bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the Effects of Primary and Secondary Doping via Post‐Treatment of P‐Type and N‐Type Hybrid Organic–Inorganic Thin Film Thermoelectric Materials
Authors: Rubio‐Govea Rodrigo , Félix Roberto , Wilks Regan G. , Bär Marcus , Mazzio Katherine A. 
Published: April 2023

AbstractHybrid organic/inorganic materials have emerged as promising thermoelectric (TE) materials since they inherit the individual strengths of each component, enabling rational materials design with enhanced TE performance. The doping of hybrid TE materials via post‐treatment processes is used to improve their performance, but there is still an incomplete understanding of the elicited effects. Here, the impact of different doping methods on the thin film TE performance of p‐type Te/poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) and n‐type Ag2Te/PEDOT:PSS hybrid materials is investigated. Primary doping through acid–base and charge transfer processes using H2SO4 and tetrakis(dimethylamino)ethylene, respectively, and the effects of secondary doping using ethylene glycol is examined. Through a combination of Hall effect measurements, hard X‐ray photoelectron spectroscopy, and Raman spectroscopy, variations in the charge carrier concentration, mobility, and overall TE performance are related to the morphological and chemical structure of the hybrid materials. This study provides an improved understanding of the effects that different post‐treatments have on hybrid materials and shows that the impact of these post‐treatments on pure PEDOT:PSS does not always apply to hybrid systems. These new insights into post‐treatment effects on hybrid materials is expected to facilitate further enhancement of their performance as electronic materials in general and thermoelectric materials in particular.
Photonic Synapses for Image Recognition and High Density Integration of Simplified Artificial Neural Networks
Authors: Fang Yuqing , Li Qingxuan , Meng Jialin , Wang Tianyu , Zhu Hao , Sun Qing‐Qing , Zhang David Wei , Chen Lin 
Published: April 2023

AbstractWith the rapid development of artificial intelligence (AI), there is an urgent need for developing a biological sensory perception system that can simulate the human brain for information processing. Inspired by the biological vision system, photo‐responsive photonic synapses are ideal devices for constructing photosensitive artificial neural networks for neuromorphic computing tasks. This paper reports a stable photonic synaptic device in an array layout with adjustable synaptic plasticity under ultraviolet light pulses. Since the heterojunction has a photoconductivity effect and the trap layer provides superior charge carrier trapping capability, optical sensing, memory, and neuromorphic computing are integrated into a single device. Meanwhile, supervised learning of handwritten digitals is achieved by exploiting the multistate conductance by photoelectric co‐modulation and the specific decay law. The recognition rate reaches 90.6% and hardly changes with time. Additionally, the device can simplify the artificial neural network (ANN) and reduce its size to 3.78% of the original network while retaining strong fault tolerance and learning ability. The photonic artificial synapses based on ultraviolet light modulation provide a novel and effective approach for photosensory ANNs to perform in situ computation.
Kinetic study in an automatic continuous‐flow photochemical platform with machine learning
Authors: Wang Yuhan , Shen Chong , Qiu Min , Shang Minjing , Su Yuanhai 
Published: April 2023

AbstractIn this work, we first solved the partial differential equation of the one‐dimensional axial diffusion model in an open‐source platform, that is, FEniCS, to explore the influence of the axial dispersion on the reaction yield‐to‐time profile. Then, we built an automatic platform, which included a photomicroreactor, a continuously controlled pump, a high‐power UV‐LED light source, an in‐line visible‐light absorbance analytical unit, and a Raspberry Pi based controlling unit. Moreover, steady‐state feeding and sampling functions could be realized in this continuous‐flow photochemical platform. The homogeneous photolysis of methylene blue and the photo‐Favorskii rearrangement synthesis of ibuprofen as the model reactions were used to validate the robustness of this automatic platform with unsteady‐state and steady‐state operations, through which kinetic study was carried out using genetic algorithm based symbolic regression, leading to deep understanding on reaction mechanisms and benefits for process optimization.
Equivalence of plasma p‐tau217 with cerebrospinal fluid in the diagnosis of Alzheimer's disease
Authors: Therriault Joseph , Servaes Stijn , Tissot Cécile , Rahmouni Nesrine , Ashton Nicholas J. , Benedet Andréa Lessa , Karikari Thomas K. , Macedo Arthur C. , Lussier Firoza Z. , Stevenson Jenna , Wang Yi‐Ting , Fernandez‐Arias Jaime , Stevenson Alyssa , Socualaya Kely Quispialaya , Haeger Arlette , Nazneen Tahnia , Aumont Étienne , Hosseini Ali , Rej Soham , Vitali Paolo , Triana‐Baltzer Gallen , Kolb Hartmuth C. , Soucy Jean‐Paul , Pascoal Tharick A. , Gauthier Serge , Zetterberg Henrik , Blennow Kaj , Rosa‐Neto Pedro 
Published: April 2023

AbstractINTRODUCTIONPlasma biomarkers are promising tools for Alzheimer's disease (AD) diagnosis, but comparisons with more established biomarkers are needed.METHODSWe assessed the diagnostic performance of p‐tau181, p‐tau217, and p‐tau231 in plasma and CSF in 174 individuals evaluated by dementia specialists and assessed with amyloid‐PET and tau‐PET. Receiver operating characteristic (ROC) analyses assessed the performance of plasma and CSF biomarkers to identify amyloid‐PET and tau‐PET positivity.RESULTSPlasma p‐tau biomarkers had lower dynamic ranges and effect sizes compared to CSF p‐tau. Plasma p‐tau181 (AUC = 76%) and p‐tau231 (AUC = 82%) assessments performed inferior to CSF p‐tau181 (AUC = 87%) and p‐tau231 (AUC = 95%) for amyloid‐PET positivity. However, plasma p‐tau217 (AUC = 91%) had diagnostic performance indistinguishable from CSF (AUC = 94%) for amyloid‐PET positivity.DISCUSSIONPlasma and CSF p‐tau217 had equivalent diagnostic performance for biomarker‐defined AD. Our results suggest that plasma p‐tau217 may help reduce the need for invasive lumbar punctures without compromising accuracy in the identification of AD.Highlights
p‐tau217 in plasma performed equivalent to p‐tau217 in CSF for the diagnosis of AD, suggesting the increased accessibility of plasma p‐tau217 is not offset by lower accuracy.
p‐tau biomarkers in plasma had lower mean fold‐changes between amyloid‐PET negative and positive groups than p‐tau biomarkers in CSF.
CSF p‐tau biomarkers had greater effect sizes than plasma p‐tau biomarkers when differentiating between amyloid‐PET positive and negative groups.
Plasma p‐tau181 and plasma p‐tau231 performed worse than p‐tau181 and p‐tau231 in CSF for AD diagnosis.
Coordinating the Edge Defects of Bismuth with Sulfur for Enhanced CO2 Electroreduction to Formate
Authors: Lv Lei , Lu Ruihu , Zhu Jiexin , Yu Ruohan , Zhang Wei , Cui Enhui , Chen Xingbao , Dai Yuhang , Cui Lianmeng , Li Jiong , Zhou Liang , Chen Wei , Wang Ziyun , Mai Liqiang 
Published: April 2023

AbstractBismuth‐based materials have been recognized as promising catalysts for the electrocatalytic CO2 reduction reaction (ECO2RR). However, they show poor selectivity due to competing hydrogen evolution reaction (HER). In this study, we have developed an edge defect modulation strategy for Bi by coordinating the edge defects of bismuth (Bi) with sulfur, to promote ECO2RR selectivity and inhibit the competing HER. The prepared catalysts demonstrate excellent product selectivity, with a high HCOO− Faraday efficiency of ≈95 % and an HCOO− partial current of ≈250 mA cm−2 under alkaline electrolytes. Density function theory calculations reveal that sulfur tends to bind to the Bi edge defects, reducing the coordination‐unsaturated Bi sites (*H adsorption sites), and regulating the charge states of neighboring Bi sites to improve *OCHO adsorption. This work deepens our understanding of ECO2RR mechanism on bismuth‐based catalysts, guiding for the design of advanced ECO2RR catalysts.
Isolated Electron Trap‐Induced Charge Accumulation for Efficient Photocatalytic Hydrogen Production
Authors: Huang Wenhuan , Su Chenyang , Zhu Chen , Bo Tingting , Zuo Shouwei , Zhou Wei , Ren Yuanfu , Zhang Yanan , Zhang Jing , Rueping Magnus , Zhang Huabin 
Published: April 2023

AbstractThe solar‐driven evolution of hydrogen from water using particulate photocatalysts is considered one of the most economical and promising protocols for achieving a stable supply of renewable energy. However, the efficiency of photocatalytic water splitting is far from satisfactory due to the sluggish electron‐hole pair separation kinetics. Herein, isolated Mo atoms in a high oxidation state have been incorporated into the lattice of Cd0.5Zn0.5S (CZS@Mo) nanorods, which exhibit photocatalytic hydrogen evolution rate of 11.32 mmol g−1 h−1 (226.4 μmol h−1; catalyst dosage 20 mg). Experimental and theoretical simulation results imply that the highly oxidized Mo species lead to mobile‐charge imbalances in CZS and induce the directional photogenerated electrons transfer, resulting in effectively inhibited electron‐hole recombination and greatly enhanced photocatalytic efficiency.
Nickel‐Catalyzed Kinetic Resolution of Racemic Unactivated Alkenes via Enantio‐, Diastereo‐, and Regioselective Hydroamination
Authors: Kang Hyung‐Joon , Lee Changseok , Hong Sungwoo 
Published: April 2023

AbstractKinetic resolution is a powerful strategy for the isolation of enantioenriched compounds from racemic mixtures, and the development of selective catalytic processes is an active area of research. Here, we present a nickel‐catalyzed kinetic resolution of racemic α‐substituted unconjugated carbonyl alkenes via the enantio‐, diastereo‐, and regioselective hydroamination. This protocol affords both chiral α‐substituted butenamides and syn‐β2,3‐amino acid derivatives with high enantiomeric purity (up to 99 % ee) and selectivity factor up to >684. The key to the excellent kinetic resolution efficiency is the distinctive architecture of the chiral nickel complex, which enables successful resolution and enantioselective C−N bond construction. Mechanistic investigations reveal that the unique structure of the chiral ligand facilitates a rapid migratory insertion step with one enantiomer. This strategy provides a practical and versatile approach to prepare a wide range of chiral compounds.
Nano‐Impact Single‐Entity Electrochemistry Enables Plasmon‐Enhanced Electrocatalysis**
Authors: Ganguli Sagar , Zhao Ziwen , Parlak Onur , Hattori Yocefu , Sá Jacinto , Sekretareva Alina 
Published: April 2023

AbstractPlasmon‐enhanced electrocatalysis (PEEC), based on a combination of localized surface plasmon resonance excitation and an electrochemical bias applied to a plasmonic material, can result in improved electrical‐to‐chemical energy conversion compared to conventional electrocatalysis. Here, we demonstrate the advantages of nano‐impact single‐entity electrochemistry (SEE) for investigating the intrinsic activity of plasmonic catalysts at the single‐particle level using glucose electrooxidation and oxygen reduction on gold nanoparticles as model reactions. We show that in conventional ensemble measurements, plasmonic effects have minimal impact on photocurrents. We suggest that this is due to the continuous equilibration of the Fermi level (EF) of the deposited gold nanoparticles with the EF of the working electrode, leading to fast neutralization of hot carriers by the measuring circuit. The photocurrents detected in the ensemble measurements are primarily caused by photo‐induced heating of the supporting electrode material. In SEE, the EF of suspended gold nanoparticles is unaffected by the working electrode potential. As a result, plasmonic effects are the dominant source of photocurrents under SEE experimental conditions.
Chlorination‐Mediated π–π Stacking Enhances the Photodynamic Properties of a NIR‐II Emitting Photosensitizer with Extended Conjugation
Authors: Gu Ying , Lai Hanjian , Chen Zi‐Yi , Zhu Yulin , Sun Zongzhao , Lai Xue , Wang Hengtao , Wei Zixiang , Chen Lin , Huang Limin , Zhang Yuanzhu , He Feng , Tian Leilei 
Published: April 2023

AbstractNIR‐II‐emitting photosensitizers (PSs) have attracted great research interest due to their promising clinical applications in imaging‐guided photodynamic therapy (PDT). However, it is still challenging to realize highly efficient PDT on NIR‐II PSs. In this work, we develop a chlorination‐mediated π–π organizing strategy to improve the PDT of a PS with conjugation‐extended A‐D‐A architecture. The significant dipole moment of the carbon‐chlorine bond and the strong intermolecular interactions of chlorine atoms bring on compact π–π stacking in the chlorine‐substituted PS, which facilitates energy/charge transfer and promotes the photochemical reactions of PDT. Consequently, the resultant NIR‐II emitting PS exhibits a leading PDT performance with a yield of reactive oxygen species higher than that of previously reported long‐wavelength PSs. These findings will enlighten the future design of NIR‐II emitting PSs with enhanced PDT efficiency.
Fine‐tuning of fully‐aromatic polyamide membrane for fluorinated water purification
Authors: Gao Sheng‐Li , Li Lan‐Qian , Huang Jie , Xu Zhen‐Liang , Tang Yong‐Jian 
Published: April 2023

AbstractHigh concentrations of fluoride in drinking water can lead to fluorosis of teeth and bones and other serious diseases, while nanofiltration is an attractive technique for fluoride removal. Interfacial temperature can determine the monomer diffusion rate in interfacial polymerization (IP) process, thereby tuning the structure of membrane such as thickness, pore size and surface charge. Herein, a fully‐aromatic polyamide nanofiltration membrane with desirable separation performance was customized by interface temperature. The resulting membrane exhibits a flux of 6 L m−2 h−1 bar−1 and the molecular weight cut‐off is 211 Da, most importantly, a 90.3% F− rejection to underground water, indicating that the membrane has application potential in underground water treatment. This work helps to better understand the effects of interface temperature on the IP process and provides a new strategy to address the drinking water problem.
Decomposability versus detectability: First validation of TED‐GC/MS for microplastic detection in different environmental matrices
Authors: Kittner Maria , Eisentraut Paul , Dittmann Daniel , Braun Ulrike 
Published: April 2023

AbstractA fast method for microplastic detection is thermal extraction desorption‐gas chromatography/mass spectrometry (TED‐GC/MS), which uses polymer‐specific thermal decomposition products as marker compounds to determine polymer mass contents in environmental samples. So far, matrix impacts of different environmental matrices on TED‐GC/MS performance had not yet been assessed systematically. Therefore, three solid freshwater matrices representing different aquatic bodies with varying organic matter contents were spiked with a total of eight polymers. Additionally, for the first time, the two biodegradable polymers polybutylene adipate terephthalate (PBAT) and polylactide (PLA) were analysed using TED‐GC/MS. The methodological focus of this work was on detectability, quality of signal formation as well as realisation of quantification procedures and determination of the limit of detection (LOD) values. Overall, TED‐GC/MS allowed the unambiguous detection of the environmentally most relevant polymers analysed, even at low mass contents: 0.02 wt% for polystyrene (PS), 0.04 wt% for the tyre component styrene butadiene rubber (SBR) and 0.2 wt% for polypropylene (PP), polyethylene (PE) and PBAT. Further, all obtained LOD values were increased in all matrices compared to the neat polymer without matrix. The LOD of the standard polymers were increased similarly (PS: 0.21–0.34 µg, SBR: 0.27–0.38 µg, PP: 0.32–0.36 µg, PMMA: 0.64–1.30 µg, PET: 0.90–1.37 µg, PE: 3.80–6.99 µg) and their decompositions by radical scission processes were not significantly influenced by the matrices. In contrast, matrix‐specific LOD increases of both biodegradable polymers PBAT (LOD: 1.41–7.18 µg) and PLA (0.84–20.46 µg) were observed, probably due to their hetero‐functional character and interactions with the matrices. In conclusion, the TED‐GC/MS performance is not solely determined by the type of the polymers but also by the composition of the matrix.
A new belief rule base based distributed online fault diagnosis method for multi‐agent systems
Authors: Wang Ziyi , He Wei , Yang Ruohan , Feng Zhichao , Luo Shuyang 
Published: April 2023

AbstractIn this paper, based on belief rule base (BRB), we studied the distributed online fault diagnosis problem of multi‐agent systems (MASs). To begin with, considering the distributed nature of MASs, by using the relative information between an agent and its neighbors, a distributed online fault diagnosis model is constructed. Next, for the results of fault diagnosis, when an agent doesn't get enough relative information to diagnose the fault, the fault diagnosis result may be inaccurate, and if there exist too many neighbors of an agent, the number of attributes of the proposed BRB fault diagnosis model will be too large, which will lead to large computation. To improve the performance of the proposed distributed online fault diagnosis model, a real‐time communication topology switching strategy was proposed. Under the constructed distributed fault diagnosis model, the real‐time performance and the accuracy of fault diagnosis for agents can be guaranteed simultaneously. Finally, a simulation is given to validate the effectiveness and advancement of the distributed online fault diagnosis method proposed in this paper.
Druckversuche zur Ermittlung der Tragfähigkeit von ebenen und feinverzahnten Trockenfugen für modulare Segmentbrücken
Authors: Rettinger Martin , Lounis Ali , Hückler Alex , Schlaich Mike 
Published: April 2023

AbstractDie modularisierte und automatisierte Serienfertigung von Betonfertigteilen verspricht enorme Produktivitätssteigerungen in der Betonfertigteilindustrie bei gleichzeitig höherer Bauteilqualität, effizienterem Rohstoffeinsatz und verringerten Prozessabfällen. So werden durch die Modernisierung eines bisher überwiegend handwerklich geprägten Industriezweigs sowohl Ressourcen und Emissionen eingespart, als auch neue Wachstums‐ und Wertschöpfungsmöglichkeiten in Zeiten des anhaltenden Fachkräftemangels erschlossen. Modulares Bauen erfordert dabei die Erforschung und Entwicklung von neuartigen Prozessen, Bauweisen und Baumaterialien, welche die serielle und automatisierte Herstellung von Betonfertigteilen in effizienter Weise ermöglichen. Passgenau hergestellte Betonfertigteilmodule können ohne übergreifende Längsbewehrung und mit trockenen, ohne Kleber ausgeführten Fugen schnell und flexibel zu z. B. Segmentbrücken gefügt werden. Am Ende ihrer Nutzungszeit können sie zerstörungsfrei zurückgebaut und idealerweise in einem zweiten Lebenszyklus wiederverwendet werden. In einer Versuchsreihe haben die Autoren die Tragfähigkeit von glatten und feinverzahnten Trockenfugen untersucht, welche sich für das Fügen von modularen Segmentbrücken aus Carbonbeton eignen. In dem vorliegenden Beitrag werden die durchgeführten Versuche, die beobachteten Versagensmechanismen und quantitativen Versuchsergebnisse sowie der Vergleich mit international verfügbaren Bemessungsregeln diskutiert.
Optimization of medium with perfusion microbioreactors for high density CHO cell cultures at very low renewal rate aided by design of experiments
Authors: Schwarz Hubert , Lee Kevin , Castan Andreas , Chotteau Veronique 
Published: April 2023

AbstractA novel approach of design of experiment (DoE) is developed for the optimization of key substrates of the culture medium, amino acids, and sugars, by utilizing perfusion microbioreactors with 2 mL working volume, operated in high cell density continuous mode, to explore the design space. A mixture DoE based on a simplex‐centroid is proposed to test multiple medium blends in parallel perfusion runs, where the amino acids concentrations are selected based on the culture behavior in presence of different amino acid mixtures, and using targeted specific consumption rates. An optimized medium is identified with models predicting the culture parameters and product quality attributes (G0 and G1 level N‐glycans) as a function of the medium composition. It is then validated in runs performed in perfusion microbioreactor in comparison with stirred‐tank bioreactors equipped with alternating tangential flow filtration (ATF) or with tangential flow filtration (TFF) for cell separation, showing overall a similar process performance and N‐glycosylation profile of the produced antibody. These results demonstrate that the present development strategy generates a perfusion medium with optimized performance for stable Chinese hamster ovary (CHO) cell cultures operated with very high cell densities of 60 × 106 and 120 × 106 cells/mL and a low cell‐specific perfusion rate of 17 pL/cell/day, which is among the lowest reported and is in line with the framework recently published by the industry.
Data‐driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins
Authors: Park Seo‐Young , Kim Sun‐Jong , Park Cheol‐Hwan , Kim Jiyong , Lee Dong‐Yup 
Published: April 2023

AbstractRecently, the advancement in process analytical technology and artificial intelligence (AI) has enabled the generation of enormous culture data sets from biomanufacturing processes that produce various recombinant therapeutic proteins (RTPs), such as monoclonal antibodies (mAbs). Thus, now it is very important to exploit them for the enhanced reliability, efficiency, and consistency of the RTP‐producing culture processes and for the reduced incipient or abrupt faults. It is achievable by AI‐based data‐driven models (DDMs), which allow us to correlate biological and process conditions and cell culture states. In this work, we provide practical guidelines for choosing the best combination of model elements to design and implement successful DDMs for given hypothetical in‐line data sets during mAb‐producing Chinese hamster ovary cell culture, as such enabling us to forecast dynamic behaviors of culture performance such as viable cell density, mAb titer as well as glucose, lactate and ammonia concentrations. To do so, we created DDMs that balance computational load with model accuracy and reliability by identifying the best combination of multistep ahead forecasting strategies, input features, and AI algorithms, which is potentially applicable to implementation of interactive DDM within bioprocess digital twins. We believe this systematic study can help bioprocess engineers start developing predictive DDMs with their own data sets and learn how their cell cultures behave in near future, thereby rendering proactive decision possible.