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ijms International Journal of Molecular Sciences Int. J. Mol. Sci. 1422-0067 Molecular Diversity Preservation International (MDPI) 10.3390/ijms141020064 ijms-14-20064 Review Marine Polysaccharide Networks and Diatoms at the Nanometric Scale SvetličićVesna* ŽutićVera PletikapićGalja RadićTea Mišić Division for Marine and Environmental Research, Ruđer Bošković Institute, Bijenička 54, 10000 Zagreb, Croatia; E-Mails: zutic@irb.hr (V.Ž.); gpletik@irb.hr (G.P.); tmisic@irb.hr (T.M.R.) Author to whom correspondence should be addressed; E-Mail: svetlicic@irb.hr; Tel.: +385-1-4561-185; Fax: +385-1-4680-242. 10 2013 09 10 2013 14 10 20064 20078 02 08 2013 14 09 2013 18 09 2013 © 2013 by the authors; licensee MDPI, Basel, Switzerland 2013

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

Despite many advances in research on photosynthetic carbon fixation in marine diatoms, the biophysical and biochemical mechanisms of extracellular polysaccharide production remain significant challenges to be resolved at the molecular scale in order to proceed toward an understanding of their functions at the cellular level, as well as their interactions and fate in the ocean. This review covers studies of diatom extracellular polysaccharides using atomic force microscopy (AFM) imaging and the quantification of physical forces. Following a brief summary of the basic principle of the AFM experiment and the first AFM studies of diatom extracellular polymeric substance (EPS), we focus on the detection of supramolecular structures in polysaccharide systems produced by marine diatoms. Extracellular polysaccharide fibrils, attached to the diatom cell wall or released into the surrounding seawater, form distinct supramolecular assemblies best described as gel networks. AFM makes characterization of the diatom polysaccharide networks at the micro and nanometric scales and a clear distinction between the self-assembly and self-organization of these complex systems in marine environments possible.

atomic force microscopy marine diatoms extracellular polymeric substance extracellular polysaccharides marine gel network self assembly self-organization Cylindrotheca closterium Bacteriastrum jadranum northern Adriatic Sea

Diatoms, important marine photoautotrophic protists that account for up to 25% of the primary production on Earth [1], produce large quantities of extracellular polymeric substances (EPS), consisting predominantly of polysaccharides [2]. Diatom extracellular polymers participate in various processes, both at the cellular level and in the environment. At the cellular level, extracellular polymers have several important functions, of which some of the most frequently recognized are sessile adhesion, gliding, protection against drying, stabilization of habitats through prevention of sediment erosion, and the formation of biofilms and colonies [2,3]. The total amount of exopolysaccharides produced by diatoms is far in excess of that required for movement or adhesion [35] and is referred to as the photosynthetic overflow. In the marine environment, extracellular polysaccharide production by diatoms is a significant route by which photosynthetically produced organic carbon enters the trophic web and may influence the physical environment in the sea. Specifically, species of diatoms in the northern Adriatic Sea can produce large amounts, up to 50 g/m3 of extracellular polysaccharides in a month [6], resulting in the episodic formation of a macroscopic gel phase [7,8].

Marine polysaccharide gels represent a form of molecular organization in which biopolymer molecules form solvated three-dimensional networks imbedded in seawater. Intense metabolic activities of microorganisms within gel aggregates (e.g., [9]) result in the formation of sharp microbiogeochemical gradients. The diffusion-slowing properties of the gel phase aid in maintaining these gradients over a very small (μm) spatial scale. The continued presence of sharp microbiogeochemical gradients results in the formation of microbial consortia, structured arrangements of microorganisms exhibiting different but highly specific physiological activities over small spatial scales.

Unlike chemical gels that are formed by chemical reaction using a cross-linking agent, it is characteristic of anionic polysaccharide macromolecules to form gels by physical bonds through the intermolecular forces among polymer chains [10,11]. Among the new methodologies (experimental and theoretical) developed for and applied to polysaccharide conformation and dynamics, solution properties, chain aggregation and gelation [12] using atomic force microscopy (AFM) have yielded the most striking results [13].

AFM has been extensively used in nanoscale studies of EPS intimately associated with frustules as coating and adhesive structures (strands, tethers, pads and stalks), as recently reviewed by Higgins and Wetherbee, 2012 [14]. Here, we intend to review recent AFM studies of diatom EPS focusing on the detection of the supramolecular structures of polysaccharide fibrils produced by marine diatoms, either attached to the diatom cell wall or released into the surrounding seawater.

Basic Principles of AFM and Its Application to Polysaccharides

AFM connects the nanometer- and micrometer-length scales, utilizing a sharp probe that senses interatomic forces acting between the surface of a sample and the atoms at the apex of the tip. The physical basis behind AFM and its ability to “feel” the surface make AFM a versatile tool in biophysics, allowing high resolution imaging, nanomechanical characterization and measurements of inter- and intramolecular forces in living and non-living structures [1519]. Thanks to the simple principle on which it is based, the AFM is a surprisingly small and compact instrument. Its use includes an electronic control unit, computer and usually two monitors for the simultaneous checking of the image and imaging parameters. The probe, which scans the sample surface, consists of a cantilever and a tip located at its free end. The deflection of the cantilever is measured by an optical detection system. Registered values of cantilever deflection are electronically converted into a pseudo 3D image of a sample. As a result AFM produces real 3D images of a sample with a vertical resolution of 0.1 nm and lateral resolution of 1 nm. The measured forces range from 10−6 N to 10−11 N. In AFM force spectroscopy, a single molecule or fiber is stretched between the AFM flexible cantilever tip and a flat substrate. A polysaccharide molecule, protein or other biopolymer is either adsorbed to the substrate or linked to it through the formation of covalent bonds. When the tip and substrate are brought together and then withdrawn, one or more molecules can attach to the tip. The deflection of the cantilever measures the force on the polymer with an accuracy of ~5 pN, while the piezoelectric positioner records the changes in the end-to-end length of the molecule with an accuracy of 0.1 nm. AFM force spectroscopy is a widely used method in polymer biophysics, allowing the measurement of the mechanical properties of single molecules with the possibility of quantifying the forces involved directly in both intra- and inter-molecular polymer interactions [18,2023]. It has also been adopted in advancing diatom research into the nanotechnology [14].

In the AFM imaging mode that makes visualization at the molecular scale of polysaccharide samples possible [2432], the molecules are usually spread on freshly cleaved mica (a hydrophilic aluminosilicate mineral). The imaging of hydrated samples is preferably conducted in air to inhibit the unfavorable motion of polysaccharides in liquid medium. Protocols for marine sample AFM imaging have been recently developed for single diatom cells and released polymers, isolated polysaccharides from diatom cultures and polymer networks of the marine gel phase [3339].

AFM Studies of Diatom EPS

Higgins and coworkers [40] were the first to use AFM for the characterization of diatom extracellular polymers. Intra- and intermolecular forces were measured between polymers on the cell wall and between those extruded from the diatom raphe on diatom species Craspedostauros australis E.J. Cox and Pinnularia viridis (Nitzsch) Ehrenberg [41,42]. The resulting force curves obtained from the pores of cell walls were attributed to the soft and compressible material. However, due to their complexity, it was difficult to assign specific interactions between biopolymers to patterns on the force curves. AFM force spectroscopy was also applied to study extracellular adhesive pads released by the diatom Toxarium undulatum Bailey [4345]. These pads are very sticky and cells use them to form colonies or attach themselves to the surface. The resulting force profiles with numerous sawtooth patterns (e.g., [46]) were attributed to the extensible modular proteins that are associated into the nanofibers. In a differently designed experiment, Arce and coworkers [47] compared the adhesion of whole diatom Navicula spp. cells on different surfaces. In that study, individual cells were glued to tipless cantilevers. With such “diatom probes,” standard force curves were recorded on surfaces such as Intersleek (a hydrophobic agent inhibiting biofilm formation) and mica. The resulting force curves showed comparable adhesion forces, and it was concluded that the extracellular polymeric material on the surface of Navicula spp. has both hydrophobic and hydrophilic properties. Direct imaging of EPS molecules was, however, hampered by the weak interaction of strands and tethers with the substrates used in the liquid [41]. These difficulties were overcome by using mica as a substrate and by imaging in air under ambient conditions (experimental details in [35]).

EPS of <italic>Cylindrotheca</italic> Species

The ubiquitous marine diatoms of the Cylindrotheca spp. were used in AFM studies of exopolysaccharide production [3538]. The Cylindrotheca closterium (Ceratonea Closterium Ehrenberg) strain CCNA1 [35] was isolated from northern Adriatic seawater, while the CCMP1544 and Cylindrotheca fusiformis Reimann & J.C. Lewin, CCMP343 strains were obtained from the Bigelow Laboratory for Ocean Sciences.

The molecular organization of the EPS biopolymers released by C. closterium was approached at different levels: (i) EPS released by a single cell; (ii) EPS released in the culture medium and (iii) as biofilms grown on mica slides inserted in the culture [35]. The release of extracellular polymers by single cells was investigated by AFM in exponential and stationary growth phases. While the release of extracellular polymers in the exponential phase of growth was negligible, in the stationary phase extracellular polymers were visualized on more than 25% of the cells. The AFM data are in line with literature data on increased production of extracellular polymers in the stationary growth phase [4852]. Parallel experiments with Alcian Blue staining and light microscopy performed in the cell culture have shown that the fibrils extending from the cell rostrum were mainly polysaccharides that existed in the liquid phase before the cell deposition to the mica surface [53].

AFM images of extracellular polymers released by C. closterium are shown in Figure 1. The image of the whole cell (Figure 1a) presents the general features of the C. closterium cell with two chloroplasts and its drawn-out flexible rostra. The arrow indicates the position of polymer release shown in b and c of Figure 1. Bundles of polymer fibrils appear at the position close to the site of excretion. Their heights were 5–7 nm. These bundles unfold into a fibrillar network with gradually decreasing fibril heights reaching a distance of up to 10 μm from the cell wall. At the distance of 1 μm, a dense network is observed with fibril heights of 2–3 nm. At larger distances, C. closterium EPS appeared as a relaxed network of fibrils with incorporated spherical nanoparticles/globules. The fibrils appeared flexible, usually with a curved shape, some of them even forming loops. The globules were found to interconnect two or more fibrils but were also imbedded along a single fibril. The fibril heights were in the range of 0.6 to 1.2 nm, while the average height of the incorporated globules was 5 nm. It was hypothesized that the globules are positively charged proteins whose function is the intracellular packing of negatively charged polysaccharide fibrils [35].

Biofilm of <italic>Cylindrotheca Closterium</italic>

Although several AFM studies exist that explored the nature of diatom biofilms and adhesives [40,45,47,54], visualization of a biofilm has only been achieved by AFM imaging in air [35]. The mica slides were withdrawn from the flasks when the cultures of diatom C. closterium entered the stationary growth phase (after 18 days), washed with ultrapure water and imaged in air after drying.

The observed biofilm appeared as a continuous fibrillar network between predominantly individual cells (Figure 2). Some cells were associated (Figure 2a) and 2–6 cells were captured on a 35 μm × 35 μm scanned biofilm surface. At a higher resolution, the biofilm was visualized as a dense fibrillar network with pore sizes ranging from 50 nm to 300 nm (Figure 2b,c). A gradual increase in pore sizes was detected going from the cell wall to the distance of 10 μm (Figure 2b). The globules (3–12 nm high) found exclusively on the fibrillar network appear as silica nanoparticles nucleated from the culture medium. Shchipunov and coworkers applied AFM to demonstrate that gel-forming polysaccharides (e.g., carrageenans) promote silica precipitation, serving as a template [55,56]. Comparison of the fibril and globule height analyses in the EPS of the two C. closterium strains and the biofilm grown in a C. closterium (CCNA1) culture is given in Table 1.

Polysaccharide Network in Diatom Colony Formation

Diatoms have evolved a variety of colonial life forms in which cells are connected by organic threads, mucilage pads or silicate structures. In general, these connecting structures are clearly visible by light or electron microscopy. The colonial planktonic diatom Bacteriastrum jadranum Godrijan, Marić & Phannkuchen [57] was found to be unusual, since the chain formation does not involve fusion of the setae of adjacent cells [39], unlike all other known colonial Bacteriastrum species [58]. Moreover, no thread or any other organic or inorganic substance clearly visible by light or electron microscopy connects the cells.

AFM imaging [39] provided the first evidence that B. jadranum cells in colonies are enclosed in a fibrillar polysaccharide network, termed a cell jacket. At nanoscale resolution, the cell jacket appeared as a cross-linked fibrillar network organized into recognizable patterns (Figure 3). Circular high-density domains (patches, Figure 3B), were surrounded and interconnected by thicker fibrils in a continuous network and appear as the basic structural motive. Pores inside a patch were of the same hexagonal shape, 8–100 nm in size. Their size was continuously smaller from the patch edge toward the center. The branching fibrils (Figure 3A) can be considered as the backbone of the network, critical for assuring its integrity. The pore-forming fibrils within the patches were only 0.6–1.6 nm high, the surrounding fibrils connecting the patches were 2.0–2.8 nm high, while the branching fibrils were considerably wider but not higher than 4.0 nm. Quantitative analysis of the cell jacket network is given in Table 2.

It was concluded that the Bacteriastrum polysaccharide jacket represents an essential part of the cell, as the conjunction of the polymer network with the frustule appears to be extremely tight and such specific and unique patterns were not found in the polysaccharide networks of marine gel imaged by AFM.

AFM of Marine Gel

The broad polydispersity of marine gels ranges from microscopic to macroscopic dimensions [59]. Santschi and coworkers [60] were the first to use AFM to image individual fibrillar polysaccharides in marine macromolecular organic matter. The massive appearance of gelatinous macroaggregates known as mucilage events [7,8,61] offered a possibility for systematic studies of the marine gel phase using AFM [53,62]. The macromolecular characterization of the isolated polysaccharide fraction using physico-chemical techniques [63] showed that they are polydisperse high-molecular weight heteropolysaccharides, in which at least some of the hydroxyl groups of sugar residues are substituted by ester sulfate groups and to a minor extent by carboxylic groups-uronic acid.

These features, conferring a marked polyelectrolytic behavior of the polysaccharides in salt solutions, were also found for the polysaccharide fraction from C. closterium EPS [36]. The fact that the EPS isolated polysaccharide fraction has the capacity to self-assemble into a gel network (Figure 4) is an important finding, with implications on the mechanism of gel phase formation in marine systems [36].

Imaging a Polysaccharide Network of Marine Gel

Development of the protocol for the AFM imaging of the marine gel phase was a critical step. The sampling procedure and specimen preparation protocol for AFM imaging is described in detail by Mišić, Radić et al. [34]. The main organizational features of the polymer gel network were preserved during the transfer of marine gel from seawater to a mica substrate in air. The appearance of a marine gel network at micro and nanometric scales is shown in Figure 5. The gel network imaged by AFM is to a certain extent distorted from the 3D structure in the aqueous phase due to attachment and stretching on the mica surface. Nevertheless, such constraints make studies of fibril associations at the molecular level that would not be accessible by other techniques possible. AFM imaging of marine gel provided insight into the molecular organization of the gel network and associations between polysaccharide fibrils forming the network. Among the complex network structures, associations of fibrils forming junction zones were identified. Modes of fibril associations into junction zones are exemplified in Figure 6.

The evolution of polysaccharide fibrils into marine gel during the mucilage event in the northern Adriatic Sea was captured by AFM [36]. The samples were prepared from macroaggregates collected after different residence times in the water column, from the early stage of gel phase formation to the condensed (mature) gel network of an older macroaggregate. The long polymer strands with small patches of initial fibril associations (Figure 7a) coexisted with the continuous gel network shown in Figure 7b. With a prolonged residence time (one month), a more condensed network was formed, as presented in Figure 7c.

Force Spectroscopy of a Marine Gel Network

The knowledge of the mechanical strength of individual molecular assemblies within a marine gel network contributes to the understanding of the gel phase formation and its persistence in the marine environment. Due to the inherent complexity and heterogeneity of the marine gel phase, it is difficult to isolate the physical forces in the biopolymer network assemblies. However, based on AFM imaging and differential scanning calorimetry, the marine gel was characterized as a thermoreversible physical gel and the dominant mode of gelation was proposed to be the crosslinking of polysaccharide fibrils by hydrogen bonding, which results in helical structures and their associations [34].

Force spectroscopy and high resolution AFM imaging were applied to quantify the intramolecular, interdomain and intermolecular forces within the marine gel network [63,64]. The ability to control the degree of gel network entanglements by dilution and stirring was used to probe marine polysaccharides at different levels of association. The typical events that lead to specific patterns upon stretching include the entropic behavior of individual fibrils (Figure 8) and more complex events, such as the unfolding of polysaccharide entanglements (Figure 9).

Marine gels are highly extensible, as they may be stretched with very little force to distances of up to several micrometers. Fairly large forces are required to unzip the fibrils, suggesting that lateral stability may be important in maintaining the structural integrity of the marine gel.

AFM made characterization of diatom polysaccharide networks at the nanometric scale and a clear distinction between the self-assembly and self-organization of these complex systems possible. Marine polysaccharides produced by diatoms are shown to form distinct supramolecular assemblies that are best described as gel networks. These photosynthetically produced macromolecules may stay attached to the cell wall or be released into the environment.

This review encompasses three specific examples of polysaccharide polymer networks attached to the diatom cell wall: (i) Cylindrotheca closterium polymers at the moment of their release; (ii) a C. closterium biofilm grown on an atomically smooth substrate and (iii) a 3D polysaccharide network enclosing a cell colony of planktonic diatom Bacteriastrum jadranum.

Extracellular polymers produced by C. closterium exhibit a certain level of self-organization, while the highest level of self-organization was found in a 3D polysaccharide network produced by B. jadranum. The polysaccharide fibrillar network of B. jadranum represents an essential part of the cell and not a random extracellular polysaccharide structure. With a more generalized use of AFM, it would probably be discovered that there are many similar types of coverings among planktonic diatoms, as well as diatoms adapted to other habitats (e.g., benthos, tychoplankton etc.). This may be additionally extended to a wider range of microalgae and protists.

In contrast to the networks attached to the diatom cells, free-floating marine gel aggregates are formed by a self-assembly of diatom-released polymers. Structural details of the gel network visualized down to the molecular level revealed monomolecular, helical and superhelical associations.

The physical forces in marine gel network assemblies have been quantified using force spectroscopy together with high resolution AFM imaging. The marine gels appeared highly extensible, as they could be stretched with very little force to distances of up to several micrometers. Such self-assembled networks with randomly distributed microscopic features and high extensibility are capable of responding to environmental conditions, such as change in salinity, temperature, pH and shear stress, maintaining favorable physiological conditions for microbial communities.

Figures and Tables

Extracellular polymers released by C. closterium (CCNA1) obtained by AFM imaging in contact mode after deposition on mica surface. (a) AFM image of the whole cell presented as deflection data. The arrow indicates the position of the polymer excretion site; (b) The released polymers still attached to the apex of the cell rostrum, deflection data, scan size 5 μm × 5 μm; (c) Released polymers presented as height data, scan size 4 μm × 4 μm and vertical scale shown as the color bar (reproduced from [33]).

AFM image of biofilm grown in a CCNA1 culture formed on a mica slide. (a) Association of cells in the biofilm (height data, vertical scale 1.5 μm); (b) Cell rostrum surrounded by the biofilm network (deflection data); (c) The biofilm network (height data, vertical scale 10 nm). Images were acquired in contact mode (reproduced from [35]).

Structural details of the cell jacket network obtained by AFM. (A) branching fibril with height analysis along the indicated line; (B) 2D network of interconnect patches; (C) Spatial arrangement of interconnected patches in the 3D collapsed network (3D view). Images were acquired in tapping mode (reproduced from [39]).

AFM images of polysaccharides isolated from the CCNA1 culture and dissolved in ultrapure water: (a) Single fibrils (concentration 5 mg/L) vertical scale 2.5 nm; (b,c) Fibril networks (concentration 10 mg/L), vertical scales: 5 nm (b) and 10 nm (c). The height analyses are shown along the indicated lines. The images were acquired in tapping mode and are presented as height data (reproduced from [35]).

Marine gel fibrils at micro and nanometric scales: (a) A polysaccharide network of marine gel aggregate imaged in seawater by confocal microscopy after FITC-Concavalin A staining; (b,c) High resolution AFM images of marine gel fibrils with different degrees of cross-linking. AFM images were acquired in tapping mode in air using mica as a substrate (reproduced from [53]).

Mode of fibril associations into junction zones obtained by high resolution AFM imaging: (a) Two 0.7 nm high fibrils forming a 260 nm long junction zone; (b) Two 1.3 nm high fibrils forming 70 and 120 nm long junction zones; (c) Side-by-side association of two 1.6 nm high fibrils. The images were acquired in contact mode (adapted from [34]).

Evolution of polymer networks in the macroscopic gel phase from the early stage of gel phase formation (a,b) to the condensed gel network of an older macroaggregate (c). The AFM images were acquired in contact mode and presented as height data, scan size 4 μm × 4 μm (reproduced from [36]).

Force curves of a single polysaccharide fibril from a disentangled gel network (AFM image shown as the insert) acquired in filtered seawater: approach curve in red and extension curve in blue (adapted from [63]).

Force curves of polysaccharide fibrils in a marine gel network (AFM image shown as the insert) acquired in filtered seawater: approach curve in red and extension curve in blue (adapted from [63]).

Height ranges of the fibrils and globules in the EPS and biofilm of C. closterium strains CCNA1 and CCMP1544 (data from [35]).

Cell culture Fibril height/nm Globule height/nm
EPS bound to cell EPS in bulk culture Biofilm EPS bound to cell EPS in bulk culture Biofilm
CCNA1 0.4–1.9 0.4–2.2 1.7–4.0 3–12 2–12 3–12
CCMP1544 0.6–1.6 0.7–2.6 3–9 2–13

Cell jacket network: pores and pore-forming fibrils analyzed over a surface area of 4 × 4 μm2 (data from [39]).

Pores Pore-forming fibrils

size/nm number height/nm
8–100 900 0.6–1.6
100–160 200 2.0–2.8
500–1000 10 2.5–4.0

The research was supported by the Croatian Ministry of Science, Education and Sport, the project Surface Forces on an Atomic Scale Applied in Marine Science and Nanotechnology (No. 0982934-2744).

Conflicts of Interest

The authors declare no conflict of interest.

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Sensors Sensors 1424-8220 Molecular Diversity Preservation International (MDPI) 10.3390/s140203065 sensors-14-03065 Article A Wireless and Passive Low-Pressure Sensor NicolayPascal* LenzhoferMartin Carinthian Tech Research (CTR AG), Villach/St. Magdalen 9524, Austria; E-Mail:

Author Contributions: Pascal Nicolay developed the concept of the sensor and the models needed to understand and predict its behavior. He wrote the paper and contributed to the experimental measurements. Martin Lenzhofer implemented the solution and performed most of the experimental tasks.

Author to whom correspondence should be addressed; E-Mail:; Tel.: +43-4242-56300-234.
02 2014 17 02 2014 14 2 3065 3076 16 01 2014 27 01 2014 07 02 2014 © 2014 by the authors; licensee MDPI, Basel, Switzerland. 2014

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (

This paper will discuss the results obtained with a first prototype of a completely passive and wireless low pressure sensor. The device is a heat conductivity gauge, based on a wireless and passive SAW temperature sensor. The required heating energy is applied to the sensor using inductive coupling. The prototype was successfully tested in a vacuum chamber. Its equilibrium temperature changed drastically and in a reproducible way when pressure steps were applied. However, the response time was very long. A model is provided to account for the sensor's behavior. It is then used to show that the response time could be strongly improved using basic design improvements. Further possible improvements are discussed.

low pressure sensor Pirani wireless passive SAW inductive heating

Low pressure sensors of the Pirani kind are routinely used, most notably in the semiconductor industry. They are robust sensors with a simple working principle. A constantly heated element is plunged into a rarefied gas and the pressure is deduced from its equilibrium temperature. Indeed, the equilibrium temperature depends on the gas thermal conductivity which itself depends on the gas pressure, especially at low pressure where the dependence is quasi linear. Another operating mode consists in adjusting the heating power to keep the sensor's temperature constant and then deducing the pressure from the heating power itself. This is the preferred mode of operation for standard Pirani gauges. In these commercial gauges, the sensing element is a hot wire. Its temperature is deduced from its resistance. The wire being a long and thin cylinder, its surface/volume ratio is big. Hence, gas-surface interaction is enhanced and thermal inertia is reduced. This basically means a very short time to equilibrium, or response-time. Besides, the wire is mounted in a Wheatstone bridge which allows for very quick and very sensitive detection of resistance and therefore temperature imbalance. The bridge drives the power source through a feedback-loop. This enables the almost instantaneous adjustment of the heating power to re-balance the bridge and therefore keep the wire at a constant temperature. Thanks to this clever configuration, standard Pirani gauges have response times shorter than 20 ms for a measurement uncertainty of about 15% over a wide pressure range, from 0.05 Pa (5.10−4 mbar) to atmospheric pressure. They are often the best choice for reliable and durable pressure monitoring under medium vacuum, between 0.05 Pa and 100 Pa (1 mbar).

However, a standard Pirani gauge costs around 1.5 k€, it is quite big (the standard housing is the size of a small coffee mug) and it comes with an electronic reader which is required to extract the pressure information. It is therefore difficult if not impossible to mount a Pirani gauge directly inside a small vacuum chamber, let alone vacuum housings for special devices like MEMS sensors. To answer the demand for small and accurate Pirani sensors, a lot of efforts have been dedicated worldwide to the development of MEMS Pirani gauges [13] and the first solutions are already commercialized [4,5].

Nevertheless, all of these solutions are essentially miniaturized versions of the standard Pirani gauge. The operating principle is identical. This means that the sensors have to be wired to their conditioning electronics, and the need for active electronics next to the sensor is already a big enough constraint to make the existing MEMS Pirani gauges a non-viable solution for a whole range of possible applications where small, embedded, low-cost, accurate and maintenance-free “patch” sensors would be needed. In this case, the ideal solution would be a passive and wireless Pirani device. To realize such a sensor, only two functions would actually have to be implemented in a passive and wireless way: heating and temperature monitoring. For instance, a hot wire connected to a flat spiral coil designed for efficient energy transfer via inductive coupling would already constitutes a reasonably good passive and wireless low-pressure sensor. The “patch” made of the wire and the coil would be mounted inside a vacuum chamber. Provided that the vacuum chamber has a glass window, heating energy would be transferred to the coil using inductive coupling. This energy would be dissipated in the hot wire, making its temperature change. And the pressure-dependent temperature would then be monitored from outside using an IR-thermometer. If possible in principle, this solution would be quite hard to implement and use. First of all, the accuracy of the IR-thermometer would not be good enough to allow for an accurate determination of the inner pressure. In addition, IR-thermometer would be easily blinded by hot gases flowing around the sensor. To solve these two issues, one could rely on another “more robust” frequency range to transmit the temperature information and use a more accurate measuring principle. One possible solution would be to use a Surface Acoustic Wave (SAW) temperature sensor instead of the hot wire. SAW sensors are small, robust, passive and wireless. An extensive literature exists on the working principles and possible applications of SAW wireless sensors [6,7], notably at high temperature [810]. Off-the-shelf SAW sensors can operate at 2.45 GHz and withstand temperatures up to 300 °C for thousands of hours. The temperature accuracy achieved in wireless and passive mode is better than ±0.1 °C even in aggressive and perturbed environment [11]. Therefore, a heated SAW temperature sensor could certainly constitute a good wireless and passive low-pressure sensor. The additional elements that would be needed here are (again) a coil for wireless energy transfer, a resistive heater connected to the coil and attached to the SAW device, and an antenna for remote interrogation of the SAW device (for temperature monitoring vs. pressure).

The idea of a “SAW Pirani” is not new. The principle was invented in 2006 [12] and successfully tested in the following years [13]. The sensitivity was proven to be very high, but the response time was poor. Efforts have been made to improve the response time by reducing the sensor's dimensions [14] or improving the sensor's modus operandi [15,16], but a really efficient and practical solution still remains to be found. It is now clear that the development of a SAW Pirani that would be at the same time very fast (i.e., very small) and accurate-enough to compete with standard and MEMS-based Pirani gauges would require advanced packaging and hetero-integration techniques. Unfortunately, this would most certainly result in an overpriced and unsellable device. However, a wireless and passive version of the SAW Pirani (WiPirani), would present numerous advantages over competing solutions that might open new interesting perspectives in the field of low pressure monitoring, where only small, cheap and robust embedded sensors can be used.

We report here the experimental results obtained with the first prototype of a WiPirani sensor (Section 2). The prototype was used to monitor the inner pressure of a fused quartz vacuum tube, from outside the tube and without any form of embedded electronics. High pressure sensitivity was observed, even at low operating temperature. The response-time was poor but could be strongly improved through redesign and miniaturization. To prove this point, a complete numerical model of the sensor is provided in Section 3. The coils used for inductive heating are simulated using Finite Element Modeling Magnetics (FEMM). A thermal/electrical analogy is used to simulate the behavior of the sensor itself using Quite Universal Circuit Simulator (QUCS). A good agreement is observed between simulated and experimental data. This validates the model which is then used to check and confirm the positive effect of some basic design improvements on the response time. The next development steps are shortly described before conclusion.

Experimental Section

The sensor prototype is presented in Figure 1. The two main components are a planar spiral coil and a SAW Tag. The coil is one of the two coils used in the wireless power charging device developed by Texas Instruments (WE-WPCC, distributed by Würth Elektronik GmbH & Co. KG, Germany). We used the receiver (Rx) coil, which is smaller. The SAW Tag was designed by CTR AG and already used for several applications in different fields, ranging from biomedical to automotive. A detailed description of its working principle can be found elsewhere [17]. The SAW Tag responds to a radar-like excitation with a series of echoes. The relative delays between the echoes depend on the temperature. This commonly allows for remotely sensing the temperature up to 5 m in air, with a standard accuracy of 0.1 °C. The CTR SAW Tag we used operates at 2.45 GHz and comes in Kovar housing. It can withstand and work at relatively high temperature (200 °C) for a long period of time (>1,000 h). Its dimensions are 10 mm × 3.1 mm × 1.8 mm. In the WiPirani prototype, the SAW Tag was equipped with an in-house manufactured dipole antenna and with a small heating resistor (35 Ω). The heating resistor was glued on the SAW Tag's bottom surface and electrically connected to the coil. Then, the SAW Tag was glued on a small PCB. Consequently, the heating resistor was located between the PCB and the SAW Tag and was not visible anymore. The remote and passive monitoring of the Tag temperature was performed using a classical CTR FMCW SAW Reader. Its working principle was described elsewhere [18].

Non-contact inductive heating was used to heat up the SAW Tag with a constant and well-controlled heating power. To transmit the energy, a second identical spiral coil was used. The driving electronics of this transmitter (Tx) coil was designed at CTR for similar purposes (i.e., wireless energy transfer) and advantageously used for the present feasibility study. It consists essentially of a microcontroller, a switch or gate driver and a MOSFET-based half bridge to adjust the frequency, the duty cycle and the power level. The device is supplied with a voltage of 10 V. The output square wave AC signal was fed into the resonance circuit formed by the coil and the additional capacitor. The capacitor was used to make the whole circuit resonate at 125 kHz. In our case, a capacitor of 0.1 μF was used to match the coil which presents an inductance of 10 μH at 125 kHz. The bloc diagram of the electronics is presented in Figure 2.

Schematics of the complete system are presented in Figure 3. It is stressed that CTR already developed a handheld version of its FMCW reader, for specific purposes. The inductive heating electronics presented in Figure 2 could be easily integrated in the handheld device to form a unique, easy-to-handle interrogation device.

For test purposes, the sensor was placed into the vacuum tube of a high-temperature tube furnace. The tube is made of fused quartz. It has a thickness of 2.5 mm. It is connected to “house” vacuum (100 Pa) and to an additional pumping circuit driven by a turbo molecular pump. A reference pressure gauge is also connected to the tube. During the experiments, room temperature was 29 °C. The Tx coil was mounted outside the tube. The distance between the Rx and Tx coils was close to 15 mm. The reading antenna was placed outside the tube at a distance of about 15 cm. An (inductive) heating power of about 1.5 W was used all along the experiment. After the heating power was switched on, “house” vacuum was first applied inside the tube. The pressure quickly stabilized around 100 Pa. After the sensor reached its equilibrium temperature, a valve connecting the tube to the high-vacuum pumping circuit was turned on and off several times. This generated fast pressure steps in the tube, between 100 Pa and 0.1 Pa. The initial equilibrium temperature before stepping was around 80 °C. This temperature will be referred to as the ‘working temperature’ in the following chapters. The temperature evolution versus time is showed in Figure 4.

It can be seen that the pressure steps made the temperature change drastically, in a reproducible way. An equilibrium temperature of 95 °C was reached under high vacuum (0.1 Pa) versus 78 °C at 100 Pa. This means a sensitivity of 0.17 °C/Pa, below 100 Pa. This demonstrates the high pressure sensitivity of the WiPirani system, in the low pressure range at least. With a reasonable resolution of 0.1 °C, such a system could easily detect pressure variations of 0.6 Pa (6.10−3 mbar). It is worth noting that the resolution could be significantly improved by operating at higher temperature [13]. This opens interesting perspectives that will have to be further investigated in future work.

However, the prototype also shows obvious drawbacks. One limitation is the huge response time observed during the experiments (τ > 5 min). Such a sensor could still be used for some specific applications where a fast response-time is not required. This is the case for applications where good vacuum must be guaranteed over long periods of time and only vacuum default has to be detected, most often during maintenance operation. However, such a long response time would strongly restrict the range of possible applications for the sensor.

As will be shown in Section 3, the huge response time was due to the big size of the prototype's building blocks, especially the bulky antenna used for the interrogation of the SAW sensor. The big size of these components implies a big thermal inertia and therefore a long response time. Ways to strongly improve the response time will be discussed in Section 3. We believe that the response time can be made smaller than a few seconds, especially if MEMS technology is employed.

The second limitation is a more fundamental one. It is linked to the working principle itself. Indeed, the temperature depends on the pressure but also on the distance between the Rx and Tx coils. A small change in the respective position of the inductive coils would change the amount of transmitted energy and have a non-negligible effect on the sensor's temperature and therefore on the pressure reading. To allow for a practical and easy use of the whole system, a technical solution to this problem will have to be found. This issue will be addressed in future work.

Modeling and Discussion

In the following section, we first describe a complete model of the prototype. The wireless power transmitter device (i.e., the two coupled coils) was modeled using FEMM, a finite element modeling freeware dedicated to the simulation of magnetic effects [19] (see Section 3.1). The thermal behavior of the WiPirani was then computed using QUCS, a well-known circuit simulator, after conversion of the prototype into its equivalent circuit (see Section 3.2). A simple, easy-to-build equivalent circuit could be used here because thermal radiation and convection can both be neglected as a first approximation. Indeed, in the experimental configuration described above, thermal radiation accounted for less than 15% of the outgoing energy flow and convection couldn't take place at all, at low pressure. Hence, the only phenomenon to be taken into account is thermal conduction which can be easily modeled using equivalent resistors (analogous to thermal resistance) and capacitors (analogous to thermal capacity). The results showed good agreement between model and experiment. In Section 3.3, the model is used to predict what could be the response time of a slightly improved version of the WiPirani prototype that is a WiPirani equipped with a wire antenna.

Wireless Heating Model

The power transmitting coils were modeled using FEMM. The layout is presented in Figure 5. The solution region was chosen to be a sphere with a radius of 40 mm. The Tx coil was positioned on the equatorial plane. The sphere was filled with air. Asymptotic boundary conditions were applied on the outer boundaries. The individual windings were not considered and each coil was approximated as a flat copper disc with a circular hole in its center.

The ferrite core and ferrite support were not considered. Indeed, we observed–using FEMM models including these two elements–that they have almost no effect on the power transmission ratio. A current of 1 A was injected in the Tx coil, resulting in a current density of 0.19 MA/m2. The AC frequency was 125 kHz. The induced magnetic field is also shown in Figure 5 (field lines and field density). The induced current was computed in the Rx coil, along the center line marked in red. As a very first approximation, the average value along the line was considered to be the average induced current in the Rx coil. The computation was performed for different Rx/Tx distances (center to center), ranging from 2 mm to 30 mm. The power transmission ratio was given by the squared ratio between the induced and injected current densities (the respective impedances of the Rx and Tx coils were considered equal). The power transmission ratio is plotted in Figure 6. Additionally, the two coils were characterized experimentally. The Tx coil was fixed in front of the Rx coil, which was itself mounted on a sliding rail. This time, a constant voltage (Uin) of 15 V was injected in the Tx coil. The induced voltage (Uout) in the Rx coil was recorded as the Rx/Tx distance was increased. The respective impedances of the Rx and Tx coils were again considered equal and the power transmission ratio was given by (Uin/Uout)2. It is also plotted in Figure 6. There is a reasonably good agreement between experimental and simulated results above 15 mm. The experimental power transmission ratio is actually better than the computed one. The rough approximations used to compute the induced current as well as the additional capacitance used to generate a resonance at 125 kHz and therefore improve the transmission efficiency might account for the observed discrepancy, which strongly increases at short distances. However, the agreement is already good enough to validate the model as a first approximation and allow for its use as a simple design tool if the Rx/Tx distance is bigger than 15 mm.

Thermal Behavior Model

As already mentioned above, it is possible to use a simple circuit simulator to compute the thermal behavior of the WiPirani. The main step consists in converting the physical layout into its equivalent RC circuit, using a simple thermal-electrical analogy. The principle of the conversion we made is described in Figure 7. To calculate the equivalent resistance and capacitance of the different elements, the only parameters we used were the thermal conductivity, specific heat capacity, density and geometrical dimensions of these elements. The analogy between Ohm's law for electrical circuits and the Fourier's law of heat conduction and the analogy between the electrical and thermal capacitances yield the following relationships. The equivalent capacitance is directly equal to the heat capacity, one farad (F) corresponding to one J/K. The equivalent resistance is directly equal to the thermal resistance, one ohm (Ω) corresponding to one K/W. For one half of the PCB micro-strip antenna (made of FR4 with a thermal conductivity λ of 0.3 W·K−1·m−1, a density ρ of 1,850 kg/m3, a specific heat capacity Cv of 600 J·kg−1·K−1, a length L of 25 × 10−3 m and a cross-section S of 9 × 10−6 m2) we obtain the thermal resistance Rant = (1/λ)·(L/S) ∼9,260 Ω and the thermal capacity C = ρ·L·S·Cv ∼250 mF. In the equivalent thermal circuit, the antenna is made of two half antennas ‘in parallel’ because the SAW sensor is physically connected to the middle of the dipole antenna. Therefore, using electrical transformation laws for parallel circuits, it can be represented by one single circuit with Rant = 4,630 Ω and Cant = 500 mF. The equivalent resistance and capacitance of the SAW sensor housing (made of Kovar) and its FR4 support were computed in the same way. The obtained values are reported in the QUCS model presented in Figure 8. To take into account the pressure-dependent effect of the surrounding gas, an additional resistor must be used. The resistor models the energy leak into the gas. This resistance decreases when the gas pressure increases. It is known from [13] that the thermal conductivity of air in our present case can be approximated by λ = 0.592·S·P, where S is the gas-sensor surface contact area and P is the pressure in Pa. With S∼25.4 × 10−6 m2 (S is equal to the whole SAW sensor surface minus the bottom surface glued on the FR4 support minus the lateral surface in direct contact with the antenna) a sudden ±100 Pa (i.e., ±1 mbar) pressure variation can therefore be modeled using a 665 Ω resistor. In addition, a programmable switch can be used to model pumping steps (see Figure 8).

In the thermal-electrical analogy, temperature corresponds to voltage and energy flow corresponds to current. Therefore, the heating energy can be directly included in the QUCS model by setting up a current source delivering one ampere (A) for one watt of heating energy. In our case, the heating energy was generated between the SAW sensor and its PCB support using a heating resistor connected to the Rx coil. The heating resistor is therefore the branching point between the Wireless Heating Model (WHM) from Section 3.1 and the Thermal Behavior Model (TBM) described above. Once both models are connected, it becomes possible to compute the behavior of the whole system, as follows. The current induced in the Rx coil must be first calculated using the WHM. The heating power generated by Joule effect in the heating resistor is then calculated and the equivalent current source in the TBM is set accordingly. Then, the QUCS model is run to compute the equivalent temperature behavior of the WiPirani. To get the temperature behavior of the SAW sensor, the voltage (i.e., the equivalent temperature) must be taken right after the current source (see VIN in Figure 8). Indeed, the heating resistor is directly in contact with the SAW sensor. To obtain the absolute temperature, it is also necessary to add the initial room temperature to the calculated VIN. Once the TBM and WHM are built and ready, the only required data to compute the WiPirani temperature behavior versus pressure are Iin (i.e., the current injected in the Tx coil) and the distance between the two coils (D). The results obtained with Iin= 60 mA and D = 15 mm are presented in Figure 4 (red line). There is a good agreement between experimental and numerical results.

It can be seen from the QUCS equivalent circuit that the thermal resistance and thermal capacity of the antenna are big compared to the resistance and capacity of the other elements. It is therefore this building block that is mainly responsible for the very long response time of the whole WiPirani. The TBM-WHM model can be used to check what would be the response time of a WiPirani equipped with a much less massive antenna, made of free-standing aluminum wire (half-length = 6.2 cm, diameter = 0.1 mm). In this case, the equivalent resistance would be 1 kΩ and the equivalent capacity only 19 mF. For such an antenna, the TBM-WHM model yields a response time shorter than 60 s with a still good-enough sensitivity (0.12 °C/Pa). This would already constitute a significant improvement compared to what was obtained with the first WiPirani prototype. The response time might be further improved using miniaturization techniques. It will be the purpose of future work to use these techniques (including MEMS established solutions and processes) to design, fabricate and test a miniaturized and better performing version of the WiPirani. We think that an achievable target is a response time of 1 s, with an accuracy of ±0.1 Pa (±1.10−3 mbar).

We have demonstrated the technical feasibility of a fully wireless and passive low pressure sensor. The sensor is based on a SAW temperature sensor connected to a wireless induction-heating device and requested remotely using a specific Radar-like reader. The first prototype had a high sensitivity of 0.17 °C/Pa but a very long response time (τ > 5 min). A model was developed to account for the sensor's behavior. It was validated against measured data. Then, the model was used to test an improved configuration of the WiPirani using a much less massive antenna than the one used in the first demonstrator. It was shown that the response time might be easily reduced down to 40 s. Next steps will be the design, fabrication and test of a miniaturized version of the WiPirani. A response time of 1s with an accuracy of ±0.1 Pa are expected.

This work was partly funded within the COMET program, coordinated by the Austrian Research Promotion Agency (FFG). Additionally, the authors express thanks to Christoph Krall for the realization of the inductive heating driving electronics, and to Roman Bosshard for his help in the choice of the appropriate magnetics simulation software (FEMM).

Conflicts of Interest

The authors declare no conflict of interest.

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The WiPirani prototype, made of a SAW Tag with its antenna, a planar coil designed for inductive power transfer and a heating resistor. The resistor is located between the SAW Tag and its PCB support. It is not visible on the picture. The underlying grid is made of 0.5 mm × 0.5 mm squares.

Bloc diagram of the driving electronics of the wireless heating stage.

Schematics of the whole WiPirani system, including the WiPirani sensor and its reader.

Experimental and simulated temperature behavior of the first WiPirani demonstrator submitted to pressure cycles, at low pressure. The pressure was changed between two levels–100 Pa and 0.1 Pa–using an on/off valve. The pressure changed quickly between these two levels (the pressure equilibrium was reached in a few seconds only).

FEMM Model of the power transmission component of the WiPirani.

Power transmission ratio vs. distance.

Thermal-Electrical conversion.

QUCS model of the WiPirani prototype.

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