Materials Today Advances最新文献_第4页

Endosomal escape in magnetic nanostructures: Recent advances and future perspectives 磁性纳米结构中的内体逃逸：最新进展与未来展望

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-03-21 DOI: 10.1016/j.mtadv.2024.100484

Shubhangi D. Shirsat, Prajkta V. Londhe, Ashwini P. Gaikwad, Muhammad Rizwan, Suvra S. Laha, Vishwajeet M. Khot, Varenyam Achal, Tanveer A. Tabish, Nanasaheb D. Thorat

{"title":"Endosomal escape in magnetic nanostructures: Recent advances and future perspectives","authors":"Shubhangi D. Shirsat, Prajkta V. Londhe, Ashwini P. Gaikwad, Muhammad Rizwan, Suvra S. Laha, Vishwajeet M. Khot, Varenyam Achal, Tanveer A. Tabish, Nanasaheb D. Thorat","doi":"10.1016/j.mtadv.2024.100484","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100484","url":null,"abstract":"Several evolving therapies depend on the delivery of therapeutic cargo into the cytoplasm. Engineered magnetic nanoparticles (MNPs) have played a pivotal role in advancing and modernizing cancer theranostics, vaccination and gene therapies. The main advantages of MNP-based delivery approaches are due to their potential to decrease the side effects by targeting specific cell types, shielding delicate therapeutics from early degradation, increasing the solubility of hard-to-deliver drugs and long-sustained and precise release of these drugs. Like other nanoparticles (NPs), MNPs enter cells by endocytosis and are frequently stuck inside endocytic vesicles, which mature into early and late endosomes and accumulate in the lysosome. Endocytosed MNPs are ultimately degraded in lysosomes or recycled towards the cell membrane. Thereby, they must escape endocytic vesicles on a priority basis. Endosomal escape is highly important for the effectiveness of nanoparticle-based treatments. This review is concerned with the use of magnetic nanoparticles (MNPs) as functional nano-objects to enhance the therapeutic effects by disrupting or rupturing the endocytic vesicles in terms of endosomal escape. The current strategies and future challenges concerning an efficient endosomal escape of MNPs are discussed in this review.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"66 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140314089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Crystal growth characterization of WSe2 thin film using machine learning 利用机器学习分析 WSe2 薄膜的晶体生长特征

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-03-19 DOI: 10.1016/j.mtadv.2024.100483

Isaiah A. Moses, Chengyin Wu, Wesley F. Reinhart

{"title":"Crystal growth characterization of WSe2 thin film using machine learning","authors":"Isaiah A. Moses, Chengyin Wu, Wesley F. Reinhart","doi":"10.1016/j.mtadv.2024.100483","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100483","url":null,"abstract":"Materials characterization remains a labor-intensive process, with a large amount of expert time required to post-process and analyze micrographs. As a result, machine learning has become an essential tool in materials science, including for materials characterization. In this study, we perform an in-depth analysis of the prediction of crystal coverage in WSe thin film atomic force microscopy (AFM) height maps with supervised regression and segmentation models. Regression models were trained from scratch and through transfer learning from a ResNet pretrained on ImageNet and MicroNet to predict monolayer crystal coverage. Models trained from scratch outperformed those using features extracted from pretrained models, but fine-tuning yielded the best performance, with an impressive 0.99 value on a diverse set of held-out test micrographs. Notably, features extracted from MicroNet showed significantly better performance than those from ImageNet, but fine-tuning on ImageNet demonstrated the reverse. As the problem is natively a segmentation task, the segmentation models excelled in determining crystal coverage on image patches. However, when applied to full images rather than patches, the performance of segmentation models degraded considerably, while the regressors did not, suggesting that regression models may be more robust to scale and dimension changes compared to segmentation models. Our results demonstrate the efficacy of computer vision models for automating sample characterization in 2D materials while providing important practical considerations for their use in the development of chalcogenide thin films.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"39 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140199186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-temperature oxidation behaviors of Co-free Cr30Fe30Ni30Al5Ti5 dual-phase multi-component alloys with multi-scale nanoprecipitates 具有多尺度纳米沉淀物的无钴 Cr30Fe30Ni30Al5Ti5 双相多组分合金的高温氧化行为

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-03-16 DOI: 10.1016/j.mtadv.2024.100482

Qingwei Gao, Yingying Wang, Jianhong Gong, Changshan Zhou, Jiyao Zhang, Xiaoming Liu, Junlei Tang, Pingping Liu, Xiangyan Chen, Dong Chen, Wenquan Lv, Konda Gokuldoss Prashanth, Kaikai Song

{"title":"High-temperature oxidation behaviors of Co-free Cr30Fe30Ni30Al5Ti5 dual-phase multi-component alloys with multi-scale nanoprecipitates","authors":"Qingwei Gao, Yingying Wang, Jianhong Gong, Changshan Zhou, Jiyao Zhang, Xiaoming Liu, Junlei Tang, Pingping Liu, Xiangyan Chen, Dong Chen, Wenquan Lv, Konda Gokuldoss Prashanth, Kaikai Song","doi":"10.1016/j.mtadv.2024.100482","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100482","url":null,"abstract":"In the context of the growing research interest in multi-component alloys (MAs) and their exceptional performance under extreme environments, the high-temperature oxidation resistance and applications of MAs have attracted significant attention in the field of metallic materials. While the cost-effective and mechanical properties of Co-free MAs are of great importance, their oxidation resistance remains insufficiently understood. In this work, we designed multiple heterogeneous structures within a cast dual-phase CrFeNiAlTi MA by tailoring the Al and Ti ratio, which consists of body-centered-cubic (BCC) grains reinforced by multi-scale nanoprecipitates (i.e., L2, B2, and phase) and an L1-strengthened face-centered cubic (FCC) skeleton. Isothermal oxidation experiments at 800 °C, 1000 °C, and 1200 °C with varying exposure durations were conducted. The oxidation kinetics at 800 °C and 1000 °C followed a parabolic law, while both low weight increment and oxidation rate confirm remarkable oxidation resistance. At 800 °C, the oxides mainly consist of CrO and AlO, while are dominated by (TiO + CrO) and the mixed oxides of AlO, TiO and TiO above 1000 °C. Importantly, the inability to form a continuous AlO oxide scale at higher temperatures led to a deterioration in oxidation resistance. These findings offer valuable insights into underlying mechanisms contributing to oxidation resistance for Co-free MAs.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"142 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140198869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Copper–zinc oxide heterostructure photocathodes for hydrogen and methanol production 用于制氢和制甲醇的铜锌氧化物异质结构光阴极

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-03-06 DOI: 10.1016/j.mtadv.2024.100477

Tomasz Baran, Szymon Wojtyła, Marco Scavini, Francesco Carlà, Edmund Welter, Roberto Comparelli, Angela Dibenedetto, Michele Aresta

引用次数: 0

Toward fast and accurate machine learning interatomic potentials for atomic layer deposition precursors 为原子层沉积前驱体实现快速准确的机器学习原子间势能

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-03-01 DOI: 10.1016/j.mtadv.2024.100474

Seungpyo Kang, Joonchul Kim, Taehyun Park, Joonghee Won, Chul Baik, Jungim Han, Kyoungmin Min

{"title":"Toward fast and accurate machine learning interatomic potentials for atomic layer deposition precursors","authors":"Seungpyo Kang, Joonchul Kim, Taehyun Park, Joonghee Won, Chul Baik, Jungim Han, Kyoungmin Min","doi":"10.1016/j.mtadv.2024.100474","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100474","url":null,"abstract":"Under thin film deposition, when used in conjunction with the semiconductor atomic layer deposition (ALD) method, the choice of precursor determines the properties and quality of the thin film. Organometallic precursors such as alkaline earth metals (Sr and Ba) and group 4 transition metals (Zr and Hf) with cyclopentadienyl and tetrakis (ethylmethylamino) ligands have recently gained attention for their stable deposition within high-temperature windows in the ALD. The design of organometallic precursors with an molecular dynamics (AIMD) simulations-based approach ensures high accuracy but comes with significant computational costs. In this study, we aim to develop a machine-learning interatomic potential (MLIP) through moment tensor potential (MTP) for fast and accurate potential development of Sr, Ba, Zr, and Hf precursors. To establish the reliable training database for MTP construction, we conducted AIMD simulations on each precursor across a range of temperature settings, resulting in a variety of atomic structures. Constructed MTPs enable efficient utilization of molecular dynamics (MD) simulations as well as calculations that achieve an accuracy that approximates density functional theory (DFT). MTP construction coupled with active learning ensures that the MTP for each precursor is reliable and that databases can be expanded. High prediction accuracy is demonstrated by a mean absolute error (MAE) of less than 0.04 eV/atom in all structures. In addition, generalization performance is confirmed for general structures (structures with the same chemical elements but different proportions) and is extended to cluster structures. The constructed MTP exhibits an MAE of less than 0.15 eV/atom, even for untrained cluster structures. These results demonstrate adequate representation and scalability as a basis for the development of MLIPs capable of atomic simulations of organometallic precursors under various thermodynamic conditions.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"104 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140045938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dielectric interface engineering using aminosilane coupling agent for enhancement of negative differential resistance phenomenon 使用氨基硅烷偶联剂进行介电界面工程，以增强负差分电阻现象

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-02-28 DOI: 10.1016/j.mtadv.2024.100475

Kyu Hyun Han, Seung-Geun Kim, Seung-Hwan Kim, Jong-Hyun Kim, Seong-Hyun Hwang, Min-Su Kim, Sung-Joo Song, Hyun-Yong Yu

{"title":"Dielectric interface engineering using aminosilane coupling agent for enhancement of negative differential resistance phenomenon","authors":"Kyu Hyun Han, Seung-Geun Kim, Seung-Hwan Kim, Jong-Hyun Kim, Seong-Hyun Hwang, Min-Su Kim, Sung-Joo Song, Hyun-Yong Yu","doi":"10.1016/j.mtadv.2024.100475","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100475","url":null,"abstract":"Negative differential resistance (NDR) devices have recently attracted interest as multi-valued logic (MVL) circuits, owing to their folded electrical characteristics. However, with necessity of sophisticated computing systems, advanced NDR devices are required for stable low-power-consumption MVL circuits. Here, we developed van der Waals (vdW) NDR device with high peak-to-valley current ratio (PVCR) and low peak voltage (V), utilizing the passivation and doping effects of APTES layer as aminosilane coupling agent, at dielectric interface. The PVCR of NDR device reached 10 through reduced interface trap owing to the passivation effect of APTES silane group. Additionally, low V of NDR device was achieved at 0.2 V through doping effect of the APTES amine group. These PVCR and V values indicate the one of the best vdW NDR performance. Furthermore, stable logic state and low operation voltage of the ternary inverter were implemented using NDR device with high PVCR and low V. This NDR device represents a significant advancement for next-generation MVL technologies.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"66 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140046186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Additively manufactured flexible piezoelectric lead zirconate titanate-nanocellulose films with outstanding mechanical strength, dielectric and piezoelectric properties 具有出色机械强度、介电和压电特性的锆钛酸铅-纳米纤维素叠加制造柔性压电薄膜

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-02-27 DOI: 10.1016/j.mtadv.2024.100478

Muhammad Latif, Yangxiaozhe Jiang, Jaehwan Kim

{"title":"Additively manufactured flexible piezoelectric lead zirconate titanate-nanocellulose films with outstanding mechanical strength, dielectric and piezoelectric properties","authors":"Muhammad Latif, Yangxiaozhe Jiang, Jaehwan Kim","doi":"10.1016/j.mtadv.2024.100478","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100478","url":null,"abstract":"Nanocellulose (NC)-based piezoelectric films prepared via solution casting show low mechanical, dielectric, and piezoelectric performance due to the randomly oriented cellulose nanofibers and dispersion of piezoelectric domains. Moreover, a high electric field for piezoelectric domain alignment may also increase the brittleness of the piezoelectric films. For the first time, an additive manufacturing (AM) technology is demonstrated to fabricate high mechanical strength and flexible NC-based piezoelectric films efficiently. Different concentrations (10, 20, and 30 wt%) of lead zirconate titanate (PZT) particles are mixed in the NC suspension and additively manufactured, followed by drying at cleanroom conditions. Next, the magnetically induced electric field is introduced into the PZT-NC films coated with silver electrodes. The obtained flexible piezoelectric PZT-NC films show outstanding mechanical strength of 203.5 ± 4.8 MPa, good flexibility, high dielectric constant (87.7 at 1 kHz), low dielectric loss (0.09 at 1 kHz), and high piezoelectric constant (d = 53 pC/N). Furthermore, the 30PZT-NC piezoelectric nanogenerator showed a peak-to-peak voltage of 2.24 V and an output power density of 1.56 μW/cm. The measured mechanical, dielectric, and piezoelectric properties are superior to the previously reported NC-based piezoelectric and commercially available PVDF films. Based on the outstanding multifunctional properties of NC-based piezoelectric films, AM technology can replace traditional solution casting methods and open a wide range of applications in flexible piezoelectric materials.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"19 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140006950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Irreversible pressure effect on phase transitions and bandgap narrowing of layered MoO3 压力对层状氧化钼相变和带隙变窄的不可逆影响

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-02-23 DOI: 10.1016/j.mtadv.2024.100476

Shixia Wang, Yalin Wang, Tao Liu, Lu Wang, Yuxuan Huang, Yang Lu

引用次数: 0

Naturally derived electrically active materials for eco-friendly electronics 用于环保电子产品的天然电活性材料

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-02-17 DOI: 10.1016/j.mtadv.2024.100470

Busra Ozlu, Mohammad Boshir Ahmed, Ruth M. Muthoka, Zuwang Wen, Yechan Bea, Ji Ho Youk, Yongjin Lee, Myung Han Yoon, Bong Sup Shim

引用次数: 0

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network 电子显微镜的新范例：利用动态分割卷积中性网络自动分析微观结构

IF 1 2区材料科学

Materials Today Advances Pub Date : 2024-02-08 DOI: 10.1016/j.mtadv.2024.100468

Stephen Taller, Luke Scime, Ty Austin

{"title":"A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network","authors":"Stephen Taller, Luke Scime, Ty Austin","doi":"10.1016/j.mtadv.2024.100468","DOIUrl":"https://doi.org/10.1016/j.mtadv.2024.100468","url":null,"abstract":"Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.","PeriodicalId":48495,"journal":{"name":"Materials Today Advances","volume":"4 1","pages":""},"PeriodicalIF":10.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139924670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0