Unraveling the molecular mechanism for enhanced gas adsorption in mixed-metal MOFs via solid-state NMR spectroscopy.

The incorporation of multiple metal ions in metal-organic frameworks (MOFs) through one-pot synthesis can induce unique properties originating from specific atomic-scale spatial apportionment, but the extraction of this crucial information poses challenges. Herein, nondestructive solid-state NMR spectroscopy was used to discern the atomic-scale metal apportionment in a series of bulk Mg1-xCox-MOF-74 samples via identification and quantification of eight distinct arrangements of Mg/Co ions labeled with a 13C-carboxylate, relative to Co content. Due to the structural characteristics of metal-oxygen chains, the number of metal permutations is infinite for Mg1-xCox-MOF-74, making the resolution of atomic-scale metal apportionment particularly challenging. The results were then employed in density functional theory calculations to unravel the molecular mechanism underlying the macroscopic adsorption properties of several industrially significant gases. It is found that the incorporation of weak adsorption sites (Mg2+ for CO and Co2+ for CO2 adsorption) into the MOF structure counterintuitively boosts the gas adsorption energy on strong sites (Co2+ for CO and Mg2+ for CO2 adsorption). Such effect is significant even for Co2+ remote from Mg2+ in the metal-oxygen chain, resulting in a greater enhancement of CO adsorption across a broad composition range, while the enhancement of CO2 adsorption is restricted to Mg2+ with adjacent Co2+. Dynamic breakthrough measurements unambiguously verified the trend in gas adsorption as a function of metal composition. This research thus illuminates the interplay between atomic-scale structures and macroscopic gas adsorption properties in mixed-metal MOFs and derived materials, paving the way for developing superior functional materials.

Effect of Remimazolam on Emergence Delirium in Children Undergoing Laparoscopic Surgery: A Double-Blinded Randomized Trial.

BACKGROUND: Preventing emergence delirium is a clinical goal for pediatric anesthesia, yet there is no consensus on its prevention. This study investigated the hypothesis that a continuous infusion or a single bolus of remimazolam can reduce the incidence of emergence delirium in children. METHODS: A hundred and twenty children aged 1-6 years old were randomly and equally allocated into three groups: group RC, which received a continuous infusion of remimazolam at 1 mg kg -1 h -1; group RB, which received a single bolus of remimazolam at 0.2 mg kg -1 at the beginning of wound closure; and group C, which received a continuous infusion of saline at 1 mL kg -1 h -1 and single bolus of saline at 0.2 mL kg -1 at the beginning of sutures. The primary outcome was the incidence of emergence delirium assessed by pediatric anesthesia emergence delirium (PAED) scale. Secondary outcomes included the number of rescues propofol administrations in the post-anesthesia care unit (PACU), recovery time, end-tidal sevoflurane concentration when maintaining BIS within the range of 40-60, and adverse events. RESULTS: The incidence of emergence delirium in group RC (5%, vs. group C, risk ratio, 0.14; 95% CI, 0.04 to 0.59; P=0.001) and group RB (7.7%, vs. group C, risk ratio, 0.22; 95% CI, 0.07 to 0.71; P=0.003) was significantly lower compared with group C (32.5%). Propofol was given to 2 patients in each of groups RC and RB to treat delirium and to 10 patients in group C (group RC vs. group C, risk ratio, 0.20; 95% CI, 0.05 to 0.86; P=0.012; group RB vs. group C, risk ratio, 0.21; 95% CI, 0.05 to 0.88; P=0.014). No differences in the recovery time and adverse effects were detected. CONCLUSIONS: Both continuous infusion and single bolus administration of remimazolam can effectively reduce the occurrence of emergence delirium in children.

Learning spiking neuronal networks with artificial neural networks: neural oscillations.

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by a spiking neuronal network model. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.

Transformation-Optics-Designed Plasmonic Singularities for Efficient Photocatalytic Hydrogen Evolution at Metal/Semiconductor Interfaces.

Inspired by transformation optics, we propose a new concept for plasmonic photocatalysis by creating a novel hybrid nanostructure with a plasmonic singularity. Our geometry enables broad and strong spectral light harvesting at the active site of a nearby semiconductor where the chemical reaction occurs. A proof-of-concept nanostructure comprising Cu2ZnSnS4 (CZTS) and Au-Au dimer (t-CZTS@Au-Au) is fabricated via a colloidal strategy combining templating and seeded growth. On the basis of numerical and experimental results of different related hybrid nanostructures, we show that both the sharpness of the singular feature and the relative position to the reactive site play a pivotal role in optimizing photocatalytic activity. Compared with bare CZTS, the hybrid nanostructure (t-CZTS@Au-Au) exhibits an enhancement of the photocatalytic hydrogen evolution rate by up to ∼9 times. The insights gained from this work might be beneficial for designing efficient composite plasmonic photocatalysts for diverse photocatalytic reactions.

Single-pixel reconstructive mid-infrared micro-spectrometer.

Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO2). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF2) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications.

Application of plasma donor-derived cell free DNA for lung allograft rejection diagnosis in lung transplant recipients.

BACKGROUND: Donor-derived cell-free DNA (dd-cfDNA) has been applied to monitor acute rejection (AR) in kidney and heart transplantation. This study was aimed to investigate the application of dd-cfDNA levels in the diagnosis of AR and chronic lung allograft dysfunction (CLAD) among the lung transplantation recipients (LTRs). METHODS: One hundred and seventy LTRs were enrolled at the First Affiliated Hospital of Guangzhou Medical University between 1 June 2015 and 30 March 2021. Patients were divided into 4 groups: stable group, AR group, infection group and CLAD group. The level of dd-cfDNA was analyzed using target region sequencing and the performance characteristics of dd-cfDNA for diagnosis of AR and CLAD were determined, respectively. RESULTS: Kruskal-Wallis test showed that there were some significant differences in the level of dd-cfDNA (%) among the 4 groups, with p < 0.001. Among them, the level of dd-cfDNA (%) was highest (median 2.17, IQR [1.40-3.82]) in AR group, and higher in CLAD group (median 1.07, IQR [0.98-1.31]), but lower in infection group (median 0.71, IQR [0.57-1.07]) and lowest in stable group (median 0.71, IQR [0.61-0.84]). AUC-ROC curve analysis showed that the threshold of dd-cfDNA for AR was 1.17%, with sensitivity being 89.19% and specificity being 86.47%, and the optimal threshold of 0.89% was determined of CLAD, with sensitivity being 95.00% and specificity of 76.99%. CONCLUSIONS: Plasma dd-cfDNA could be a useful tool for the assessment of lung allograft rejection, including AR and CLAD, and holds promise as a noninvasive biomarker for "allograft injury" in both acute and chronic rejection following lung transplantation.

Multi-band oscillations emerge from a simple spiking network.

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.

Antifungal prophylactic effectiveness and intrapulmonary concentrations of voriconazole versus posaconazole in lung transplant recipients.

Invasive fungal diseases (IFDs) are one of the leading causes of death in lung transplant recipients. This study aimed to compare the antifungal prophylactic effectiveness, intrapulmonary and plasma levels of voriconazole with posaconazole in lung transplant recipients. This retrospective cohort study analyzed adult recipients who underwent lung transplantation between June 2017 and December 2020. Voriconazole oral tablets or posaconazole oral suspension was used for prophylaxis against posttransplant IFD. Drug concentrations in bronchoalveolar lavage fluid (BALF) and plasma were measured by using liquid chromatography-mass spectrometry. The 182 recipients included 142 in the voriconazole group and 40 in the posaconazole group. The trough plasma levels were comparable between voriconazole and posaconazole (1.65 ± 0.09 vs. 1.69 ± 0.03 µg/ml, P = 0.55). However, the BALF levels were significantly higher for posaconazole than voriconazole (17.47 ± 11.51 vs. 0.56 ± 0.49 µg/ml, P < 0.001). There was no significant difference in the total incidence of breakthrough IFDs between the voriconazole and posaconazole groups (10.6% vs. 7.5%, P = 0.77). The intrapulmonary concentrations of posaconazole were significantly higher than voriconazole. The two agents had comparable antifungal prophylactic effectiveness.

Palladium (Pd0) Loading-Controlled Catalytic Activity and Selectivity for Chlorophenol Hydrodechlorination and Hydrosaturation.

Reductive catalysis by zero-valent palladium nanoparticles (Pd0NPs) has emerged as an efficient strategy for promoting the detoxification of chlorophenols (CPs) via hydrogenation. Most studies achieved hydrodechlorination of CP to phenol for detoxification, but it requires considerably high energy input and harsh conditions to further hydrosaturate phenol to cyclohexanone (CHN) as the most desired product for resource recovery. This study documented 4-CP hydrodechlorination and hydrosaturation catalyzed by Pd0NPs deposited on H2-transfer membranes in the H2-based membrane catalyst-film reactor, which yielded up to 99% CHN selectivity under ambient conditions. It was further discovered that the Pd0 morphology and size, both determined by Pd0 loading, were the key factors controlling the catalytic activity and selectivity: while sub-nano Pd particles catalyzed only 4-CP hydrodechlorination, Pd0NPs were able to catalyze the subsequent hydrosaturation that requires more Pd0 reactive sites than hydrodechlorination. In addition, better dispersion of Pd0, caused by lower Pd0 loading, yielded higher activity for hydrodechlorination but lower activity for hydrosaturation. During the 15 day continuous tests, the substantial product from 4-CP hydrogenation was constantly phenol (>98%) for 0.2 g-Pd/m2 and CHN (>92%) for 1.0 g-Pd/m2. This study opens the door for selectively manipulating desired products from Pd0-catalyzed CP hydrogenation under ambient conditions.

Reductive Dehalogenation of Herbicides Catalyzed by Pd0NPs in a H2-Based Membrane Catalyst-Film Reactor.

More food production required to feed humans will require intensive use of herbicides to protect against weeds. The widespread application and persistence of herbicides pose environmental risks for nontarget species. Elemental-palladium nanoparticles (Pd0NPs) are known to catalyze reductive dehalogenation of halogenated organic pollutants. In this study, the reductive conversion of 2,4-dichlorophenoxyacetic acid (2,4-D) was evaluated in a H2-based membrane catalyst-film reactor (H2-MCfR), in which Pd0NPs were in situ-synthesized as the catalyst film and used to activate H2 on the surface of H2-delivery membranes. Batch kinetic experiments showed that 99% of 2,4-D was removed and converted to phenoxyacetic acid (POA) within 90 min with a Pd0 surface loading of 20 mg Pd/m2, achieving a catalyst specific activity of 6.6 ± 0.5 L/g-Pd-min. Continuous operation of the H2-MCfR loaded with 20 mg Pd/m2 sustained >99% removal of 50 µM 2,4-D for 20 days. A higher Pd0 surface loading, 1030 mg Pd/m2, also enabled hydrosaturation and hydrolysis of POA to cyclohexanone and glycolic acid. Density functional theory identified the reaction mechanisms and pathways, which involved reductive hydrodechlorination, hydrosaturation, and hydrolysis. Molecular electrostatic potential calculations and Fukui indices suggested that reductive dehalogenation could increase the bioavailability of herbicides. Furthermore, three other halogenated herbicides─atrazine, dicamba, and bromoxynil─were reductively dehalogenated in the H2-MCfR. This study documents a promising method for the removal and detoxification of halogenated herbicides in aqueous environments.

GSA: an independent development algorithm for calling copy number and detecting homologous recombination deficiency (HRD) from target capture sequencing.

BACKGROUND: The gain or loss of large chromosomal regions or even whole chromosomes is termed as genomic scarring and can be observed as copy number variations resulting from the failure of DNA damage repair. RESULTS: In this study, a new algorithm called genomic scar analysis (GSA) has developed and validated to calculate homologous recombination deficiency (HRD) score. The two critical submodules were tree recursion (TR) segmentation and filtering, and the estimation and correction of the tumor purity and ploidy. Then, this study evaluated the rationality of segmentation and genotype identification by the GSA algorithm and compared with other two algorithms, PureCN and ASCAT, found that the segmentation result of GSA algorithm was more logical. In addition, the results indicated that the GSA algorithm had an excellent predictive effect on tumor purity and ploidy, if the tumor purity was more than 20%. Furtherly, this study evaluated the HRD scores and BRCA1/2 deficiency status of 195 clinical samples, and the results indicated that the accuracy was 0.98 (comparing with Affymetrix OncoScan™ assay) and the sensitivity was 95.2% (comparing with BRCA1/2 deficiency status), both were well-behaved. Finally, HRD scores and 16 genes mutations (TP53 and 15 HRR pathway genes) were analyzed in 17 cell lines, the results showed that there was higher frequency in HRR pathway genes in high HRD score samples. CONCLUSIONS: This new algorithm, named as GSA, could effectively and accurately calculate the purity and ploidy of tumor samples through NGS data, and then reflect the degree of genomic instability and large-scale copy number variations of tumor samples.

Adaptive dynamic self-learning grey wolf optimization algorithm for solving global optimization problems and engineering problems.

The grey wolf optimization algorithm (GWO) is a new metaheuristic algorithm. The GWO has the advantages of simple structure, few parameters to adjust, and high efficiency, and has been applied in various optimization problems. However, the orginal GWO search process is guided entirely by the best three wolves, resulting in low population diversity, susceptibility to local optima, slow convergence rate, and imbalance in development and exploration. In order to address these shortcomings, this paper proposes an adaptive dynamic self-learning grey wolf optimization algorithm (ASGWO). First, the convergence factor was segmented and nonlinearized to balance the global search and local search of the algorithm and improve the convergence rate. Second, the wolves in the original GWO approach the leader in a straight line, which is too simple and ignores a lot of information on the path. Therefore, a dynamic logarithmic spiral that nonlinearly decreases with the number of iterations was introduced to expand the search range of the algorithm in the early stage and enhance local development in the later stage. Then, the fixed step size in the original GWO can lead to algorithm oscillations and an inability to escape local optima. A dynamic self-learning step size was designed to help the algorithm escape from local optima and prevent oscillations by reasonably learning the current evolution success rate and iteration count. Finally, the original GWO has low population diversity, which makes the algorithm highly susceptible to becoming trapped in local optima. A novel position update strategy was proposed, using the global optimum and randomly generated positions as learning samples, and dynamically controlling the influence of learning samples to increase population diversity and avoid premature convergence of the algorithm. Through comparison with traditional algorithms, such as GWO, PSO, WOA, and the new variant algorithms EOGWO and SOGWO on 23 classical test functions, ASGWO can effectively improve the convergence accuracy and convergence speed, and has a strong ability to escape from local optima. In addition, ASGWO also has good performance in engineering problems (gear train problem, ressure vessel problem, car crashworthiness problem) and feature selection.

A two-stage design enhanced biodegradation of high concentrations of a C16-alkyl quaternary ammonium compound in oxygen-based membrane biofilm reactors.

Quaternary ammonia compounds (QAC), such as hexadecyltrimethyl-ammonium (CTAB), are widely used as disinfectants and in personal-care products. Their use as disinfectants grew during the SARS-CoV-2 (COVID-19) pandemic, leading to increased loads to wastewater treatment systems and the environment. Though low concentrations of CTAB are biodegradable, high concentrations are toxic to bacteria. Sufficient O2 delivery is a key to achieve high CTAB removal, and the O2-based Membrane Biofilm Reactor (O2-MBfR) is a proven means to biodegrade CTAB in a bubble-free, non-foaming manner. A strategy for achieving complete biodegradation of high-concentrations of CTAB is a two-stage O2-MBfR, in which partial CTAB removal in the Lead reactor relieves inhibition in the Lag reactor. Here, more than 98 % removal of 728 mg/L CTAB could be achieved in the two-stage MBfR, and the CTAB-removal rate was 70 % higher than for a one-stage MBfR with the same O2-delivery capacity. CTAB exposure shifted the bacterial community toward Pseudomonas and Stenotrophomonas as the dominant genera. In particular, P. alcaligenes and P. aeruginosa were enriched in the Lag reactor, as they were capable of biodegrading the metabolites of initial CTAB monooxygenation. Metagenomic analysis also revealed that the Lag reactor was enriched in genes for CTAB and metabolite oxygenation, due to reduced CTAB inhibition.

Preoperative Anxiolytic and Sedative Effects of Intranasal Remimazolam and Dexmedetomidine: A Randomized Controlled Clinical Study in Children Undergoing General Surgeries.

Purpose: Remimazolam, an ultra-short-acting and fast-metabolized sedative, has only been sporadically investigated in children. This study was performed to determine the beneficial effects of intranasal remimazolam or dexmedetomidine on preoperative anxiety in children undergoing general surgeries. Patients and Methods: Ninety children were randomly and equally assigned to Group R (intranasal remimazolam 1.5mg kg-1), Group D (intranasal dexmedetomidine 2 mcg kg-1), and Group C (intranasal distilled water). The primary outcomes were the preoperative anxiety scores using the modified Yale preoperative anxiety scale (m-Ypas). The secondary outcomes included the cooperation behaviour of intranasal drug application, preoperative sedation levels, parental separation anxiety scores (PSAS), and mask acceptance scores (MAS). Results: Group R showed a significant low anxiety at 10 min after intranasal premedication (vs group C, P=0.010; vs group D, P = 0.002) and at anaesthesia induction (vs group C, P = 0.004). Group D showed a significantly low anxiety score only prior to anaesthesia induction (vs group C, P = 0.005). Most children in group R achieved mild sedation at 10 min (vs group C, P < 0.001; vs group D, P < 0.001), with a few progressing to deep sedation afterwards, while group D tended toward deep sedation. Compared to Group C, patients in Group R performed significantly better on the MAS (P = 0.014) and PSAS (P = 0.008). However, remimazolam did cause poor cooperation behavior to the intranasal application due to its mucosal irritation (vs group C, P = 0.001; vs group D, P = 0.010). Conclusion: Both intranasal remimazolam and dexmedetomidine can effectively alleviate preoperative anxiety in children. While intranasal remimazolam has a rapid onset, it produces only mild sedation and causes substantial nasal irritation. Trial Registration: NCT04720963, January 22, 2021, ClinicalTrials.Gov.

Ion diffusion retarded by diverging chemical susceptibility.

For first-order phase transitions, the second derivatives of Gibbs free energy (specific heat and compressibility) diverge at the transition point, resulting in an effect known as super-elasticity along the pressure axis, or super-thermicity along the temperature axis. Here we report a chemical analogy of these singularity effects along the atomic doping axis, where the second derivative of Gibbs free energy (chemical susceptibility) diverges at the transition point, leading to an anomalously high energy barrier for dopant diffusion in co-existing phases, an effect we coin as super-susceptibility. The effect is realized in hydrogen diffusion in vanadium dioxide (VO2) with a metal-insulator transition (MIT). We show that hydrogen faces three times higher energy barrier and over one order of magnitude lower diffusivity when it diffuses across a metal-insulator domain wall in VO2. The additional energy barrier is attributed to a volumetric energy penalty that the diffusers need to pay for the reduction of latent heat. The super-susceptibility and resultant retarded atomic diffusion are expected to exist universally in all phase transformations where the transformation temperature is coupled to chemical composition, and inspires new ways to engineer dopant diffusion in phase-coexisting material systems.

The effect of remimazolam-based total intravenous anesthesia versus sevoflurane-based inhalation anesthesia on emergence delirium in children undergoing tonsillectomy and adenoidectomy: study protocol for a prospective randomized controlled trial.

Background: Remimazolam, a new ultrashort-acting benzodiazepine, is becoming increasingly applied in general anesthesia. This study is designed to investigate the effect of remimazolam-based total intravenous anesthesia and sevoflurane-based inhalation anesthesia on emergence delirium in pediatric tonsillectomy and adenoidectomy. Methods and analysis: This is a monocentric, prospective, randomized, double-blind clinical trial. A total of 90 pediatric patients will be randomized to receive remimazolam-based total intravenous anesthesia (remimazolam group, n = 45) or sevoflurane-based inhalation anesthesia (sevoflurane group, n = 45). The primary outcome will be the incidence of emergence delirium, which will be evaluated using the Pediatric Anesthesia Emergence Delirium (PAED) scale. The secondary outcomes include the extubation time, recovery time, behavior change using the post-hospitalization behavior questionnaire for ambulatory surgery (PHBQ-AS), and adverse events. Ethics and dissemination: This study has been approved by the Institutional Review Board (IRB) of the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University (2023-K-262-02). Clinical trial registration: ClinicalTrials.gov, identifier NCT06214117.

Comparison of postoperative analgesia and side effects in pediatric laparoscopic surgery with morphine and nalbuphine.

There is currently no consensus on the optimal perioperative pain management strategy involving specific opioids. This study aims to compare the postoperative analgesia, the associated side effects between nalbuphine and morphine in children undergoing laparoscopic surgery. One hundred ninety children were randomly assigned to nalbuphine (0.2 mg/kg) or morphine (0.2 mg/kg). Nalbuphine's analgesic effect was non-inferior to morphine, with similar total rescue analgesic consumption during PACU stay (0.03 ± 0.05mg vs. 0.04 ± 0.06 mg, p > 0.05). Nalbuphine group had a lower incidence of respiratory depression (RR ≤ 10/min) (4.8% vs. 38.6%, p < 0.001), PONV (2.4% vs. 18.1%, p = 0.002), and pruritus (0% vs. 16.9%, p < 0.001) than morphine. Additionally, nalbuphine showed a shorter laryngeal mask airway removal time (13.9 [12.7, 15.1]) compared with morphine (17.0 [15.1, 18.9], p = 0.011). Nalbuphine provides equipotent analgesia with significantly lower incidences of respiratory depression, PONV, and pruritus compared with morphine in pediatric laparoscopic surgery.

Polaron interfacial entropy as a route to high thermoelectric performance in DAE-doped PEDOT:PSS films.

Enhancing the thermoelectric transport properties of conductive polymer materials has been a long-term challenge, in spite of the success seen with molecular doping strategies. However, the strong coupling between the thermopower and the electrical conductivity limits thermoelectric performance. Here, we use polaron interfacial occupied entropy engineering to break through this intercoupling for a PEDOT:PSS (poly(3,4-ethylenedioxythiophene)-poly(4-styrenesulfonate)) thin film by using photochromic diarylethene (DAE) dopants coupled with UV-light modulation. With a 10-fold enhancement of the thermopower from 13.5 µV K-1 to 135.4 µV K-1 and almost unchanged electrical conductivity, the DAE-doped PEDOT:PSS thin film achieved an extremely high power factor of 521.28 µW m-1 K-2 from an original value of 6.78 µW m-1 K-2. The thermopower was positively correlated with the UV-light intensity but decreased with increasing temperature, indicating resonant coupling between the planar closed DAE molecule and PEDOT. Both the experiments and theoretical calculations consistently confirmed the formation of an interface state due to this resonant coupling. Interfacial entropy engineering of polarons could play a critical role in enhancing the thermoelectric performance of the organic film.

Metal transducer-assisted acoustic deformation potential characterization via coherent acoustic phonon dynamics.

Acoustic deformation potential (ADP) plays a significant role in quantifying carrier-acoustic phonon interactions in semiconductors. In this work, we report a novel ultrafast spectroscopy method to extract the ADP coupling constant of a semiconductor by jointly analyzing the coherent acoustic phonon signals with and without a metal transducer. By applying this method to GaAs, the ADP coupling constant corresponding to the band gap was extracted using a pump photon energy near the band gap, which agrees well with literature values. With a larger pump photon energy, the ADP coupling constant deviates from the one for the band gap, which is attributed to contributions from the carrier dynamics in multiple energy and wavevector states.

A synergistic platform enables co-oxidation of halogenated organic pollutants without input of organic primary substrate.

While co-oxidation is widely used to biodegrade halogenated organic pollutants (HOPs), a considerable amount of organic primary substrate is required. Adding organic primary substrates increases the operating cost and also leads to extra carbon dioxide release. In this study, we evaluated a two-stage Reduction and Oxidation Synergistic Platform (ROSP), which integrated catalytic reductive dehalogenation with biological co-oxidation for HOPs removal. The ROSP was a combination of an H2-based membrane catalytic-film reactor (H2-MCfR) and an O2-based membrane biofilm reactor (O2-MBfR). 4-chlorophenol (4-CP) was used as a model HOP to evaluate the performance of ROSP. In the MCfR stage, zero-valent palladium nanoparticles (Pd0NPs) catalyzed reductive hydrodechlorination that converted 4-CP to phenol, with a conversion yield over 92%. In the MBfR stage, the phenol was oxidized and used as a primary substrate that supported the co-oxidation of residual 4-CP. Genomic DNA sequencing revealed that phenol produced from 4-CP reduction enriched bacteria having genes for functional enzymes for phenol biodegradation in the biofilm community. In the ROSP, over 99% of 60 mg/L 4-CP was removed and mineralized during continuous operation: Effluent 4-CP and chemical oxygen demand concentrations were below 0.1 and 3 mg/L, respectively. H2 was the only added electron donor to the ROSP, which means no extra carbon dioxide was produced by primary-substrate oxidation.