The design of hypersonic vehicles is primarily driven by thermal considerations. Additionally, due to the lack of turbomachinery in these vehicles, the provision of electrical energy to vehicle systems is done almost exclusively by batteries. This paper outlines the analysis of photovoltaic cells embedded in the skin of a hypersonic vehicle to reduce the heat transfer from the hot external aerodynamic surface and the internal vehicle structure and to produce electrical energy from a portion of the thermal radiation. By treating each of the surfaces involved in the radiative exchange as coplanar surfaces in local thermodynamic equilibrium, the equations governing the transfer of thermal energy through the skin structure are derived. Two nominal refractory metals and a nominal ceramic matrix composite material are analyzed at a range of temperatures to determine the relative effectiveness of a thermophotovoltaic (TPV) skin in heat flux reduction and electrical energy generation compared to a simple skin structure. A TPV skin is shown to reduce the heat flux to the vehicle interior by more than an order of magnitude and simultaneously convert more than 10% of the external heat load into electrical energy at high temperatures.

Evaporation cooling is enhanced by forming a thin liquid film with low resistance for heat conduction and using an impinging gas jet for effective removal of the vapor from the interface. Our previous experiments show that when nanoelectrospray (nES) is directed onto a nearby surface, ultra-thin liquid films can be formed with thicknesses less than 260 nm. Our previous experiments and simulations also show that the stream of highvelocity liquid droplets emanating from the nES capillary entrain the surrounding ambient air, forming a narrow gas jet with speeds of tens of meters per second resulting in a means for vapor advection from the evaporating interface. With promising results from the previous work, the current work considers the problem of hotspot thermal management using the nES-generated evaporating films of methanol and water as coolants. A comprehensive model, which considers the charged droplet transport, liquid/gas momentum exchange, fluid film evaporation, vapor transport, and heat transfer by evaporation, convection, and conductive spreading is used to evaluate the theoretical performance of nES evaporative cooling. The key demonstrated result is that hotspots on the order of tens of mu m in diameter with heat fluxes of over 1000 W/cm2 (or larger hotspots of a few hundred mu m in diameter with heat fluxes of a few hundred W/cm2) can be effectively cooled while keeping the surface temperatures below the boiling point of the working fluid at atmospheric pressure. The effects of the key nES parameters (emitter positioning, applied potential, droplet size, liquid mass flowrate) and thermophysical properties of the coolants (mass density, maximum stable electric charge density, saturated vapor density, latent heat of vaporization, thermal conductivity) are analyzed, resulting in fundamental guidelines for heat and mass transfer enhancement in thin film evaporative cooling with application to microelectronics thermal management.

Computational bioheat modeling offers a powerful approach for characterizing brain temperature when direct measurements are limited. We developed a multiscale biophysical model with conservation of mass, momentum, and energy across all spatial scales to predict human brain temperature and compared the temperature maps with a previously developed model without global momentum conservation and in vivo magnetic resonance (MR) thermometry. Subject-specific brain anatomy obtained from MR images was incorporated into bioheat equations, integrating physiological parameters such as metabolic heat and cerebral blood flow. A novel approach using "transitional" microvasculature was introduced to bridge macro- and micro-scale domains, enabling momentum conservation and accurate prediction of cerebral hemodynamics. Across 30 healthy subjects, voxel-wise mean absolute differences of 0.18-0.36 °C between modeled and experimentally measured temperatures were observed. ROI-based analysis showed significant correlations between model predictions and MR measurements of brain temperature when system-wide momentum is properly conserved, but no correlation was observed for model predictions without momentum conservation. A simulated scenario of middle cerebral artery occlusion highlighted the importance of momentum conservation to mimic realistic physiological changes. The agreement of model predicted temperatures with MR measurements support future clinical applications where brain temperature may serve as a biomarker for neurological disorders.

Visualization and scaling of charged droplet transport in gas jet crossflows at nearand sub-atmospheric pressures are presented to describe the physics of droplet-gas interactions and predict when gas jets can redirect droplet trajectories. Laser scattering of electrospray and schlieren photography of gas jet expansion are employed to assess charged droplet-gas interactions in variable pressure environments. Experimental results reveal that the greatest gas influence on droplet trajectories occurs at intermediate pressures (P/Patm = 2.1 x 10-2), when gas jets achieve supersonic velocities and exert substantial drag before rarefaction effects become significant. A fundamental understanding of the underlying physics is gained through a scaling analysis for an individual charged droplet's transport that introduces a dimensionless parameter, representing the ratio of gas drag to the maximum of the electric or inertial force, to predict droplet deflection in a gas crossflow. This dimensionless parameter that can be predicted analytically using the experimentally controlled inputs is shown to effectively capture the behavior without the need for complex and computationally expensive multiphysics simulations. Comparisons with experimental results and computational fluid dynamics and electrostatic simulations validate the scaling framework while identifying limitations of continuum models at high Knudsen numbers. These results delineate distinct regimes of droplet transport and provide a predictive foundation for droplet control strategies by gas jets for numerous engineering applications.

In recent years, cell-based therapies have transformed medical treatment. These therapies present a multitude of challenges associated with identifying the mechanism of action, developing accurate safety and potency assays, and achieving low-cost product manufacturing at scale. The complexity of the problem can be attributed to the intricate composition of the therapeutic products: living cells with complex biochemical compositions. Identifying and measuring critical quality attributes (CQAs) that impact therapy success is crucial for both the therapy development and its manufacturing. Unfortunately, current analytical methods and tools for identifying and measuring CQAs are limited in both scope and speed. This Perspective explores the potential for microfluidic-enabled mass spectrometry (MS) systems to comprehensively characterize CQAs for cell-based therapies, focusing on secretome, intracellular metabolome, and surfaceome biomarkers. Powerful microfluidic sampling and processing platforms have been recently presented for the secretome and intracellular metabolome, which could be implemented with MS for fast, locally sampled screening of the cell culture. However, surfaceome analysis remains limited by the lack of rapid isolation and enrichment methods. Developing innovative microfluidic approaches for surface marker analysis and integrating them with secretome and metabolome measurements using a common analytical platform hold the promise of enhancing our understanding of CQAs across all "omes," potentially revolutionizing cell-based therapy development and manufacturing for improved efficacy and patient accessibility.

Electrospray (ES) is production of a charged droplet plume that transits from an electrically biased supply capillary to a counter electrode under the influence of an electric field. Drag interactions with the surrounding gas decelerate the droplets while transferring the momentum from droplets to accelerate the surrounding gas, resulting in an induced gas flow. This work seeks to characterize the structure of the resulting gas jet and identify the key mechanisms defining the flow structure. The phenomenon of gas jets produced by momentum transfer from nano-electrospray (nES) plumes is explored with schlieren visualization, thermal anemometry, and numerical simulations. Schlieren visualization experiments provide information on the flow structure in support of simulation predictions, and the hot thermistor anemometry measurements of gas velocities outside the spray demonstrate quantitatively validated simulation results. The study reveals the formation of a moderately high velocity coaxial gas jet within the nES plume and provides insight into the overall flow structure of the induced flow. The multiphase electrohydrodynamic simulations enable numerical experimentation to explore the fundamental physics of coupled droplet-gas transport and the resulting flow structure. The simulations, confirmed by the experiments, reveal gas jetting induced by nES with a narrow (sub hundred micrometers in diameter) core originating from the nES liquid-jet breakup region and a surrounding larger-in-extent zone (several hundred micrometers in diameter) of lower velocity gas flow within the electrospray plume. This behavior is due to nES ejecting a stream of droplets from the tip of a narrow liquid cone-jet, where the combined effect of many small droplets transferring momentum to a confined region of gas yields a narrow but high-velocity gas stream. The micro-jets produced by nES have practical utility for mass spectrometry, 3D printing and fabrication, and thermal management.

The advancement of liquid phase electron/ion beam induced deposition has enabled an effective direct-write approach for functional nanostructure synthesis with the possibility of three-dimensional control of morphology. For formation of a metallic solid phase, the process employs ambient temperature, beam-guided, electrochemical reduction of precursor cations, resulting in rapid formation of structures, but with challenges for retention of resolution achievable via slower electron beam approaches. The possibility of spatial control of redox pathways via the use of water-ammonia solvents has opened avenues for improved nanostructure resolution without sacrificing the growth rate. In particular, ammonia enables "electrochemical lensing" in which a tightly confined and highly reducing environment is created locally to enable high resolution, rapid beam-directed nanostructure growth. We demonstrate this unique approach to high resolution synthesis through a combination of analysis and experiment.

Nano-electrospray (nES) produces a plume of charged liquid droplets which have drag interactions with the surrounding gas after they are emitted from a source capillary. The resulting induced gas flow has often been considered unimportant, but we have demonstrated that a gas microjet of significant velocity up to 10s of m/s can be produced. In this work we present a thermodynamic framework that enables analysis of gas jet generation from electrosprays and introduce the important metrics for such analysis, effectiveness (a measure of momentum transfer from the electrosprayed aerosol to gas) and efficiency (a measure of energy conversion from electrical energy generating the electrospray to gas kinetic energy). This analytical framework is applicable to any two-phase flows consisting of discrete conservative-force-driven particles which exchange momentum with an inert, otherwise quiescent fluid medium to yield a co-flowing two-phase jet. We apply this framework to sprays of water from nano-electrospray emitters to demonstrate that increasing the applied electrical potential difference, increasing liquid mass flowrate, and decreasing droplet size all can increase electrospray induced gas jet strength, but only the latter two do so while also increasing the momentum transfer effectiveness and energy conversion efficiency.

BACKGROUND AIMS:In-process monitoring and control of biomanufacturing workflows remains a significant challenge in the development, production, and application of cell therapies. New process analytical technologies must be developed to identify and control the critical process parameters that govern ex vivo cell growth and differentiation to ensure consistent and predictable safety, efficacy, and potency of clinical products. METHODS:This study demonstrates a new platform for at-line intracellular analysis of T-cells. Untargeted mass spectrometry analyses via the platform are correlated to conventional methods of T-cell assessment. RESULTS:Spectral markers and metabolic pathways correlated with T-cell activation and differentiation are detected at early time points via rapid, label-free metabolic measurements from a minimal number of cells as enabled by the platform. This is achieved while reducing the analytical time and resources as compared to conventional methods of T-cell assessment. CONCLUSIONS:In addition to opportunities for fundamental insight into the dynamics of T-cell processes, this work highlights the potential of in-process monitoring and dynamic feedback control strategies via metabolic modulation to drive T-cell activation, proliferation, and differentiation throughout biomanufacturing.

To advance our understanding of thermal dynamics in the human brain, a thermal modeling framework was previously developed to facilitate temperature predictions in the absence of clinical thermometry. Here, predicted brain temperatures using our fully conserved model were compared with MR thermometry in 21 healthy human subjects. Bland-Altman plots demonstrated agreement between predictions and MR-measurements for average temperature values, but some differences were observed at the lowest and highest temperatures. Regional variations were similar between predicted and measured temperatures. We anticipate our modeling framework will form the necessary baseline for predicting injury-induced brain temperature changes in patients.

Brain temperature is an understudied parameter relevant to brain injury and ischemia. To advance our understanding of thermal dynamics in the human brain, combined with the challenges of routine experimental measurements, a biophysical modeling framework was developed to facilitate individualized brain temperature predictions. Model-predicted brain temperatures using our fully conserved model were compared with whole brain chemical shift thermometry acquired in 30 healthy human subjects (15 male and 15 female, age range 18–36 years old). Magnetic resonance (MR) thermometry, as well as structural imaging, angiography, and venography, were acquired prospectively on a Siemens Prisma whole body 3 T MR scanner. Bland–Altman plots demonstrate agreement between model-predicted and MR-measured brain temperatures at the voxel-level. Regional variations were similar between predicted and measured temperatures (< 0.55 °C for all 10 cortical and 12 subcortical regions of interest), and subcortical white matter temperatures were higher than cortical regions. We anticipate the advancement of brain temperature as a marker of health and injury will be facilitated by a well-validated computational model which can enable predictions when experiments are not feasible.

In this study, a method for using arrays of mesoscale structures to modify the apparent optical properties of an opaque composite surface has been theoretically demonstrated to both raise and lower the apparent emissivity as compared to the intrinsic properties of the constitutive materials. For design problems where thermomechanical and optical material properties are both of importance, mesoscale surface structuring can greatly expand the design space. Analysis via the net radiosity method herein illustrates the ability to achieve a wide range of spectral apparent optical properties. Notably, a hexagonal array of spheres on a planar surface can raise the apparent emissivity of a planar surface by 50%. Conversely, a hexagonal enclosure of reradiating surfaces, realized by thin adiabatic walls, can reduce the apparent emissivity of a blackbody by half. As this method of modifying apparent optical properties utilizes structures much larger than the wavelengths of interest, the relationship between intrinsic planar emissivity, geometry, and apparent emissivity can be computed semi-analytically at low computational expense. Passive solar cooling, thermophotovoltaic cells, aerodynamic surfaces exposed to intense heating, and solar absorbers are presented as case studies that could benefit from the use of mesoscale structures on opaque surfaces to modify the apparent optical properties. (C) 2022 Elsevier Ltd. All rights reserved.

The ability to control and optimize interactions between light and matter has much utility in engineering design. A well-researched way to achieve optical property modulation is via the use of optical metamaterials, which feature sub-wavelength scale surface structures. In this work, an alternative approach for modulating optical properties is presented using a composite surface modified with a periodic array of semitransparent hemispherical shell mesoscale structures which are larger than the incident light wavelength. A ray-tracing simulation approach is used to predict the optical behavior for an arrayed surface. At oblique angles of incidence, significant increases and decreases in apparent absorptance are achieved via the use of optically thick and thin shells, respectively. Additionally, a potential application to solar cells is described with optimal spectral behavior achieved via the use of semitransparent external structures.

The exceptional photochromic and redox properties of polyoxometalate anions, PW12O403-, have been exploited to develop an integrated photoelectrochemical energy storage cell for conversion and storage of solar energy. Elimination of strongly coordinating cations using benchtop ion soft landing leads to a ∼370% increase in the maximum power output of the device. Additionally, the photocathode displayed a pronounced color change from clear to blue upon irradiation, which warrants the potential application of the IPES cell in advanced smart windows and photochromic lenses.

Brain temperature is an important yet understudied medical parameter, and increased brain temperature after injury is associated with worse patient outcomes. The scarcity of methods for measuring brain temperature non-invasively motivates the need for computational models enabling predictions when clinical measurements are challenging. Here, we develop a biophysical model based on the first principles of energy and mass conservation that uses data from magnetic resonance imaging of individual brain tissue and vessel structure to facilitate personalized brain temperature predictions. We compare model-predicted 3D thermal distributions with experimental temperature measured using whole brain magnetic resonance-based thermometry. We find brain thermometry maps predicted by the model capture unique spatial variations for each subject, which are in agreement with experimentally-measured temperatures. As medicine becomes more personalized, this foundational study provides a framework to develop an individualized approach for brain temperature predictions.

Real-time, advanced diagnostics of the biochemical state within cells remains a significant challenge for research and development, production, and application of cell-based therapies. The fundamental biochemical processes and mechanisms of action of such advanced therapies are still largely unknown, including the critical quality attributes that correlate to therapeutic function, performance, and potency and the critical process parameters that impact quality throughout cell therapy manufacturing. An integrated microfluidic platform has been developed for in-line analysis of a small number of cells via direct infusion nano-electrospray ionization mass spectrometry. Central to this platform is a microfabricated cell processing device that prepares cells from limited sample volumes removed directly from cell culture systems. The sample-to-analysis workflow overcomes the labor intensive, time-consuming, and destructive nature of existing mass spectrometry approaches for analysis of cells. By providing rapid, high-throughput analyses of the intracellular state, this platform enables untargeted discovery of critical quality attributes and their real-time, in-process monitoring.

Irradiation of a liquid solution generates solvated electrons and radiolysis products, which can lead to material deposition or etching. The chemical environment dictates the dominant reactions. Radiolysis-induced reactions in salt solutions have substantially different results in pure water versus water-ammonia, which extends the lifetime of solvated electrons. We investigate the interplay between transport and solution chemistry via the example of solid silver formation from e-beam irradiation of silver nitrate solutions in water and water-ammonia. The addition of ammonia results in the formation of a secondary ring-shaped deposit tens of micrometers in diameter (formed over tens of seconds) around the primary point of deposition (formed over milliseconds). Simulations uncover the relative importance of oxidizing and reducing reactions and transport effects. Our explanation of this behavior involves mechanisms beyond ammonia’s role in extending solvated electron lifetimes.

Nascent advanced therapies, including regenerative medicine and cell and gene therapies, rely on the production of cells in bioreactors that are highly heterogeneous in both space and time. Unfortunately, advanced therapies have failed to reach a wide patient population due to unreliable manufacturing processes that result in batch variability and cost prohibitive production. This can be attributed largely to a void in existing process analytical technologies (PATs) capable of characterizing the secreted critical quality attribute (CQA) biomolecules that correlate with the final product quality. The Dynamic Sampling Platform (DSP) is a PAT for cell bioreactor monitoring that can be coupled to a suite of sensor techniques to provide real-time feedback on spatial and temporal CQA content in situ. In this study, DSP is coupled with electrospray ionization mass spectrometry and direct-from-culture sampling to obtain measures of CQA content in bulk media and the cell microenvironment throughout the entire cell culture process (≈3 weeks). Post hoc analysis of this real-time data reveals that sampling from the microenvironment enables cell state monitoring (e.g., confluence, differentiation). These results demonstrate that an effective PAT should incorporate both spatial and temporal resolution to serve as an effective input for feedback control in biomanufacturing.

Vortical jet flows in the Reynolds number (Re) range from 1000 to 3425 and swirl number (S) below 0.5, alone and in combination with suction through a small aperture, are experimentally investigated using optical visualization. Schlieren photography is employed to assess the vortical flow structure and establish the fundamental understanding of the source-to-sink gas-dynamic coupling, including the role played by the flow rate, jet diameter, and separation distance between the gas jet source and the suction sink. Compared to vortex-free jets, vortical jets for Re > 2700 with swirl number S > 0.27 experience earlier laminar-to-turbulent transition, resulting in a rapid growth of the jet boundary. The ability to control the growth of the jet expansion and mass and momentum dissipation into the surrounding is demonstrated via the use of a coaxially aligned flow suction placed in the path of a jet. When a swirling jet is completely coupled with a flow suction, jet expansion is significantly suppressed. The suction/sink flow rate imposes a limit on the maximum input/source flow rate of the gas jet to achieve complete coupling. Furthermore, there is a maximum distance over which effective coupling can occur, and for all Reynolds numbers considered, this distance is shorter than the distance at which the jet structure breaks up into turbulent eddies in the absence of a sink.