Publisher Correction: Materials for high-temperature digital electronics
Related Articles
The risk effects of corporate digitalization: exacerbate or mitigate?
This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.
Dual-mode temperature monitoring using high-performance flexible thermocouple sensors based on PEDOT:PSS/CNTs and MXene/Bi2Se3
Due to the limited thermoelectric (TE) performance of polymer materials and the inherent rigidity of inorganic materials, developing low-cost, highly flexible, and high-performance materials for flexible thermocouple sensors (FTCSs) remains challenging. Additionally, dual-mode (contact/non-contact) temperature monitoring in FTCSs is underexplored. This study addresses these issues by using p-type (PEDOT:PSS/CNTs, 2:1) and n-type (MXene/Bi2Se3, 2:1) TE materials applied via screen printing and compression onto a PPSN substrate (paper/PDMS/Si3N₄). The resulting FTCSs exhibit excellent TE properties: electrical conductivities of 61,197.88 S/m (n-type) and 55,697.77 S/m (p-type), Seebeck coefficients of 39.88 μV/K and -29.45 μV/K, and power factors (PFs) of 97.66 μW/mK² and 55.64 μW/mK², respectively. In contact mode, the sensor shows high-temperature sensitivity (ST = 379.5 μV/°C), a broad detection range (20-200 °C), high resolution (~0.3 °C), and fast response (~12.6 ms). In non-contact mode, it maintains good sensitivity (STmax = 52.67 μV/°C), a broad detection range, high resolution (~0.8 °C), and even faster response (~9.8 ms). The sensor also demonstrates strong mechanical durability, maintaining stable performance after 1000 bending cycles. When applied to dual-mode temperature monitoring in wearable devices and lithium batteries, the FTCS shows high accuracy and reliability compared to commercial K-type thermocouples, indicating significant potential for advanced medical monitoring systems and smart home technologies.
3D printing of micro-nano devices and their applications
In recent years, the utilization of 3D printing technology in micro and nano device manufacturing has garnered significant attention. Advancements in 3D printing have enabled achieving sub-micron level precision. Unlike conventional micro-machining techniques, 3D printing offers versatility in material selection, such as polymers. 3D printing technology has been gradually applied to the general field of microelectronic devices such as sensors, actuators and flexible electronics due to its adaptability and efficacy in microgeometric design and manufacturing processes. Furthermore, 3D printing technology has also been instrumental in the fabrication of microfluidic devices, both through direct and indirect processes. This paper provides an overview of the evolving landscape of 3D printing technology, delineating the essential materials and processes involved in fabricating microelectronic and microfluidic devices in recent times. Additionally, it synthesizes the diverse applications of these technologies across different domains.
Digital infrastructure construction and corporate innovation efficiency: evidence from Broadband China Strategy
Adopting the Broadband China Strategy as a quasi-natural experiment, we construct a multi-period Difference-in-Differences (DID) model to examine the impact of digital infrastructure construction on corporate innovation efficiency with panel data from Chinese listed companies between 2010 to 2022. Our findings indicate that the development of digital infrastructure significantly boosts corporate innovation efficiency. Mechanistic analysis reveals that financing constraints negatively moderates this innovation impact, while human capital positively moderates it. The effects of the Broadband China Strategy are particularly pronounced in non-state-owned enterprises, non-high-tech enterprises, and firms located in the non-eastern region of China. Our research provides important insights for enterprises seeking to enhance their innovation efficiency, while also offering strong empirical evidence on the role of digital infrastructure in fostering corporate innovation. Our study contributes to the literature on digital economy and innovation, with practical implications for policymakers and firms aiming to leverage digital infrastructure for sustained competitive advantage.
When the customers comes to you: mobile apps and corporate investment efficiency
Firms are increasingly shifting towards digital channels, yet the implications of this shift remain underexplored. Using a unique database of customer behaviors extracted from the top 2000 mobile apps developed by companies in China, this study investigates the impact of mobile apps on inefficient corporate investments. The results indicate that metrics such as active user count, usage duration, and app launch frequency can mitigate inefficient investments, notably by curtailing overinvestment. These findings survive a series of robustness checks such as altering the measures of inefficient investment, extending the analysis to include the top five apps, incorporating H-share listed firms, and employing instrumental variables regression. Moreover, the mechanism analysis indicates that mobile apps help reduce inefficient investments by lowering agency costs and relaxing financial constraints. Further analysis examines the business models of these apps (paid vs. free) as well as their reputation mechanisms, revealing that the pricing strategies of apps and the reputation of corporate brands also play a role in how the adoption of mobile apps affects inefficient investment.
Responses