Tag Archives: mechanics

Nano biomechanical engineering of agent delivery to cells

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figure 1 from [1] with text explanationWhile many of us are being jabbed in the arm to deliver an agent that stimulates our immune system to recognize the coronavirus SARS-CoV-2 as a threat and destroy it, my research group has been working, in collaboration with colleagues at the European Commission Joint Research Centre, on the dynamics of nanoparticles [1] [see ‘Size matters‘ on October 23rd, 2019] which could be used as carriers for the targeted delivery of therapeutic, diagnostic and imaging agents in the human body [2].  The use of nanoparticles to mechanically stimulate stem cells to activate signalling pathways and modulate their differentiation also has some potential [3]. In studies of the efficacy of nanoparticles in these biomedical applications, the concentration of nanoparticles interacting with the cell is a primary factor influencing both the positive and negative effects.  Such studies often involve exposing a monolayer of cultured cells adhered to the bottom of container to a dose of nanoparticles and monitoring the response over a period of time.  Often, the nominal concentration of the nanoparticles in biological medium supporting the cells is reported and used as the basis for determining the dose-response relationships.  However, we have shown that this approach is inaccurate and leads to misleading results because the nanoparticles in solution are subject to sedimentation due to gravity, Brownian motion [see ‘Slow moving nanoparticles‘ on December 13th, 2017] and inter-particle forces [see ‘ Going against the flow‘ on February 3rd, 2021] which affect their transport within the medium [see graphic] and the resultant concentration adjacent to the monolayer of cells.  Our experimental results using the optical method of caustics [see ‘Holes in fluids‘ on October 22nd, 2014] have shown that nanoparticle size, colloidal stability and solution temperature influence the distribution of nanoparticles in solution.  For particles larger than 60 nm in diameter (about one thousandth of the diameter of a human hair) the nominal dose differs significantly from the dose experienced by the cells.  We have developed and tested a theoretical model that accurately describes the settling dynamics and concentration profile of nanoparticles in solution which can be used to design in vitro experiments and compute dose-response relationships.

References

[1] Giorgi F, Macko P, Curran JM, Whelan M, Worth A & Patterson EA. 2021 Settling dynamics of nanoparticles in simple and biological media. Royal Society Open Science, 8:210068.

[2] Daraee H, Eatemadi A, Abbasi E, Aval SF, Kouhi M, & Akbarzadeh A. 2016 Application of gold nanoparticles in biomedical and drug delivery. Artif. Cells Nanomed. Biotechnol. 44, 410–422. (doi:10.3109/21691401.2014.955107)

[3] Wei M, Li S, & Le W. 2017 Nanomaterials modulate stem cell differentiation: biological
interaction and underlying mechanisms. J. Nanobiotechnol. 15, 75. (doi:10.1186/s12951-
017-0310-5)

Jigsaw puzzling without a picture

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A350 XWB passes Maximum Wing Bending test

A350 XWB passes Maximum Wing Bending test

Research sometimes feels like putting together a jigsaw puzzle without the picture or being sure you have all of the pieces.  The pieces we are trying to fit together at the moment are (i) image decomposition of strain fields [see ‘Recognising strain’ on October 28th 2015] that allows fields containing millions of data values to be represented by a feature vector with only tens of elements which is useful for comparing maps or fields of predictions from a computational model with measurements made in the real-world; (ii) evaluation of the variation in measurement uncertainty over a field of view of measured displacements or strains in a large structure [see ‘Industrial uncertainty’ on December 12th 2018] which provides information about the quality of the measurements; and (iii) a probabilistic validation metric that provides a measure of how well predictions from a computational model represent measurements made in the real world [see ‘Million to one’ on November 21st 2018].  We have found some of the missing pieces of the jigsaw, for example we have established how to represent the distribution of measurement uncertainty in the feature vector domain [see ‘From strain measurements to assessing El Niño events’ on March 17th 2021] so that it can be used to assess the significance of differences between measurements and predictions represented by their feature vectors – this connects (i) and (ii) together.  Very recently we have demonstrated a generic technique for performing image decomposition of irregularly shaped fields of data or data fields with holes [see Christian et al, 2021] which extends the applicability of our method for comparing measurements and predictions to real-world objects rather than idealised shapes.  This allows (i) to be used in industrial applications but we still have to work out how to connect this to the probabilistic metric in (iii) while also incorporating spatially-varying uncertainty.  These techniques can be used in a wide range of applications, as demonstrated in our recent work on El Niño events [see Alexiadis et al, 2021], because, by treating all fields of data as images, the techniques are agnostic about the source and format of the data.  However, at the moment, our main focus is on their application to ground tests on aircraft structures as part of the Smarter Testing project in collaboration with Airbus, Centre for Modelling & Simulation, Dassault Systèmes, GOM UK Ltd, and the National Physical Laboratory with funding from the Aerospace Technology Institute.  Together we are working towards digital continuity across virtual and physical testing of aircraft structures to provide live data fusion and enable condition-led inspections, test control and validation of computational models.  We anticipate these advances will reduce time and costs for physical tests and accelerate the development of new designs of aircraft that will contribute to global sustainability targets (the aerospace industry has committed to reduce CO2 emissions to 50% of 2005 levels by 2050).  The Smarter Testing project has an ambitious goal which reveals that our pieces of the jigsaw puzzle belong to a small section of a much larger one.

For more on the Smarter Testing project see:

https://www.aerospacetestinginternational.com/news/structural-testing/smarter-testing-research-program-to-link-virtual-and-physical-aerospace-testing.html

https://www.aerospacetestinginternational.com/opinion/how-integrating-the-virtual-and-physical-will-make-aerospace-testing-and-certification-smarter.html

References

Alexiadis A, Ferson S, Patterson EA. Transformation of measurement uncertainties into low-dimensional feature vector space. Royal Society open science. 8(3):201086, 2021.

Christian WJ, Dean AD, Dvurecenska K, Middleton CA, Patterson EA. Comparing full-field data from structural components with complicated geometries. Royal Society open science. 8(9):210916, 2021.

Image: http://www.airbus.com/galleries/photo-gallery

If you don’t succeed, try and try again…

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Photograph of S-shaped plateYou would not think it was difficult to build a thin flat metallic plate using a digital description of the plate and a Laser Powder Bed Fusion (L-PBF) machine which can build complex components, such as hip prostheses.  But it is.  As we have discovered since we started our research project on the thermoacoustic response of additively manufactured parts (see ‘Slow start to an exciting new project on thermoacoustic response of AM metals‘ on September 9th, 2020).  L-PBF involves using a laser beam to melt selected regions of a thin layer of metal powder spread over a flat bed.  The selected regions represent a cross-section of the desired three-dimensional component and repeating the process for each successive cross-section results in the additive building of the component as each layer solidifies.  And there in those last four words lies the problem because ‘as each layer solidifies’ the temperature distribution between the layers causes different levels of thermal expansion that results in strains being locked into our thin plates.  Our plates are too thin to build with their plane surfaces horizontal or perpendicular to the laser beam so instead we build them with their plane surface parallel to the laser beam, or vertical like a street sign.  In our early attempts, the residual stresses induced by the locked-in strains caused the plate to buckle into an S-shape before it was complete (see image).  We solved this problem by building buttresses at the edges of the plate.  However, when we remove the buttresses and detach the plate from the build platform, it buckles into a dome-shape.  Actually, you can press the centre of the plate and make it snap back and forth noisily.  While we are making progress in understanding the mechanisms at work, we have some way to go before we can confidently produce flat plates using additive manufacturing that we can use in comparisons with our earlier work on the performance of conventionally, or subtractively, manufactured plates subject to the thermoacoustic loading experienced by the skin of a hypersonic vehicle [see ‘Potential dynamic buckling in hypersonic vehicle skin‘ on July 1st 2020) or the containment walls in a fusion reactor.  Sometimes research is painfully slow but no one ever talks about it.  Maybe because we quickly forget the painful parts once we have a successful outcome to brag about. But it is often precisely the painful repetitions of “try and try again” that allow us to reach the bragging stage of a successful outcome.

The research is funded jointly by the National Science Foundation (NSF) in the USA and the Engineering and Physical Sciences Research Council (EPSRC) in the UK (see Grants on the Web).

References

Silva AS, Sebastian CM, Lambros J and Patterson EA, 2019. High temperature modal analysis of a non-uniformly heated rectangular plate: Experiments and simulations. J. Sound & Vibration, 443, pp.397-410.

Magana-Carranza R, Sutcliffe CJ, Patterson EA, 2021, The effect of processing parameters and material properties on residual forces induced in Laser Powder Bed Fusion (L-PBF). Additive Manufacturing. 46:102192

Our last DIMES

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Photograph of wing test in AWICThirty-three months ago (see ‘Finding DIMES‘ on February 6th, 2019) we set off at a gallop ‘to develop and demonstrate an automated measurement system that integrates a range of measurement approaches to enable damage and cracks to be detected and monitored as they originate at multi-material interfaces in an aircraft assembly’. The quotation is taken directly from the aim of the DIMES project which was originally planned and funded as a two-year research programme. Our research, in particular the demonstration element, has been slowed down by the pandemic and we resorted to two no-cost extensions, initially for three months and then for six months to achieve the project aim.   Two weeks ago, we held our final review meeting, and this week we will present our latest results in the third of a series of annual workshops hosted by Airbus, the project’s topic manager.   The DIMES system combines visual and infrared cameras with resistance strain gauges and fibre Bragg gratings to detect 1 mm cracks in metals and damage indications in composites that are only 6 mm in diameter.  We had a concept design by April 2019 (see ‘Joining the dots‘ on July 10th, 2019) and a detailed design by August 2019.  Airbus supplied us with a section of A320 wing, and we built a test-bench at Empa in Zurich in which we installed our prototype measurement system in the last quarter of 2019 (see ‘When seeing nothing is a success‘ on December 11th, 2019).  Then, the pandemic intervened and we did not finish testing until May 2021 by which time, we had also evaluated it for monitoring damage in composite A350 fuselage panels (see ‘Noisy progressive failure of a composite panel‘ on June 30th, 2021).  In parallel, we have installed our ‘DIMES system’ in ground tests on an aircraft wing at Airbus in Filton (see image) and, using a remote installation, in a cockpit at Airbus in Toulouse (see ‘Most valued player performs remote installation‘ on December 2nd, 2020), as well as an aircraft at NRC Aerospace in Ottawa (see ‘An upside to lockdown‘ on April 14th 2021).   Our innovative technology allows condition-led monitoring based on automated damage detection and enables ground tests on aircraft structures to be run 24/7 saving about 3 months on each year-long test.

The University of Liverpool is the coordinator of the DIMES project and the other partners are Empa, Dantec Dynamics GmbH and Strain Solutions Ltd.

The DIMES project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 820951.

The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.