Electrotunable liquid sulfur microdroplets.

Manipulating liquids with tunable shape and optical functionalities in real time is important for electroactive flow devices and optoelectronic devices, but remains a great challenge. Here, we demonstrate electrotunable liquid sulfur microdroplets in an electrochemical cell. We observe electrowetting and merging of sulfur droplets under different potentiostatic conditions, and successfully control these processes via selective design of sulfiphilic/sulfiphobic substrates. Moreover, we employ the electrowetting phenomena to create a microlens based on the liquid sulfur microdroplets and tune its characteristics in real time through changing the shape of the liquid microdroplets in a fast, repeatable, and controlled manner. These studies demonstrate a powerful in situ optical battery platform for unraveling the complex reaction mechanism of sulfur chemistries and for exploring the rich material properties of the liquid sulfur, which shed light on the applications of liquid sulfur droplets in devices such as microlenses, and potentially other electrotunable and optoelectronic devices

Demand management concept and tool in a dynamic context

ChainScope B.V. is a startup company that develops supply chain optimization and planning software. The optimization software is currently based on the assumption of stationary demand. However, in real-life situation future demand is forecasted through a combination of time series analysis and human judgment. On the other hand, at present most companies have sophisticated business forecast figures from high strategy level in long horizon and also have the ability to collect the real demand data at low level. Nevertheless, there is a gap to make full use of these data together to do the demand management and make proper supply chain management or further strategic management. Therefore, a detailed assessment is carried out in this project to investigate the requirements for a new demand management concept as an extension of the current forecasting process. The demand management module is the outcome of the research study with a couple of new features. The interface for other data input helps planners integrate all relevant information in the demand management. Moreover, supply chain structure is involved into the tool together with more data handling capabilities. It enables planners to have a comparable view from end item level to component item level and to execute advanced forecast assessment

eFarm: A Tool for Better Observing Agricultural Land Systems

Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human–land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies