Soldering Pressure Effect on Lifetime of Thermoelectric Modules under Thermal Cycling.

For practical industrial applications, enhancing the longevity and the reliability of thermoelectric modules (TEMs) is equally as crucial as improving their conversion efficiency. This study proposes a strategy for extending the lifespan and introduces the quality evaluation criteria for the most extensively used commercial bismuth telluride TEM. By varying the soldering pressure during module assembly, its impact on the quality of the module's internal interfacial connections was investigated, via analyzing its contact resistivity, shear modulus, and antifatigue ability through thermal cycling tests. The findings reveal that increasing the soldering pressure leads to a slight reduction in interfacial contact resistivity and has no significant effect on the shear modulus but notably enhances the module's antifatigue ability during thermal cycling tests. According to the SEM results, it can be evidently deduced that the aforementioned phenomena are directly correlated with the size and quantity of voids distributed in the solder layer, which is regarded as the origin of antifatigue ability. Thus, it can be inferred that augmenting the soldering pressure represents an effective approach to prolonging the lifespan of TEMs assembled by using the soldering method. Furthermore, the existence of voids within the solder layer can serve as a criterion for an initial assessment of module longevity. This study provides a reference for both the industrial assembly and lifespan evaluation of commercial bismuth telluride TEMs.

High Thermoelectric Performance in Bismuth Telluride via Constructing MoSe2-2D Heterojunction.

Currently, the only thermoelectric (TE) materials commercially available at room temperature are those based on bismuth telluride. However, their widespread application is limited due to their inferior thermoelectric and mechanical properties. In this study, a strategy of growing a rigid second phase of MoSe2 is employed, in situ within the matrix phase to achieve n-type bismuth telluride-based materials with exceptional mechanical and thermoelectric properties. The in situ grown second phase contributes to both the electronic and lattice thermal conductivities. This is primarily attributed to the strong energy filtering effect, as the second phase forms a semi-common lattice interfacial structure with the matrix phase during growth. Furthermore, for composites containing 2 wt% MoSe2, a maximum zT value of 1.24 at 373 K can be achieved. On this basis, 8-pair TE module is fabricated and 1-pair TE module is optimized using a homemade p-type material. The optimized 1-pair TE module generates a maximum output power of 13.6 µW, which is twice that of the 8-pair TE module and four times more than the 8-pair TE module fabricated by commercial material. This work facilitates the development of the TE module by presenting a novel approach to obtaining bismuth telluride-based thermoelectric materials with superior thermoelectric and mechanical properties.

Inactivation of microorganisms on fabrics using plasma-activated nebulized mist driven by different plasma gases.

The disinfection of fabrics is crucial in preventing the spread of infectious diseases caused by pathogenic microorganisms to maintain public health. A previous study proved that plasma-activated nebulized mist (PANM) could effectively inactivate microorganisms both in aerosol and attached to the surface. In this study, the PANM driven by different plasma gases were employed to inactivate microorganisms on diverse fabrics. The PANM could efficiently inactivate a variety of microorganisms, including bacteria, fungi, and viruses, contaminating different fabrics, and even across covering layers of different fabrics. The mites residing on the cotton fabrics both uncovered and covered with various types of fabrics were also effectively inactivated by the PANM. After 30 times repeated treatments of the PANM, notable changes were observed in the color of several fabrics while the structural integrity and mechanical strength of the fabrics were unaffected and maintained similarly to the untreated fabrics with slight changes in elemental composition. Additionally, only trace amounts of nitrate remained in the fabrics after the PANM treatment. Therefore, the PANM treatment supplied an efficient, broad-spectrum, and environmentally friendly strategy for industrial and household disinfection of fabrics.

Interfacial Crack Growth-Based Fatigue Lifetime Prediction of Thermoelectric Modules under Thermal Cycling.

As a result of the complexity and difficulty of the lifetime assessment of the thermoelectric (TE) module, the related research is still immature. In this work, to predict the lifetime of the Bi2Te3-based TE module from the perspective of cyclic thermal stress leading to interface cracking, the viscoplastic behavior of the solder layer is first described by the Anand material ontology model, and then the sprouting and expansion of interface cracking of the module are simulated by combining the Darveaux model and the viscoplastic dissipation energy accumulated during the thermal stress cyclic loading. After that, the complete lifetime prediction model of the TE module is established on the basis of the thermal cycling experiments and the finite element simulation calculation data, which can simply and efficiently predict the cycle number of the module resistance rise and its rise rate. The prediction deviations are 6.1 and 6.7%, respectively, verifying the feasibility of the model. The work in this paper can provide a reference for the life evaluation of TE modules.

Real-Time Monitoring of Air Discharge in a Switchgear by an Intelligent NO2 Sensor Module.

An air-insulated power equipment adopts air as the insulating medium and is widely implemented in power systems. When discharge faults occur, the air produces decomposition products represented by NO2. The efficient NO2 sensor enables the identification of electrical equipment faults. However, single-sensor-dependent NO2 detection is vulnerable to interfering gases. Implementing the sensor array could reduce the interference and improve detection efficiency. In the field of NO2 detection, In2O3 sensors have exhibited tremendous advantages. In our work, four composites based on In2O3 are integrated into sensor arrays, which could detect 250 ppb of NO2 and exhibit excellent selectivity when simultaneously exposed to CO. To further reduce the impact of humidity on gas-sensing performance, a convolutional neural network and a long short-term memory model equipped with an attention mechanism are proposed to evaluate NO2 concentration within 1 ppm, and the detection error is 63.69 ppb. In addition, the NO2 concentration estimation platform based on a microgas sensor is established to detect air discharge faults. The average concentration of NO2 generated by 10 consecutive discharge faults at 15 kV is 726.58 ppb, which indicates severe discharge in the switchgear. Our NO2 estimation method has great potential for large-scale deployment in low- and medium-voltage switchgears.

Inactivation of airborne pathogenic microorganisms by plasma-activated nebulized mist.

The airborne microorganisms in the aerosols are one main transmission way of pathogenic microorganisms and therefore inactivation of microorganisms in aerosols could effectively prevent the transmission of pathogenic microorganisms to control epidemics. The mist nebulized by plasma-activated air could effectively inactivate bacteria and could be developed for the sterilization of microorganisms in aerosols. In this study, the plasma-activated nebulized mist (PANM) was applied for the inactivation of microorganisms in aerosols and efficiently inactivated the bacteria, yeast, and viruses in aerosols after 2-min treatment. The PANM treatment caused morphologic changes and damage to the bacteria cells in aerosols. The PANM could also inactivate the microorganisms attached to the surface of the treatment chamber and the bacteria attached to the skin of mice within 6-min treatment. The biosafety assays demonstrated that the PANM treatment exhibited no effects on the behavior, hematological and serum biochemical parameters of blood, and organs from the mice. This study would supply an efficient, broad-spectrum, and safe aerosol sterilization strategy based on plasma technology to prevent the transmission of airborne microorganisms.

Research progress and prospects on gas-sensitive mechanisms of semiconductor sensors.

Semiconductor materials with wide bandgaps are extensively employed for gas detection due to their advantages of low cost, high sensitivity, fast speed, excellent stability, and distinctive selectivity. Previous studies have reported on different kinds of semiconductor materials and their complex synthesis procedures. However, the research progress on gas-sensitive mechanisms seriously lags behind the performance improvement. The research route of the gas-sensing mechanism is not clear, resulting in an unclear development direction of novel sensitive materials. This review aims to summarize existing approaches and their progress on the interpretation of gas-sensing mechanisms in semiconductors, such as the calculations based on density functional theory, semiconductor physics, and in situ experiments. Ultimately, a reasonable route for the mechanism investigation has been proposed. It guides the development direction of novel materials and reduces the cost of screening highly selective materials. Overall, this review can provide helpful guidance concerning the gas-sensitive mechanism for scholars.

Plasma-Activated Hydrogels for Microbial Disinfection.

A continuous risk from microbial infections poses a major environmental and public health challenge. As an emerging strategy for inhibiting bacterial infections, plasma-activated water (PAW) has proved to be highly effective, environmental-friendly, and non-drug resistant to a broad range of microorganisms. However, the relatively short lifetime of reactive oxygen and nitrogen species (RONS) and the high spreadability of liquid PAW inevitably limit its real-life applications. In this study, plasma-activated hydrogel (PAH) is developed to act as reactive species carrier that allow good storage and controlled slow-release of RONS to achieve long-term antibacterial effects. Three hydrogel materials, including hydroxyethyl cellulose (HEC), carbomer 940 (Carbomer), and acryloyldimethylammonium taurate/VP copolymer (AVC) are selected, and their antibacterial performances under different plasma activation conditions are investigated. It is shown that the composition of the gels plays the key role in determining their biochemical functions after the plasma activation. The antimicrobial performance of AVC is much better than that of PAW and the other two hydrogels, along with the excellent stability to maintain the antimicrobial activity for more than 14 days. The revealed mechanism of the antibacterial ability of the PAH identifies the unique combination of short-lived species (1 O2 , ∙OH, ONOO- and O2 - ) stored in hydrogels. Overall, this study demonstrates the efficacy and reveals the mechanisms of the PAH as an effective and long-term disinfectant capable of delivering and preserving antibacterial chemistries for biomedical applications.

Efficient inactivation of the contamination with pathogenic microorganisms by a combination of water spray and plasma-activated air.

The global pandemic caused by SARS-CoV-2 has lasted two and a half years and the infections caused by the viral contamination are still occurring. Developing efficient disinfection technology is crucial for the current epidemic or infectious diseases caused by other pathogenic microorganisms. Gas plasma can efficiently inactivate different microorganisms, therefore, in this study, a combination of water spray and plasma-activated air was established for the disinfection of pathogenic microorganisms. The combined treatment efficiently inactivated the Omicron-pseudovirus through caused the nitration modification of the spike proteins and also the pathogenic bacteria. The combined treatment was improved with a funnel-shaped nozzle to form a temporary relatively sealed environment for the treatment of the contaminated area. The improved device could efficiently inactivate the Omicron-pseudovirus and bacteria on the surface of different materials including quartz, metal, leather, plastic, and cardboard and the particle size of the water spray did not affect the inactivation effects. This study supplied a disinfection strategy based on plasma-activated air for the inactivation of contaminated pathogenic microorganisms.

Simulation and experimental study on the degradation of the greenhouse gas SF6 by thermal plasma.

SF6 gas is widely used on many occasions especially in the power equipment, but it has been restricted since Kyoto Protocol as the strongest greenhouse gas. To reduce the SF6 emission, several methods are now used such the recycling & purification and the SF6 degradation. Considering the huge market of SF6 and the recent demand in the field of power equipment, it is necessary to explore new ways to thoroughly destroy SF6. This work brought out the idea to degrade retired SF6 by thermal plasma. A simplified kinetic model was established to predict the feasibility of this idea as well as the degradation products of SF6, and then the prototype of SF6 degradation by thermal plasma was built and tested. In thermal plasma, SF6 gradually decomposed into atoms, and then H2 was added to capture the released F atoms to generate HF and also prevent the association reactions of SF6. In order to achieve the desired degradation effect, the reaction temperature and the mixing ratio of H2 should be sufficiently high. However, excessive H2 could generate the H2S, and excessive discharge power could decrease the energy yield. When the flow rate of SF6/H2 was set as 8/30 L/min and the discharge current was set as 100A, the destruction removal efficiency (DRE) of SF6 was 99.0% and the energy yield was 206 g/kWh. This work also discusses how to further treat the by-products such as HF and S from this prototype effectively.

Plasma-enhanced microbial electrolytic disinfection: Decoupling electro- and plasma-chemistry in plasma-electrolyzed oxidizing water using ion-exchange membranes.

Pathogenic microorganisms pose a global threat to public health and environment. Common antibacterial chemicals produce toxic residues, inevitably harming the environment. Electrolyzed oxidizing water (EOW), a promising environment-friendly alternative disinfectant, still lacks effective production processes, sufficient bactericidal efficacy and stability, while the enabling physico-chemical mechanisms remain unclear. Here, we report, for the first time, an effective hybrid plasma electrochemical EOW production process and reveal the mechanisms by combining nonthermal plasmas and a two-chamber electrochemical cell separated by a cation exchange membrane (CEM) for decoupling the chemical reactions during the plasma treatment of water. Experimental results demonstrate that combined chlorine (chloramine) was the main chlorine product in the plasma-enhanced EOW (P-EOW) without a membrane, owing to the consumption of free chlorine  (Cl2, HOCl, ClO-) by plasma-generated reactive nitrogen species. With a CEM in the plasma electrolysis system and through controlling the plasma discharge polarity, the production of free chlorine and other reactive species can be selectively controlled, with the highest concentration of free chlorine obtained in the negative plasma-enhanced EOW (NP-EOW). According to the transportation of cations by the CEM, the high concentrations of free chlorine may be attributed to the higher consuptions of H+ in cathode cell of negative plasma. The study of antibacterial ability of EOW produced under different conditions revealed that Staphylococcus aureus cells were best inactivated by the NP-EOW with CEM, which is mainly attributed to the higher concentration of free chlorine. This study demonstrates the feasibility of plasma-enhanced microbial electrolytic disinfection and offers new insights into the fundamental aspects of P-EOW chemistries for the future development of sustainable, efficient, and cost-effective multipurpose sustainable chemical technologies for water research and treatment.

Bonding Performance of Ag-Cu Brazing Solders and Half-Heusler Alloys for High-Performance Thermoelectric Generators.

Due to the uncertainty of the brazing solder composition and its unknown effect on the long-term stability of the interface, the brazing interface connection process for half-Heusler (hH) thermoelectric (TE) devices is still partially concealed and incomplete. In this work, we selected different types of Ag-Cu-based brazing solders with different Ag and Cu contents to assemble hH TE devices, observed the microstructure of the interface contact, and analyzed its formation mechanism. It is found that when the Cu element in the brazing solder is high, it tends to form an intermetallic compound (IMC) layer at the interface, which threatens the life of the device. On the contrary, when the content of the Ag element is high, the formation of the IMC layer will be avoided. Then, the long-term stability of the interface brazed by Ag72Cu28 with high Ag content was verified: the interface connection showed good contact resistivity stability and mechanical reliability; the fabricated uni-couple TE module achieved a maximum output power of 0.28 W and a maximum conversion efficiency of 7.34% at a temperature difference of 538 K. This work summarizes the selection principle of Cu-Ag-based brazing solder when assembling hH TE modules and verifies the long-term stability of the brazed connection interface. The experiment results can provide a reference for the actual fabrication of hH TE devices.

Upcycle hazard against other hazard: Toxic fluorides from plasma fluoropolymer etching turn novel microbial disinfectants.

The release of toxic fluoride byproducts is a seemingly unavoidable artifact of surface engineering, causing severe environmental and human health problems. Here we propose and implement a new "upcycle hazard against other hazard" concept in the case study of cold atmospheric plasma surface modification of fluoropolymers such as polytetrafluorethylene (PTFE). Capitalizing on the excellent controllability, precision and energy efficiency of the plasma surface processing, complemented with the recently discovered ability of plasmas to activate water to produce a potent electrochemical disinfectant, referred to as the plasma-activated water (PAW), we demonstrate a radically new solution to capture the hazardous gaseous fluorides into the PAW and use the as-fluorinated PAW (F-PAW) as a very effective antimicrobial disinfectant. A customized surface discharge reactor is developed to evaluate the effects of fluorides released from the plasma etching of PTFE on the chemistries in gas-phase plasmas and F-PAW, as well as the antibacterial effect of F-PAW. The results show that gaseous fluorides, including COF2, CF3COF, and SiF4 are produced in gas-phase plasmas, and the dissolution of thus-generated fluorides into PAW has a strong effect on inactivating catalase and destroying the oxidation resistance of bacterial cells. As a result, the antibacterial effect of PAW-fluorides against the methicillin-resistant Staphylococcus aureus (MRSA) is enhanced by > 5 log reductions, suggesting that otherwise hazardous fluorides from the plasma processing of PTFE can be used to enhance the microbial disinfection efficiency of PAW. The demonstrated approach opens new avenues for sustainable hazard valorization exemplified by converting toxic fluoride-etching products into potent antimicrobial and potentially anti-viral disinfectants.

Multicomponent SF6 decomposition product sensing with a gas-sensing microchip.

A difficult issue restricting the development of gas sensors is multicomponent recognition. Herein, a gas-sensing (GS) microchip loaded with three gas-sensitive materials was fabricated via a micromachining technique. Then, a portable gas detection system was built to collect the signals of the chip under various decomposition products of sulfur hexafluoride (SF6). Through a stacked denoising autoencoder (SDAE), a total of five high-level features could be extracted from the original signals. Combined with machine learning algorithms, the accurate classification of 47 simulants was realized, and 5-fold cross-validation proved the reliability. To investigate the generalization ability, 30 sets of examinations for testing unknown gases were performed. The results indicated that SDAE-based models exhibit better generalization performance than PCA-based models, regardless of the magnitude of noise. In addition, hypothesis testing was introduced to check the significant differences of various models, and the bagging-based back propagation neural network with SDAE exhibits superior performance at 95% confidence.

Plasma-activated thermosensitive biogel as an exogenous ROS carrier for post-surgical treatment of cancer.

Post-surgical residual tumor cells are the primary cause of relapse and progression of cancer but unfortunately, there are limited therapeutic options. In this work, a fillable plasma-activated biogel is produced on a thermosensitive biogel [(Poly-DL-lactide)-(poly-ethylene glycol)-(poly-DL-lactide), PLEL] with the aid of a discharge plasma for local post-operative treatment of cancer. In vivo data show that the plasma-activated PLEL biogel (PAPB) eliminates residual tumor tissues after removal surgery and also inhibits in situ recurrence while showing no evident systemic toxicity. Moreover, the PAPB possesses excellent storage capability, allows for slow release of plasma-generated reactive oxygen species (ROS), and exhibits good ROS-mediated anticancer effects in vitro. Our results reveal that the novel plasma-activated biogel is an effective therapeutic agent for local post-operative treatment of cancer.

Plasma-activated water: An alternative disinfectant for S protein inactivation to prevent SARS-CoV-2 infection.

SARS-CoV-2 is a highly contagious virus and is causing a global pandemic. SARS-CoV-2 infection depends on the recognition of and binding to the cellular receptor human angiotensin-converting enzyme 2 (hACE2) through the receptor-binding domain (RBD) of the spike protein, and disruption of this process can effectively inhibit SARS-CoV-2 invasion. Plasma-activated water efficiently inactivates bacteria and bacteriophages by causing damage to biological macromolecules, but its effect on coronavirus has not been reported. In this study, pseudoviruses with the SARS-CoV-2 S protein were used as a model, and plasma-activated water (PAW) effectively inhibited pseudovirus infection through S protein inactivation. The RBD was used to study the molecular details, and the RBD binding activity was inactivated by plasma-activated water through the RBD modification. The short-lived reactive species in the PAW, such as ONOO-, played crucial roles in this inactivation. Plasma-activated water after room-temperature storage of 30 days remained capable of significantly reducing the RBD binding with hACE2. Together, our findings provide evidence of a potent disinfection strategy to combat the epidemic caused by SARS-CoV-2.

Multivariate Evaluation Method for Screening Optimum Gas-Sensitive Materials for Detecting SF6 Decomposition Products.

In previous studies, the selection of optimal gas-sensing materials for detecting target gases mainly relied on their response value, but other indices, such as the recovery capability of materials, have usually been overlooked. Here, we propose a new method for evaluating sensor effectiveness that includes a broader range of performance indices. In this study, four gas sensors based on metal-oxide semiconductors (WO3, CeO2, In2O3, and SnO2) were used as examples, and their performance in the detection of four decomposition products of sulfur hexafluoride (SF6) was investigated. After gas-sensing experiments, values for working temperature, response value, and recovery capability were obtained. A multivariate evaluation method of mixing principal component analysis, information entropy, and variation coefficient was developed to calculate the weights of various indices, and the sensors' optimal working temperatures could be identified quantitatively. Using five variables (working temperature, response value, recovery capability, fluctuation rate, and detection limit), we continued to apply this multivariate evaluation method to calculate the weights and acquire comprehensive scores for the four sensors. Finally, these scores were used to identify the optimal materials for detecting SF6 decomposition products. This procedure has the potential for selecting the best sensors for other gases.

Hydrophobic Ionic Liquid Gel-Based Triboelectric Nanogenerator: Next Generation of Ultrastable, Flexible, and Transparent Power Sources for Sustainable Electronics.

Wearable devices have become a research hotspot due to their prospective applications in wireless sensor networks and the Internet of Things. However, these technologies demand the generation of new power sources, which are efficient, flexible, sustainable, and stable. Triboelectric nanogenerators (TENGs), as a new type of power supply, have been widely studied for environmental energy harvesting and self-powered sensing; however, they have vastly limited stretchability, flexibility, and stability. For the first time, we report a single-electrode TENG based on hydrophobic ionic liquid gel, which is simultaneously transparent (average transmittance of 89% for visible light), stretchable (400%), and has super-stability-up to 3 months in various weather conditions (from -25 to +60 °C and humidity up to 80%). This TENG was used to power a vast range of flexible electronics, including 30 green light-emitting diodes (LEDs), an arch-shaped finger-bending sensor, and a transparent keyboard. This work provides a creative platform to access the next-generation sustainable wearable electronics.

Short period sinusoidal thermal modulation for quantitative identification of gas species.

The field of chemical (gas) sensing has witnessed an unprecedented increase in device sensitivity with single molecule detection now becoming a reality. In contrast to this, the ability to distinguish or discriminate between gas species has lagged behind. This is problematic and results in a high rate of false alarms. Here, we demonstrate a short period sinusoidal thermal modulation strategy to quantitatively and rapidly identify two industrially relevant gases (hydrogen sulfide (H2S) and sulfur dioxide (SO2)) by using a single semiconducting metal oxide sensor device. By applying sinusoidal heating voltages with a fixed short period, we were able to simultaneously obtain distinct patterns of dynamic responses. These characteristic patterns were adopted to build and validate a gas recognition library. Our approach does not rely on large-scale sensor arrays and complex algorithms and is amenable for real-time and low-power gas monitoring.

Partial Discharge Recognition with a Multi-Resolution Convolutional Neural Network.

Partial discharge (PD) is not only an important symptom for monitoring the imperfections in the insulation system of a gas-insulated switchgear (GIS), but also the factor that accelerates the degradation. At present, monitoring ultra-high-frequency (UHF) signals induced by PDs is regarded as one of the most effective approaches for assessing the insulation severity and classifying the PDs. Therefore, in this paper, a deep learning-based PD classification algorithm is proposed and realized with a multi-column convolutional neural network (CNN) that incorporates UHF spectra of multiple resolutions. First, three subnetworks, as characterized by their specified designed temporal filters, frequency filters, and texture filters, are organized and then intergraded by a fully-connected neural network. Then, a long short-term memory (LSTM) network is utilized for fusing the embedded multi-sensor information. Furthermore, to alleviate the risk of overfitting, a transfer learning approach inspired by manifold learning is also present for model training. To demonstrate, 13 modes of defects considering both the defect types and their relative positions were well designed for a simulated GIS tank. A detailed analysis of the performance reveals the clear superiority of the proposed method, compared to18 typical baselines. Several advanced visualization techniques are also implemented to explore the possible qualitative interpretations of the learned features. Finally, a unified framework based on matrix projection is discussed to provide a possible explanation for the effectiveness of the architecture.