资源环境科技发展态势分析平台

A quantum dot device designed to host four electrons is used to demonstrate Nagaoka ferromagnetism-a model of itinerant magnetism that has so far been limited to theoretical investigation.

Engineered, highly controllable quantum systems are promising simulators of emergent physics beyond the simulation capabilities of classical computers(1). An important problem in many-body physics is itinerant magnetism, which originates purely from long-range interactions of free electrons and whose existence in real systems has been debated for decades(2,3). Here we use a quantum simulator consisting of a four-electron-site square plaquette of quantum dots(4) to demonstrate Nagaoka ferromagnetism(5). This form of itinerant magnetism has been rigorously studied theoretically(6-9) but has remained unattainable in experiments. We load the plaquette with three electrons and demonstrate the predicted emergence of spontaneous ferromagnetic correlations through pairwise measurements of spin. We find that the ferromagnetic ground state is remarkably robust to engineered disorder in the on-site potentials and we can induce a transition to the low-spin state by changing the plaquette topology to an open chain. This demonstration of Nagaoka ferromagnetism highlights that quantum simulators can be used to study physical phenomena that have not yet been observed in any experimental system. The work also constitutes an important step towards large-scale quantum dot simulators of correlated electron systems.

A synthetic approach is described, for efficiently converting non-van der Waals solids into two-dimensional van der Waals transition-metal chalcogenide layers with specific phases, enabling the high-throughput production of monolayers.

Although two-dimensional (2D) atomic layers, such as transition-metal chalcogenides, have been widely synthesized using techniques such as exfoliation(1-3) and vapour-phase growth(4,5), it is still challenging to obtain phase-controlled 2D structures(6-8). Here we demonstrate an effective synthesis strategy via the progressive transformation of non-van der Waals (non-vdW) solids to 2D vdW transition-metal chalcogenide layers with identified 2H (trigonal prismatic)/1T (octahedral) phases. The transformation, achieved by exposing non-vdW solids to chalcogen vapours, can be controlled using the enthalpies and vapour pressures of the reaction products. Heteroatom-substituted (such as yttrium and phosphorus) transition-metal chalcogenides can also be synthesized in this way, thus enabling a generic synthesis approach to engineering phase-selected 2D transition-metal chalcogenide structures with good stability at high temperatures (up to 1,373 kelvin) and achieving high-throughput production of monolayers. We anticipate that these 2D transition-metal chalcogenides will have broad applications for electronics, catalysis and energy storage.

Cancer develops through a process of somatic evolution(1,2). Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes(3). Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)(4), we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.