Optode Based Chemical Imaging-Possibilities, Challenges, and New Avenues in Multidimensional Optical Sensing

Simultaneous Measurement of Total Ammonia Nitrogen and Free Ammonia via Integrated Electrochemical Acidification─Optode Flow Cell

The accurate measurement of total ammonia nitrogen (TAN) and free ammonia is crucial for various environmental, biomedical and industrial applications. We present a novel integrated system combining electrochemical water splitting with ammonia optodes to simultaneously measure TAN and free ammonia. Water electrolysis induces localized pH shifts, altering the ammonia speciation in the sample solution: an increase in pH near the cathode leads to conversion of NH4+ to NH3, enabling the measurement of TAN. Concurrently, a decrease in pH near the anode reduces the NH3 concentration to zero, enabling real-time zero calibration. In areas unaffected by these pH changes, the optode readout can effectively measure free NH3. The system demonstrates a measurement range of 0-300 mg·L-1 for both TAN and NH3, with a complete measurement cycle requiring only 6 min. The method was validated through the analysis of urine samples, showcasing its potential for real-time monitoring in clinical and environmental settings. The electrochemical speciation shifting allows for precise TAN measurement, while the zero-point calibration provided by the anode enhances the method's robustness and reliability. Overall, this study introduces a versatile and efficient approach for the simultaneous determination of TAN and NH3, offering significant improvements in speed and operational simplicity.

Novel Approach for Lifetime-Proportional Luminescence Imaging Using Frame Straddling

Optode-based chemical imaging is a rapidly evolving field that has substantially enhanced our understanding of the role of microenvironments and chemical gradients in biogeochemistry, microbial ecology, and biomedical sciences. Progress in sensor chemistry has resulted in a broadened spectrum of analytes, alongside enhancements in sensor performance (e.g., sensitivity, brightness, and photostability). However, existing imaging techniques are often costly, challenging to implement, and limited in their recording speed. Here we use the "frame-straddling" technique, originally developed for particle image velocimetry for imaging the O2-dependent, integrated luminescence decay of optical O2 sensor materials. The method synchronizes short excitation pulses and camera exposures to capture two frames at varying brightness, where the first excitation pulse occurs at the end of the exposure of the first frame and the second excitation pulse at the beginning of the second frame. Here the first frame truncates the luminescence decay, whereas the second frame fully captures it. The difference between the frames quantifies the integral of the luminescence decay curve, which is proportional to the luminescence lifetime, at time scales below one millisecond. Short excitation pulses avoid depopulation of the ground state of luminophores, resulting in a linear Stern-Volmer response with increasing concentrations of the quencher (O2), which can be predicted through a simple model. This methodology is compatible with a wide range of camera systems, making it a versatile tool for various optode based chemical imaging applications. We showcase the utility of frame straddling in measuring O2 dynamics around algae and by observing O2 scavenging sodium dithionite particles sinking through oxygenated water.

Simultaneous Imaging of Temperature and Oxygen by Utilizing Thermally Activated Delayed Fluorescence and Phosphorescence of a Single Indicator

Chemical gradients are essential in biological systems, affecting processes like microbial activity in soils and nutrient cycling. Traditional tools, such as microsensors, offer high-resolution data but are limited to one-dimensional measurements. Planar optodes allow for two-dimensional (2D) and three-dimensional (3D) chemical imaging but are often sensitive to temperature changes. This study presents an advanced dual-emission optical sensor that simultaneously measures temperature and oxygen using a modified platinum(II) meso-tetrakis(3,5-ditert-butylphenyl)-tetra(2-tert-butyl-1,4-naphthoquinono)porphyrin. The ratio between thermally activated delayed fluorescence and phosphorescence was optimized by modifying platinum(II) naphthoquinonoporphyrin with tert-butyl groups which simultaneously improved solubility in apolar solvents and polymer matrix (polystyrene). This dual-function sensor enables two-parameter chemical imaging with a consumer-grade RGB camera or a hyperspectral camera. We demonstrated 2D visualization of temperature and oxygen distribution in a model soil system. The RGB camera provided rapid and cost-effective imaging, while the hyperspectral camera offered more detailed spectral information despite some limitations. Our findings revealed the formation of a stable temperature gradient and oxygen depletion, driven by water content and temperature-sensitive microbial activity. This dual O2/T sensor, with further potential improvements, shows considerable promise for advanced multiparameter sensing in complex biological and environmental studies, providing deeper insights into dynamic microenvironments.

Highly Reversible "On-Off-On" Fluorescence Switch Governed by pH, Utilizing Bis(Benzimidazole) Derivatives with Varied Link Groups

In this work, a series of dibenzimidazole derivatives 1-4, act as highly reversible colorimetric and fluorescent pH chemosensor, were designed and synthesized. Excellent reversible pH response of these sensors could be found by a specific pH change through obvious fluorescent color changes. The response is not affected by common cations (including Al3+, Cu2+, Ca2+, Cd2+, Co2+, Cr3+, Mg2+, Na+, K+, Ni2+, Pb2+ and Zn2+) and anions (including F-, Cl-, Br-, I-, ClO4-, H2PO4-, HSO4-, HCO3- and CH3COO-). Notably, these sensors can be reused more than 10 times without losing functionality. Unlike previous reports, the distinct properties of 1-4 are attributed to the varied link groups. Based on comprehensive experimental data and mechanistic analyses, it is concluded that sensors 1-4 are promising candidates for use as highly reversible "on-off-on" fluorescence switches under precise pH control.

Conducting polymer functionalization in search of advanced materials in ionometry: ion-selective electrodes and optodes

Functionalized conducting polymers (FCPs) have recently garnered attention as ion-selective sensor materials, surpassing their intrinsic counterparts due to synergistic effects that lead to enhanced electrochemical and analytical parameters. Following a brief introduction of the fundamental concepts, this article provides a comprehensive review of the recent developments in the application of FCPs in ion-selective electrodes (ISEs) and ion-selective optodes (ISOs), particularly as ion-to-electron transducers, optical transducers, and ion-selective membranes. Utilizing FCPs in these devices offers a promising avenue for detecting and measuring ions in various applications, regardless of the sample nature and composition. Research has focused on functionalizing different conducting polymers, such as polyaniline and polypyrrole, through strategies such as doping and derivatization to alter their hydrophobicity, conductance, redox capacitance, surface area, pH sensitivity, gas and light sensitivity, etc. These modifications aim to enhance performance outcomes, including potential stability/emission signal stability, reproducibility and low detection limits. The advancements have led to the transition of ISEs from conventional zero-current potentiometric ion sensing to innovative current-triggered sensing approaches, enabling calibration-free applications and emerging concepts such as opto-electro dual sensing systems. The intrinsic pH cross-response and instability of the optical signal of ISOs have been overcome through the novel optical signal transduction mechanisms facilitated by FCPs. In this review, the characteristics of materials, functionalization approaches, particular implementation strategies, specific performance outcomes and challenges faced are discussed. Consolidating dispersed information in the field, the in-depth analysis presented here is poised to drive further innovations by broadening the scope of ion-selective sensors in real-world scenarios.

Comparative analysis of a bulk optode based on a valinomycin ionophore and a nano-optode in micelles with pluronic F-127 for the quantification of potassium in aqueous solutions

In this work, two types of optical sensors were prepared for the quantification of potassium: the bulk optode (BO) and nano-optode (NO). The BO was prepared using three main components: the ionophore valinomycin, the ion exchanger tetrakis(4-chlorophenyl) potassium borate (K-TCPB), and the chromoionophore ETH 5294 (CHI). The optimal composition was found to be in a ratio of [1 : 1 : 1]. The NO was prepared by miniaturizing the BO through sonication in surfactant Pluronic F-127. The working range for the linear calibration model of BO was from 10-6 to 1.0 M K+ with a LODBO = 0.31 μM, meanwhile for NO was from 10-4 to 1.0 M K+ with a LODNO = 30.3 μM. Both optodes were tested for selectivity towards K+ in the presence of alkaline and alkaline earth ions, with a selectivity coefficient > 1.0. Furthermore, precision and stability studies of BO and NO were performed for three levels of K+ concentrations, 10-6, 10-3, 1.0 M for BO and 10-4, 10-2, 1.0 M for NO, showing a good homogeneity of the NO in the whole concentration range. However, an excessive variability was obtained for BO at 1.0 M K+. Therefore, the NO represents a potential tool for quantification of K+.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Ratiometric fluorescent sensor with large pseudo-Stokes shifts for precise sensing and imaging of pH without interferential background fluorescence

Endowing fluorescent pH sensors with large Stokes shifts promises to resolve interferential background fluorescence in practice, and yet few such method has been reported, owing to lack of luminescent materials with large Stokes shifts used in fluorescent sensors. Herein, we elaborately designed NaGdF4:Ce@NaGdF4:Nd@NaYF4:Eu core-double shells (CDS) lanthanide-doped fluoride nanoparticles (LFNPs), employing Gd3+-mediated energy migration and interfacial energy transfer to realize intense red and NIR emissions under 254 nm irradiation, and pseudo-Stokes shifts of which reached up to striking 361 nm and 610 nm, respectively. The CDS LFNPs collaborated with absorption-based pH indicator bromocresol green to from a novel fluorescent sensor film, and employing low-cost dual chip RGB-NIR camera to precisely record luminescence signals. On the basis of inner-filter effects, this senor system enabled accurate ratiometric read-out of pH value ranging from 5 to 6 (pKa ± 0.5), according to intensity ratios of pH-sensitive red emissions and referenced NIR emissions, avoiding common errors (e.g., fluctuant light sources). Notably, the large pseudo-Stokes shifts allowed red and NIR emissions far from the interfering background fluorescence possessing relatively small Stokes shifts, ensuring elevated signal-to-noise ratio and accurate pH determination. Therefore, the devised pH sensor system based on the CDS LFNPs exhibited sufficient accuracy in autofluorescent real samples (e.g., algae, serum), revealing a novel way of employing large pseudo-Stokes shifts to realize the background-free pH measurement and 2D imaging.

Differential impacts of sewage sludge and biochar on phosphorus-related processes: An imaging study of the rhizosphere

Recycling of phosphorus (P) from waste streams in agriculture is essential to reduce the negative environmental effects of surplus P and the unsustainable mining of geological P resources. Sewage sludge (SS) is an important P source; however, several issues are associated with the handling and application of SS in agriculture. Thus, post-treatments such as pyrolysis of SS into biochar (BC) could address some of these issues. Here we elucidate how patches of SS in soil interact with the living roots of wheat and affect important P-related rhizosphere processes compared to their BC counterparts. Wheat plants were grown in rhizoboxes with sandy loam soil, and 1 cm Ø patches with either SS or BC placed 10 cm below the seed. A negative control (CK) was included. Planar optode pH sensors were used to visualize spatiotemporal pH changes during 40 days of plant growth, diffusive gradients in thin films (DGT) were applied to map labile P, and zymography was used to visualize the spatial distribution of acid (ACP) and alkaline (ALP) phosphatase activity. In addition, bulk soil measurements of available P, pH, and ACP activity were conducted. Finally, the relative abundance of bacterial P-cycling genes (phoD, phoX, phnK) was determined in the patch area rhizosphere. Labile P was only observed in the area of the SS patches, and SS further triggered root proliferation and increased the activity of ACP and ALP in interaction with the roots. In contrast, BC seemed to be inert, had no visible effect on root growth, and even reduced ACP and ALP activity in the patch area. Furthermore, there was a lower relative abundance of phoD and phnK genes in the BC rhizosphere compared to the CK. Hence, optimization of BC properties is needed to increase the short-term efficiency of BC from SS as a P fertilizer.

Optical sensors (optodes) for multiparameter chemical imaging: classification, challenges, and prospects

Chemical gradients and uneven distribution of analytes are common in natural and artificial systems. As a result, the ability to visualize chemical distributions in two or more dimensions has gained significant importance in recent years. This has led to the integration of chemical imaging techniques into all domains of analytical chemistry. In this review, we focus on the use of optical sensors, so-called optodes, to obtain real-time and multidimensional images of two or more parameters simultaneously. It is important to emphasize that multiparameter imaging in this context is not confined solely to multiple chemical parameters (analytes) but also encompasses physical (e.g., temperature or flow) or biological (e.g., metabolic activity) parameters. First, we discuss the technological milestones that have paved the way for chemical imaging using optodes. Later, we delve into various strategies that can be taken to enable multiparameter imaging. The latter spans from developing novel receptors that enable the recognition of multiple parameters to chemometrics and machine learning-based techniques for data analysis. We also explore ongoing trends, challenges, and prospects for future developments in this field. Optode-based multiparameter imaging is a rapidly expanding field that is being fueled by cutting-edge technologies. Chemical imaging possesses the potential to provide novel insights into complex samples, bridging not only across various scientific disciplines but also between research and society.

Machine learning for optical chemical multi-analyte imaging : Why we should dare and why it's not without risks

Simultaneous sensing of metabolic analytes such as pH and O2 is critical in complex and heterogeneous biological environments where analytes often are interrelated. However, measuring all target analytes at the same time and position is often challenging. A major challenge preventing further progress occurs when sensor signals cannot be directly correlated to analyte concentrations due to additional effects, overshadowing and complicating the actual correlations. In fields related to optical sensing, machine learning has already shown its potential to overcome these challenges by solving nested and multidimensional correlations. Hence, we want to apply machine learning models to fluorescence-based optical chemical sensors to facilitate simultaneous imaging of multiple analytes in 2D. We present a proof-of-concept approach for simultaneous imaging of pH and dissolved O2 using an optical chemical sensor, a hyperspectral camera for image acquisition, and a multi-layered machine learning model based on a decision tree algorithm (XGBoost) for data analysis. Our model predicts dissolved O2 and pH with a mean absolute error of < 4.50·10-2 and < 1.96·10-1, respectively, and a root mean square error of < 2.12·10-1 and < 4.42·10-1, respectively. Besides the model-building process, we discuss the potentials of machine learning for optical chemical sensing, especially regarding multi-analyte imaging, and highlight risks of bias that can arise in machine learning-based data analysis.

Simple colorimetric copper(II) sensor - Spectral characterization and possible applications

New o-hydroxyazocompound L bearing pyrrole residue was obtained in the simple synthetic protocol. The structure of L was confirmed and analyzed by X-ray diffraction. It was found that new chemosensor can be successfully used as copper(II) selective spectrophotometric regent in solution and can be also applied for the preparation of sensing materials generating selective color signal upon interaction with copper(II). Selective colorimetric response towards copper(II) is manifested by a distinct color change from yellow to pink. Proposed systems were effectively used for copper(II) determination at concentration level 10^-8 M in model and real samples of water.

Optode-based chemical imaging of laboratory burned soil reveals millimeter-scale heterogeneous biogeochemical responses

Soil spatial responses to fire are unclear. Using optical chemical sensing with planar 'optodes', pH and dissolved O₂ concentration were tracked spatially with a resolution of 360 μm per pixel for 72 h after burning soil in the laboratory with a butane torch (∼1300 °C) and then sprinkling water to simulate a postfire moisture event. Imaging data from planar optodes correlated with microbial activity (quantified via RNA transcripts). Post-fire and post-wetting, soil pH increased throughout the entire ∼13 cm × 17 cm × 20 cm rectangular cuboid of sandy loam soil. Dissolved O₂ concentrations were not impacted until the application of water postfire. pH and dissolved O₂ both negatively correlated (p < 0.05) with relative transcript expression for galactose metabolism, the degradation of aromatic compounds, sulfur metabolism, and narH. Additionally, dissolved O₂ negatively correlated (p < 0.05) with the relative activity of carbon fixation pathways in Bacteria and Archaea, amoA/amoB, narG, nirK, and nosZ. nifH was not detected in any samples. Only amoB and amoC correlated with depth in soil (p < 0.05). Results demonstrate that postfire soils are spatially complex on a mm scale and that using optode-based chemical imaging as a chemical navigator for RNA transcript sampling is effective.

Imaging Sample Acidification Triggered by Electrochemically Activated Polyaniline

In this letter, we demonstrate 2D acidification of samples at environmental and physiological pH with an electrochemically activated polyaniline (PANI) mesh. A novel sensor–actuator concept is conceived for such a purpose. The sample is sandwiched between the PANI (actuator) and a planar pH optode (sensor) placed at a very close distance (∼0.50 mm). Upon application of a mild potential to the mesh, in contrast to previously reported acidification approaches, PANI releases a significant number of protons, causing an acid–base titration in the sample. This process is monitored in time and space by the pH optode, providing chemical imaging of the pH decrease along the dynamic titration via photographic acquisition. Acidification of samples at varying buffer capacity has been investigated: the higher the buffer capacity, the more time (and therefore proton charge) was needed to reach a pH of 4.5 or even lower. Also, the ability to map spatial differences in buffer capacity within a sample during the acid–base titration was unprecedentedly proven. The sensor–actuator concept could be used for monitoring certain analytes in samples that specifically require acidification pretreatment. Particularly, in combination with different optodes, dynamic mapping of concentration gradients will be accessible in complex environmental samples ranging from roots and sediments to bacterial aggregates.

Selective and simultaneous high resolution 2-D imaging of AsIII, CrIII and SbIII and dissolved oxygen by developing a new DGT technique comprising a hybrid sensor

A new diffusive gradients in thin films technique (HR-MPTS DGT) with mercapto-functionalized attapulgite in a binding gel was developed for simultaneous two-dimensional (2-D) chemical imaging of As^III, Cr^III and Sb^III selectively at the submillimeter scale, combined with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis. The HR-MPTS DGT exhibited selective accumulation of As^III, Sb^III and Cr^III (> 97%), yet negligible accumulation of As^V, Sb^V and Cr^VI (< 2%). Accumulation of As^III, Cr^III and Sb^III on the binding gel had a linear relationship (R² > 0.99) with the corresponding standardized laser ablation signals, proving the feasibility of LA-ICP-MS analysis. Analysis for As^III, Cr^III and Sb^III was provided with favorable analytical precision (relative standard deviation <10%). With the purpose of evaluating the dynamics of As^III, Cr^III, Sb^III and O₂ in the rooting zone, a hybrid sensor, which comprises the HR-MPTS gel overlying an O₂ planar optode, was deployed in rhizosphere sediments. Results showed that the consumption of both As^III and Sb^III due to the oxidation extended ~4.48 mm into the sediments, which was consistent with the extension length of the oxidized sediment layers around the roots created by O₂ leakage.

Noise versus Resolution in Optical Chemical Imaging-How Reliable Are Our Measurements?

Optical chemical imaging has established itself as a valuable technique for visualizing analyte distributions in 2D, notably in medical, biological, and environmental applications. In particular for image acquisitions on small scales between few millimeter to the micrometer range, as well as in heterogeneous samples with steep analyte gradients, image resolution is essential. When individual pixels are inspected, however, image noise becomes a metric as relevant as image accuracy and precision, and denoising filters are applied to preserve relevant information. While denoising filters smooth the image noise, they can also lead to a loss of spatial resolution and thus to a loss of relevant information about analyte distributions. To investigate the trade-off between image resolution and noise reduction for information preservation, we studied the impact of random camera noise and noise due to incorrect camera settings on oxygen optodes using the ratiometric imaging technique. First, we estimated the noise amplification across the calibration process using a Monte Carlo simulation for nonlinear fit models. We demonstrated how initially marginal random camera noise results in a significant standard deviation (SD) for oxygen concentration of up to 2.73% air under anoxic conditions, although the measurement was conducted under ideal conditions and over 270 thousand sample pixels were considered during calibration. Second, we studied the effect of the Gaussian denoising filter on a steep oxygen gradient and investigated the impact when the smoothing filter is applied during data processing. Finally, we demonstrated the effectiveness of a Savitzky-Golay filter compared to the well-established Gaussian filter.

Recent improvements to the selectivity of extraction-based optical ion sensors

Optical sensors continue to demonstrate tremendous potential across a wide range of applications due to their high versatility and low cost. This feature article will focus on a number of recent advances made in improving the performance of extraction-based optical ion sensors within our group. This includes the progress of anchored solvatochromic transduction to provide pH and sample volume independent optical responses in nanoemulsion-based sensors. A recent breakthough is in polyion sensing in biological fluids that uses a novel indirect transduction mechanism that significantly improves the selectivity of dinonylnaphthalenesulfonate-based protamine sensors and its potential applications beyond polyion sensing. The role of particle stabilizers in relation to the response of emulsified sensors is shown to be important. Current challenges in the field and possible opportunities are also discussed.

Selectivity remains a constant challenge in the development of optical extraction-based sensors. Fortunately, there are several mechanistic and compositional changes with the potential to improve selectivity without developing new ionophores.

Trihexyltetradecylphosphonium chloride based ratiometric fluorescent nanosensors for multiplex anion discrimination

A multiplex anion-responsive platform was developed with [THTP][Cl] and ETH5350, providing colorimetric and spectroscopic transformations. By choosing suitable ionophores, a pool of nanosensors for extended anions could be achieved.

Reagentless Acid-Base Titration for Alkalinity Detection in Seawater

Herein, we report on a reagentless electroanalytical methodology for automatized acid–base titrations of water samples that are confined into very thin spatial domains. The concept is based on the recent discovery from our group (WiorekA.Anal. Chem.2019, 91, 14951−1495931691565), in which polyaniline (PANI) films were found to be an excellent material to release a massive charge of protons in a short time, achieving hence the efficient (and controlled) acidification of a sample. We now demonstrate and validate the analytical usefulness of this approach with samples collected from the Baltic Sea: the titration protocol indeed acts as an alkalinity sensor via the calculation of the proton charge needed to reach pH 4.0 in the sample, as per the formal definition of the alkalinity parameter. In essence, the alkalinity sensor is based on the linear relationship found between the released charge from the PANI film and the bicarbonate concentration in the sample (i.e., the way to express alkalinity measurements). The observed alkalinity in the samples presented a good agreement with the values obtained by manual (classical) acid–base titrations (discrepancies <10%). Some crucial advantages of the new methodology are that titrations are completed in less than 1 min (end point), the PANI film can be reused at least 74 times over a 2 week period (<5% of decrease in the released charge), and the utility of the PANI film to even more decrease the final pH of the sample (pH ∼2) toward applications different from alkalinity detection. Furthermore, the acidification can be accomplished in a discrete or continuous mode depending on the application demands. The new methodology is expected to impact the future digitalization of in situ acid–base titrations to obtain high-resolution data on alkalinity in water resources.