Phase Engineered Composite Phase Change Materials for Thermal Energy Manipulation.

Phase change materials (PCMs) present a dual thermal management functionality through intrinsic thermal energy storage (TES) capabilities while maintaining a constant temperature. However, the practical application of PCMs encounters challenges, primarily stemming from their low thermal conductivity and shape-stability issues. Despite significant progress in the development of solid-solid PCMs, which offer superior shape-stability compared to their solid-liquid counterparts, they compromise TES capacity. Herein, a universal phase engineering strategy is introduced to address these challenges. The approach involves compositing solid-liquid PCM with a particulate-based conductive matrix followed by surface reaction to form a solid-solid PCM shell, resulting in a core-shell composite with enhanced thermal conductivity, high thermal storage capacity, and optimal shape-stability. The core-shell structure designed in this manner not only encapsulates the energy-rich solid-liquid PCM core but also significantly enhances TES capacity by up to 52% compared to solid-solid PCM counterparts. The phase-engineered high-performance PCMs exhibit excellent thermal management capabilities by reducing battery cell temperature by 15 °C and demonstrating durable solar-thermal-electric power generation under cloudy or no sunshine conditions. This proposed strategy holds promise for extending to other functional PCMs, offering a compelling avenue for the development of high-performance PCMs for thermal energy applications.

High-Efficiency Thermal-Shock Resistance Enabled by Radiative Cooling and Latent Heat Storage.

Radiative cooling technology is well known for its subambient temperature cooling performance under sunlight radiation. However, the intrinsic maximum cooling power of radiative cooling limits the performance when the objects meet the thermal shock. Here, a dual-function strategy composed of radiative cooling and latent heat storage simultaneously enabling the efficient subambient cooling and high-efficiency thermal-shock resistance performance is proposed. The electrospinning and absorption-pressing methods are used to assemble the dual-function cooler. The high sunlight reflectivity and high mid-infrared emissivity of radiative film allow excellent subambient temperature of 5.1 °C. When subjected the thermal shock, the dual-function cooler demonstrates a pinning effect of huge temperature drop of 39 °C and stable low-temperature level by isothermal heat absorption compared with the traditional radiative cooler. The molten phase change materials provide the heat-time transfer effect by converting thermal-shock heat to the delayed preservation. This strategy paves a powerful way to protect the objects from thermal accumulation and high-temperature damage, expanding the applications of radiative cooling and latent heat storage technologies.

A Novel Thermal Interface Material Composed of Vertically Aligned Boron Nitride and Graphite Films for Ultrahigh Through-Plane Thermal Conductivity.

The relentless drive toward miniaturization in microelectronic devices has sparked an urgent need for materials that offer both high thermal conductivity (TC) and excellent electrical insulation. Thermal interface materials (TIMs) possessing these dual attributes are highly sought after for modern electronics, but achieving such a combination has proven to be a formidable challenge. In this study, a cutting-edge solution is presented by developing boron nitride (BN) and graphite films layered silicone rubber composites with exceptional TC and electrical insulation properties. Through a carefully devised stacking-cutting method, the high orientation degree of both BN and graphite films is successfully preserved, resulting in an unprecedented through-plane TC of 23.7 Wm-1 K-1 and a remarkably low compressive modulus of 4.85 MPa. Furthermore, the exceptional properties of composites, including low thermal resistance and high resilience rate, make them a reliable and durable option for various applications. Practical tests demonstrate their outstanding heat dissipation performance, significantly reducing CPU temperatures in a computer cooling system. This research work unveils the possible upper limit of TC in BN-based TIMs and paves the way for their large-scale practical implementation, particularly in the thermal management of next-generation electronic devices.

Deep autoencoder based domain adaptation for transfer learning.

The concept of transfer learning has received a great deal of concern and interest throughout the last decade. Selecting an ideal representational framework for instances of various domains to minimize the divergence among source and target domains is a fundamental research challenge in representative transfer learning. The domain adaptation approach is designed to learn more robust or higher-level features, required in transfer learning. This paper presents a novel transfer learning framework that employs a marginal probability-based domain adaptation methodology followed by a deep autoencoder. The proposed frame adapts the source and target domain by plummeting distribution deviation between the features of both domains. Further, we adopt the deep neural network process to transfer learning and suggest a supervised learning algorithm based on encoding and decoding layer architecture. Moreover, we have proposed two different variants of the transfer learning techniques for classification, which are termed as (i) Domain adapted transfer learning with deep autoencoder-1 (D-TLDA-1) using the linear regression and (ii) Domain adapted transfer learning with deep autoencoder-2 (D-TLDA-2) using softmax regression. Simulations have been conducted with two popular real-world datasets: ImageNet datasets for image classification problem and 20_Newsgroups datasets for text classification problem. Experimental findings have established and the resulting improvements in accuracy measure of classification shows the supremacy of the proposed D-TLDA framework over prominent state-of-the-art machine learning and transfer learning approaches.

Interval type-2 fuzzy logic system based similarity evaluation for image steganography.

Similarity measure, also called information measure, is a concept used to distinguish different objects. It has been studied from different contexts by employing mathematical, psychological, and fuzzy approaches. Image steganography is the art of hiding secret data into an image in such a way that it cannot be detected by an intruder. In image steganography, hiding secret data in the plain or non-edge regions of the image is significant due to the high similarity and redundancy of the pixels in their neighborhood. However, the similarity measure of the neighboring pixels, i.e., their proximity in color space, is perceptual rather than mathematical. Thus, this paper proposes an interval type-2 fuzzy logic system (IT2 FLS) to determine the similarity between the neighboring pixels by involving an instinctive human perception through a rule-based approach. The pixels of the image having high similarity values, calculated using the proposed IT2 FLS similarity measure, are selected for embedding via the least significant bit (LSB) method. We term the proposed procedure of steganography as 'IT2 FLS-LSB method'. Moreover, we have developed two more methods, namely, type-1 fuzzy logic system based least significant bits (T1FLS-LSB) and Euclidean distance based similarity measures for least significant bit (SM-LSB) steganographic methods. Experimental simulations were conducted for a collection of images and quality index metrics, such as PSNR (peak signal-to-noise ratio), UQI (universal quality index), and SSIM (structural similarity measure) are used. All the three steganographic methods are applied on dataset and the quality metrics are calculated. The obtained stego images and results are shown and thoroughly compared to determine the efficacy of the IT2 FLS-LSB method. We have also demonstrated the high payload capacity of our proposed method. Finally, we have done a comparative analysis of the proposed approach with the existing well-known steganographic methods to show the effectiveness of our proposed steganographic method.

Evaluation and management of acquired methemoglobinemia associated with topical benzocaine use.

Benzocaine is a widely used topical oropharyngeal anesthetic and has been reported to cause methemoglobinemia. We discuss benzocaine-induced methemoglobinemia and review the causes, presentation, and management of this serious complication. Treatment with methylene blue will result in reversal of methemoglobinemia and clinical recovery in most cases but needs to be used at appropriate doses in carefully selected individuals. Physicians who perform procedures involving the application of benzocaine for topical anesthesia need to rapidly identify and treat methemoglobinemia to avoid significant associated morbidity and mortality.

Conservative management of post-transplant central nervous system lymphoma.

Primary CNS lymphoma (PCNSL) is a rare B cell variant non-Hodgkins lymphoma that is confined to the brain, leptomeninges, spinal cord and eyes. Its incidence is increasing, primarily due to increase in the number of organ transplantations being undertaken. The majority of the PTLD (post-transplant lymphoproliferative disorder) is seen in kidney transplant recipients simply because they constitute a larger group of transplant recipients each year as compared to other solid organ transplantations. Primary infection of previously infected EBV seronegative patients and immunosuppression are found to be the main etiologic factors in the development of PTLD-PCNSL. There are no clear guidelines on treatment regimens, and it should be individualized according to patient comorbidities. We report a case of PCNS lymphoproliferative disorder in a kidney transplant recipient, which underwent complete remission with decreasing immunosuppression. The patient could not undergo chemotherapy/radiotherapy due to underlying comorbidities. We highlight the available treatment modalities for PTLD-PCNSL.