Sep 2026· Solar Energy· Vol 318, pp. 115028· 28 references
Photovoltaic Systems and Sustainability
Abstract
An efficient medium for silver (Ag) recovery from end-of-life crystalline silicon (c-Si) solar cells should combine strong Ag reactivity with limited co-extraction of non-target metals and good reusability. In this study, an acetamide-based deep eutectic solvent (DES) composed of choline chloride (ChCl) and acetamide (Ac) (ChCl:Ac = 1:2), with copper chloride (CuCl 2 ) as the oxidant, was developed as an Ag-leaching medium. Under identical 1 h conditions, ChCl:Ac-CuCl 2 produced an Ag-wire mass loss of 53.50 ± 4.55 mg, compared with 30.41 ± 4.29 mg for ChCl:Urea-CuCl 2 , demonstrating stronger Ag-leaching performance. Using Ag wire as a model linear substrate, kinetic analysis showed that the conversion data were better described by the reaction-controlled cylindrical shrinking-core model than by the product-layer diffusion-controlled model. Within 50–80 °C, the apparent activation energy derived from the reaction-controlled model was 55.40 kJ·mol −1 . The apparent reaction order with respect to CuCl 2 decreased from 1.42 in the low-concentration interval to 1.30 in the higher-concentration interval, indicating weakened concentration sensitivity at higher CuCl 2 concentration. Validation using commercial c-Si solar cells showed preferential removal of the front-side Ag grid, whereas the rear-side Al electrode was less affected under the same conditions. The medium also exhibited good recyclability, retaining 97.1% of its initial Ag-wire leaching performance after 32 cycles. These results identify the ChCl:Ac-CuCl 2 system as a reusable medium for selective Ag leaching from c-Si solar cells and clarify how solvent structure, interfacial reaction, and kinetic constraints jointly govern its performance.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.