A microfabricated steel and glass radiation detector with inherent wireless signaling

This paper describes an investigation of the performance compromises imposed by a manufacturing approach that utilizes lithographic micromachining processes to fabricate a wireless beta/gamma radiation detector. The device uses in-package assembly of stainless steel electrodes and glass spacers. These elements are micromachined using photochemical etching and powder blasting, respectively. The detector utilizes a commercial, TO-5 package that is hermetically sealed at 760 Torr with an Ar fill-gas. Gas microdischarges between the electrodes, which are initiated by the radiation, transmit wideband wireless signals. The detector diameter and height are 9 and 9.6 mm, respectively, and it weighs 0.97 g. The device performance has been characterized using various sealed, radioisotope sources, e.g., 30–99 µCi from 137 Cs (which is a beta and gamma emitter) and 0.1 µCi from 90 Sr (which is a pure beta emitter). It has a measured output of >15.5 counts s _1 when in close proximity to 99 µCi from 137 Cs. The wireless signaling spans 1.25 GHz at receiving antenna-to-detector distances >89 cm, when in close proximity to a 0.1 µCi 90 Sr source. The estimated intrinsic detection efficiency (i.e. with the background rate subtracted) is 3.34% as measured with the biasing arrangement described in the paper.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90792/1/0960-1317_21_1_015003.pd

A Si-micromachined 48-stage Knudsen pump for on-chip vacuum

This paper describes a thermal transpiration-driven multistage Knudsen pump for vacuum pumping applications. This type of pump relies upon the motion of gas molecules from the cold end to the hot end of a channel in which the flow is restricted to the free molecular or transitional regimes. To achieve a high compression ratio, 48 stages are cascaded in series in a single chip. A five-mask, single silicon wafer process is used for monolithic integration of the designed Knudsen pump. The pump has several monolithically integrated Pirani gauges to experimentally measure the vacuum pumping characteristics of the pump. It has a footprint of 10.35 × 11.45 mm 2 . For an input power of 1350 mW, the fabricated pump self-evacuates the encapsulated cavities from 760 to ≈50 Torr, resulting in a compression ratio of 15. It also pumps down from 250 to ≈5 Torr, resulting in a compression ratio of 50. Each integrated Pirani gauge requires ≈3.9 mW of power consumption, and its response is sufficiently sensitive in the operating pressure range of 760–1 Torr.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98610/1/0960-1317_22_10_105026.pd

Sustainable Approaches for the Additive Manufacturing of Ceramic Materials

Additive manufacturing technologies collectively refer to a set of layer-wise deposition methods that typically rely on CAD-CAM approaches for obtaining products with a complex shape/geometry and high precision and reliability. If the additive manufacturing of polymers is relatively easy and scalable due to the low temperatures needed to obtain processable inks, using similar technologies to fabricate ceramic products is indeed more challenging and expensive but, on the other hand, allows for obtaining high-quality results that would not be achievable through conventional methods. Furthermore, the implementation of additive manufacturing allows for the addressing of some important concerns related to the environment and sustainability, including the minimization of resource depletion and waste production/disposal. Specifically, additive manufacturing technologies can provide improvements in energy consumption and production costs, besides obtaining less waste material and less CO2 emissions, which are all key points in the context of the circular economy. After providing an overview of the additive manufacturing methods which are specifically applied to ceramics, this review presents the sustainability elements of these processing strategies, with a focus on both current and future benefits. The paucity of specific available studies in the literature—which are included and discussed in this review—suggests that the research on additive manufacturing sustainability in the field of ceramic materials is in the preliminary stage and that more relevant work still deserves to be carried out in the future to explore this fascinating field at the boundary among ceramics science/technology, production engineering and waste management

Controlling ultra wideband transmissions from a wireless micromachined Geiger counter,”

ABSTRACT This paper reports a parametric study of the wireless spectrum generated by discharge-based devices with focus specifically on micromachined Geiger counters as a function of the packaging, biasing circuitry, and sample isotope. Experiments are conducted with discharge devices attached to commercial high voltage (HV) packages with hermetic sealing capabilities. Influences of packaging as well as isotope type are studied and reported. Preliminary results show that current discharges emit RF spectra spanning a bandwidth greater than 3 GHz, which extends into the ultra wideband (UWB) window (from 100 MHZ to 10.6 GHz) that decreases in intensity with increasing observer distance

Energy scavenging from insect flight

This paper reports the design, fabrication and testing of an energy scavenger that generates power from the wing motion of a Green June Beetle (C otinis nitida ) during its tethered flight. The generator utilizes non-resonant piezoelectric bimorphs operated in the d 31 bending mode to convert mechanical vibrations of a beetle into electrical output. The available deflection, force, and power output from oscillatory movements at different locations on a beetle are measured with a meso-scale piezoelectric beam. This way, the optimum location to scavenge energy is determined, and up to ~115 µW total power is generated from body movements. Two initial generator prototypes were fabricated, mounted on a beetle, and harvested 11.5 and 7.5 µW in device volumes of 11.0 and 5.6 mm 3 , respectively, from 85 to 100 Hz wing strokes during the beetle's tethered flight. A spiral generator was designed to maximize the power output by employing a compliant structure in a limited area. The necessary technology needed to fabricate this prototype was developed, including a process to machine high-aspect ratio devices from bulk piezoelectric substrates with minimum damage to the material using a femto-second laser. The fabricated lightweight spiral generators produced 18.5–22.5 µW on a bench-top test setup mimicking beetles' wing strokes. Placing two generators (one on each wing) can result in more than 45 µW of power per insect. A direct connection between the generator and the flight muscles of the insect is expected to increase the final power output by one order of magnitude.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90804/1/0960-1317_21_9_095016.pd

Gradient Descent Optimization in Gene Regulatory Pathways

BACKGROUND: Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. METHODOLOGY: In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings. CONCLUSIONS: We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods

Spontaneous Reaction Silencing in Metabolic Optimization

Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical non-optimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.Comment: 34 pages, 6 figure