), which has the appropriate energy level, was selected to be the carrier-selective transmission layer. In Mode 1, the dual-band PD exhibits a near-infrared (NIR) narrowband response in 750-900 nm, which indicates a responsivity of 360 mA/W, a full-width at half-maximum (fwhm) of 81 nm, and a specific detectivity (D*) of 7.49 × 1010 Jones at 810 nm. Simultaneously, in Mode 2, the dual-band PD exhibits a UV-visible-NIR broadband responsivity of 180 mA/W and a specific detectivity (D*) of 3.8 × 1010 Jones at 520 nm. Our study provides a reliable idea for the commercial applications of dual-function photodetectors.

Enhancing Blue Polymer Light-Emitting Diode Performance by Optimizing the Layer Thickness and the Insertion of a Hole-Transporting Layer.

Polymer light-emitting diodes (PLEDs) hold immense promise for energy-efficient lighting and full-color display technologies. In particular, blue PLEDs play a pivotal role in achieving color balance and reducing energy consumption. The optimization of layer thickness in these devices is critical for enhancing their efficiency. PLED layer thickness control impacts exciton recombination probability, charge transport efficiency, and optical resonance, influencing light emission properties. However, experimental variations in layer thickness are complex and costly. This study employed simulations to explore the impact of layer thickness variations on the optical and electrical properties of blue light-emitting diodes. Comparing the simulation results with experimental data achieves valuable insights for optimizing the device's performance. Our findings revealed that controlling the insertion of a layer that works as a hole-transporting and electron-blocking layer (EBL) could greatly enhance the performance of PLEDs. In addition, changing the active layer thickness could optimize device performance. The obtained results in this work contribute to the development of advanced PLED technology and organic light-emitting diodes (OLEDs).

Buffering Donor Shuttles in Proton-Coupled Electron Transfer Kinetics for Electrochemical Hydrogenation of Hydroxyacetone to Propylene Glycol.

Electrochemical hydrogenation reactions demand rapid proton-coupled electron transfer at the electrode surface, the kinetics of which depend closely on pH. Buffer electrolytes are extensively employed to regulate pH over a wide range. However, the specific role of buffer species should be taken into account when interpreting the intrinsic pH dependence, which is easily overlooked in the current research. Herein, we report the electrochemical hydrogenation of hydroxyacetone, derived from glycerol feedstock, to propylene glycol with a faradaic efficiency of 56 ± 5% on a polycrystalline Cu electrode. The reaction activities are comparable in citrate, phosphate, and borate buffer electrolytes, encompassing different buffer identities and pH. The electrokinetic profile reveals that citrate is a site-blocking adsorbate on the Cu surface, thereby decreasing buffer concentration and increasing pH will enhance the reaction rate; phosphate is an explicit proton donor, which promotes the interfacial rate by increasing buffer concentration and decreasing pH, while borate is an innocent buffer, which can be used to investigate the intrinsic pH effect. Combined with in situ SEIRAS, we demonstrate that water is the primary proton source in citrate and borate electrolytes, reiterating the rationality of the proposed mechanism based on the microkinetic modeling. Our results emphasize the intrinsic complexity of the buffer system on the kinetic activity for electrocatalysis. It calls for special care when we diagnose the mechanistic pathway in buffer electrolytes convoluted by different buffer identities and pH.

Organic ammonium salt assisted crystallization and defect passivation of a quasi-two-dimensional pure blue perovskite at the buried interface.

Quasi-two-dimensional (quasi-2D) perovskites exhibit excellent performance in light-emitting diodes (LEDs). However, the quality of perovskite films prepared via the solution method is significantly impacted by the enormous number of defects that unavoidably form at the grain boundaries and interfaces during the precursor to the crystal formation process. Here, we propose a strategy to assist perovskite crystallization and defect passivation at the buried interface through interfacial modification. The organic ammonium salt, ethylamine chloride (EACl), is added to the hole transport material and modifies the buried interface of the perovskite film. EACl introduces the nucleation sites for perovskite precursors, and promotes the crystallization process of the perovskite grains, contributing to the formation of high-quality perovskite films. At the same time, the presence of Lewis base (-NH2) groups in EACl and their lone electron pairs effectively inactivate unlocated Pb2+ ions at the buried interface, thereby reducing non-radiative recombination. In addition, chloride ions help to mitigate defects and to improve the morphology of perovskite films. Devices with this modification show a higher performance than control devices on all metrics. This work proposes a facile but efficient way for improving quasi-2D pure blue perovskite crystallization and growth.

Defects in lead halide perovskite light-emitting diodes under electric field: from behavior to passivation strategies.

Lead halide perovskites (LHPs) are emerging semiconductor materials for light-emitting diodes (LEDs) owing to their unique structure and superior optoelectronic properties. However, defects that initiate degradation of LHPs through external stimuli and prompt internal ion migration at the interfaces remain a significant challenge. The electric field (EF), which is a fundamental driving force in LED operation, complicates the role of these defects in the physical and chemical properties of LHPs. A deeper understanding of EF-induced defect behavior is crucial for optimizing the LED performance. In this review, the origins and characterization of defects are explored, indicating the influence of EF-induced defect dynamics on LED performance and stability. A comprehensive overview of recent defect passivation approaches for LHP bulk films and nanocrystals (NCs) is also provided. Given the ubiquity of EF, a summary of the EF-induced defect behavior can enhance the performance of perovskite LEDs and related optoelectronic devices.

Investigating the Impact of Prompt Engineering on the Performance of Large Language Models for Standardizing Obstetric Diagnosis Text: Comparative Study.

BACKGROUND: The accumulation of vast electronic medical records (EMRs) through medical informatization creates significant research value, particularly in obstetrics. Diagnostic standardization across different health care institutions and regions is vital for medical data analysis. Large language models (LLMs) have been extensively used for various medical tasks. Prompt engineering is key to use LLMs effectively. OBJECTIVE: This study aims to evaluate and compare the performance of LLMs with various prompt engineering techniques on the task of standardizing obstetric diagnostic terminology using real-world obstetric data. METHODS: The paper describes a 4-step approach used for mapping diagnoses in electronic medical records to the International Classification of Diseases, 10th revision, observation domain. First, similarity measures were used for mapping the diagnoses. Second, candidate mapping terms were collected based on similarity scores above a threshold, to be used as the training data set. For generating optimal mapping terms, we used two LLMs (ChatGLM2 and Qwen-14B-Chat [QWEN]) for zero-shot learning in step 3. Finally, a performance comparison was conducted by using 3 pretrained bidirectional encoder representations from transformers (BERTs), including BERT, whole word masking BERT, and momentum contrastive learning with BERT (MC-BERT), for unsupervised optimal mapping term generation in the fourth step. RESULTS: LLMs and BERT demonstrated comparable performance at their respective optimal levels. LLMs showed clear advantages in terms of performance and efficiency in unsupervised settings. Interestingly, the performance of the LLMs varied significantly across different prompt engineering setups. For instance, when applying the self-consistency approach in QWEN, the F1-score improved by 5%, with precision increasing by 7.9%, outperforming the zero-shot method. Likewise, ChatGLM2 delivered similar rates of accurately generated responses. During the analysis, the BERT series served as a comparative model with comparable results. Among the 3 models, MC-BERT demonstrated the highest level of performance. However, the differences among the versions of BERT in this study were relatively insignificant. CONCLUSIONS: After applying LLMs to standardize diagnoses and designing 4 different prompts, we compared the results to those generated by the BERT model. Our findings indicate that QWEN prompts largely outperformed the other prompts, with precision comparable to that of the BERT model. These results demonstrate the potential of unsupervised approaches in improving the efficiency of aligning diagnostic terms in daily research and uncovering hidden information values in patient data.

Electrokinetic Analyses Uncover the Rate-Determining Step of Biomass-Derived Monosaccharide Electroreduction on Copper.

Electrochemical biomass conversion holds promise to upcycle carbon sources and produce valuable products while reducing greenhouse gas emissions. To this end, deep insight into the interfacial mechanism is essential for the rational design of an efficient electrocatalytic route, which is still an area of active research and development. Herein, we report the reduction of dihydroxyacetone (DHA)-the simplest monosaccharide derived from glycerol feedstock-to acetol, the vital chemical intermediate in industries, with faradaic efficiency of 85±5 % on a polycrystalline Cu electrode. DHA reduction follows preceding dehydration by coordination with the carbonyl and hydroxyl groups and the subsequent hydrogenation. The electrokinetic profile indicates that the rate-determining step (RDS) includes a proton-coupled electron transfer (PCET) to the dehydrated intermediate, revealed by coverage-dependent Tafel slope and isotopic labeling experiments. An approximate zero-order dependence of H+ suggests that water acts as the proton donor for the interfacial PCET process. Leveraging these insights, we formulate microkinetic models to illustrate its origin that Eley-Rideal (E-R) dominates over Langmuir-Hinshelwood (L-H) in governing Cu-mediated DHA reduction, offering rational guidance that increasing the concentration of the adsorbed reactant alone would be sufficient to promote the activity in designing practical catalysts.

Abdominal Symptom Improvement During Clinical Trials of Tenapanor in Patients With Irritable Bowel Syndrome With Constipation: A Post Hoc Analysis.

INTRODUCTION: This post hoc analysis evaluated the efficacy of tenapanor on abdominal symptoms in patients with irritable bowel syndrome with constipation. Abdominal symptoms assessed included pain, discomfort, bloating, cramping, and fullness. METHODS: The abdominal symptom data were pooled from 3 randomized controlled trials (NCT01923428, T3MPO-1 [NCT02621892], and T3MPO-2 [NCT02686138]). Weekly scores were calculated for each abdominal symptom, and the Abdominal Score (AS) was derived as the average of weekly scores for abdominal pain, discomfort, and bloating. The overall change from baseline during the 12 weeks was assessed for each symptom weekly score and the AS. The AS 6/12-week and 9/12-week response rates (AS improvement of ≥2 points for ≥6/12- or ≥9/12-week) were also evaluated. The association of weekly AS response status (reduction of ≥30%) with weekly complete spontaneous bowel movement (CSBM) status (=0 and >0) was assessed. RESULTS: Among 1,372 patients (684 tenapanor [50 mg twice a day] and 688 placebo), the least squares mean change from baseline in AS was -2.66 for tenapanor vs -2.09 for placebo ( P < 0.0001). The 6/12-week AS response rate was 44.4% for tenapanor vs 32.4% for placebo ( P < 0.0001), and for 9/12-week AS, 30.6% for tenapanor vs 20.5% for placebo ( P < 0.0001). A significant association between weekly CSBM status and weekly AS response status was observed each week ( P < 0.0001), with a greater proportion achieving an AS reduction in patients with >0 CSBMs in a week. DISCUSSION: Tenapanor significantly reduced abdominal symptoms in patients with irritable bowel syndrome with constipation, particularly pain, discomfort, and bloating measured by AS, compared with placebo.

Long-term safety of tenapanor in patients with irritable bowel syndrome with constipation in the T3MPO-3 study.

BACKGROUND: Tenapanor, a first-in-class, minimally systemic inhibitor of intestinal sodium/hydrogen exchanger isoform 3 (NHE3), is approved for the treatment of irritable bowel syndrome with constipation (IBS-C) in adults based on two randomized, placebo-controlled, phase III studies (T3MPO-1 [NCT02621892], T3MPO-2 [NCT02686138]). The open-label T3MPO-3 extension study (NCT02727751) enrolled patients who completed these studies to investigate long-term safety and tolerability of tenapanor. METHODS: Patients who completed T3MPO-1 (16 weeks) or T3MPO-2 (26 weeks) were eligible for enrollment in T3MPO-3. Patients in T3MPO-3 received open-label tenapanor 50 mg twice a day for up to an additional 39 (T3MPO-1) or 26 (T3MPO-2) weeks. Treatment-emergent adverse events (TEAEs) were evaluated in the entire T3MPO-3 safety population and in patients who received a total of ≥52 weeks of tenapanor. KEY RESULTS: A total of 312 patients were enrolled in T3MPO-3; 90 received ≥52 weeks of tenapanor. TEAEs were reported in 117 (37.5%) patients in the safety population and in 52 (57.8%) patients who received ≥52 weeks of tenapanor. Diarrhea was the most common TEAE, occurring in 10.6% of the safety population and in 11.1% of patients who received ≥52 weeks of tenapanor. Most cases were mild or moderate in severity, with only two severe cases reported in the safety population. No deaths occurred during the T3MPO-3 study. CONCLUSIONS: Tenapanor was tolerable over ≥52 weeks of treatment and showed similar safety to that seen in shorter studies. Combined results of the T3MPO studies indicate that tenapanor is a valuable new treatment option for patients with IBS-C.

Modulation Phase Distribution of Ruddlesden-Popper Quasi-2D Perovskites with a Similarly Spaced Dion-Jacobson Phase.

Quasi-two-dimensional (quasi-2D) perovskites exhibit excellent performance when applied to light-emitting diodes (LEDs). However, quasi-2D perovskite films generally have nonuniform n phases and irregular internal crystal structures, which degrade the device's performance. Here, we propose using a Dion-Jacobson (DJ)-type organic spacer to modulate the phase distribution of the Ruddlesden-Popper (RP) quasi-2D perovskite. A DJ-type organic spacer cation, 1.6-hexamethylenediamine (HDABr2), was introduced into the perovskite as the second spacer cation with propylamine hydrobromide (PABr). As DJ-type and RP-type perovskites have similar spacings, RP-DJ style does not cause a chaotic crystalline structure; instead, it modulates the perovskite crystallization and narrows the phase distribution. In parallel, there is a substantial improvement in the maximum luminance, current efficiency, external quantum efficiency, and device stability of the quasi-2D perovskite LEDs. This work provides a novel concept for combining the organic spacer cations for quasi-2D perovskites.

Stability and Degradation in Lead Halide Perovskite Nanocrystals via Regulation of Lattice Strain.

It is still quite challenging to achieve high-performance and stable blue perovskite materials due to their instability and degradation. The lattice strain provides an important pathway to investigate the degradation process. In this article, the lattice strain in perovskite nanocrystals was regulated by the ratio of Cs+, EA+, and Rb+ cations with different sizes. Their electrical structure, formation energy, and ion migration activation energy were calculated with the density functional theory (DFT) method. The luminescence properties and stability of blue lead bromide perovskite nanocrystals were analyzed with spectra regulation from 516 to 472 nm. It was demonstrated that the lattice strain plays an important role in the luminescence performance and degradation process of perovskite materials. The study provides the positive correlation between lattice strain and degradation as well as luminescence properties in lead halide perovskite materials, which is of great importance in uncovering their degradation mechanism and developing stable and high-performance blue perovskite materials.

B1 SINE-binding ZFP266 impedes mouse iPSC generation through suppression of chromatin opening mediated by reprogramming factors.

Induced pluripotent stem cell (iPSC) reprogramming is inefficient and understanding the molecular mechanisms underlying this inefficiency holds the key to successfully control cellular identity. Here, we report 24 reprogramming roadblock genes identified by CRISPR/Cas9-mediated genome-wide knockout (KO) screening. Of these, depletion of the predicted KRAB zinc finger protein (KRAB-ZFP) Zfp266 strongly and consistently enhances murine iPSC generation in several reprogramming settings, emerging as the most robust roadblock. We show that ZFP266 binds Short Interspersed Nuclear Elements (SINEs) adjacent to binding sites of pioneering factors, OCT4 (POU5F1), SOX2, and KLF4, and impedes chromatin opening. Replacing the KRAB co-suppressor with co-activator domains converts ZFP266 from an inhibitor to a potent facilitator of iPSC reprogramming. We propose that the SINE-KRAB-ZFP interaction is a critical regulator of chromatin accessibility at regulatory elements required for efficient cellular identity changes. In addition, this work serves as a resource to further illuminate molecular mechanisms hindering reprogramming.

In-Well Ionization from Monolayer Quantum Dots for Non-Carrier-Injection Electroluminescence.

Quantum dot (QD) light-emitting devices operating in non-carrier-injection (NCI) mode have attracted intense interest. Revealing the source of carriers that support the periodic electroluminescence is important because there is no injection of carriers from the external electrode. Electrons/holes generated by well-to-well multiple ionization in adjacent QDs are generally recognized as the carrier source for electroluminescence, and the stacked QD layers are necessary. In this work, NCI electroluminescence (NCI-EL) from monolayer QDs is successfully demonstrated, which cannot be properly explained by the previously proposed mechanism of multiple ionization. A working mechanism related to periodic in-well ionization is proposed, in which electrons tunnel directly from the valence band of QDs to the conduction band to form free electrons and holes. The effects of driving voltage amplitude, frequency, and QD size on the NCI-EL performance are investigated. Finite element simulation is used to clarify the ionization process. We believe this work can extend the working mechanism model of NCI-EL from QDs and provide guidance for promoting QD-based light-emitting device performance.

Predicting the photon energy of quasi-2D lead halide perovskites from the precursor composition through machine learning.

Quasi-2D perovskites with the general formula of L2A n-1Pb n X3n+1 (L = organic spacer cation, A = small organic cation or inorganic cation, X = halide ion, and n ≤ 5) are an emerging kind of luminescent material. Their emission color can be easily tuned by their composition and n value. Accurate prediction of the photon energy before experiments is essential but unpractical based on present studies. Herein, we use machine learning (ML) to explore the quantitative relationship between the photon energies of quasi-2D perovskite materials and their precursor compositions. The random forest (RF) model presents high accuracy in prediction with a root mean square error (RMSE) of ∼0.05 eV on a test set. By feature importance analysis, the composition of the A-site cation is found to be a critical factor affecting the photon energy. Moreover, it is also found that the phase impurity greatly lowers the photon energy and needs to be minimized. Furthermore, the RF model predicts the compositions of quasi-2D perovskites with high photon energies for blue emission. These results highlight the advantage of machine learning in predicting the properties of quasi-2D perovskites before experiments and also providing color tuning directions for experiments.

Identifying optimal photovoltaic technologies for underwater applications.

Improving solar energy collection in aquatic environments would allow for superior environmental monitoring and remote sensing, but the identification of optimal photovoltaic technologies for such applications is challenging as evaluation requires either field deployment or access to large water tanks. Here, we present a simple bench-top characterization technique that does not require direct access to water and therefore circumvents the need for field testing during initial trials of development. Employing LEDs to simulate underwater solar spectra at various depths, we compare Si and CdTe solar cells, two commercially available technologies, with GaInP cells, a technology with a wide bandgap close to ideal for underwater solar harvesting. We use this method to show that while Si cells outperform both CdTe and GaInP cells under terrestrial AM1.5G solar irradiance, CdTe and GaInP cells outperform Si cells at depths >2 m, with GaInP cells operating with underwater efficiencies approaching 54%.

Improved phase purity and film quality in quasi-2D perovskite light-emitting diodes by an additive with the trimethacrylate group.

Quasi-2D perovskites are potential materials for optoelectronics like light-emitting diodes (LEDs); compared to their 3D counterparts, they are considered more stable against the atmosphere and more efficient in exciton confining. However, the simultaneous formation of different phases in the quasi-2D perovskite film, i.e., the phase impurity issue, lowers the device performance. We propose using a small molecule additive, trimethylolpropane trimethacrylate (TMPTA), to suppress the phase impurity by mixing it into the antisolvent. The phase pure quasi-2D perovskite film was obtained, and meanwhile, the film quality was also improved. Moreover, the ester functional groups in TMPTA also passivate the charged defects in the perovskite film, minimizing the carrier recombination in the device. Correspondingly, with TMPTA modification, the maximum current efficiency is increased by 25%, and the half lifetime of the PeLEDs is prolonged by three times.

Key Factors Governing the External Quantum Efficiency of Thermally Activated Delayed Fluorescence Organic Light-Emitting Devices: Evidence from Machine Learning.

Thermally activated delayed fluorescence (TADF) materials enable organic light-emitting devices (OLEDs) to exhibit high external quantum efficiency (EQE), as they can fully utilize singlets and triplets. Despite the high theoretical limit in EQE of TADF OLEDs, the reported values of EQE in the literature vary a lot. Hence, it is critical to quantify the effects of the factors on device EQE based on data-driven approaches. Herein, we use machine learning (ML) algorithms to map the relationship between the material/device structural factors and the EQE. We established the dataset from a variety of experimental reports. Four algorithms are employed, among which the neural network performs best in predicting the EQE. The root-mean-square errors are 1.96 and 3.39% for the training and test sets. Based on the correlation and the feature importance studies, key factors governing the device EQE are screened out. These results provide essential guidance for material screening and experimental device optimization of TADF OLEDs.

Device performance improvements in all-inorganic perovskite light-emitting diodes: the role of binary ammonium cation terminals.

All-inorganic perovskites, like CsPbBr3, have gained particular concern due to their excellent material stability. However, aside from the general defect issue in perovskite materials, all-inorganic perovskites also suffer from poor film quality, leading to low device efficiency, especially of perovskite light-emitting diodes (PeLEDs) employing a thin perovskite film as the emission layer. Herein, 1,4-phenyldimethylammonium dibromide (phDMADBr), which has ammonium cations (NH3+) on both terminals, is introduced as the additive in the precursor solution. It is proved that phDMADBr can improve the film coverage; meanwhile, it also presents a more intense passivation effect on point defects than a similar additive with a single NH3+ terminal. As demonstrated by density functional theory (DFT) calculations, phDMADBr tends to anchor onto the Br-dangling bond with both NH3+ tails and enhances the adhesion to the perovskite grain surface. The exposed hydrophobic aryl also protects the perovskite from detrimental environmental factors. Correspondingly, the maximum luminance (Lmax), current efficiency (CE), and device stability of the PeLEDs are enhanced. This work offers special guidance for screening passivation additives for inorganic perovskites.

The Improvement of the Performance of Sky-Blue OLEDs by Decreasing Interface Traps and Balancing Carriers with PSVA Treatment.

The mitigation of interfacial charge accumulation in solution-processed organic light-emitting diodes (s-OLEDs) is an effective method to improve device performance. In this study, the polar solvent vapor annealing (PSVA) method was used to treat two layers in s-OLED, PEDOT:PSS and mCP:DMAC-DPS emitting layers, separately, to optimize the carrier transmission and balance. After the double-layer PSVA treatment, the current efficiency increased, the lifetime of the device is improved, the efficiency roll-off alleviated from 33.3% to 26.6%, and the maximum brightness increased by 31.3%. It is worth mentioning that the work function of the EML interface reduced by 0.36 eV, and the initial injection voltage of the electrons also reduced. Simulating the solubility of the LUMO and HOMO molecule parts of the mCP and DMAC-DPS, it was found that the LUMO parts had stronger polarity and higher solubility in polar solution than the HOMO parts. By comparing the untreated luminescent layer films, it was found that the PSVA treatment improved the uniformity of the film morphology. We may infer that a more ordered molecular arrangement enhances carrier transport as the LUMO parts tend to be close to the surface and the reduced local state traps on the EML surface promote electron injection. According to the experimental results, the injection of holes and electrons is enhanced from both sides of the EML, respectively, and the charge accumulated at the interface of s-OLEDs is significantly reduced due to the improvement of carrier-transported characteristics.