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Interface issues between cathode and electrolyte in sulfide-based all-solid-state lithium batteries and improvement strategies of interface performance through cathode modification
Get PDFSulfide electrolyte-based all-solid-state lithium batteries (ASSLB) are heralded as a cornerstone for next-generation energy storage solutions, distinguished by their exceptional ionic conductivity, superior energy density, and enhanced safety features. Nonetheless, the ascendancy of sulfide-based ASSLB in augmenting energy density and elongating cycle life is curtailed by the suboptimal solid-solid interfacial contact and the compromised chemical/electrochemical stability of both the cathode and the sulfide solid electrolyte (SSE). This review dissects the quintessential challenges at the cathode-SSE interface, elucidating the underlying mechanisms contributing to elevated interfacial resistance, the formation of space charge layers, and interfacial compatibility dilemmas. It addresses the primary challenges at the cathode-SSE interface, highlighting the mechanisms behind increased interfacial resistance, chemical/electrochemical instability, and poor interfacial compatibility. It systematically explores strategies to improve the interface, including microstructure regulation, coating cathode, synthesis modification, and other treatments. Finally, it summarizes the development prospects and improvement methods of sulfide-based ASSLB.</p
Bed census prediction combining expert opinion and patient statistics
Get PDFPredictions of bed census are crucial for hospital capacity management choices, encompassing ward sizing, staffing, patient bed assignments, and surgical scheduling. Presently, these predictions heavily rely on doctors’ estimated Expected Discharge Date (EDD). This paper introduces two probabilistic models that integrate EDD with Length of Stay (LoS) distributions derived from data. By employing the Poisson binomial distribution and probabilistic convolution, we generate full census distributions. Applying our approach to real hospital data demonstrates its ability to provide precise predictions, leading to valuable managerial insights.</p
Evaluating sensor performance for impact identification in composites: a comprehensive comparison of FBGs with PZTs
Get PDFAerospace composite components require effective monitoring techniques to detect possible internal damage from impact events. To ensure reliable impact identification, sensor measurements can provide valuable information about impact energy and identify potential issues that may require further investigation. However, selecting the most appropriate sensor technology to measure impact force and energy is a challenge. In this article, a systematic and structured approach is presented to compare the expected performance of sensors and their metrological parameters in terms of their ability for impact identification in aerospace composites. The proposed methodology is demonstrated using an application example where fibre Bragg grating (FBG) are compared with piezoelectric (PZT) sensors through comprehensive tests. These tests include the correlation test, the sensitivity test, and the factor test. The correlation test showed a high agreement between FBG and PZT sensors in the time and frequency domain. The sensitivity test indicated a significant correlation between the signal features and the impact energy levels in the energy profiling diagrams, revealing nonlinearities and energy losses indicative of damage. Furthermore, these results emphasise the superior resolution of the FBG sensors and the comparable repeatability of the two sensor types. Finally, the factor test showed that FBG sensors are sensitive to different angles of incidence, while PZT sensors have a more stable directivity. Further analysis also showed that the signal strength of both sensor types decreases with increasing distance from the impact source. Overall, the proposed approach enables a thorough evaluation of the capabilities and limitations of both sensor types. Consequently, it provides information to make an informed decision on the most suitable sensor for impact monitoring systems
Working toward Personalized Intervention Advice:A Survey Study on Preference Heterogeneity in Patients with Breast Cancer–Related Fatigue
Get PDFIntroduction: Many breast cancer survivors experience cancer-related fatigue (CRF), and several interventions to treat CRF are available. One way to tailor intervention advice is based on patient preferences. In this study, we explore preference heterogeneity regarding between-attribute and within-attribute preferences. In addition, we propose simple decision rules to match preferences to interventions.Methods: Nine attributes were included with dichotomized levels. Participants selected their preferred level per attribute and ranked the attributes using best-worst scaling. Between-attribute and within-attribute preferences were determined, together with their heterogeneity. Using decision rules, matching scores were calculated for a hypothetical intervention.Results: Sixty-seven breast cancer survivors completed the survey. They were on average 52 y old, 4.5 y after diagnosis, experienced CRF (6.5–7.2/10) on 3 dimensions (physical, mental, and emotional), and 43% already followed an intervention for CRF. Overall, participants ranked costs highest. Next to costs, proveneffectiveness and type of intervention were also frequently ranked first. Only 13 participants (19%) shared the most common preference pattern of shorter interventions, daily sessions, shorter session time, a psychosocial intervention, no anonymity, and contact with a therapist and peers. Matching scores for a hypothetical intervention with attributes corresponding with the overall within-attribute preferences varied from 44% to 100%.Conclusion: A large heterogeneity in preferences of breast cancer survivors for CRF intervention attributes was demonstrated. Using simple decision rules, the effect of this heterogeneity on linking preferences to interventions with matching scores was demonstrated. Implications. Personalization of intervention advice is necessary due to preference heterogeneity. Tailored advice can result in higher involvement of patients in decision making, intervention adherence and satisfaction, and subsequently a potential higher quality of life after breast cancer. Many breast cancer survivors experience cancer-related fatigue for which many interventions exist. Our results show large preference heterogeneity in breast cancer patients’ preferences for attributes of eHealth interventions. Based on this preference heterogeneity, intervention advice for cancer-related fatigue after breast cancer can be personalized, ultimately improving quality of life after breast cancer.</p
Suppressed degradation by stabilizers during mixing of silica/silane-filled natural rubber
Get PDFAging antioxidants and processing stabilizers, i.e., quinoline (TMQ) and phenylenediamine (6PPD) derivatives, a radical chain terminator (TEMPO), a phenylphosphite (TBPP) and a hydroxyphenylpropionate (PTBHPP) derivative, were considered potential degradation suppressors during mixing for silica-reinforced Natural Rubber (NR) compounds. Thus, the influences of these stabilizers on rubber degradation during mixing were investigated. Results show that TMQ and 6PPD give higher viscosities and larger elastic responses compared to the reference compound, attributed to their ability to suppress rubber degradation during compounding leading to maintained molecular weight. Additionally, these two antioxidants enhance filler-rubber interaction due to a boosting effect on the reaction between silane and rubber. TEMPO appears to terminate chain radicals of rubber during mixing, leading to permanent breakdown of the chains and so lower molecular weight. TBPP does not work in this system as its melting point is higher than the mixing temperature. Results from a model compound study suggest that TMQ slightly reduces the silanization efficiency in the compounds, while other stabilizers do not intervene. However, this interference does not give an adverse effect to the final properties. A practical silica-filled NR compound containing a blend of TMQ/6PPD shows improved mechanical properties of the vulcanizates, highlighting the essential role of these antioxidants added during mixing to suppress rubber degradation. PTBHPP does not noticeably help in preventing rubber degradation during mixing, but it provides a significant positive effect on long term aging stability.</p
SIRE:Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks
Get PDFThe orientation of a blood vessel as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation, labeling, and visualization. Blood vessels appear at multiple scales and levels of tortuosity, and determining the exact orientation of a vessel is a challenging problem. Recent works have used 3D convolutional neural networks (CNNs) for this purpose, but CNNs are sensitive to variations in vessel size and orientation. We present SIRE: a scale-invariant rotation-equivariant estimator for local vessel orientation. SIRE is modular and has strongly generalizing properties due to symmetry preservations. SIRE consists of a gauge equivariant mesh CNN (GEM-CNN) that operates in parallel on multiple nested spherical meshes with different sizes. The features on each mesh are a projection of image intensities within the corresponding sphere. These features are intrinsic to the sphere and, in combination with the gauge equivariant properties of GEM-CNN, lead to SO(3) rotation equivariance. Approximate scale invariance is achieved by weight sharing and use of a symmetric maximum aggregation function to combine predictions at multiple scales. Hence, SIRE can be trained with arbitrarily oriented vessels with varying radii to generalize to vessels with a wide range of calibres and tortuosity. We demonstrate the efficacy of SIRE using three datasets containing vessels of varying scales; the vascular model repository (VMR), the ASOCA coronary artery set, and an in-house set of abdominal aortic aneurysms (AAAs). We embed SIRE in a centerline tracker which accurately tracks large calibre AAAs, regardless of the data SIRE is trained with. Moreover, a tracker can use SIRE to track small-calibre tortuous coronary arteries, even when trained only with large-calibre, non-tortuous AAAs. Additional experiments are performed to verify the rotational equivariant and scale invariant properties of SIRE. In conclusion, by incorporating SO(3) and scale symmetries, SIRE can be used to determine orientations of vessels outside of the training domain, offering a robust and data-efficient solution to geometric analysis of blood vessels in 3D medical images.</p
Cu-based transparent conductive materials with enhanced conductivity
Get PDFTransparent conductive materials (TCMs) are a unique class of semiconductors that combine optical transparency with electronic conductivity, making them critical components in various electronic devices, such as solar cells, touchscreens, displays, transistors, and smart windows. While n-type TCMs have seen significant technological advancements and widespread use, the performance of p-type TCMs lags behind, primarily due to their low electrical conductivity. This disparity poses a significant barrier to the development of fully transparent electronic systems. In this thesis, we explore innovative doping strategies to enhance the p-type conductivity of copper iodide, a wide bandgap semiconductor. The first two sections focus on the roles of sulfur and cesium as dopants, using a range of structural and optoelectronic characterization techniques. Our findings reveal that these elements act as indirect dopants, facilitating favorable growth conditions that promote native defect formation, which enhances conductivity. These unconventional dopants will inspire further exploration of new doping strategies for p-type TCMs. In the final section, we present ultra-thin p-type copper sulfide as a promising alternative to indium oxide-based n-type TCMs in photovoltaic applications. This approach demonstrates the potential for integrating narrow bandgap, high-conductivity p-type TCMs into transparent electronic systems. Our work provides a foundation for reimagining the role of p-type TCMs and encourages future research into novel applications and materials in this field
Revealing the strain rate-dependent asymmetric deformation mechanisms of TWIP steel by crystal plasticity modeling
Get PDFIn this study, the strain rate-dependent tension-compression asymmetric (TCA) plastic behavior of twinning-induced plasticity (TWIP) steel is investigated by developing a dislocation density-based crystal plasticity model. This model incorporates strain rate effects on dislocation mechanisms, with particular emphasis on the interactions between different types of dislocations and twins. By integrating the crystal plasticity finite element (CPFE) model with experimental tests, the TCA plastic behavior of TWIP steel and the underlying micro-mechanisms were systematically explored. The study reveals that, with random initial crystal orientations, TWIP steel exhibits a higher flow stress during compression than tension. Moreover, dynamic loading, compared to quasi-static loading, exacerbates the difference between compression and tension. The TCA plastic behavior is primarily attributed to differences in texture evolution under varying loading conditions. A quantitative analysis was further conducted to examine the influence of back stress, dislocation-twin boundaries (TB) interactions, twining mechanisms, and initial texture on strain rate-dependent TCA plastic behavior. Our findings show that, when back stress and the influence of dislocation types in dislocation-TB interactions are excluded, the stress levels during tensile and compressive deformation under quasi-static loading are nearly identical. Similarly, when twinning mechanisms are not considered, the stress difference between tensile and compressive deformation under quasi-static and dynamic loading is minimal
A Capacitive Stacking Mixer-First Receiver With Higher Order Capacitive Feedback
Get PDFThis article presents a capacitive stacking mixer-first receiver (MF-RX) with a higher order capacitive feedback (CFB) loop designed to increase interferer rejection right at the mixer baseband (BB) node, benefiting both the out-of-band (OOB) linearity of the passive mixer switches and the active BB circuitry. The CFB loop consists of a left-half-plane (LHP) and right-half-plane (RHP) zero together with an OOB complex pole pair so as to transition in-band (IB) positive feedback into stronger OOB negative feedback, resulting in a steep closed-loop (CL) filtering slope of -15 dB/octave. Using a normalized BB model, the CFB loop is implemented on the system level while a dual-path approach is introduced to map the system to the schematic level. A prototype of the MF-RX is realized in 22-nm fully depleted silicon-on-insulator (FDSOI) technology and achieves an adjacent-channel third-order intercept point (IIP3) of over 18 dBm across the wide 1.2–7.2-GHz local oscillator (LO) range as a direct result of the improved selectivity. The design achieves a channel bandwidth (BW) of 40 MHz, while the total radio frequency (RF)-to-BB gain is 32 dB. The 2× passive voltage gain of the capacitive stacking MF-RX enables a static power consumption of 9.7 mW at a minimum double sideband (DSB) noise figure (NF) varying from 5.1 to 9.0 dB across the LO range
