Skip to content
#diffusion models Open access

Dual-phase CoS2/Co3S4 nanostructures for enhanced electrochemical charge storage in symmetric supercapacitors

Sep 2026 · Nanotechnology · Vol 37 · 0 citations · 67 references
Physics Medicine

Abstract

The rational design of nanostructured heterophase materials has emerged as an effective strategy for enhancing charge storage and transport in electrochemical energy-storage systems. Herein, a dual-phase CoS2/Co3S4 nanostructured heterostructure was synthesized via a hydrothermal route and investigated as an electrode material for supercapacitors. Structural characterization confirmed the formation of crystalline CoS2 and Co3S4 phases, while electron microscopy revealed hierarchical micro–nanostructures composed of interconnected nanoparticles that provide abundant electrochemically active interfaces. The electrochemical charge storage behavior was systematically evaluated using cyclic voltammetry, galvanostatic charge–discharge, and electrochemical impedance spectroscopy in both three- and two-electrode configurations. Detailed kinetic analysis using b-value determination and Dunn’s model demonstrated the combined contribution of surface-controlled and diffusion-governed charge-storage processes. The electrode delivered a specific capacitance of 716.8 F g−1 at 0.5 A g−1 in a three-electrode system. In a two electrode configuration, the symmetric supercapacitor delivered a capacitance of 303.3 F g−1 with an energy density of 2.42 Wh kg−1 at a power density of 60 W kg−1. The device also demonstrated appreciable electrochemical stability with capacitance retention of 90% and 88% after 2000 charge–discharge cycles in three- and two-electrode systems, respectively. The enhanced performance is attributed to heterophase-induced charge-transfer pathways and improved ion accessibility arising from the hierarchical nanostructure. This study highlights the role of intrinsic phase-engineered cobalt sulfide nanostructures in governing electrochemical functionality and provides insights for the development of advanced nanomaterials for next-generation energy-storage technologies.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

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. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

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. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

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. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

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. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

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. · 78 citations · ⚡6
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

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 angle and explores waste in the Kanban-driven software development project context. A preliminary research model is presented for helping the consequent replication of the study. The results from the empirical analysis suggest Kanban can be an effective method in visualizing and organizing the current work, but does not prevent waste from creeping in, although the overall project outcome may be successful.

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9

Related blog posts

MIT News · Artificial Intelligence Sep 14, 2026

New method enables AI for safety-critical situations

The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.

GPT-Lab Sep 10, 2026

Responsible AI Must Consider Its Afterlife

AI may appear weightless, but every model depends on physical infrastructure. To understand responsible AI, we need to look beyond algorithms and consider the entire lifecycle of the hardware behind them. The post Responsible AI Must Consider Its Afterlife appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.