Hydrogen Behavior at Crystalline/Amorphous Interface of Transparent Oxide Semiconductor and Its Effects on Carrier Transport and Crystallization.

The role of disorder and particularly of the interfacial region between crystalline and amorphous phases of indium oxide in the formation of hydrogen defects with covalent (In-OH) or ionic (In-H-In) bonding are investigated using ab initio molecular dynamics and hybrid density-functional approaches. The results reveal that disorder stabilizes In-H-In defects even in the stoichiometric amorphous oxide and also promotes the formation of deep electron traps adjacent to In-OH defects. Furthermore, below-room-temperature fluctuations help switch interfacial In-H-In into In-OH, creating a new deep state in the process. This H-defect transformation limits not only the number of free carriers but also the grain size, as observed experimentally in heavily H-doped sputtered In2Ox. On the other hand, the presence of In-OH helps break O2 defects, abundant in the disordered indium oxide, and thus contributes to faster crystallization rates. The divergent electronic properties of the ionic vs covalent H defects─passivation of undercoordinated In atoms vs creation of new deep electron traps, respectively─and the different behavior of the two types of H defects during crystallization suggest that the resulting macroscopic properties of H-doped indium oxide are governed by the relative concentrations of the In-H-In and In-OH defects. The microscopic understanding of the H defect formation and properties developed in this work serves as a foundation for future research efforts to find ways to control H species during deposition.

Quantifying Chemical Structure and Machine-Learned Atomic Energies in Amorphous and Liquid Silicon.

Amorphous materials are being described by increasingly powerful computer simulations, but new approaches are still needed to fully understand their intricate atomic structures. Here, we show how machine-learning-based techniques can give new, quantitative chemical insight into the atomic-scale structure of amorphous silicon (a-Si). We combine a quantitative description of the nearest- and next-nearest-neighbor structure with a quantitative description of local stability. The analysis is applied to an ensemble of a-Si networks in which we tailor the degree of ordering by varying the quench rates down to 1010  K s-1 . Our approach associates coordination defects in a-Si with distinct stability regions and it has also been applied to liquid Si, where it traces a clear-cut transition in local energies during vitrification. The method is straightforward and inexpensive to apply, and therefore expected to have more general significance for developing a quantitative understanding of liquid and amorphous states of matter.

Amorphous graphene: a constituent part of low density amorphous carbon.

In this paper, we provide evidence that low density nano-porous amorphous carbon (a-C) consists of interconnected regions of amorphous graphene (a-G). We include experimental information in producing models, while retaining the power and accuracy of ab initio methods with no biasing assumptions. Our models are highly disordered with predominant sp2 bonding and ring connectivity mainly of sizes 5-8. The structural, dynamical and electronic signatures of our 3-D amorphous graphene are similar to those of monolayer amorphous graphene. We predict an extended x-ray absorption fine structure (EXAFS) signature of amorphous graphene. Electronic density of states calculations for 3-D amorphous graphene reveal similarity to monolayer amorphous graphene and the system is non conducting.