Nano Letters最新文献

Altermagnets, due to spontaneous spin splitting induced by the breaking of the PT inversion symmetry, are now widely used in the design of novel antiferromagnetic (AFM) spintronic devices. Herein, we demonstrate symmetry breaking in AFM via slip and strain engineering, achieving a non-alter spin splitting compensated magnet. As a demo concept, a four-layer sliding strategy in GdI₂ is put forward, enabling sliding-induced ferroelectric (FE) and magnetic switching. The FE polarization breaks PT symmetry, inducing spin-split band structures that drive AFM to ferromagnetic (FM) phase transformation or nonrelativistic spin-splitting (NRSS) AFM. The designed multiferroic tunnel junction demonstrates electric-field-controlled four-state resistance switching with low resistance area. The regulation effect of strain on the device's transport properties has also been simulated. The compressive strain enhances the crystal symmetry in the FE-FM phase, triggering an FM-NRSS-mediated AFM transition and boosting tunneling electromagnetic resistance, providing a novel strategy and mechanism for developing low-power, high-density memory devices.

Achieving full electrical control of spin-polarized transport at the nanoscale remains a key challenge for spintronic technologies. Here, we demonstrate that integrating a ferroelectric layer into a ferromagnetic semiconductor sandwich structure enables nonvolatile generation and reversible switching of spin-polarized currents. Taking the Cr₂Si₂Te₆/Sc₂CO₂/Cr₂Ge₂Te₆ van der Waals multiferroic heterostructure as an example, our first-principles calculations show that by reversing the polarization direction of the intermediate ferroelectric layer, the heterostructure system can flexibly switch between spin-up and spin-down half-metallic states. This functionality originates from polarization-induced band shifts and interfacial charge transfer. Accordingly, the proposed multiferroic device exhibits a fully spin-polarized current with electrically switchable spin orientations and a perfect spin-filtering efficiency. Furthermore, we validated the effectiveness of this strategy in several other lattice-matched multiferroic heterostructures, thereby providing a new class of multiferroic systems with electrically switchable half-metallicity.

We synthesized a new type of complex nanoparticle: truncated satellite octahedral Au nanoparticles (SONs). The synthesis began with octahedral Au nanoparticles, followed by selective Pt deposition and a mild polyol synthesis to generate triakis-octahedral Ag nanoparticles (TONs). Subsequent Au deposition on the TONs led to the formation of cavities within the shell, and selective growth of truncated satellite structures from each (111) facet resulted in SONs with exposed line-shaped nanotrench gaps along the edges of the outer octahedral structure. The SONs exhibited strong near-field focusing in single-particle surface-enhanced Raman spectroscopy (SERS) measurement due to (1) efficient focusing by the exterior line-shaped nanotrench gaps and (2) activation of internal hot nanocavities as the exterior Au shell enabled 785 nm light penetration, producing additional field enhancement. SONs were applied to SERS-based imaging of liposarcoma cells, and the high signal stability of SON nanoparticles enabled cell imaging for up to 4 weeks.

Oral squamous cell carcinoma (OSCC), the most common oral malignancy, requires accurate diagnostic methods for patient stratification and treatment guidance. Exosome-based liquid biopsy represents a promising minimally invasive approach to cancer detection. This study develops an explainable artificial intelligence (xAI)-assisted label-free surface-enhanced Raman spectroscopy (SERS) platform for profiling salivary exosomes to enable noninvasive OSCC diagnosis and metastatic stratification. A fully connected artificial neural network is designed to extract discriminative features from complex SERS data. Trained on cellular exosome SERS data sets, the model achieves 90.63% accuracy in distinguishing OSCC patients from healthy subjects and 86.63% accuracy in differentiating nonmetastatic and metastatic OSCC cases. Importantly, Shapley additive explanation-based xAI interpretation identifies tryptophan residues in transmembrane proteins as regulators of carcinogenesis, while genetic mutations are linked to metastatic progression, thereby bridging diagnostic outcomes with molecular mechanisms. This work establishes a biochemically interpretable SERS-xAI framework for cancer diagnosis, advancing precision oncology through mechanistic insights.