Graphene is used as flexible electrodes in various optoelectronic devices. In these applications, ultrafast charge transfer from semiconducting light absorbers to graphene can impact the overall device performance. Here, we propose a mechanism in which the charge-transfer rate can be controlled by varying the number of graphene layers and their stacking. Using an organic semiconducting molecule as a light absorber, the charge-transfer rate to graphene is measured by using time-resolved photoemission spectroscopy. Compared to graphite, the charge transfer to monolayer graphene is about 2 times slower. Surprisingly, the charge transfer to A-B-stacked bilayer graphene is slower than that to both monolayer graphene and graphite. This anomalous behavior disappears when the two graphene layers are randomly stacked. The observation is explained by a charge-transfer model that accounts for the band-structure difference in mono-and bilayer graphene, which predicts that the charge-transfer rate depends nonintuitively on both the layer number and stacking of graphene.

Electronic transport in organic semiconductors is mediated by localized polarons. However, the dynamics on how delocalized electrons collapse into polarons through electron-nuclear interaction is not well-known. In this work, we use time and angle resolved photoemission spectroscopy (TR-ARPES) to study polaron formation in titanyl phthalocyanine deposited on Au(111) surfaces. Electrons are optically excited from the metal to the organic layer via the image potential state, which evolves from a dispersive to a non-dispersive state after photoexcitation. The spatial size of the electrons is determined from the band-structure using a tight-binding model. It is observed that the two-dimensional electron wave collapses into a wave packet of size ~ 3 nm within 100 fs after photoexcitation.

Understanding the interfacial electron transfer (IET) between 2D layers is central to technological applications. We present a first-principles study of the IET between a zinc phthalocyanine film and few-layer graphene by using our recent method for the calculation of electronic coupling in periodic systems. The ultimate goal is the development of a predictive in silico approach for designing new 2D materials. We find IET to be critically dependent on the number of layers and their stacking orientation. In agreement with experiment, IET to single-layer graphene is shown to be faster than that to double-layer graphene due to interference effects between layers. We predict that additional graphene layers increase the number of IET pathways, eventually leading to a faster rate. These results shed new light on the subtle interplay between structure and IET, which may lead to more effective "bottom up" design strategies for these materials.

We study theoretically the effect of the effective dimensionality of the phonon gas distribution on the heat exchange between electrons and phonons in layered nanostructures. If we denote the electrons temperature by Te and the phonons temperature by T ph , then the total heat power P is proportional-in general-to T x e −T x ph , the exponent x being dependent on the effective dimensionality of the phonon gas distribution. If we vary the temperature in a wide enough range, the effective dimensionality of the phonon gas distribution changes going through a crossover around some temperature, TC . These changes are reflected by a change in x. On one hand, in a temperature range well below a crossover temperature TC only the lowest branches of the phonon modes are excited.They form a (quasi) two-dimensional gas, with x = 3.5. On the other hand, well above TC , the phonon gas distribution is quasi three-dimensional and one would expect to recover the three dimensional results, with x = 5. But this is not the case in our layered structure. The exponent x has a complicated, non-monotonous dependence on temperature forming a "plateau region" just after the crossover temperature range, with x between 4.5 and 5. After the plateau region, x decreases, reaching values between 3.5 and 4 at the highest temperature used in our numerical calculations, which is more than 40 times higher than TC .