Small Devices Research Articles

Development of blue-light GaN based micro light-emitting diodes using ion implantation technology

This study fabricated 10 μm chip size μLEDs of blue-light GaN based epilayers structure with different mesa processes using dry etching and ion implantation technology. Two ion sources, As and Ar, were applied to implant into the LED structure to achieve material isolation and avoid defects on the mesa sidewall caused by the plasma process. Excellent turn-on behavior was obtained in both ion-implanted samples, which also exhibited lower leakage current compared to the sample fabricated by the dry etching process. Additionally, lower dynamic resistance (Rd) and series resistance (Rs) were obtained with Ar implantation, leading to a better wall-plug efficiency of 10.66% in this sample. Consequently, outstanding external quantum efficiency (EQE) values were also present in both implant samples, particularly in the sample implanted with Ar ions. This study proves that reducing defects on the mesa sidewall can further enhance device properties by suppressing non-radiative recombination behavior in small chip size devices. Overall, if implantation is used to replace the traditional dry etching process for mesa fabrication, the ideality factor can decrease from 11.89 to 2.2, and EQE can improve from 8.67 to 11.03%.

Tracking Unique Device Identifiers (UDIs) of Mini Fragment Implants with a Novel Optical Imaging System

Background Small and mini fragment implantable medical devices (0.5 – 4.4mm) such as plates and screws that are placed into surgical trays pose a challenge to unique device identification (UDI) and tracking because they are difficult to directly mark, and often separated from labeling prior to reaching the point of care. Our objective was to demonstrate a novel optical system’s ability to track the unique identities of these small implants. Methods We performed a series of simulated craniotomy surgeries involving implants as small as 1.5mm in size, representing 13 different products from two manufacturers, to test whether a commercially available optical system (QuanTEK, Covisus, Inc.) could accurately track all implants through these simulations. The system was used to capture the unique surface texture of 236 implants at a micrometer scale and convert this to a unique “fingerprint” (vTag) for each item. Implants were placed in surgical trays, and these trays were subjected to a series of 16 simulated surgeries. After each surgery, trays were scanned and identified to determine which had been used, moved, or added. Results Post-surgical scans accurately identified the location and unique identity of 100% of implants (953 out of 953 times; 853 screws, 62 plates, 38 burr hole covers scanned; 95% confidence interval = 99.6 to 100%). Conclusions Results demonstrate that under simulated conditions, the system was able to register and verify the unique identities of mini fragment implants through surgical procedures with 100% accuracy. This technology could therefore be used to finally fulfill the goal of providing hospitals and supply chain management a solution to tracking the full UDI of all implantable medical devices used in the operating room, including the very smallest devices.

Competing technologies: determining the geographical origin of strawberries (Fragaria × ananassa) using laboratory based near-infrared spectroscopy compared to a simple portable device.

The application and development of fast and simple screening methods for the authentication of foods has increased continuously in recent years. A widely used analytical technique is Fourier transform near-infrared spectroscopy (FT-NIR). Despite the simple application of FT-NIR analysis, the analyses are usually carried out on benchtop devices in the laboratory. However small, inexpensive and mobile NIR devices could be used on-site. Despite the simple use of FT-NIR analysis, the examinations are usually carried out on a stationary benchtop device in a laboratory. However, in order to be able to perform the application directly on site, the application of small, cost-effective and mobile NIR devices for food analysis is crucial. In this study, both, a benchtop NIR instrument and a handheld NIR device with a lower resolution and analyzed wavenumber range were applied for the differentiation of strawberries from different geographical origins. Distinguishing German and non-German strawberries using linear discriminant analysis (LDA) yielded an accuracy of 91.9% and 84.0% using the benchtop and the handheld devices, respectively. Relevant variables could be assigned to lipids, carbohydrates and proteins. Overall, our study demonstrated for the first time that analyzing the geographical origin of strawberries using NIR spectroscopy is also possible by means of a handheld device.

LOGIC: LLM-originated guidance for internal cognitive improvement of small language models in stance detection.

Stance detection is a critical task in natural language processing that determines an author's viewpoint toward a specific target, playing a pivotal role in social science research and various applications. Traditional approaches incorporating Wikipedia-sourced data into small language models (SLMs) to compensate for limited target knowledge often suffer from inconsistencies in article quality and length due to the diverse pool of Wikipedia contributors. To address these limitations, we utilize large language models (LLMs) pretrained on expansive datasets to generate accurate and contextually relevant target knowledge. By providing concise, real-world insights tailored to the stance detection task, this approach surpasses the limitations of Wikipedia-based information. Despite their superior reasoning capabilities, LLMs are computationally intensive and challenging to deploy on smaller devices. To mitigate these drawbacks, we introduce a reasoning distillation methodology that transfers the reasoning capabilities of LLMs to more compact SLMs, enhancing their efficiency while maintaining robust performance. Our stance detection model, LOGIC (LLM-Originated Guidance for Internal Cognitive improvement of small language models in stance detection), is built on Bidirectional and Auto-Regressive Transformer (BART) and fine-tuned with auxiliary learning tasks, including reasoning distillation. By incorporating LLM-generated target knowledge into the inference process, LOGIC achieves state-of-the-art performance on the VAried Stance Topics (VAST) dataset, outperforming advanced models like GPT-3.5 Turbo and GPT-4 Turbo in stance detection tasks.

Self-encapsulation ultra-soft micro-channel with high thermal conductivity and passive radiation cooling

Oriented towards the industrialization of micro-electronic products, micro-channels suitable for micro and small electronic devices are committed to solving the issue of efficient thermal dissipation in the systems. Accordingly, research on integrating multifunctional thermal management composite materials for designing micro-channels has become a hot development trend. Notably, the design concept of efficient thermal dissipation micro-channel with the dual functional synergy of high thermal conductivity and passive radiation cooling was advanced. The compound of high thermal conductivity hexagonal boron nitride (h-BN) and high-elastic thermoplastic polyurethane (TPU) entrusts the micro-channel with a superb substrate with flexibility, stretchability, hydrophobicity, and high thermal conductivity. Draw support from a zero-energy consumption and environmentally friendly passive radiation cooling strategy, the micro-channel with a polyvinylidene fluoride/cellulose acetate (PVDF/CA) nanofiber film acquires an ultra-high reflectivity of up to 99.50 % (0.2–2.5 μm) and a high emissivity of 94.81 % (8–13 μm). The programmable patterned graphene oxide (GO) ink is assisted with high-viscosity natural Gleditsia sinensis polysaccharide (GSP) through 3D printing. Ultimately, a self-encapsulated, flexible, high thermal conductivity (0.42 W m-1K−1), passive radiation cooling micro-channel accumulated a temperature difference of 10.76 °C, potentially making a promising thermal management micro-channel system for development.

Recent Advancements in Bioelectronic Medicine: A Review.

Bioelectronic medicine is a multidisciplinary field that combines molecular medicine, neurology, engineering, and computer science to design devices for diagnosing and treating diseases. The advancements in bioelectronic medicine can improve the precision and personalization of illness treatment. Bioelectronic medicine can produce, suppress, and measure electrical activity in excitable tissue. Bioelectronic devices modify specific neural circuits using electrons rather than pharmaceuticals and uses of bioelectronic processes to regulate the biological processes underlining various diseases. This promotes the potential to address the underlying causes of illnesses, reduce adverse effects, and lower costs compared to conventional medication. The current review presents different important aspects of bioelectronic medicines with recent advancements. The area of bioelectronic medicine has a lot of potential for treating diseases, enabling non-invasive therapeutic intervention by regulating brain impulses. Bioelectronic medicine uses electricity to control biological processes, treat illnesses, or regain lost capability. These new classes of medicines are designed by the technological developments in the detection and regulation of electrical signaling methods in the nervous system. Peripheral nervous system regulates a wide range of processes in chronic diseases; it involves implanting small devices onto specific peripheral nerves, which read and regulate the brain signaling patterns to achieve therapeutic effects specific to the signal capacity of a particular organ. The potential for bioelectronic medicine field is vast, as it investigates for treatment of various diseases, including rheumatoid arthritis, diabetes, hypertension, paralysis, chronic illnesses, blindness, etc.

Analysis of hyperbolic crystals with non-square lattice for improving acoustic energy harvesting

Abstract With the increase in the production of small and low-power electrical devices, there has been an increased focus on creating a useful power source to replace the battery. The energy contained in acoustic waves is one of the attractive energy sources for powering low-power devices. The design and fabrication of metamaterials is one of the effective methods of harvesting acoustic energy that has recently attracted the attention of many researchers. As is presented in this article, the aim is to design and fabricate a novel metamaterial structure with optimal dimensions to improve acoustic energy harvesting in a specific frequency range using a piezoelectric patch. In this metamaterial, hyperbolic crystals with non-square lattice have been used for the first time. This analysis is simulated using the 3D version of Comsol software 6.0. In addition, artificial neural networks and genetic algorithms were used to select the optimal parameters. The results showed that using the non-square lattice of the hyperbolic crystal, more average energy can be harvested in the frequency range of 3310-4325 Hz than in the metamaterial with the cylindrical crystal. Furthermore, the maximum amount of voltage and power extraction with an optimal electrical resistance of 10 kΩ in the metamaterial with the hyperbolic crystals at a frequency of 3374.71 Hz is equal to 27.26 mV and 74.33 nW, respectively, which is much larger compared to the metamaterial with the cylindrical crystals under the same mass and conditions. The simulation results are compared and validated with the experimental results by fabricating the present metamaterial and conducting laboratory tests.

Reconfigurable logic-in-memory circuits with ferroelectric nanosheet field-effect transistors

Abstract To accommodate the requirements of small device dimensions and the application of ferroelectric field-effect transistors (FeFETs) in logic-in-memory circuits, we realize the reconfigurable logic-in-memory circuits with ferroelectric nanosheet field-effect transistors (FeNSFETs) through simulation. By evaluating the memory window and logic performances of the devices, it is demonstrated that the key to constructing logical functions are the magnitudes of the drain current at program (PGM) and erase (ERS) state when V G = 0 V. We find that appropriately increasing the number of nanosheets can enhance the current at PGM state, and appropriately increasing the write voltage can decrease the current at ERS state, which are both beneficial for the achievement of reconfigurable circuits. Thus, it is necessary to take into consideration the trade-offs between the process complexity, power consumption, and logical function realization. This work contributes to the prospective design for ferroelectric reconfigurable logic-in-memory circuits.

Next-generation hybrid nanogenerators using giant piezoelectric lead-free KNNS composites for sustainable self-powered electronics

This study presents a flexible hybrid nanogenerator that utilizes lead-free KNNS-BF-xBNZ materials integrated with polydimethylsiloxane (PDMS) to enhance energy harvesting performance. The findings demonstrate that by combining piezoelectric and triboelectric effects, the energy conversion efficiency of the nanogenerator is significantly improved, resulting in high output voltage and current, suitable for real-world applications. Specifically, the optimal composition of KNNS-BF-xBNZ ceramics, with x = 0.03 mol.%, yields superior piezoelectric, ferroelectric, and dielectric properties, with remnant polarization (Pr), spontaneous polarization (Ps), and piezoelectric coefficient (d33) values reaching 18.8 μmC/cm², 30.3 μmC/cm², and 358 pC/N, respectively. In the hybrid device, incorporating 15 wt% of KNNS-BF-3BNZ into PDMS resulted in the highest open-circuit voltage (VOC) of 107 V and short-circuit current (ISC) of 4.68 μA. The developed hybrid nanogenerator effectively charges capacitors for energy storage, powers LEDs, and drives small electronic devices, such as watches, showcasing its potential for practical energy harvesting applications. The findings suggest that the integration of KNNS-BF-3BNZ with PDMS provides an efficient and scalable pathway for fabricating high-performance nanogenerators, paving the way for advancements in self-powered devices and sustainable energy solutions.

A machine-learning assisted measurement device for circadian lighting based on spectral sensors

Light has an undeniable impact on the human body, as it can to some extent affect hormone secretion and emotional changes. Spectral power distribution (SPD) is the main indicator for evaluating the quality of light sources, but traditional spectral measurement equipment is bulky and expensive, and cannot be widely used in our daily life. In order to fill this gap, this article designs a low-cost and small lighting measurement device for measuring the circadian lighting, which obtains spectral data from 8 channels in the visible light range through multi-channel spectral sensors. Machine learning methods are used to reconstruct the SPD of 81 wavelength data points, thereby improving the accuracy of designed measurement device. This device can simultaneously achieve real-time measurement of SPD and real-time monitoring of circadian related parameters, and return circadian related parameters (such as circadian action factor, melanopic efficacy of luminous radiation, equivalent melanopic lux, etc.). Results have found that the error of circadian parameters measured by this equipment is less than 5%.

Physics-Informed Neural Networks for Modeling Li-ion Batteries: Solving the Single Particle Model Without Labeled Data

Abstract Li-ion batteries are garnering significant attention due to the electrification of critical sectors. High-fidelity battery cell models have proven effective in assessing performance and optimizing design, alleviating the financial burden associated with extensive experimental procedures. However, the computational costs associated with such simulations can become prohibitive, particularly when numerous iterations are required or when integration into small devices, such as battery management systems, is necessary. To address these challenges and provide an alternative to traditional methods such as finite element and finite volume solvers, we propose the development of an algorithm that utilizes Physics-Informed Neural Networks (PINNs) to solve the Single Particle Model across multiple parameter ranges. A notable advantage of this machine learning approach is its capacity to generate competitive solutions post-training by relying solely on the governing equations, without the necessity for experimental or simulation data. Additionally, the lightweight nature of the model indicates its potential for embedding within small-scale devices.

BN SO27 - Articulative Minimally Invasive Surgery and Placement of Anti-reflux Magnetic Surgical Appliance (LINX)

Abstract Background Gastro-oesophageal reflux disease (GORD) is a condition of prolonged retrograde flow of gastric contents into the oesophagus or structures beyond, causing symptoms such as heartburn and regurgitation.1 Laparoscopic Nissen Fundoplication (LNF) has been the surgical gold standard, however its side effects and technical challenges has limited its use to 1% of the GERD population.2 The use of a magnetic surgical appliance (LINX) has recently emerged as a promising treatment in overcoming the limitations of conventional LNF.3 Literature has shown patients aged less than 45 with satisfactory mean contraction amplitude (MAP) of 30mmHg and typical symptoms have favourable outcomes with LINX.3 Method This is a case of a 35-year-old patient presenting with typical reflux symptoms, with satisfactory MAP and high DeMeester score, patulous gastro-oesophageal junction and no hiatus hernia endoscopically. Steps for LINX placement are described in the video and we demonstrate the use of ArtiSential, an articulating laparoscopic instrument that provides better range of motion and angulation comparable to that of a robotic instrument. Results Using a magnetic surgical appliance (LINX) is superior to LNF through preservation of physiological belching and vomiting, reducing surgical time and duration of hospital stay while also scoring highly on quality of life and patient satisfaction.4 Conclusion We would recommend considering the placement of a LINX device in suitable patients as it provides good outcomes on par with LNF and to consider the use of an articulating instrument (ArtiSential) as it provides the surgeon better control and ease in placing a small device laparoscopically.

A Sub-Channel Spatial Homogeneity-Based Channel Estimation Method for Underwater Optical Densely Arrayed MIMO Systems

The limited surface area and structural constraints of small underwater communication devices necessitate a dense placement of transmitting and receiving array elements in optical multiple-input multiple-output (MIMO) systems. The compact layout leads to the formation of sub-channels that exhibit notable spatial correlation and a tendency toward homogeneity. Although sub-channel spatial homogeneity (SSH) may diminish the communication capacity of MIMO systems, it provides a significant advantage by reducing the pilot overhead. In this study, we exploit the inherent SSH and the natural time-domain sparsity of channel impulse response (CIR) in the underwater optical densely arrayed MIMO (UODA-MIMO) system to propose an innovative SSH-based channel estimation (SSH-CE) method. We model the underwater optical CIR at Gbaud rates and integrate it with SSH characteristics. This approach transforms the reconstruction targets of compressive sensing (CS) from conventional CIR samples to prior CIR model parameters and the fitting residuals of the homogeneous sub-channels, reducing the pilot overhead. The simulation results of photon tracing for UODA-MIMO sub-channels in turbid harbor water indicate a monotonic, exponential decay in CIR at Gbaud rates, with transmission delays exceeding 5 nanoseconds for distances over 8 m. Moreover, the correlation coefficients among sub-channels reach a minimum of 0.975, confirming the presence of SSH in UODA-MIMO systems. In comparison to existing CS methods that rely on known sparsity, sparsity adaptation, and the structural sparsity of MIMO channels, the SSH-CE method achieves a lower degree of sparsity in reconstruction targets and a reduced lower bound for pilot requirements under the SPARK criterion. Specifically, the SSH-CE method achieves a reduction in the pilot overhead for reconstructing Nt sub-channels of K-sparse to 2Nt irrespective of CIR residual compensation.

Source-detector trajectory optimization for FOV extension in dental CBCT imaging

In dental imaging, Cone Beam Computed Tomography (CBCT) is a widely used imaging modality for diagnosis and treatment planning. Small dental scanning units are the most popular due to their cost-effectiveness. However, these small systems have the limitation of a small field of view (FOV) as the source and detector move at a limited angle in a circular path. This often limits the FOV size. In this study, we addressed this issue by modifying the source-detector trajectory of the small dental device. The main goal of this study was to extend the FOV algorithmically by acquiring projection data with optimal projection angulation and isocenter location rather than upgrading any physical parts of the device. A novel algorithm to implement a Volume of Interest (VOI) guided trajectory is developed in this study based on the small dental imaging device's geometry. In addition, this algorithm is fused with a previously developed off-axis scanning method which uses an elliptical trajectory, to compensate for the existing constraints and to further extend the FOV. A comparison with standard circular trajectory is performed. The FOV of such a standard trajectory is a circle of 11 cm diameter in the axial plane. The proposed novel trajectory extends the FOV significantly and a maximum FOV of 19.5 cm is achieved with the Structural Similarity Index Measure (SSIM) score ranging between (≈98-99%) in different VOIs. The study results indicate that the proposed source-detector trajectory can extend dental imaging FOV and increase imaging performance, which ultimately results in more precise diagnosis and enhanced patient outcomes.

Phase change thermal interface materials with interface adaptability and self-healing properties

Thermal stress resulting from excessive temperatures is a major cause of electronic device failure. In this work, with easy installation and good interface adaptability, Phase Change Thermal Interface Materials (PCTIMs) which possess high thermal conductivity were prepared. By incorporating phase change material stearic acid (SA) into the thermal interface material, the instantaneous heat absorption during the solid-liquid phase transition of SA effectively alleviates the problem of instantaneous high heat flux impacting electronic devices. Additionally, the solid-liquid transition reduces the modulus of TIMs, thereby minimizing the contact thermal resistance between the heat source and the heat sink during mechanical installation. To further enhance performance, the thermal interface material utilizes a dynamically cross-linked polyolefin elastomer (POE) with borate bonds, which effectively restricts the flow of SA even at its phase change point due to the three-dimensional cross-linked framework. By constructing a thermal conductive network using carbon fibers and aluminum nitride of different dimensions, the thermal conductivity of the thermal interface material reached 1.82 W∙m−1K−1 with a filler content of only 30 vol % . At 70 °C, with a force of 50 N applied to a sample area of 400 mm², the contact thermal resistance was only 2.39×10−4 K∙m2W−1. Furthermore, the PCTIMs exhibits excellent self-healing ability under thermal conditions, assuring the permanent encapsulation of small electronic devices.

Oxygen-vacancy-rich CeO2/LaFeO3 for peroxymonosulfate activation: Singlet oxygen as the main active oxygen to degrade organic pollutants in high-salinity environments

Due to the quenching effect of typical anions on free radicals, free radical based advanced oxidation processes have always been difficult to effectively treat high-salinity organic wastewater. In this work, an oxygen-vacancy-rich ceria-perovskite composite (CeO2/LaFeO3) was successfully prepared, and the oxygen vacancy became the active sites for activating peroxomonosulfate to produce a large amount of singlet oxygen (1O2) as the main reactive oxygen species (ROS) for tetracycline degradation in high-salinity organic wastewater. In the typical high-salinity environments (30000–70000 mg·L−1, NaCl, Na2SO4, NaNO3, Na2CO3, NaH2PO4, or NaBr), CeO2/LaFeO3 can achieve more than 95 % removal of TC within 40 min, and the 40 min removal rate of TC in a variety of mixed salt environments is also maintained above 94 %. Common cations (K+, Fe3+, Mn2+, Ca2+, Mg2+, Cu2+, and Ba2+) were also not found to have a significant negative effect on TC removal. CeO2/LaFeO3 can completely remove TC within 40 min in 5 cycles, the granular CeO2/LaFeO3 immobilized in a self-made small device can also achieve continuous removal of more than 96.6 % of TC within 420 min. The results of pea seed germination test showed that CeO2/LaFeO3 as catalyst for heterogeneous water treatment would not bring additional environmental risks.

Aromatic carboxyl acid regulated nanoparticle deposition and passivation of tin oxide for high performance perovskite solar cells

The composition and nano particle agglomeration of hydrolyzed species in chemical bath deposition (CBD) plays a key role in obtaining efficient SnO2 film for high performance perovskite solar cells (PSCs). In this work, the aromatic acids with varied carboxyl groups were investigated to regulate the nano particle deposition and passivate the buried SnO2/perovskite interface. The quasi in-situ dynamic light scattering and Zeta potential results indicated that the nano particle agglomeration with trimesic acid (TMA) was significantly refined throughout the whole deposition process. The TMA-SnO2 achieved an ideal energy band alignment with perovskite and released the internal residual strain, promoting the growth and crystallization of the perovskite film due to the corrdination of carboxyl groups. As a result, the interface defects were effectively passivated with enhanced efficiency and stability. The small area device based on TMA-SnO2 obtained an efficiency of 25.07 %. The devices with an enlarged area of 1.4 cm2 and the 5x5 cm2 mini-module (active area 10.054 cm2) showed impressive PCEs of 23.93 % and 22.40 %, respectively. Furthermore, the unencapsulated devices exhibit enhanced long-term stability, maintaining 80 % and 90 % of the initial efficiencies under 80 ± 5°C thermal annealing in nitrogen for 1176 h and in air condition for 3224 h, respectively.

Does preprocedural ultrasound prior to lumbar neuraxial anesthesia or analgesia increase first-pass success in adults with obesity? A systematic review.

Preprocedural ultrasound (PPU) reduces the risk of technical failure in non-obese patients and when technical difficulty is predicted. We conducted this review to determine if PPU improves first-pass needle insertion success for neuraxial anesthesia in patients with obesity. We conducted a systematic review without meta-analysis, due to the small number of included studies. The study protocol was registered (PROSPERO: CRD42022368271). We conducted searches in MEDLINE, Embase, PubMed, and Cochrane Library from January 1, 1980 to October 1, 2022 for peer-reviewed randomized controlled or observational studies comparing PPU versus landmark techniques in patients with body mass index >30 kg/m2. The quality of evidence was assessed using the revised Cochrane risk-of-bias tool for randomized trials and Grading of Recommendations Assessment, Development, and Evaluation approach. There were nine randomized controlled studies, comprising 866 patients having lumbo-sacral neuraxial techniques. Three studies utilized a small handheld ultrasound device called Accuro™ and six utilized non-handheld ultrasound devices. Certainty of evidence was low for improving the first-pass success rate. There was evidence (moderate certainty) that PPU decreased number of passes, increased first insertion attempt success, and reduced number of insertion attempts. There was no evidence that PPU affected identifying time, needling time, or overall procedural time. There was no evidence that PPU influenced procedural failure rate (very low certainty evidence) and insufficient evidence to suggest that artificial intelligence-supported handheld devices were superior to conventional ultrasound devices. In patients with obesity, there is evidence of very-low to moderate certainty that PPU improves markers of insertion success, with no indication of increased adverse effects. PPU should be used to reduce attempts. Further studies adhering to standardized outcome definitions are required for definitive recommendations. The study protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO: CRD42022368271).

Enhanced performance of TENG through graphene oxide and transition layer coupling: Achieving green energy harvesting and powering wearable devices

Triboelectric nanogenerators (TENGs) offer a novel approach to harvesting green energy due to their simple structure, low manufacturing cost, and suitability for collecting low-frequency mechanical energy. Previous research has primarily focused on the impact of single factors on the electrical output of TENGs, such as the generation, storage, or loss of triboelectric charges. In this study, we enhanced the generation of triboelectric charges by introducing graphene oxide (GO) and reduced charge loss through a Polyimide (PI) film as a transition layer. By combining both, we maximized the electrical output performance of the TENG. The ISC, VOC and charge of the optimized TL-TENG are 33.23 μA, 318.52 V and 152.03 nC, respectively, with a maximum output power of 2.6 W/m2. The results indicate that the performance enhancement from the transition layer exceeded that of GO alone, possibly because it reduced the electron drift rate by 97.37 %. Additionally, the TL-TENG demonstrated excellent mechanical durability, with ISC decrease of only 2.25 % after 5×104 contact-separation cycles. The device also showed effective metal anti-corrosion properties and could harvest energy from mechanical vibrations and human motion, powering at least 107 LEDs and supporting small electronic devices such as digital watches. The outcomes of this study hold promise for providing reliable energy sources for wearable devices and offer theoretical guidance for designing high performance TENGs.

Do-it-yourself flavored capsule cigarettes: Exploiting potential regulatory loopholes?

Capsule cigarettes allow users to crush liquid-filled capsules to release flavors into cigarettes' filters. New devices are emerging across the globe that allow people who smoke to circumvent tobacco flavor restrictions via injectable capsules. This study examined TikTok videos marketing flavored capsule injector devices. TikTok videos (n = 832) posted worldwide between July 6, 2021, and December 28, 2023, that used hashtags #injectorflavor, #flavourclickball, #flavorball, and #injectorballcigarette were collected using a TikTok application programing interface. A codebook was developed using a systematic iterative approach, identifying six codes: flavor capsules, promotes flavors (i.e., fruit, mint or menthol flavors, non-alcoholic drinks, alcoholic drinks), demonstrates how to use or refill large injector devices, demonstrates how to use small convenient devices, includes music (any or English-language). Two independent coders annotated all videos. Overall, 88.3% (n=735) of the videos displayed flavor capsules and had been viewed more than 72 million times. Half (51.6%) of the videos demonstrated how to use large box-shaped devices to inject capsules into the filter of a cigarette, and 15.0% of the videos showed how to do this with smaller, more convenient devices. Flavors including fruit (35.5%), menthol/mint (27.8%), non-alcoholic drinks (21.9%), and alcoholic drinks (11.6%) were used to promote these capsules. Most videos (85.6%) were uploaded by sellers on "TikTok shop." TikTok accounts are promoting injectable capsule devices that circumvent flavored tobacco sales restrictions. Policy makers, tobacco control advocates, and public health practitioners should be aware of such marketing to inform regulation and develop prevention strategies. Our findings identified an emerging product that can encourage circumvention of flavor restriction policies. Regulators, policy makers, public health practitioners, researchers, and advocates should be aware of such products to inform regulation and develop prevention strategies. Given the potential for these products to reduce the intended effects of flavored tobacco sales restrictions, policy makers must be poised to address materials that consumers use to create their own flavored tobacco products, including flavor capsules designed to be inserted into cigarettes.