Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-20T12:23:36.845Z Has data issue: false hasContentIssue false

pH-Responsive textile with anthocyanin-laden hydrogel yarns: a colorimetric and feasibility study

Published online by Cambridge University Press:  25 October 2024

A response to the following question: Living textiles

Nikoletta Karastathi
Affiliation:
Bartlett School of Architecture, University College London, London, UK
Anete Krista Salmane*
Affiliation:
Bartlett School of Architecture, University College London, London, UK Department of Biochemical Engineering, University College London, London, UK
Brenda Parker
Affiliation:
Department of Biochemical Engineering, University College London, London, UK
*
Corresponding author: Anete Krista Salmane; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Responsive materials can transform their visual appearance in reaction to environmental stimuli. One example of such responsiveness involves the use of plant-based anthocyanins as pH-mediated allochroic pigments. Despite the increasing interest and applications of this pigment, its applications in urban contexts are very limited. By using pH-mediated colour change as a phenomenon to trial a colourimetric quantitative framework, this study seeks to bridge smart material design with colour science approaches to enable future scale-up applications. The colour values of anthocyanins immobilised in sodium alginate-based hydrogel discs and yarns were measured in response to varying pH values. The colourimetric measurements in CIELAB colour space provided a device for setting independent colour values that demonstrated a clear pattern across the pH range of 1–12. The colour difference (ΔE00) of mean colour values was perceivably different across the pH scale, with a minimum value of 2.7. Key variables of the process have been summarised, and their relationships have been discussed. Finally, a proof-of-concept small-scale textile prototype encompassing anthocyanin-laden hydrogel yarns was developed. The findings of this study contribute towards the integration of non-destructive means of colour measurement as a quantitative tool for biochemical process evaluation.

Type
Results
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Introduction

Smart textiles, which can sense and react to environmental stimuli, have been of particular interest to designers since the discovery of shape memory materials in the 1960s (Kim et al. Reference Kim, Mun, Ko, Zhai, Kafy and Kim2016; Ramlow et al. Reference Ramlow, Andrade and Immich2021; Van Langenhove et al. Reference Van Langenhove, Hertleer, Westbroek and Priniotakis2007). To date, a variety of methods have been used, including textiles that change colour depending on physical and/or chemical conditions, textiles that respond to biological processes and the use of biological materials in the production of responsive textiles. One such example is the use of hydrogels for textile innovations. Hydrogels can enable features such as responsiveness to external stimuli, biocompatibility and encapsulation and controlled release of active ingredients (Sikdar et al. Reference Sikdar, Uddin, Dip, Islam, Hoque, Dhar and Wu2021). The relatively low cost and abundance of raw materials for bio-based formulations is another beneficial aspect. Hydrogels have been developed for a vast range of applications, and while it is clearly beneficial to look outside the boundaries of one’s own discipline, it can be challenging to directly adapt the processes both from a technical and practical point of view. Establishing a conceptual framework to evaluate a reproducibility of process at multiple scales could be a mechanism to catalyse innovations at the intersection of design and sciences.

This study aims to integrate the disciplines of colour science and smart material design. Our primary objective was to utilise colorimetric techniques to evaluate the pH sensitivity of yarns composed of sodium alginate hydrogels that incorporate anthocyanins. Subsequently, we sought to delineate the crucial workflow variables associated with the process and create a framework that can be utilised for scaling the process. The workflow includes the development of pH-responsive fibres, encompassing pigment extraction, material formulation and the colour value assessment as a function of pH values. Furthermore, it aims to open the possibilities of employing pH-responsive textiles as an environmental assessment tool within the built environment.

Responsive materials

Smart textiles, also known as intelligent or stimuli-sensitive textiles, are at the forefront of material innovation. These textiles actively interact with their environment, offering programmability that enables diverse applications across fields such as biomedicine, defence, aerospace, energy storage, fashion, sports, leisure and wireless communication (Yilmaz Reference Yilmaz2019). Within the broad spectrum of smart textiles, the work focuses on colour-changing textiles that have the capacity to change colour in response to a variety of stimuli.

Colour-changing responsive textiles can be categorised according to their triggering mechanisms: (a) photochromic textiles change colour when exposed to electromagnetic radiation, (b) thermochromic fabrics change colour based on temperature changes in their environment, (c) electrochromic textiles alter colour when subjected to an electrical potential, (d) ionochromic textiles change colour due to interactions with ionic species affecting the absorption or emission spectrum, (e) solvatochromic textiles undergo reversible changes in absorption or emission spectrum induced by solvents and (f) halochromic textiles change colour with shifts in pH (Ramlow et al. Reference Ramlow, Andrade and Immich2021).

With our increasing understanding and control of these materials, the textile industry is shifting towards adopting more intelligent and environmentally conscious materials. While chemical technologies have made important breakthroughs in the field of responsive textiles, the biotechnology offers means of unlocking new and unusual textile features and enhancement of sustainability. The bio-integrated approach spans across a variety of scales. A material can be synthesised by cell cultures, such as bacterial cellulose or polyesters or supplemented with biologically produced molecules or organisms, for example, enzymes or probiotics (Hu et al. Reference Hu, Meng, Li and Ibekwe2012; Provin et al. Reference Provin, Regina De Aguiar Dutra, Machado and Vieira Cubas2021; Rathinamoorthy and Kiruba Reference Rathinamoorthy and Kiruba2020). Within the latter approach, there is a lot to learn from the fields of biofabrication and tissue engineering, wherein biologically active constructs with pre-determined architectures can offer valuable insights into biocompatible materials with properties suitable for multiple means of fabrication. Similarly, as in biomedicine also in the context of living textiles, biopolymers are a particularly promising area of exploration. Materials such as sodium alginate, chitin, cellulose and starch nanocomposites exhibit significant potential to be transformed into fibres and filaments (Agarwal et al. Reference Agarwal, Tripathy, Gupta and Kuanr2022). These bio-based materials not only provide unique functionalities but also align with the rising need for sustainable and environmentally friendly textile solutions.

Hydrogels are an important group of materials due to their possibilities of functionalisation, rheological modification and responsiveness to both environmental and physiological conditions (Bashari et al. Reference Bashari, Hemmati Nejad and Pourjavadi2013). Their three-dimensional polymeric network structure can be generated by either natural or synthetic polymers and defines their capability to contain a significant amount of water (Chatterjee and Chi-leung Hui Reference Chatterjee, Chi-leung Hui, Popa, Violeta Ghica and Dinu-Pîrvu2019). Furthermore, they can be tuned to respond to multiple stimuli allowing for a wide range of applications. Their responses are categorised as (a) physical (e.g. temperature, pressure, electrical field, magnetic field and ultrasound), (b) chemical (e.g. pH, solvent, ionic composition, redox) and (c) biological (e.g. enzymatic, antibody) (Sikdar et al. Reference Sikdar, Uddin, Dip, Islam, Hoque, Dhar and Wu2021; Yang et al. Reference Yang, Chen, McClements, Qiu, Li, Zhang, Miao, Tian, Zhu and Jin2022; Yilmaz Reference Yilmaz2019). Looking specifically at pH-sensitive hydrogels, some of the advantageous characteristics include biodegradability, low production cost and accessibility of raw materials (Nascimento Alves et al. Reference Nascimento Alves, Lorranne Santos Lima, Silva Chaves and Albuquerque Meireles2021; Ren et al. Reference Ren, He, Lv, Zhu, Xue, Zhan, Sun, Luo, Li, Song, Niu, Huang, Fang, Fu and Xie2023). An example of such a pH-responsive hydrogel is anthocyanin-laden sodium alginate.

Anthocyanins

Anthocyanins are a group of naturally occurring phenolic compounds found across a range of species in the plant kingdom. In addition to their biological functions, these compounds are also responsible for the bright pigmentation of the plants and fruit ranging in colour from pink/red to blue/purple. The exact colour is dependent on the molecular configuration, which changes as a function of the pH value of the surrounding environment (Alpaslan et al. Reference Alpaslan, Dudu and Aktaş2018; Moldovan et al. Reference Moldovan, David, Chişbora and Cimpoiu2012). Anthocyanin’s ability to function as a visual pH indicator is utilised in various sectors. For example, in the food industry, anthocyanins are incorporated into biodegradable films detecting product deterioration due to pH changes serving as a natural alternative to conventional petroleum-based packaging and alerting consumers to potential product fowling (Abedi-Firoozjah et al. Reference Abedi-Firoozjah, Yousefi, Heydari, Seyedfatehi, Jafarzadeh, Mohammadi, Rouhi and Garavand2022). This has been tested with various food items, including chicken, shrimp and dairy products to provide an indication of the freshness and quality of the contents (Devarayan and Kim Reference Devarayan and Kim2015; Nascimento Alves et al. Reference Nascimento Alves, Lorranne Santos Lima, Silva Chaves and Albuquerque Meireles2021; Ren et al. Reference Ren, He, Lv, Zhu, Xue, Zhan, Sun, Luo, Li, Song, Niu, Huang, Fang, Fu and Xie2023). Anthocyanins also exhibit promising uses in medicine, serving as a biomarker of oral and general health by testing for salivary-pH change (Devarayan and Kim Reference Devarayan and Kim2015). They also have applications in monitoring epidermal wounds, facilitating drug delivery (Hendi et al. Reference Hendi, Umair Hassan, Elsherif, Alqattan, Park, Yetisen and Butt2020) and acting as a biosensor for urea recognition (Al-Qahtani et al. Reference Al-Qahtani, Alzahrani, Azher, Owidah, Abualnaja, Habeebullah and El-Metwaly2021). Finally, there are potential applications for environmental monitoring such as measuring of heavy metal ions in aqueous environments (Mohan and Prakash Reference Mohan and Prakash2022) and as a signalling technology for acid rain (Stojkoski and Kert Reference Stojkoski and Kert2020). Overall, the adaptability of pH-responsive hydrogels extends across environmental, educational, food monitoring and medical applications, highlighting their relevance for a diverse range of practical applications. Thus, understanding all variables that play a role in colour change is critical for future applications, requiring accurate recording and interpretation of the occurring colour change.

Colour measurements

Colour is a visual perception that is used to describe the part of the electromagnetic spectrum that the human eye is sensitive towards ranging from approximately 380 to 770 nm (Nimeroff Reference Nimeroff1968). Not only is it a term that is difficult to define, but it is also challenging to describe an exact colour without using physical examples. This is partially because the way that a colour is perceived broadly depends on three elements – the object, the light source and the viewer (or device). In order to reliably describe or compare colours, within the field of colorimetry, various colour systems have been developed (Ohta and Robertson Reference Ohta and Robertson2006). The choice of a colour space for image processing largely depends on the intended application and context. One of the most widely used colour spaces is CIE 1976 L*a*b* (CIELAB) colour space, which was proposed by the International Commission on Illumination (CIE) (McLaren Reference McLaren2008). This colour space attributes three values to each point, and it can describe any colour perceivable by the human eye in a perceptually uniform manner. CIELAB coordinates are always calculated relative to a reference white, with D65 recommended by the CIE. D65 describes an average daylight spectrum and its colour temperature (Judd et al. Reference Judd, MacAdam, Wyszecki, Budde, Condit, Henderson and Simonds1964). Within this colour system, numerical colour differences correspond to perceived colour differences (Tkalčič and Tasič Reference Tkalčič and Tasič2003). Because it is also a device-independent system, it is often used as a reference colour space.

The orthogonal a* and b* axes or colour coordinates display the gradient from green to red and blue to yellow, respectively, as shown in (Figure 1). These axes can also express the attributes of hue and chroma (Ohta and Robertson Reference Ohta and Robertson2006). The perpendicular L* axis represents the lightness, which ranges from 0 (black) to 100 (white). Using the coordinates of two points situated in this colour space, it is possible to calculate the colour difference (ΔE):

$${\rm{\Delta }}E = \sqrt {{{\left( {L_i^* - L_{i + 1}^*} \right)}^2} + {{\left( {a_i^* - a_{i + 1}^*} \right)}^2} + {{\left( {b_i^* - b_{i + 1}^*} \right)}^2}} $$

Figure 1. CIELAB colour space.

The colour difference is an essential quality control metric used in many industries, such as textiles, coatings, graphic arts and imaging (Luo Reference Luo and Xin2006).

Methods

For the experiments, hydrogel discs and filaments loaded with anthocyanin were produced using cabbage extract (Figure 2). The samples were subsequently divided into segments and exposed to different pH buffers to evaluate their capacity to undergo colour changes in accordance with varying pH levels. The alterations in colour were quantified utilising a portable spectrophotometer. Finally, the obtained measurements were analysed to assess the correlation between pH and CIELAB colour values.

Figure 2. Experimental workflow consisting of pigment extraction, hydrogel material preparation, fabrication and the colour value measurement.

Extraction and quantification of anthocyanins

For the pigment extraction, fresh red cabbage (obtained from a local supermarket) was combined with 50% aqueous ethanol solution (Severn Biotech Ltd.) in a 1:1 (w/v) ratio and subjected to high-speed maceration for a duration of 1 minute, adapting the methodology outlined previously (Chandrasekhar et al. Reference Chandrasekhar, Madhusudhan and Raghavarao2012; Halász et al. Reference Halász, Kóczán and Joóbné Preklet2023). Subsequently, the resulting slurry was stirred at ambient temperature for a period of 3 hours, followed by filtration through a Whatman No.1 filter paper. The resulting extract was then stored under dark conditions at a temperature of 4°C, pending further use.

Anthocyanin content was measured by the pH-differential method to assess the overall monomeric anthocyanin concentration. This procedure, which has been accepted as an industry standard (Lee et al. Reference Lee, Durst and Wrolstad2005), was adapted from the work of Wrolstad et al. (Reference Wrolstad, Acree, Decker, Penner, Reid, Schwartz, Shoemaker, Smith and Sporns2005). Since red cabbage anthocyanins are primarily derivatives of cyanidin glucoside, the pigment yield is calculated as cyanidin-3-glucoside equivalent (Chandrasekhar et al. Reference Chandrasekhar, Madhusudhan and Raghavarao2012). The anthocyanin extract was diluted with aqueous pH 1 (0.1 M potassium chloride) and pH 4.4 (0.1 M sodium acetate) buffers, ensuring absorbance readings at 530 nm remained below 1.2. Post-dilution, the samples were allowed to equilibrate in darkness for a period of 30 minutes. The UV-vis spectrometer was blanked using deionised water, and absorbance spectra within the range of 250–750 nm were recorded in triplicate for both pH values. For the yield calculations, molecular weight (Mw = 449.2 g/mol−1), molar absorptivity (E = 26,900 L/cm mol) and the cell path length (L = 1 cm) were used.

Preparation of anthocyanin-laden sodium alginate discs and yarns

The hydrogel material was prepared by dissolving 90 g/L of sodium alginate (Sigma-Aldrich) and 45 g/L glycerol (Special Ingredients Ltd.) in a 50% solution of previously obtained anthocyanin extract in deionised water. To obtain a homogenous gel, an overhead stirrer was used for a duration of 15 minutes. The hydrogel mixture was then cast into 36 mm x 5 mm (diameter by height) silicon moulds and immersed in a 1 M calcium chloride solution (Sigma-Aldrich) for crosslinking for 20 minutes. For the preparation of the yarns, the pigment-laden hydrogel mixture was loaded in a syringe and extruded in a bath of 1 M calcium chloride solution. The yarns were crosslinked for a period of 10 minutes.

Colour value measurement

The methodology involved the preparation of a total of 12 buffers, as outlined in Table 1. Individual measurements of the hydrogels’ response were conducted for each pH level. This was achieved by longitudinally bisecting the hydrogel discs using a sterile blade to achieve a flat surface and a thickness of 4–5 mm. For each pH value, testing was performed fully submerging three samples in the buffer solution for a duration of 20 minutes in ambient temperature. Colorimetric measurements were conducted 60 minutes after the removal from the buffer solution, whereby the colorimetric changes reached a stable point as was identified from pilot work. Measurements were obtained in triplicate from all three samples for each buffer using a portable spectrophotometer (X-Rite Ci62, Pantone Inc.) with a 4 mm aperture on a standard black background. The device was calibrated using an X-Rite white ceramic plaque and the black trap.

Table 1. Buffering system choice for the colour assessment of anthocyanin-laden sodium alginate-based hydrogels

The anthocyanin-laden hydrogel yarn measurements followed the same methodology with minor adjustments due to the sample geometry. The pH buffer compositions for values 7, 8, 10 and 11 were altered due to issues with precipitation in the first experiment. The following solutions were used instead: 0.1 M MOPS buffer (pH 7), 0.1 M MOPS buffer (pH 7.9), 10−4 M sodium hydroxide (pH 10) and 10−3 M sodium hydroxide (pH 11). Due to the thickness of the yarns being smaller, they were immersed in the pH buffers for 10 minutes, and the colorimetric measurement was taken directly after the exposure. The surface of three segments of the anthocyanin-laden hydrogel yarns was measured simultaneously for nine segments in total.

The L*, a*, b* values were averaged across pH value replicates and displayed in the CIELAB colour space. For presentation purposes, the graph was projected into two-dimensional plots including all axes combinations. Finally, the colour difference (ΔE00) was calculated using the latest refinements to the colour difference calculation described by Sharma et al. (Reference Sharma, Wu and Dalal2005) to compare each consecutive pair of pH values.

Results and discussion

Anthocyanin extraction yield

To obtain the optimal absorbance spectrum readings (<1.2), the initial anthocyanin extract was diluted 19 times. After determining the absorbance difference between pH values 1 and 4.4, the yield of total monomeric anthocyanins in the extract was calculated using the pH-differential method (Lee et al. Reference Lee, Durst and Wrolstad2005). Accounting for the solvent to fresh weight ratio, it was possible to extract 20.1 mg of pigment per 100 g of fresh weight red cabbage.

Although similar anthocyanin extraction procedures have yielded higher results by other authors (439 mg/L [Halász et al. Reference Halász, Kóczán and Joóbné Preklet2023)], 381 mg/L [Chandrasekhar et al. Reference Chandrasekhar, Madhusudhan and Raghavarao2012] and 146.9 mg/100 g [Prietto et al. Reference Prietto, Correa Mirapalhete, Pinto, Hoffmann, Levien Vanier, Lim, Renato, Dias, Da and Zavareze2017]), the current study did not focus on the pigment extraction optimisation. On the contrary, it aims to demonstrate a simple workflow utilising readily available materials that would allow for the integration of anthocyanins as environment-responsive pigments to various biomaterials and design contexts. For increased pigment extraction sample pre-treatments such as freezing and pulverising the biomass, varying extraction time, temperature, solvent type and concentration and application of ultrasound during the solvent extraction phase could be applied (Demirdöven et al. Reference Demirdöven, Özdoğan and Erdoğan-Tokatli2015).

Anthocyanin-laden hydrogel colour value assessment

To evaluate the suitability of anthocyanin-laden hydrogels as an environmental pH indicator, the colour change of the pigment-laden hydrogel discs was analysed across a range of pH values spanning from 1 to 12. The mean colour values are predominantly distributed along the a* (red-green) axis within the CIELAB three-dimensional colour space. This alignment corresponds to visual observations, wherein anthocyanins generally exhibit a pink hue in acidic conditions, a purple tint in neutral environments and a green in alkaline surroundings (Figures 3 and 4). Despite the apparent correlation between colour change and pH values, noteworthy outliers emerge at pH levels of 7, 8 and 11, wherein a* values range from 0 to 10. This anomaly may be due to the precipitation surrounding the anthocyanin-laden hydrogel observed in buffers at these pH values. A common trend that linked these was the presence of phosphate ions. This unexpected interaction with the pigment-laden hydrogel could account for the anomalous colour values observed and would merit further investigation due to the significance of the neutral section of the pH spectrum for many biochemical processes.

Figure 3. Overview of the data collection procedure and the mean CIELAB colour values and the respective colours of the anthocyanin-laden sodium alginate discs across the pH spectrum 1–12.

Figure 4. Projected mean CIELAB coordinates of the anthocyanin-laden sodium alginate discs across the pH spectrum 1–12.

To further test if the mean colour values obtained may serve as the colorimetric pH indicator, the colour difference (ΔE00) was calculated between the consecutive pH values (e.g. 1–2, 2–3). Even though the human eye is differently sensitive to small colour changes in different parts of the colour spectrum, the generally perceivable difference in colours occurs if ΔE00 > 2.3 (Sharma et al. Reference Sharma, Wu and Dalal2005). All of the mean pH colour values exceeded this threshold with the lowest being the difference between pH 7 and 8 (ΔE00 = 2.7) as shown in Table 2.

Table 2. Mean CIELAB colour values and the colour difference between consecutive pH values. The last column indicates the colour difference between the pH indicated in each row and the one above it

Casting hydrogel discs was initially selected as a fabrication method for the experiment due to the compatibility of the geometry for measurement with the colorimeter. To evaluate the methodology for the application of environmentally responsive textiles, a small pilot study was conducted to assess the suitability of hydrogel yarns as carriers of the pigment molecules. While the material composition remained the same, the change in geometry and sample thickness (2 mm in comparison to 4–5 mm for the hydrogel discs) resulted in substantially different colour values to those measured in the discs. The samples displayed very similar trend of an arc distribution primarily along the a* chroma axis (Figure 5). However, the b* and in particular the L* values were consistently shifted. Due to the partial translucency of hydrogel and the thinner samples in comparison to the discs, we speculate the black background of the measurement device was responsible for the universally lower L* values. While the method still requires further refinement for the measurement of yarns, this observation highlights the importance of the geometry, in particular sample thickness and opacity for reproducible colour measurement.

Figure 5. Projected mean CIELAB coordinates of the anthocyanin-laden sodium alginate yarns across a selection of pH values between 2 and 11.

Key workflow variables

The design of pH-responsive yarns requires an awareness of intersecting variables that influence how pH responsiveness may be calibrated and interpreted (Figure 6). The extraction procedure and the pigment yield influence the intensity of the perceived colour within the final material composition. Alternatively, for reproducibility, the pigment concentration in the extract can be determined and accounted for in the final material mixture. After the extraction of the pigment, it is imperative to consider the storage conditions. Anthocyanins are labile molecules, and their stability can be influenced by many chemical and environmental factors, among which temperature and pH are the most significant ones (Halász et al. Reference Halász, Kóczán and Joóbné Preklet2023; Moldovan et al. Reference Moldovan, David, Chişbora and Cimpoiu2012). The pigment colour does not perceivably change (ΔE <2) over a period of 42 days in all pH values tested at 4°C, yet this time frame decreases almost by half when the pigmented material is kept at ambient temperature (22 days in 23°C) (Halász et al. Reference Halász, Kóczán and Joóbné Preklet2023). In addition, UV-radiation, water activity, the presence of oxygen and other chemical compounds such as enzymes, ascorbic acid, hydrogen peroxide and sugars also affect anthocyanin stability (Moldovan et al. Reference Moldovan, David, Chişbora and Cimpoiu2012). Expanding the knowledge of the degradation kinetics and the lifespan of anthocyanin-laden hydrogels would allow to further determine the relevant contexts and applications of this technology outside laboratory conditions.

Figure 6. Key workflow variables for the use of anthocyanin-laden sodium alginate hydrogels as pH-responsive materials. Purple dashes indicate observed interdependencies between the variables.

Material preparation and homogeneity are also an important factor for obtaining reliable colour measurements. Factors like aeration introduced by the overhead stirrer can be mitigated by adjusting the sodium alginate dissolution phase, using a sonication bath or employing vacuum degassing. Experimental variables, such as background colour, treatment time and external physiochemical conditions, further influence colour values, particularly when working with semi-translucent materials. While these variables may play a role in the exact colour measurements obtained, they also provide a wide range of opportunities for the implementation of allochroic surfaces or structures in the design field.

Feasibility and application of pH-responsive textiles

We explored the integration of anthocyanin-laden hydrogel yarns into existing fabrics, using a knitted scaffold for intertwining the yarns (Figure 7). The outcome was a public demonstrator called “Reagent Yarn” showcased at the London Festival of Architecture 2023 (Figures 8 and 9). The prototype aimed to explore several aspects: (a) scale-up, (b) compatibility of hydrogel yarn with existing textiles, (c) the effect of pH on the colour of the yarn and (d) initiating discussions on potential applications.

Figure 7. Details of the “Reagent Yarn” exhibit for London Festival of Architecture 2023. Left: process of interweaving the anthocyanin-laden hydrogel yarns in the cotton base textile. Right: details of yarn thicknesses and pigmentation.

Figure 8. Microscopic details of the “Reagent Yarn” exhibit for the London Festival of Architecture 2023. Left: sample of the anthocyanin-laden hydrogel yarn prior to pH alteration; middle: anthocyanin-laden hydrogel yarn exhibiting colour change after partial pH 10 and pH 2 buffer application; right: anthocyanin-laden hydrogel yarn cross-section illustrating heterogenous pH change in the cross-section (×100 magnification). All images have been obtained using Keyence VHX-7000 digital microscope.

Figure 9. The “Regent Yarn” exhibit for the London Festival of Architecture 2023. Left: pH alteration by application of a pH 10 buffer; middle: pigment colour change in response to various pH values; right: display included pure anthocyanin extract with varying pH values (pH 1–10).

Scale-up

Hydrogel yarns were created using a syringe extrusion technique, following the same method as for colorimetric testing. The hydrogel formulation drew from previous design research (“Eco-Plexis, Speculative Design Projects”), prioritising cost-effectiveness and availability of materials. Several metres of hydrogel yarns can be fabricated in such a manner in short time spans. However, to further scale up and ensure reproducibility the syringe or extruder could be fitted with an automated piston.

Compatibility of hydrogel yarn with existing textiles

Knitting was chosen as the preferred method to fabricate the base textile due to its ability to create intricate programmable patterns. We designed and fabricated a patterned 30/6NE cotton scaffold textile using a programmable knitting machine (Kniterate), allowing for controlled interweaving of threads and providing the required flexibility of the scaffold textile. The hydrogel anthocyanin yarn was then manually interwoven into this fabric. While testing various scaffold textile compositions was outside of the scope of this study, an incidental find revealed that wool yarn degraded the pigments over the course of 48 hours.

The effect of pH on the colour of the yarn

The prototype examined the pH responsiveness of the hydrogel yarns in a non-laboratory environment over a course of 5 days (including exhibition set-up and take-down). The change of colour was mediated through the manual application of a clear pH buffer prior to the exhibition opening. The colour variation was maintained throughout the days, even as the yarns dried. However, as the yarns dried, the colour became darker. The exact correlation between time and colour variation was beyond the scope of this study and requires further investigation, along with the duration for which the hydrated yarns can retain the same colour while still being hydrated. Furthermore, the pigments were also transferred onto the cotton yarn visually enhancing the zone of pigmentation.

Potential applications

The “Reagent Yarn” prototype aims to visualise and prompt conversations on pH – an environmentally important parameter affecting a range of (bio)chemical processes that often is hidden to our perception. The prototype stimulated conversations about pressing environmental concerns and extreme weather events such as ocean acidification and acid rain. Means of demonstrating parameters in real time are bringing public awareness to the role and relationships of our physical and biological environment and serve as educational tools.

We speculate that this technology could be particularly applicable for monitoring urban environments due to the diversity of anthropogenic materials and processes influencing pH levels locally. For example, rainwater interacts with the gases in the atmosphere (e.g. SOx and NOx) lowering the pH value, which in turn leads to corrosion and solubilisation of heavy metals within our built environment (Göbel et al. Reference Göbel, Dierkes and Coldewey2007). In addition to the surface material, the amount and type of pollutants in storm water runoff differs depending on the pH value of the rainwater, which can dynamically change based on a myriad of factors. Furthermore, it has been shown that the pH of atmospheric particles or aerosols is lower in areas linked to the urban heat island effect (Battaglia et al. Reference Battaglia, Douglas and Hennigan2017). The pH level also plays a crucial role in biological processes; for example, the pH-dependant concertation of inorganic carbon in freshwater bodies is directly linked to the growth rate of algae, the excess of which can lead to algal blooms (Liu et al. Reference Liu, Yang, Li, Ge and Kuang2016).

The accessibility and low-cost approach of this technology open avenues for community-led environmental monitoring projects and the creation of DIY kits for the personal production of responsive textiles. Collectively, these applications illustrate the adaptability of responsive textiles in building a more networked and environmentally conscious future, while also guaranteeing that the technology is accessible to a wide spectrum of users and communities.

Demonstration of the workflow feasibility for colorimetric measurements of pigment-laden hydrogels lays the foundation for further research directions. First, the method could be adjusted to include measurements of pigmented materials of more diverse geometries. This would allow for in situ measurements and more specific explorations of suitable contexts for pH-responsive textile applications. Furthermore, longevity and reversibility of pigment colour change are also aspects to further study to evaluate a context for the application. Second, considering the suitability of hydrogels as a matrix for bioprinting (Landerneau et al. Reference Landerneau, Lemarié, Marquette and Petiot2022), colorimetric measurement of the activity of immobilised cells could be a potential avenue for exploration.

Conclusions

This work bridges the fields of colour science and smart material design by tailoring a colorimetric method for assessing pH response within anthocyanin-laden sodium alginate hydrogels. It also lays the foundation for future applications of the colorimetric method for biogenic pigment assessment. We have demonstrated a low-cost method for anthocyanin pigment extraction and hydrogel disc and yarn production. This was coupled with sample measurements across the pH scale to derive CIEL*a*b* values, which provided an understanding of anthocyanin pigment characteristics. Additionally, the successful creation of a prototype piece has showcased the scalability of the developed approach and its compatibility with cotton yarns. Notably, the prototype exhibited a perceivable colour change across a broad pH range of 1–10, speculating on the potential applications of the studied allochroic pigment–hydrogel system in diverse contexts.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Acknowledgements

The authors would like to thank Dr Miriam Wright for her support and for facilitating access to the measurement equipment at the UCL Institute for Sustainable Heritage.

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing interests

None.

Ethics statement

Ethical approval for this type of research was not required.

References

Connections references

Scott, J (2023) Living textiles. Research Directions: Biotechnology Design 1(e6), 13. https://doi.org/10.1017/btd.2022.7 Google Scholar

References

Abedi-Firoozjah, R, Yousefi, S, Heydari, M, Seyedfatehi, F, Jafarzadeh, S, Mohammadi, R, Rouhi, M and Garavand, F (2022) Application of red cabbage anthocyanins as pH-sensitive pigments in smart food packaging and sensors. Polymers 14(8), 1629. https://doi.org/10.3390/polym14081629.CrossRefGoogle ScholarPubMed
Agarwal, P, Tripathy, DB, Gupta, A and Kuanr, BK (2022) Polymeric Biomaterials: Fabrication, Properties and Applications. CRC Press.CrossRefGoogle Scholar
Al-Qahtani, SD, Alzahrani, HK, Azher, OA, Owidah, ZO, Abualnaja, M, Habeebullah, TM and El-Metwaly, NM (2021) Immobilization of anthocyanin-based red-cabbage extract onto cellulose fibers toward environmentally friendly biochromic diagnostic biosensor for recognition of urea. Journal of Environmental Chemical Engineering 9(4), 105493. https://doi.org/10.1016/j.jece.2021.105493.CrossRefGoogle Scholar
Alpaslan, D, Dudu, TE and Aktaş, N (2018) Synthesis, characterization and modification of novel food packaging material from dimethyl acrylamide/gelatin and purple cabbage extract. Materials Science, Agricultural and Food Sciences 6(2).Google Scholar
Bashari, A, Hemmati Nejad, N and Pourjavadi, A (2013) Applications of stimuli responsive hydrogels: a textile engineering approach. Journal of the Textile Institute 104(11), 11451155. https://doi.org/10.1080/00405000.2013.780787.CrossRefGoogle Scholar
Battaglia, MA, Douglas, S and Hennigan, CJ (2017) Effect of the urban heat island on aerosol pH. Environmental Science & Technology 51(22), 1309513103. https://doi.org/10.1021/acs.est.7b02786.CrossRefGoogle ScholarPubMed
Chandrasekhar, J, Madhusudhan, MC and Raghavarao, KSMS (2012) Extraction of anthocyanins from red cabbage and purification using adsorption. Food and Bioproducts Processing 90(4), 615623. https://doi.org/10.1016/j.fbp.2012.07.004.CrossRefGoogle Scholar
Chatterjee, S and Chi-leung Hui, P (2019) Stimuli-responsive hydrogels: An interdisciplinary overview. In Popa, L, Violeta Ghica, M, and Dinu-Pîrvu, C-E (eds.), Hydrogels - Smart Materials for Biomedical Applications. IntechOpen. https://doi.org/10.5772/intechopen.80536.CrossRefGoogle Scholar
Demirdöven, A, Özdoğan, K and Erdoğan-Tokatli, K (2015) Extraction of Anthocyanins from Red Cabbage by Ultrasonic and Conventional Methods: Optimization and Evaluation. Journal of Food Biochemistry 39(5), 491500. https://doi.org/10.1111/JFBC.12153.CrossRefGoogle Scholar
Devarayan, K and Kim, B-S (2015) Reversible and universal pH sensing cellulose nanofibers for health monitor. Sensors and Actuators B: Chemical 209, 281286. https://doi.org/10.1016/j.snb.2014.11.120.CrossRefGoogle Scholar
Göbel, P, Dierkes, C and Coldewey, WG (2007) Storm water runoff concentration matrix for urban areas. Journal of Contaminant Hydrology 91(1–2), 2642. https://doi.org/10.1016/j.jconhyd.2006.08.008.CrossRefGoogle ScholarPubMed
Halász, K, Kóczán, Z and Joóbné Preklet, E (2023) pH-dependent color response of cellulose-based time-temperature indicators impregnated with red cabbage extract. Journal of Food Measurement and Characterization 17(3), 25552565. https://doi.org/10.1007/s11694-023-01805-y.CrossRefGoogle Scholar
Hendi, A, Umair Hassan, M, Elsherif, M, Alqattan, B, Park, S, Yetisen, AK and Butt, H (2020) Healthcare applications of pH-sensitive hydrogel-based devices: A review. International Journal of Nanomedicine 15, 38873901. https://doi.org/10.2147/IJN.S245743.CrossRefGoogle ScholarPubMed
Hu, J, Meng, H, Li, G and Ibekwe, SI (2012) A review of stimuli-responsive polymers for smart textile applications. Smart Materials and Structures 21(5), 053001. https://doi.org/10.1088/0964-1726/21/5/053001.CrossRefGoogle Scholar
Judd, DB, MacAdam, DL, Wyszecki, G, Budde, HW, Condit, HR, Henderson, ST and Simonds, JL (1964) Spectral distribution of typical daylight as a function of correlated color temperature. JOSA 54(8), 10311040. https://doi.org/10.1364/JOSA.54.001031.CrossRefGoogle Scholar
Kim, HC, Mun, S, Ko, H-U, Zhai, L, Kafy, A and Kim, J (2016) Renewable smart materials. Smart Materials and Structures 25(7), 073001. https://doi.org/10.1088/0964-1726/25/7/073001.CrossRefGoogle Scholar
Landerneau, S, Lemarié, L, Marquette, C and Petiot, E (2022) Green 3D bioprinting of plant cells: A new scope for 3D bioprinting. Bioprinting 27, e00216. https://doi.org/10.1016/j.bprint.2022.e00216.CrossRefGoogle Scholar
Lee, J, Durst, R and Wrolstad, R (2005) Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study. Journal of AOAC International 88(5), 12691278. https://doi.org/10.1093/jaoac/88.5.1269.CrossRefGoogle Scholar
Liu, N, Yang, Y, Li, F, Ge, F and Kuang, Y (2016) Importance of controlling pH-depended dissolved inorganic carbon to prevent algal bloom outbreaks. Bioresource Technology 220, 246252. https://doi.org/10.1016/j.biortech.2016.08.059.CrossRefGoogle ScholarPubMed
Luo, MR (2006) Colour quality evaluation. In Xin, JH (ed.), Total Colour Management in Textiles, Boca Raton, FL: Woodhead Publishing, pp. 5775. https://doi.org/10.1533/9781845691080.57.CrossRefGoogle Scholar
McLaren, K (2008) The development of the CIE 1976 (L*a*b*) uniform colour-space and colour-difference formula. Journal of the Society of Dyers and Colourists 92, 338341. https://doi.org/10.1111/j.1478-4408.1976.tb03301.x.CrossRefGoogle Scholar
Mohan, A and Prakash, J (2022) Fabrication of eco-friendly hydrogel strips for the simultaneous quantification of heavy metal ions in aqueous environment. Dyes and Pigments 199, 110045. https://doi.org/10.1016/j.dyepig.2021.110045.CrossRefGoogle Scholar
Moldovan, B, David, L, Chişbora, C and Cimpoiu, C (2012) Degradation kinetics of anthocyanins from European Cranberrybush (Viburnum opulus L.) fruit extracts. Effects of temperature, pH and storage solvent. Molecules 17, 1165511666. https://doi.org/10.3390/molecules171011655.CrossRefGoogle ScholarPubMed
Nascimento Alves, R, Lorranne Santos Lima, T, Silva Chaves, K and Albuquerque Meireles, BRL (2021) Biodegradable films with Brassica Oleracea Capitata extract as a quality indicator in sheep meat. Journal of Food Processing and Preservation 45(1), e14997. https://doi.org/10.1111/jfpp.14997.CrossRefGoogle Scholar
Nimeroff, I (1968) Colorimetry, vol. 104. Washington D.C.: US National Bureau of Standards.Google Scholar
Ohta, N and Robertson, AR (2006) Colorimetry: Fundamentals and applications. In Colorimetry: Fundamentals and Applications. England: John Wiley & Sons, pp. 1334. https://doi.org/10.1002/0470094745.Google Scholar
Prietto, L, Correa Mirapalhete, T, Pinto, Z, Hoffmann, JF, Levien Vanier, N, Lim, L-T, Renato, A, Dias, G, Da, E and Zavareze, R (2017) pH-sensitive films containing anthocyanins extracted from black bean seed coat and red cabbage. LWT 80, 492500. https://doi.org/10.1016/j.lwt.2017.03.006.CrossRefGoogle Scholar
Provin, AP, Regina De Aguiar Dutra, A, Machado, MM and Vieira Cubas, AL (2021) New materials for clothing: Rethinking possibilities through a sustainability approach - A review. Journal of Cleaner Production 282, 124444. https://doi.org/10.1016/j.jclepro.2020.124444.CrossRefGoogle Scholar
Ramlow, H, Andrade, KL and Immich, APS (2021) Smart textiles: an overview of recent progress on chromic textiles. The Journal of the Textile Institute 112(1), 152171. https://doi.org/10.1080/00405000.2020.1785071.CrossRefGoogle Scholar
Rathinamoorthy, R and Kiruba, T (2020) Bacterial cellulose - A potential material for sustainable eco-friendly fashion products. Journal of Natural Fibers 19, 32753287. https://doi.org/10.1080/15440478.2020.1842841.CrossRefGoogle Scholar
Ren, G, He, Y, Lv, J, Zhu, Y, Xue, Z, Zhan, Y, Sun, Y, Luo, X, Li, T, Song, Y, Niu, F, Huang, M, Fang, S, Fu, L and Xie, H (2023) Highly biologically active and pH-sensitive collagen hydrolysate-chitosan film loaded with red cabbage extracts realizing dynamic visualization and preservation of shrimp freshness. International Journal of Biological Macromolecules 233, 123414. https://doi.org/10.1016/j.ijbiomac.2023.123414.CrossRefGoogle ScholarPubMed
Sharma, G, Wu, W and Dalal, EN (2005) The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations. Color Research & Application 30(1), 2130. https://doi.org/10.1002/col.20070.CrossRefGoogle Scholar
Sikdar, P, Uddin, MdM, Dip, TM, Islam, S, Hoque, MdS, Dhar, AK and Wu, S (2021) Recent advances in the synthesis of smart hydrogels. Materials Advances 2(14), 45324573. https://doi.org/10.1039/D1MA00193K.CrossRefGoogle Scholar
Stojkoski, V and Kert, M (2020) Design of pH responsive textile as a sensor material for acid rain. Polymers 12(10), 2251. https://doi.org/10.3390/polym12102251.CrossRefGoogle ScholarPubMed
Tkalčič, M and Tasič, JF (2003) Colour spaces - Perceptual, historical and applicational background., Vol. A. Presented at the IEEE Region 8 EUROCON 2003: Computer as a Tool - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 304308. https://doi.org/10.1109/EURCON.2003.1248032.CrossRefGoogle Scholar
Van Langenhove, L, Hertleer, C, Westbroek, P and Priniotakis, J (2007) Textile sensors for healthcare. In Smart Textiles for Medicine and Healthcare: Materials, Systems and Applications. Cambridge: Woodhead Publishing Limited, pp. 106122. https://doi.org/10.1533/9781845692933.1.106.CrossRefGoogle Scholar
Wrolstad, RE, Acree, TE, Decker, EA, Penner, MH, Reid, DS, Schwartz, SJ, Shoemaker, CF, Smith, DM and Sporns, P (2005) Handbook of food analytical chemistry. Handbook of Food Analytical Chemistry 1–2, 11362. https://doi.org/10.1002/0471709085.Google Scholar
Yang, Z, Chen, L, McClements, DJ, Qiu, C, Li, C, Zhang, Z, Miao, M, Tian, Y, Zhu, K and Jin, Z (2022) Stimulus-responsive hydrogels in food science: A review. Food Hydrocolloids 124, 107218. https://doi.org/10.1016/j.foodhyd.2021.107218.CrossRefGoogle Scholar
Yilmaz, ND (ed.) (2019) Smart Textiles: Wearable Nanotechnology. Hoboken, New Jersey; Salem, Massachusetts: John Wiley & Sons; Scrivener Publishing.Google Scholar
Figure 0

Figure 1. CIELAB colour space.

Figure 1

Figure 2. Experimental workflow consisting of pigment extraction, hydrogel material preparation, fabrication and the colour value measurement.

Figure 2

Table 1. Buffering system choice for the colour assessment of anthocyanin-laden sodium alginate-based hydrogels

Figure 3

Figure 3. Overview of the data collection procedure and the mean CIELAB colour values and the respective colours of the anthocyanin-laden sodium alginate discs across the pH spectrum 1–12.

Figure 4

Figure 4. Projected mean CIELAB coordinates of the anthocyanin-laden sodium alginate discs across the pH spectrum 1–12.

Figure 5

Table 2. Mean CIELAB colour values and the colour difference between consecutive pH values. The last column indicates the colour difference between the pH indicated in each row and the one above it

Figure 6

Figure 5. Projected mean CIELAB coordinates of the anthocyanin-laden sodium alginate yarns across a selection of pH values between 2 and 11.

Figure 7

Figure 6. Key workflow variables for the use of anthocyanin-laden sodium alginate hydrogels as pH-responsive materials. Purple dashes indicate observed interdependencies between the variables.

Figure 8

Figure 7. Details of the “Reagent Yarn” exhibit for London Festival of Architecture 2023. Left: process of interweaving the anthocyanin-laden hydrogel yarns in the cotton base textile. Right: details of yarn thicknesses and pigmentation.

Figure 9

Figure 8. Microscopic details of the “Reagent Yarn” exhibit for the London Festival of Architecture 2023. Left: sample of the anthocyanin-laden hydrogel yarn prior to pH alteration; middle: anthocyanin-laden hydrogel yarn exhibiting colour change after partial pH 10 and pH 2 buffer application; right: anthocyanin-laden hydrogel yarn cross-section illustrating heterogenous pH change in the cross-section (×100 magnification). All images have been obtained using Keyence VHX-7000 digital microscope.

Figure 10

Figure 9. The “Regent Yarn” exhibit for the London Festival of Architecture 2023. Left: pH alteration by application of a pH 10 buffer; middle: pigment colour change in response to various pH values; right: display included pure anthocyanin extract with varying pH values (pH 1–10).