Hasil untuk "Materials Science"

Lokesh D Shah, S. Gulhane

Transparent electronics is an emerging science and technology field concentrates on producing ‘invisible’ electronics circuit and optoelectronics devices. The application contains consumer electronics such as automobile windshield, transparent solar panel, transparent display and real time wearable display. In the conventional Si/III-V based electronics, the structure is based on semiconductor junction & transistor. However, the basic building material for transparent electronic devices which is to be transparent and in visible range is a true challenge! .Therefore to understand and implement such technology there are two scientific goals, to have a material which are optically transparent and electrically conductive and to implement an invisible circuitry. Development of such invisible transparent electronic devices needs expertise together from pure and applied science, material science, chemistry, physics &electronic science.

Ashka Vakil, N. Engheta

M. Jamshidian, E. Tehrany, Muhammad Imran et al.

N. Grimm, S. Faeth, N. Golubiewski et al.

D. Thilikos

S. Star

X. Gonze, J. Beuken, R. Caracas et al.

Douglas C. Runger

A. Da̧browski

T. Cummings, C. Worley

D. Bobrow, A. Collins

J. Haygreen, J. Bowyer

S. Feng, Da Xu

D. Stefanescu

A. Pickering

Yang Fu, Yuanxin Ge, Shixiong Yi et al.

Abstract Curcumin, a natural polyphenol derived from Curcuma longa, exhibits potent multimodal anticancer activity by modulating critical oncogenic pathways (e.g., NF-κB, STAT3, PI3K/Akt/mTOR), inducing apoptosis, suppressing angiogenesis, and reversing multidrug resistance (MDR). However, its clinical translation is severely hindered by poor aqueous solubility, rapid metabolism, and negligible oral bioavailability (typically <1% in serum), which result in subtherapeutic concentrations at tumor sites. Smart nanoparticle delivery systems have emerged as a transformative strategy to overcome these limitations, enabling enhanced solubility, controlled release, and targeted accumulation in tumors. This review comprehensively summarizes the advancements in curcumin-loaded nanocarriers, including polymeric nanoparticles (e.g., PLGA, chitosan), lipid-based systems (e.g., liposomes, NLCs), inorganic nanoparticles (e.g., mesoporous silica, gold nanoparticles), and stimuli-responsive platforms (pH-, redox-, enzyme-sensitive). These nanosystems leverage passive targeting via the enhanced permeability and retention (EPR) effect and active targeting through ligand conjugation (e.g., folate, transferrin, hyaluronic acid), significantly improving tumor-specific delivery and curcumin’s bioavailability—exemplified by a 178-fold increase in plasma AUC in healthy human volunteers following oral administration of the co-grinding formulation CUMINUP60® compared to standard crystalline curcumin. Preclinical and clinical studies demonstrate that nanoformulated curcumin synergizes with conventional chemo/radiotherapy, sensitizes resistant cancers, and modulates the immunosuppressive tumor microenvironment. For instance, Phase I/II trials indicate that formulations like nanomicellar curcumin (Sinacurcumin®) can modulate inflammatory cytokines, while liposomal variants (Lipocur™) have shown target engagement in metastatic cancers, albeit with the need for dose optimization. Hybrid nanocarriers co-delivering curcumin with chemotherapeutics or siRNA further augment therapeutic outcomes in models of colorectal, breast, pancreatic, and glioblastoma cancers. Despite these progresses, the gap between preclinical success and clinical translation remains significant. This review critically analyzes the barriers impeding commercialization, specifically highlighting the heterogeneity of the EPR effect, the lack of scalable GMP-compliant manufacturing for complex nanocarriers, and the regulatory hurdles regarding long-term biocompatibility and safety assessments. Graphical Abstract

Marcela Elisabeth Penoff, Facundo Ignacio Altuna, Luis Alejandro Miccio

In this study, we employ machine learning techniques to improve materials in data scarcity conditions. In particular, we focus on the prediction of the cloud point temperatures of polymer–water systems with thermoresponsive behavior. We compare a model trained directly on the available data with a model based on representations learned through an encoder–decoder model, in turn pre-trained on a larger dataset to generate molecular fingerprints. Our results demonstrate that the embedding-based model significantly outperforms the direct model in predicting the cloud point temperature under the data limitations imposed by rigorous curation. This approach highlights the potential of domain-informed representation learning to tackle complex materials science problems with limited data.

J. Osborne, Susan Collins

Gururaja Udupa, S. Shrikantha Rao, K.V. Gangadharan

Yaozhou Xie, Zhi Wang, Hangyu Dong et al.

This study systematically investigates the annealing temperature-dependent microstructural evolution and strengthening mechanisms in a cold-rolled (50 % reduction) high-manganese TWIP steel (0.4C-23.8Mn-0.2Si-3.7Cr-0.5Cu). EBSD and TEM analyses reveal that annealing at 600 °C triggers preferential recrystallization nucleation along deformation twin interfaces, generating a bimodal lamellar heterostructure (1.32 ± 1.98 μm) characterized by fine recrystallized grains and recovered coarse grains. This bimodal distribution arises from divergent growth kinetics, where recrystallized grains nucleate while recovered grains coarsen, evidenced by a sharp decline in Σ3 boundary fraction (51.5 % → 38.6 %) with minimal change in grain orientation spread (7.08° → 5.98°). The heterostructure enables synergistic strengthening via hetero-deformation-induced (HDI) hardening at hetero-zone boundaries, which alleviates stress concentration and delays strain localization. Consequently, the 600 °C annealed sample achieves an optimal strength-ductility balance (yield strength: 1051 MPa, total elongation: 22 %), superior to samples annealed at other temperatures (400–800 °C). Nanoindentation analysis further quantifies substructure contributions, confirming dislocation-dominated hardening in nucleation-stage microstructures and validating the inadequacy of conventional Hall-Petch models for heterogeneous systems. The work establishes annealing at 600°C-700 °C as critical for activating bimodal lamellar heterostructures, providing a mechanistic framework to overcome strength-ductility trade-offs in TWIP steels.