Prediction From Minimal Experience: How People Predict the Duration of an Ongoing Epidemic.

People are known for good predictions in domains they have rich experience with, such as everyday statistics and intuitive physics. But how well can they predict for problems they lack experience with, such as the duration of an ongoing epidemic caused by a new virus? Amid the first wave of COVID-19 in China, we conducted an online diary study, asking each of over 400 participants to predict the remaining duration of the epidemic, once per day for 14 days. Participants' predictions reflected a reasonable use of publicly available information but were meanwhile biased, subject to the influence of negative affect and future time perspectives. Computational modeling revealed that participants neither relied on prior distributions of epidemic durations as in inferring everyday statistics, nor on mechanistic simulations of epidemic dynamics as in computing intuitive physics. Instead, with minimal experience, participants' predictions were best explained by similarity-based generalization of the temporal pattern of epidemic statistics. In two control experiments, we further confirmed that such cognitive algorithm is not specific to the epidemic scenario and that minimal and rich experience do lead to different prediction behaviors for the same observations. We conclude that people generalize patterns in recent history to predict the future under minimal experience.

Cu2O photocathodes for unassisted solar water-splitting devices enabled by noble-metal cocatalysts simultaneously as hydrogen evolution catalysts and protection layers.

Here, we report a Cu2O-based photocathode applied with pulsed-laser-deposited overlayers with the structure of Ga2O3/AZO/TiO2 and 60 nm dense Pt simultaneously as a hydrogen evolution catalyst and protective layer under backside illumination from ITO substrate. And by depositing thin Au nanoparticles on the bottom of Cu2O, we observe the increase of light harvesting and the production of hot electrons from the surface plasmon resonance effect. The modified photocathode presents a photocurrent density of -4 mA cm-2 at 0 V versus reversible hydrogen electrode and a thermodynamically-based energy conversion efficiency of 0.27% in a weak acidic electrolyte. The stability is tremendously improved compared with other structures without the dense Pt layer. This enhancement is attributed to the formation of a p-n junction at the Cu2O and Ga2O3 interface and surface stabilization by TiO2 and Pt. To demonstrate the impact on the practical application of the photocathode, we fabricate the bias-free solar water-splitting tandem device using a transparent BiVO4 photoanode, which exhibits a stabilized peak photocurrent density of 0.1 mA cm-2 under continuous illumination.

Electronic Band Structures and Native Point Defects of Ultrafine ZnO Nanocrystals.

Ultrafine ZnO nanocrystals with a thickness down to 0.25 nm are grown by a metalorganic chemical vapor deposition method. Electronic band structures and native point defects of ZnO nanocrystals are studied by a combination of scanning tunneling microscopy/spectroscopy and first-principles density functional theory calculations. Below a critical thickness of ∼1 nm ZnO adopts a graphitic-like structure and exhibits a wide band gap similar to its wurtzite counterpart. The hexagonal wurtzite structure, with a well-developed band gap evident from scanning tunneling spectroscopy, is established for a thickness starting from ∼1.4 nm. With further increase of the thickness to 2 nm, VO-VZn defect pairs are easily produced in ZnO nanocrystals due to the self-compensation effect in highly doped semiconductors.