bluuebunny/crossref_metadata_2025_split huggingface dataset:
Broadband, Low‐Crosstalk, and Massive‐Channels OAM Modes De/Multiplexing Based on Optical Diffraction Neural Network
Authors: Liu Zhibing , Gao Shecheng , Lai Zhaoyu , Li Yuru , Ao Zhaohuan , Li Jinpei , Tu Jiajing , Wu Yanxiong , Liu Weiping , Li Zhaohui 
Published: February 2023

AbstractOptical communication technology based on the wavelength, time, polarization, and complex amplitude of light is approaching a bottleneck, while the spatial dimension is relatively unexplored. Orbital angular momentum (OAM) beams are an important group of spatial light beams that are promising for increasing the optical communication capacity based on their orthogonality. To effectively utilize this spatial dimension of light, broadband and low‐crosstalk OAM mode de/multiplexing devices are indispensable. In this work, by exploiting an optical diffraction neural network, a low‐crosstalk OAM de/multiplexer operating in the full C+L band is developed and demonstrated. The device can support 16 OAM modes (l = ±1 to ±8) with 5 phase plates (8‐level phase), and the designed insertion loss and average intermode crosstalk are better than −2.8 and −30.9 dB, respectively. In particular, multiplexing and demultiplexing are experimentally performed on the same device. The measured average insertion loss in mutltiplexing and demulteplexing is −6.1 to −5.4 and −6.8 to −5.8 dB, respectively, and the corresponding average intermode crosstalk is −27.2 to −22.7 and −26.5 to −22.4 dB. The results in this work have great application prospects for the design of mode de/multiplexers and mode division multiplexing communication systems.
Metallic Plasmonic Nanostructure Arrays for Enhanced Solar Photocatalysis
Authors: Jia Huaping , Tsoi Chi Chung , Abed Abdel El , Yu Weixing , Jian Aoqun , Sang Shengbo , Zhang Xuming 
Published: February 2023

AbstractPlasmon‐enhanced photocatalysis has emerged as a promising technology for solar‐to‐chemical energy conversion. Compared to isolated or disordered metal nanostructures, by controlling the morphology, composition, size, spacing, and dispersion of individual nanocomponents, plasmonic nanostructure arrays with coupling architectures yield strong broadband light‐harvesting capability, efficient charge transfer, enhanced local electromagnetic fields, and large contact interfaces. Although metallic nanostructure arrays are extensively studied for various applications, such as refractive index sensing, surface‐enhanced spectroscopy, plasmon‐enhanced luminescence, plasmon nanolasing, and perfect light absorption, the connection between surface plasmon resonance and enhanced photocatalysis remains relatively unexplored. In this study, an overview of plasmonic nanostructure arrays over a broad range, from 0D to 3D, for efficient photocatalysis is presented. By reviewing the fundamental mechanisms, recent applications, and latest developments of plasmonic nanostructure arrays in solar‐driven chemical conversion, this study reports on the latest guidance toward the integration of plasmonic nanostructures for functional devices in the fields of plasmonic, photonics, photodetection, and solar‐energy harvesting.
Hydrogel‐Based Reconfigurable Visualization with Pixel‐Scale Programmability by Vapor Exhalation
Authors: Hu Wanlin , Dai Chenjie , Wan Shuai , Li Zhe , Tang Jiao , Li Zhongyang 
Published: February 2023

AbstractHeading toward real‐life applications outside the laboratory, a longstanding obstacle for meta‐optics is to achieve an easy‐accessible tuning approach with practical characteristics, including a large tuning area, low complexity, low cost, and low energy consumption. Water (H2O) stimuli, a ubiquitous substance in nature, can potentially serve as a rescue solution and has attracted broad interest. However, despite its great simplicity, water tuning still faces an unresolved but critical challenge, that is, to enable independent‐programmable functionalities transformation. Herein, a pixel‐scale programmable visualization transformation simply tuned by exhaling water vapors through constructing a hydrogel‐based reconfigurable architectural metasurface (HRAM) with its geometric sensitivity to water molecules is originally demonstrated. Due to the moisture‐induced resonant mode switch from HRAM scaling up/down, the amplitude‐programmable meta‐pixels for obtaining multi‐channel encoding freedom are successfully created. Via simply exhaling vapors to the sample pattern, it dynamically exhibits independent‐programmable visualization (nanoprinting and meta‐holography) switch in real‐time at the prior‐/post‐humid states, beyond the conventional coloring change or simply on‐and‐off style switch utilizing humidity tuning scheme. Such a tuning strategy with good programmability, repeatability, and a large tuning area would blaze new trails for meta‐display dynamics in practical applications, including display/cosmetics, information storage/encryption, and humidity sensors.
Structure and Dynamics of Temperature‐Responsive Microgels and Hydrogels by NMR Spectroscopy, Relaxometry, and Diffusometry
Authors: Demco Dan E. , Pich Andrij 
Published: February 2023

AbstractStimuli‐responsive polymer networks like microgels and hydrogels possess a variety of properties that need to be analyzed for their rational design and successful application in the targeted field of interest. Nanoscale characterization of gels can be achieved by highly selective and sensitive techniques including high‐resolution NMR spectroscopy, relaxometry, and diffusometry. This review is focusing on recent results using 1H and 13C 1D and 2D NMR techniques, which give chemically site‐selective information about the polymer network revealing the interplay between structure and dynamics of polymer networks at the nanoscale level. By that, NMR can allow to obtain information about i) internal structure, ii) stimuli‐induced phase transition, iii) mesh size, and iv) aggregation of microgels and hydrogels. The rational design of responsive microgels and hydrogels with application in drug delivery, cell carrier systems, catalysis, actuators, and as antibacterial agent can be made, if crucial polymer network properties can be correlated with cross‐linking density, type of cross‐link interactions, electrical charges, hydrophobic nano‐structuring, and dispersion concentration.
Silicone‐based materials with tailored MR relaxation characteristics for use in reduced coil visibility and in tissue‐mimicking phantom design
Authors: Motovilova Elizaveta , Aronowitz Eric , Vincent Jana , Shin James , Tan Ek Tsoon , Robb Fraser , Taracila Victor , Sneag Darryl B. , Dyke Jonathan P. , Winkler Simone Angela 
Published: February 2023

AbstractBackgroundThe development of materials with tailored signal intensity in MR imaging is critically important both for the reduction of signal from non‐tissue hardware, as well as for the construction of tissue‐mimicking phantoms. Silicone‐based phantoms are becoming more popular due to their structural stability, stretchability, longer shelf life, and ease of handling, as well as for their application in dynamic imaging of physiology in motion. Moreover, silicone can be also used for the design of stretchable receive radio‐frequency (RF) coils.PurposeFabrication of materials with tailored signal intensity for MRI requires knowledge of precise T1 and T2 relaxation times of the materials used. In order to increase the range of possible relaxation times, silicone materials can be doped with gadolinium (Gd). In this work, we aim to systematically evaluate relaxation properties of Gd‐doped silicone material at a broad range of Gd concentrations and at three clinically relevant magnetic field strengths (1.5 T, 3 T, and 7 T). We apply the findings for rendering silicone substrates of stretchable receive RF coils less visible in MRI. Moreover, we demonstrate early stage proof‐of‐concept applicability in tissue‐mimicking phantom development.Materials and MethodsTen samples of pure and Gd‐doped Ecoflex silicone polymer samples were prepared with various Gd volume ratios ranging from 1:5000 to 1:10, and studied using 1.5 T and 3 T clinical and 7 T preclinical scanners. T1 and T2 relaxation times of each sample were derived by fitting the data to Bloch signal intensity equations. A receive coil made from Gd‐doped Ecoflex silicone polymer was fabricated and evaluated in vitro at 3 T.ResultsWith the addition of a Gd‐based contrast agent, it is possible to significantly change T2 relaxation times of Ecoflex silicone polymer (from 213 ms to 20 ms at 1.5 T; from 135 ms to 17 ms at 3 T; and from 111.4 ms to 17.2 ms at 7 T). T1 relaxation time is less affected by the introduction of the contrast agent (changes from 608 ms to 579 ms; from 802.5 ms to 713 ms at 3 T; from 1276 ms to 979 ms at 7 T). First results also indicate that liver, pancreas, and white matter tissues can potentially be closely mimicked using this phantom preparation technique. Gd‐doping reduces the appearance of the silicone‐based coil substrate during the MR scan by up to 81%.ConclusionsGd‐based contrast agents can be effectively used to create Ecoflex silicone polymer‐based phantoms with tailored T2 relaxation properties. The relative low cost, ease of preparation, stretchability, mechanical stability, and long shelf life of Ecoflex silicone polymer all make it a good candidate for “MR invisible” coil development and bears promise for tissue‐mimicking phantom development applicability.
Exploring the perceptions of how living with osteoarthritis affects employed people's work productivity
Authors: Ching Angela , Prior Yeliz 
Published: February 2023

AbstractBackgroundWorking people with osteoarthritis (OA) can experience difficulties at work due to pain and activity limitation.ObjectiveTo explore the impact of biopsychosocial factors on work participation in employed people with OA.MethodsAn explorative, qualitative, semi‐structured one‐to‐one telephone interview study. Employed people living with OA were recruited through an arthritis volunteer database and social media. Data was analysed using Thematic Analysis.FindingsParticipants (n = 15) included people with OA in any joints from mixture of careers. Themes were: (1) Effects of OA on work participation, (2) Impact of workplace support and accommodations on employment, and (3) Importance of clinical support and management.ConclusionImpact of OA on people's work productivity results in a spill over into their home lives. Work transitions and adaptations are not always available. Employers need to be educated to support employees to create a positive work environment and promote available workplace support.
Fibrous electrospun polycaprolactone nanomat reinforced with halloysite nanotubes: Preparation and study of its potential application as tissue engineering scaffold
Authors: Hagh Haleh Bakhtkhosh , Unsworth Larry D. , Doustdar Fatemeh , Olad Ali 
Published: February 2023

AbstractIn this work, the biocompatible and biodegradable polycaprolactone (PCL) was synthesized by a ring‐opening synthesis mechanism. To improve the mechanical and biological properties of the polymer, electrospun nanocomposite scaffolds were prepared using halloysite nanotubes (HNTs) as the reinforcing agent with the concentrations of 5, 10, 15, 20, and 25% (w/w) of PCL. PCL‐HNTs composites were prepared as fibrous nanomats by electrospinning method. The morphology and wettability of the electrospun PCL‐HNTs nanomats were investigated by scanning electron microscope images and water contact angel measurement and based on the structure of the fibers, fibers diameter and higher wettability, the PCL‐HNT composite containing 5% (w/w) of halloysite nanotubes (PCL + 5%HNTs) was selected as the proper composite and its application as tissue engineering scaffold was studied. The mechanical properties of the PCL + 5%HNTs composite was 2.6 times higher than that of PCL, as well as, comparatively higher thermal stability. To improve the antibacterial properties, HNTs were loaded with gentamycin sulfate (GM) prior to electrospinning and the PCl + 5%HNTs+GM composite were prepared and studied. The drug release profile showed that by the incorporation of HNTs into the PCL based composites, slow drug release was continued for 164 h, while neat HNTs were completed the drug release after 8 h. The GM loaded composite scaffold showed a high antibacterial effect for Staphylococcus aureus and Listeria monocytogenes, Escherichia coli. Adequate cell growth environment was provided by PCL + 5%HNTs, as indicated by the biocompatibility and protein adsorption test results. The hemolytic assay results showed a higher hemolysis value for the HNTs‐containing sample, but still lower than 5%.
Short‐term outcome after the prenatal diagnosis of right aortic arch
Authors: Bet Bo B. , Snoep Maartje C. , van Leeuwen Elisabeth , Linskens Ingeborg H. , Haak Monique C. , Rozendaal Lieke , Knobbe Ingmar , van Schuppen Joost , Hoekstra Carlijn E. L. , Koolbergen David R. , Clur Sally‐Ann , Pajkrt Eva 
Published: February 2023

AbstractObjectivesTo determine the proportion of children that require surgery in the first year of life and thereafter in order to improve the counseling of parents with a fetus with a right aortic arch (RAA).MethodsFetuses diagnosed with isolated RAA, defined as the absence of intra‐ or extracardiac anomalies, between 2007 and 2021 were extracted from the prospective registry PRECOR.ResultsIn total, 110 fetuses were included, 92 with a prenatal diagnosis of RAA and 18 with double aortic arch (DAA). The prevalence of 22q11 deletion syndrome was 5.5%. Six pregnancies were terminated and five cases were false‐positive; therefore, the follow‐up consisted of 99 neonates. Surgery was performed in 10 infants (10%) in the first year of life. In total, 25 (25%) children had surgery at a mean age of 17 months. Eight of these 25 (32%) had a DAA. Only one child, with a DAA, required surgery in the first week of life due to obstructive stridor.ConclusionsChildren with a prenatally diagnosed RAA are at a low risk of acute respiratory postnatal problems. Delivery in a hospital with neonatal intensive care and pediatric cardiothoracic facilities seems only indicated in cases with suspected DAA. Expectant parents should be informed that presently 25% of the children need elective surgery and only incidentally due to acute respiratory distress.
Tying research question and analytical strategy when variables are affected by medication use
Authors: Choi Jungyeon , Dekkers Olaf M. , le Cessie Saskia 
Published: February 2023

AbstractIll‐defined research questions could be particularly problematic in an epidemiological setting where measurements fluctuate over time due to intercurrent events, such as medication use. When a research question fails to specify how medication use should be handled methodologically, arbitrary decisions may be made during the analysis phase, which likely leads to a mismatch between the intended question and the performed analysis. The mismatch can result in vastly different or meaningless interpretations of estimated effects. Thus, a research question such as “what is the effect of X on Y?” requires further elaboration, and it should consider whether and how medication use has affected the measurements of interest. In our study, we will discuss how well‐defined questions can be formulated when medication use is involved in observational studies. We will distinguish between a situation where an exposure is affected by medication use and where the outcome of interest is affected by medication use. For each setting, we will give examples of different research questions that could be asked depending on how medication use is considered in the estimand and discuss methodological considerations under each question.
Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions
Authors: Lansford Joshua L. , Jensen Klavs F. , Barnes Brian C. 
Published: February 2023

AbstractRecent advances have enabled machine learning methodologies developed for large datasets to be applied to the small experimental datasets typically available for chemical systems. Such advances typically involve a data‐based approach to transfer learning, where a portion of the experimental data for the property of interest is used to fine‐tune a model that is pre‐trained on computationally generated data. This transfer learning approach does not work for very small experimental datasets, where there are only enough data for model validation. Here, we develop a physics‐informed transfer learning strategy to train a directed‐message passing neural network (D‐MPNN) model, enabling extrapolation outside of the training domain. We demonstrate this approach by training a D‐MPNN model on interpolated vapor pressures and validate the model on an out‐of‐sample test set of energetic molecule vapor pressures, achieving accuracy comparable to those of experiments.
Postoperative limb alignment in total knee replacement. Conventional versus navigated versus robotic techniques
Authors: Durán‐Serrano María , Lizcano‐Palomares Miguel , Laclériga‐Giménez Antonio Francisco , Roche‐Albero Adrián , Delfau‐Lafuente Daniel , Martín‐Hernández Carlos 
Published: February 2023

AbstractBackgroundOur objective was to compare the coronal mechanical axis after total knee replacement (TKR) obtained in three groups of patients subjected to conventional, navigated, and robotic surgery.MethodsRetrospective analysis.Results124 knees were included (36 conventional, 41 navigated, 47 robotic). No statistically significant differences were found between the postOp tibiofemoral angle of the conventional, navigated and robotic groups (p = 0.396). A repeated‐measure analysis of preOp‐to‐postOp also found no significant differences (p = 0.387). There were no differences in the proportion of outliers (3‐degree) found (p = 0.211). Nevertheless, a higher proportion of patients in the robotic group improved their mechanical alignment, as compared with conventional surgery (p = 0.023), although no differences were found when comparing with navigation (p = 0.121).ConclusionsNo statistically significant differences were found with respect to the postOp alignment achieved. However, statistically significant differences were detected between robotic and conventional surgery when considering the percentage of patients with improved limb alignment.
3D Printed Solid Polymer Electrolytes with Bicontinuous Nanoscopic Domains for Ionic Liquid Conduction and Energy Storage
Authors: Melodia Daniele , Bhadra Abhirup , Lee Kenny , Kuchel Rhiannon , Kundu Dipan , Corrigan Nathaniel , Boyer Cyrille 
Published: February 2023

AbstractSolid polymer electrolytes (SPEs) offer several advantages compared to their liquid counterparts, and much research has focused on developing SPEs with enhanced mechanical properties while maintaining high ionic conductivities. The recently developed polymerization‐induced microphase separation (PIMS) technique offers a straightforward pathway to fabricate bicontinuous nanostructured materials in which the mechanical properties and conductivity can be independently tuned. In this work SPEs with tunable mechanical properties and conductivities are prepared via digital light processing 3D printing, exploiting the PIMS process to achieve nanostructured ion‐conducting materials for energy storage applications. A rigid crosslinked poly(isobornyl acrylate‐stat‐trimethylpropane triacrylate) scaffold provided materials with room temperature shear modulus above 400 MPa, while soft poly(oligoethylene glycol methyl ether acrylate) domains containing the ionic liquid 1‐butyl‐3‐methylimidazolium bis‐(trifluoromethyl sulfonyl)imide endowed the material with ionic conductivity up to 1.2 mS cm−1 at 30 °C. These features make the 3D‐printed SPE very competitive for applications in all solid energy storage devices, including supercapacitors.
Sequential Sol‐Gel Self‐Assembly and Nonclassical Gel‐Crystal Transformation of the Metal‐Organic Framework Gel
Authors: Fu Jiarui , He Ziyan , Schott Eduardo , Fei Honghan , Tu Min , Wu Yi‐nan 
Published: February 2023

AbstractMetal‐organic framework (MOF) gel, an emerging subtype of MOF structure, is unique in formation and function; however, its evolutionary process remains elusive. Here, the evolution of a model gel‐based MOF, UiO‐66(Zr) gel, is explored by demonstrating its sequential sol‐gel self‐assembly and nonclassical gel‐crystal transformation. The control of the sol‐gel process enables the observation and characterization of structures in each assembly stage (phase‐separation, polycondensation, and hindered‐crystallization) and facilitates the preparation of hierarchical materials with giant mesopores. The gelation mechanism is tentatively attributed to the formation of zirconium oligomers. By further utilizing the pre‐synthesized gel, the nonclassical gel‐crystal transformation is achieved by the modulation in an unconventional manner, which sheds light on crystal intermediates and distinct crystallization motions (“growth and splitting” and “aggregation and fusion”). The overall sol‐gel and gel‐crystal evolutions of UiO‐66(Zr) enrich self‐assembly and crystallization domains, inspire the design of functional structures, and demand more in‐depth research on the intermediates in the future.
Activated FeS2@NiS2 Core–Shell Structure Boosting Cascade Reaction for Superior Electrocatalytic Oxygen Evolution
Authors: Zhang Lulu , Rong Ju , Yang Yongqiang , Zhu Huaze , Yu Xiaohua , Chen Chunlin , Cheng Hui‐Ming , Liu Gang 
Published: February 2023

AbstractUnlike single‐step reactions, multi‐step reactions can be greatly facilitated only if all the intermediate reactions can be catalyzed simultaneously and progressively. Herein, the theoretical analysis and experiments to illustrate the superiority of the cascade oxygen evolution reaction (OER) are conducted. As different OER intermediate reactions demand FexNi1‐xOOH with altered Fe/Ni ratios, gradient Fe‐doped NiOOH can be an ideal electrocatalyst for the efficient cascade OER in line. Fine controlling of the nucleation sequence of iron and nickel sulfides leads to a FeS2@NiS2 core–shell structure. The activated outward diffusion of Fe dopants results in the gradient Fe/Ni ratios in the FexNi1‐xOOH shell, where a cascade OER can happen. Electrochemical tests suggest that the FeS2@NiS2 only needs an overpotential of 237 mV to reach the current density of 10 mA cm−2, with fast reaction kinetics and good stability.
An end‐to‐end artificial intelligence platform enables real‐time assessment of superionic conductors
Authors: Wang Zhilong , Han Yanqiang , Cai Junfei , Chen An , Li Jinjin 
Published: February 2023

AbstractSuperionic conductors (SCs) exhibiting low ion migration activation energy (Ea) are critical to the performance of electrochemical energy storage devices such as solid‐state batteries and fuel cells. However, it is challenging to obtain Ea experimentally and theoretically, and the artificial intelligence (AI) method is expected to bring a breakthrough in predicting Ea. Here, we proposed an AI platform (named AI‐IMAE) to predict the Ea of cation and anion conductors, including Li+, Na+, Ag+, Al3+, Mg2+, Zn2+, Cu(2)+, F−, and O2−, which is ~105 times faster than traditional methods. The proposed AI‐IMAE is based on crystal graph neural network models and achieves a holistic average absolute error of 0.19 eV, a median absolute error of 0.09 eV, and a Pearson coefficient of 0.92. Using AI‐IMAE, we rapidly discovered 316 promising SCs as solid‐state electrolytes and 129 SCs as cathode materials from 144,595 inorganic compounds. AI‐IMAE is expected to completely solve the challenge of time‐consuming Ea prediction and blaze a new trail for large‐scale studies of SCs with excellent performance. As more experimental and high‐precision theoretical data become available, AI‐IMAE can train custom models and transfer the existing models to new models through transfer learning to constantly meet more demands.