Observation of ultrafast interfacial Meitner-Auger energy transfer in a Van der Waals heterostructure.

Atomically thin layered van der Waals heterostructures feature exotic and emergent optoelectronic properties. With growing interest in these novel quantum materials, the microscopic understanding of fundamental interfacial coupling mechanisms is of capital importance. Here, using multidimensional photoemission spectroscopy, we provide a layer- and momentum-resolved view on ultrafast interlayer electron and energy transfer in a monolayer-WSe2/graphene heterostructure. Depending on the nature of the optically prepared state, we find the different dominating transfer mechanisms: while electron injection from graphene to WSe2 is observed after photoexcitation of quasi-free hot carriers in the graphene layer, we establish an interfacial Meitner-Auger energy transfer process following the excitation of excitons in WSe2. By analysing the time-energy-momentum distributions of excited-state carriers with a rate-equation model, we distinguish these two types of interfacial dynamics and identify the ultrafast conversion of excitons in WSe2 to valence band transitions in graphene. Microscopic calculations find interfacial dipole-monopole coupling underlying the Meitner-Auger energy transfer to dominate over conventional Förster- and Dexter-type interactions, in agreement with the experimental observations. The energy transfer mechanism revealed here might enable new hot-carrier-based device concepts with van der Waals heterostructures.

Mathematical modeling for breast cancer risk assessment. State of the art and role in medicine.

Women at increased risk of breast cancer have important opportunities for early detection and prevention. There are, however, serious drawbacks to the available interventions. The magnitude of breast cancer risk is a crucial factor in the optimization of medical benefit when considering the efficacy of risk-reduction methods, the adverse effects of intervention, and economic and quality-of-life outcomes. Breast cancer risk assessment has become increasingly quantitative and is amenable to computerization. The assembly of risk factor information into practical, quantitative models for clinical and scientific use is relatively advanced for breast cancer, and represents a paradigm for broader risk management in medicine. Using a case-based approach, we will summarize the major breast cancer risk assessment models, compare and contrast their utility, and illustrate the role of genetic testing in risk management. Important considerations relevant to clinical oncology practice include the role of risk assessment in cancer prevention, the logistics of implementing risk assessment, the ramifications of conveying risk information with limited genetic counseling, and the mechanisms for genetics referral. Medical professionals can embrace new preventive medicine techniques more effectively by utilizing quantitative methods to assess their patients' risks.