Unusually stable helical coil allotrope of phosphorus

We have identified an unusually stable helical coil allotrope of phosphorus. Our ab initio Density Functional Theory calculations indicate that the uncoiled, isolated straight 1D chain is equally stable as a monolayer of black phosphorus dubbed phosphorene. The coiling tendency and the attraction between adjacent coil segments add an extra stabilization energy of about 12 meV/atom to the coil allotrope, similar in value to the approximately 16 meV/atom inter-layer attraction in bulk black phosphorus. Thus, the helical coil structure is essentially as stable as black phosphorus, the most stable phosphorus allotrope known to date. With an optimum radius of 2.4 nm, the helical coil of phosphorus may fit well and even form inside wide carbon nanotubes.Comment: The paper has been accepted by Nano. Lett. (2016

Off-Policy Evaluation of Probabilistic Identity Data in Lookalike Modeling

We evaluate the impact of probabilistically-constructed digital identity data collected from Sep. to Dec. 2017 (approx.), in the context of Lookalike-targeted campaigns. The backbone of this study is a large set of probabilistically-constructed "identities", represented as small bags of cookies and mobile ad identifiers with associated metadata, that are likely all owned by the same underlying user. The identity data allows to generate "identity-based", rather than "identifier-based", user models, giving a fuller picture of the interests of the users underlying the identifiers. We employ off-policy techniques to evaluate the potential of identity-powered lookalike models without incurring the risk of allowing untested models to direct large amounts of ad spend or the large cost of performing A/B tests. We add to historical work on off-policy evaluation by noting a significant type of "finite-sample bias" that occurs for studies combining modestly-sized datasets and evaluation metrics involving rare events (e.g., conversions). We illustrate this bias using a simulation study that later informs the handling of inverse propensity weights in our analyses on real data. We demonstrate significant lift in identity-powered lookalikes versus an identity-ignorant baseline: on average ~70% lift in conversion rate. This rises to factors of ~(4-32)x for identifiers having little data themselves, but that can be inferred to belong to users with substantial data to aggregate across identifiers. This implies that identity-powered user modeling is especially important in the context of identifiers having very short lifespans (i.e., frequently churned cookies). Our work motivates and informs the use of probabilistically-constructed identities in marketing. It also deepens the canon of examples in which off-policy learning has been employed to evaluate the complex systems of the internet economy.Comment: Accepted by WSDM 201

Why Do People Chase Fashionable Technologies? Toward a Systematic Understanding of IT Fashion Diffusion and Adoption of Fashionable IT

Fashion is a ubiquitous social phenomenon. People chase after fashionable clothes, furniture and jewelry for reasons beyond utilitarian benefits. Many people did not associate information technologies with fashion for a long time. Nevertheless, as consumer technologies become increasingly smaller and more portable, they can be carried around as body accessories that bear social meanings. The fashion elements have begun to exert tremendous influence on consumers’ behaviors and companies’ successes. The advent of fashionable technologies necessitates thorough research on IT fashion. This dissertation aims to provide a systematic understanding of fashionable technologies. It first elucidates the process of IT fashion diffusion based on extant fashion theories and the unique characteristics of fashionable technologies. Then it investigates the reasons why people adopt fashionable technologies by identifying the core characteristics of fashionable technologies perceived by adopters and explicating how these perceived characteristics affect people’s behavioral beliefs of using the technologies. To empirically test the research model, 256 responses were collected by hiring a professional survey company Qualtrics. The results support most of the hypotheses. The current dissertation lays the foundation for future IT fashion research and potentially breaks new theoretical grounds for the IS field