Elasto-inertial microfluidic separation of microspheres with submicron resolution at high-throughput

Elasto-inertial microfluidic separation offers many advantages including high throughput and separation resolution. Even though the separation efficiency highly depends on precise control of the flow conditions, no concrete guidelines have been reported yet in elasto-inertial microfluidics. Here, we propose a dimensionless analysis for precise estimation of the microsphere behaviors across the interface of Newtonian and viscoelastic fluids. Reynolds number, modified Weissenberg number, and modified elastic number are used to investigate the balance between inertial and elastic lift forces. Based on the findings, we introduce a new dimensionless number defined as the width of the Newtonian fluid stream divided by microsphere diameter. The proposed dimensionless analysis allows us to predict whether the microspheres migrate across the co-flow interface. The theoretical estimation is found to be in good agreement with the experimental results using 2.1- and 3.2-μm-diameter polystyrene microspheres in a co-flow of water and polyethylene oxide solution. Based on the theoretical estimation, we also realize submicron separation of the microspheres with 2.1 and 2.5 μm in diameter at high throughput, high purity (>95%), and high recovery rate (>97%). The applicability of the proposed method was validated by separation of platelets from similar-sized Escherichia coli (E.coli).

Twisted fiber microfluidics: a cutting-edge approach to 3D spiral devices

The development of 3D spiral microfluidics has opened new avenues for leveraging inertial focusing to analyze small fluid volumes, thereby advancing research across chemical, physical, and biological disciplines. While traditional straight microchannels rely solely on inertial lift forces, the novel spiral geometry generates Dean drag forces, eliminating the necessity for external fields in fluid manipulation. Nevertheless, fabricating 3D spiral microfluidics remains a labor-intensive and costly endeavor, hindering its widespread adoption. Moreover, conventional lithographic methods primarily yield 2D planar devices, thereby limiting the selection of materials and geometrical configurations. To address these challenges, this work introduces a streamlined fabrication method for 3D spiral microfluidic devices, employing rotational force within a miniaturized thermal drawing process, termed as mini-rTDP. This innovation allows for rapid prototyping of twisted fiber-based microfluidics featuring versatility in material selection and heightened geometric intricacy. To validate the performance of these devices, we combined computational modeling with microtomographic particle image velocimetry (μTPIV) to comprehensively characterize the 3D flow dynamics. Our results corroborate the presence of a steady secondary flow, underscoring the effectiveness of our approach. Our 3D spiral microfluidics platform paves the way for exploring intricate microflow dynamics, with promising applications in areas such as drug delivery, diagnostics, and lab-on-a-chip systems.

A value sharing method for heterogeneous energy communities archetypes

A novel value sharing (VS) method is proposed that distributes the energy communities (ECs) value based on the individual contribution to the total surplus/deficit. It considers the load-generation profile of each EC member and allocates a higher share to members who contribute to the EC revenue. The lowest share is received by the members with the highest demand that has to be supplied from the shared generation or from the grid, contributing to the EC cost. Several allocation methods are compared using the fairness index (FI), and, for setting the strategy of the EC using a decision model, as the strategy may vary over time, an objective function is defined as a combination between FI and self-sufficiency index using weighting coefficients. The methodology is implemented as an algorithm that automatically calculates and distributes the gain. For the proposed VS method, the FI is between 0.81 and 1.

Wireless sensing in high-speed railway turnouts with battery-free materials and devices

Sustainable energy technologies enable solutions for future green transportation. Realizing status awareness and effective wireless monitoring of rail transit infrastructure in dark environments, narrow spaces, and unattended conditions has always been a challenge. This study presents a battery-free vibration-powered force sensing system (VFSS) that integrates structural loading, sensing, and energy harvesting. The proposed VFSS can sense a switching force of up to 4 kN in the high-speed railway turnout section, deliver 6.9 mW of average power over a broad frequency band (ca. 500 Hz) under a vibration amplitude of 0.2 mm, and realize wireless data transmission. Through a cross-scale design from the device to the system, we demonstrate an all-in-one smart component that features stress flow, signal flow, and energy flow, which could highlight the implementation of energy structures in the future.

A single-building damage detection model based on multi-feature fusion: A case study in Yangbi

Accurate and effective identification, determination of the location, and classification of damaged buildings are essential after destructive earthquakes. However, the accuracy of image change detection is limited because of the many texture features and changes in non-building information. In this context, a model for single-building damage detection based on multi-feature fusion is proposed. First, the normalized Digital Surface Model (nDSM) was extracted from the DSM through iterative filtering and point cloud thinning, followed by the extraction of building contour information. Next, single-building images were generated from different data sources through the region of interest (ROI), and the optimal texture feature parameters were extracted for fusion. Afterward, principal-component analysis (PCA) was conducted to suppress multi-feature correlation-induced information redundancy. Finally, the damage to buildings was quantitatively evaluated, and the model was compared with 13 models. The results confirmed the practicability of the model for the Yangbi MS6.4 and Honghe MS5.0 earthquakes.

World's largest natural gas leak from nord stream pipeline estimated at 478,000 tonnes

Methane is a potent heat trapping gas believed to account for 30% of the observed global warming to-date. At a capacity of 110 bcm/year, the Nord Stream (NS) pipeline corridor measuring 1,153mm in internal diameter and stretching 1,224km from Russia to Germany is the biggest in the world. The explosions that NS sustained in September, 2022, in the Baltic Sea, have unleashed the largest single methane gas source in recent memory. Over the course of 7 days, our transient multiphase pipeline model has estimated that the gas leaks from 3 lines pumped 478,000 tonnes of methane into the atmosphere. A range of pipeline shut-in pressures as a function of leakage time deduced an envelope of gas volume that matched the timeline of observed outflows. Interestingly, the methane gas that escaped from the damaged threads amounted to the CO2 equivalent emitted by concrete sufficient to build about 27 Burj Khalifa towers.

Techno-economic analysis of underground hydrogen storage in Europe

Hydrogen storage is crucial to developing secure renewable energy systems to meet the European Union's 2050 carbon neutrality objectives. However, a knowledge gap exists concerning the site-specific performance and economic viability of utilizing underground gas storage (UGS) sites for hydrogen storage in Europe. We compile information on European UGS sites to assess potential hydrogen storage capacity and evaluate the associated current and future costs. The total hydrogen storage potential in Europe is 349 TWh of working gas energy (WGE), with site-specific capital costs ranging from $10 million to $1 billion. Porous media and salt caverns, boasting a minimum storage capacity of 0.5 TWh WGE, exhibit levelized costs of $1.5 and $0.8 per kilogram of hydrogen, respectively. It is estimated that future levelized costs associated with hydrogen storage can potentially decrease to as low as $0.4 per kilogram after three experience cycles. Leveraging these techno-economic considerations, we identify suitable storage sites.

Laser-assisted direct roller imprinting of large-area microstructured optical surfaces

In this study, a high-throughput fabrication method called laser-assisted direct roller imprinting (LADRI) was developed to lower the cost of nanoimprinting large-area polymer films and to address problems associated with nanoimprinting, namely, microstructural damage and precision in flatness of entire film. With LADRI, the laser directly heats the microstructured surface of the roller mold, which heats and melts the surface of a polymethyl methacrylate (PMMA) film to replicate the microstructures on the mold rapidly. In this study, the effects of laser power density, scanning speed, size of the microstructures, and contact pressure on the replication speed were investigated experimentally. The replication speed increased as the power and scanning speed increased. However, because the film required heating until it filled the entire depth of the microstructure, an appropriate replication speed was necessary. This result was supported by simulation of the temperature distribution inside the mold and the PMMA using transient heat conduction analyses. To demonstrate the applications of LADRI, two different optical surfaces were replicated: an antireflection (AR) structure with conical structures sized several hundred nanometers and a light-extraction structure with a microlens array (MLA) comprising 10 μm lenses, for display and illumination, respectively. The replication degree of the MLA was governed by the contact pressure. Polymer flow simulation indicated that the heat conduction and flow speeds of the melted PMMA surface were comparable within several tens of micrometers. In addition, the reflectivity of the AR structure decreased from 4 to 0.5%, and the light intensity of the light-extraction structure increased by a factor of 1.47.

An in vitro demonstration of a passive, acoustic metamaterial as a temperature sensor with mK resolution for implantable applications

Wireless medical sensors typically utilize electromagnetic coupling or ultrasound for energy transfer and sensor interrogation. Energy transfer and management is a complex aspect that often limits the applicability of implantable sensor systems. In this work, we report a new passive temperature sensing scheme based on an acoustic metamaterial made of silicon embedded in a polydimethylsiloxane matrix. Compared to other approaches, this concept is implemented without additional electrical components in situ or the need for a customized receiving unit. A standard ultrasonic transducer is used for this demonstration to directly excite and collect the reflected signal. The metamaterial resonates at a frequency close to a typical medical value (5 MHz) and exhibits a high-quality factor. Combining the design features of the metamaterial with the high-temperature sensitivity of the polydimethylsiloxane matrix, we achieve a temperature resolution of 30 mK. This value is below the current standard resolution required in infrared thermometry for monitoring postoperative complications (0.1 K). We fabricated, simulated, in vitro tested, and compared three acoustic sensor designs in the 29-43 °C (~302-316 K) temperature range. With this concept, we demonstrate how our passive metamaterial sensor can open the way toward new zero-power smart medical implant concepts based on acoustic interrogation.

Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale. Using this numerical tool, we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to microcapillary. First, using high-speed imaging, we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential (MCF-7 (less invasive), SKBR-3 (medium-high invasive), and MDA-MB-231 (highly invasive)) in terms of their entry time to a constricted microfluidic channel. We observed that MDA-MB-231, that has the highest metastatic potential, is the most deformable cell among the three. Then, by focusing on this cell line, experimental measurements were expanded to two more constricted microchannel dimensions. The experimental deformability data in three constricted microchannel sizes for various cell sizes, enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line (MDA-MB-231). Our results show that the identified parameters depend on the cell size, suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of cells. As the numerical results show, the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimental data.

Acoustofluidic separation of prolate and spherical micro-objects

Most microfluidic separation techniques rely largely on object size as a separation marker. The ability to separate micro-objects based on their shape is crucial in various biomedical and chemical assays. Here, we develop an on-demand, label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and torque. The freely rotating non-spherical micro-objects were aligned under the progressive acoustic field by the counterrotating radiation torque, and the major axis of the prolate ellipsoids was parallel to the progressive wave propagation. The specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave propagation. As a consequence, the acoustic backscattering decreased, resulting in a decreased magnitude of the radiation force. Through the variation in radiation force, which depended on the micro-object morphology enabled the acoustofluidic shape-based separation. We conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method. A series of experiments with polystyrene microspheres, prolate ellipsoids, and peanut-shaped microparticles were performed for validation. Through quantitative analysis of the separation efficiency, we confirmed the high purity and high recovery rate of the proposed acoustofluidic shape-based separation of micro-objects. As a bioparticle, we utilize Thalassiosira eccentrica to perform shape-based separation, as the species has a variety of potential applications in drug delivery, biosensing, nanofabrication, bioencapsulation and immunoisolation.

Systematic engineering enables efficient biosynthesis of L-phenylalanine in E. coli from inexpensive aromatic precursors

BACKGROUND

L-phenylalanine is an essential amino acid with various promising applications. The microbial pathway for L-phenylalanine synthesis from glucose in wild strains involves lengthy steps and stringent feedback regulation that limits the production yield. It is attractive to find other candidates, which could be used to establish a succinct and cost-effective pathway for L-phenylalanine production. Here, we developed an artificial bioconversion process to synthesize L-phenylalanine from inexpensive aromatic precursors (benzaldehyde or benzyl alcohol). In particular, this work opens the possibility of L-phenylalanine production from benzyl alcohol in a cofactor self-sufficient system without any addition of reductant.

RESULTS

The engineered L-phenylalanine biosynthesis pathway comprises two modules: in the first module, aromatic precursors and glycine were converted into phenylpyruvate, the key precursor for L-phenylalanine. The highly active enzyme combination was natural threonine aldolase LtaEP.p and threonine dehydratase A8HB.t, which could produce phenylpyruvate in a titer of 4.3 g/L. Overexpression of gene ridA could further increase phenylpyruvate production by 16.3%, reaching up to 5 g/L. The second module catalyzed phenylpyruvate to L-phenylalanine, and the conversion rate of phenylpyruvate was up to 93% by co-expressing PheDH and FDHV120S. Then, the engineered E. coli containing these two modules could produce L-phenylalanine from benzaldehyde with a conversion rate of 69%. Finally, we expanded the aromatic precursors to produce L-phenylalanine from benzyl alcohol, and firstly constructed the cofactor self-sufficient biosynthetic pathway to synthesize L-phenylalanine without any additional reductant such as formate.

CONCLUSION

Systematical bioconversion processes have been designed and constructed, which could provide a potential bio-based strategy for the production of high-value L-phenylalanine from low-cost starting materials aromatic precursors.

A C-shaped hinge for displacement magnification in MEMS rotational structures

The design, analysis, fabrication, and characterization of two distinct MEMS rotational structures are provided; these structures include a classical symmetrical lancet structure and a novel symmetrical C-shaped structure provided with a tilted arm, and both are actuated by thermal actuators. Our proposed C-shaped structure implemented a curved beam mechanism to enhance the movement delivered by the thermal actuators. The geometrical parameters of our proposed device were optimized using the design of experiment (DOE) method. Furthermore, the analytical modeling based on Castigliano's second theorem and the simulations based on the finite element method (FEM) were used to predict the behavior of the symmetrical C-shaped structure; the results were in good agreement with each other. The MEMS-based rotational structures were fabricated on silicon-on-insulator (SOI) wafers using bulk micromachining technology and deep reactive ion etching (DRIE) processes. The fabricated devices underwent experimental characterization; our results showed that our proposed MEMS rotational structure exhibited a 28% improvement in the delivered displacement compared to the symmetrical lancet structure. Furthermore, the experimental results showed good agreement with those obtained from numerical analysis. Our proposed structures have potential applications in a variety of MEMS devices, including accelerometers, gyroscopes, and resonators, due to their ability to maximize displacement and thus enhance sensitivity.

Enhancing single-cell encapsulation in droplet microfluidics with fine-tunable on-chip sample enrichment

Single-cell encapsulation in droplet microfluidics is commonly hindered by the tradeoff between cell suspension density and on-chip focusing performance. In this study, we introduce a novel droplet microfluidic chip to overcome this challenge. The chip comprises a double spiral focusing unit, a flow resistance-based sample enrichment module with fine-tunable outlets, and a crossflow droplet generation unit. Utilizing a low-density cell/bead suspension (2 × 106 objects/mL), cells/beads are focused into a near-equidistant linear arrangement within the double spiral microchannel. The excess water phase is diverted while cells/beads remain focused and sequentially encapsulated in individual droplets. Focusing performance was assessed through numerical simulations and experiments at three flow rates (40, 60, 80 μL/min), demonstrating successful focusing at 40 and 80 μL/min for beads and cells, respectively. In addition, both simulation and experimental results revealed that the flow resistance at the sample enrichment module is adjustable by punching different outlets, allowing over 50% of the aqueous phase to be removed. YOLOv8n-based droplet detection algorithms realized the counting of cells/beads in droplets, statistically demonstrating single-cell and bead encapsulation rates of 72.2% and 79.2%, respectively. All the results indicate that this on-chip sample enrichment approach can be further developed and employed as a critical component in single-cell encapsulation in water-in-oil droplets.

Aerosol jet printing of surface acoustic wave microfluidic devices

The addition of surface acoustic wave (SAW) technologies to microfluidics has greatly advanced lab-on-a-chip applications due to their unique and powerful attributes, including high-precision manipulation, versatility, integrability, biocompatibility, contactless nature, and rapid actuation. However, the development of SAW microfluidic devices is limited by complex and time-consuming micro/nanofabrication techniques and access to cleanroom facilities for multistep photolithography and vacuum-based processing. To simplify the fabrication of SAW microfluidic devices with customizable dimensions and functions, we utilized the additive manufacturing technique of aerosol jet printing. We successfully fabricated customized SAW microfluidic devices of varying materials, including silver nanowires, graphene, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). To characterize and compare the acoustic actuation performance of these aerosol jet printed SAW microfluidic devices with their cleanroom-fabricated counterparts, the wave displacements and resonant frequencies of the different fabricated devices were directly measured through scanning laser Doppler vibrometry. Finally, to exhibit the capability of the aerosol jet printed devices for lab-on-a-chip applications, we successfully conducted acoustic streaming and particle concentration experiments. Overall, we demonstrated a novel solution-based, direct-write, single-step, cleanroom-free additive manufacturing technique to rapidly develop SAW microfluidic devices that shows viability for applications in the fields of biology, chemistry, engineering, and medicine.

Interdisciplinary collaboration in critical care alarm research: A bibliometric analysis

BACKGROUND

Alarm fatigue in nurses is a major patient safety concern in the intensive care unit. This is caused by exposure to high rates of false and non-actionable alarms. Despite decades of research, the problem persists, leading to stress, burnout, and patient harm resulting from true missed events. While engineering approaches to reduce false alarms have spurred hope, they appear to lack collaboration between nurses and engineers to produce real-world solutions. The aim of this bibliometric analysis was to examine the relevant literature to quantify the level of authorial collaboration between nurses, physicians, and engineers.

METHODS

We conducted a bibliometric analysis of articles on alarm fatigue and false alarm reduction strategies in critical care published between 2010 and 2022. Data were extracted at the article and author level. The percentages of author disciplines per publication were calculated by study design, journal subject area, and other article-level factors.

RESULTS

A total of 155 articles with 583 unique authors were identified. While 31.73 % (n = 185) of the unique authors had a nursing background, publications using an engineering study design (n = 46), e.g., model development, had a very low involvement of nursing authors (mean proportion at 1.09 %). Observational studies (n = 58) and interventional studies (n = 33) had a higher mean involvement of 52.27 % and 47.75 %, respectively. Articles published in nursing journals (n = 32) had the highest mean proportion of nursing authors (80.32 %), while those published in engineering journals (n = 46) had the lowest (9.00 %), with 6 (13.04 %) articles having one or more nurses as co-authors.

CONCLUSION

Minimal involvement of nursing expertise in alarm research utilizing engineering methodologies may be one reason for the lack of successful, real-world solutions to ameliorate alarm fatigue. Fostering a collaborative, interdisciplinary research culture can promote a common publication culture across fields and may yield sustainable implementation of technological solutions in healthcare.

Exosome-based engineering strategies for the diagnosis and treatment of oral and maxillofacial diseases

Oral and maxillofacial diseases are one of the most prevalent diseases in the world, which not only seriously affect the health of patients' oral and maxillofacial tissues, but also bring serious economic and psychological burdens to patients. Therefore, oral and maxillofacial diseases require effective treatment. Traditional treatments have limited effects. In recent years, nature exosomes have attracted increasing attention due to their ability to diagnose and treat diseases. However, the application of nature exosomes is limited due to low yield, high impurities, lack of targeting, and high cost. Engineered exosomes can be endowed with better comprehensive therapeutic properties by modifying exosomes of parent cells or directly modifying exosomes, and biomaterial loading exosomes. Compared with natural exosomes, these engineered exosomes can achieve more effective diagnosis and treatment of oral and maxillary system diseases, and provide reference and guidance for clinical application. This paper reviews the engineering modification methods of exosomes and the application of engineered exosomes in oral and maxillofacial diseases and looks forward to future research directions.

Compound weighted fusion evaluation and optimization of intelligent tracking algorithm in radar seeker

This paper designs a hierarchical weighted fusion evaluation/optimization scheme for the radar seeker neural network (NN) tracking algorithm. The first weighted fusion of closed-loop performance index is carried out to exclude the hardware influence on algorithm evaluation. Then, according to different tracking scenarios, the tracking index is divided into different periods; a single period score is given by a linear-nonlinear hybrid scoring mechanism. Furthermore, in a single index, the internal scores of different time periods are weighted and fused for the second time to obtain the index overall score. Finally, the third weighted fusion of the multi-index scores obtains the comprehensive score of the algorithm. We design the parameter evaluation case sets and repeat the aforementioned compound weighting; hence the case with the highest comprehensive score is obtained. Finally, the algorithm is optimized by the highest-score case. The experiment using fuzzy NN radar seeker verifies the effectiveness of the method.