Low-Cost Portable Colorimeter for Determination of Oxidizable Organic Compounds Using Dichromate Oxidation: Application to Ethanol Analysis

Abstract

Low-cost and portable analytical devices are increasingly relevant for decentralized measurements, in situ monitoring, and educational applications. This study presents the design, construction, and validation of a low-cost, portable colorimeter for the indirect determination of ethanol in aqueous solutions via dichromate oxidation. Built with accessible components, including an Arduino microcontroller, an RGB LED, and a light-dependent resistor (LDR) photodetector, the device provides a simple open-hardware platform for visible-range colorimetric measurements without the need for optical filters. Ethanol concentration is determined through oxidation in an acidic medium, generating an optical response proportional to the analyte concentration. Data processing is performed using open-source Python scripts combined with Gaussian fitting for signal extraction and calibration. The main novelty of the system lies in integrating simplified optical components, open-hardware architecture, and computational signal processing to obtain reliable analytical responses in a portable, accessible format. The device’s performance was compared with a commercial UV–Vis spectrophotometer, showing linear behavior over 0.5–1.5% (v/v) ethanol (R² = 0.99) and relative errors below 11% for beverage samples. These results demonstrate that the proposed system is a reliable and cost-effective alternative for rapid ethanol analysis in relatively simple alcoholic matrices.

1. Introduction

The determination of oxidizable organic compounds in aqueous solutions is important in several industrial, environmental, and educational contexts, including process monitoring, wastewater analysis, alcoholic beverage production, and biofuel manufacturing. Many organic substances in aqueous systems can undergo oxidation reactions that produce measurable colorimetric responses, enabling indirect analytical determination via chemical redox reactions. Among these compounds, ethanol is one of the most widely studied due to its relevance in beverages, fuels, pharmaceuticals, and chemical processes. Accurate quantification of ethanol is essential for quality assurance, regulatory compliance, and process optimization. Conventional analytical techniques employed for ethanol determination include gas chromatography, high-performance liquid chromatography, densimetry, refractometry, and spectroscopic methods, which offer high accuracy and precision [1,2,3]. However, these techniques often require expensive instrumentation, laboratory infrastructure, and trained personnel, making them less suitable for decentralized or in situ measurements.

In recent years, there has been a growing demand for cost-effective, portable, and easy-to-use analytical devices capable of providing rapid quantitative information outside traditional laboratory environments [4,5,6,7]. Such devices are particularly relevant for field-based analyses, small-scale industrial operations, and educational laboratories, where access to advanced analytical instrumentation may be limited. In this context, colorimetric methods have attracted considerable attention due to their simplicity, low reagent consumption, and straightforward signal interpretation [8,9].

Advances in embedded electronics, microcontrollers, and solid-state light sources have enabled the development of compact and affordable optical devices for chemical analysis [10,11]. In a broader sense, the field of optical sensing has evolved towards highly sophisticated systems, such as the use of lanthanide nanoprobes for temperature sensing [12] and photonic crystal fiber sensors based on surface plasmon resonance (SPR) [13]. While these advanced technologies offer remarkable sensitivity, there is a complementary and growing need for accessible solutions. The combination of low-cost microcontrollers, light-emitting diodes (LEDs), and simple photodetectors has facilitated the construction of portable colorimeters with sufficient analytical performance for a variety of applications. These systems often rely on intensity-based measurements rather than high spectral resolution, making them particularly attractive for hardware-oriented designs focused on accessibility and reproducibility [14].

Several studies have demonstrated the feasibility of using portable colorimetric devices for the determination of inorganic ions, organic compounds, and biochemical species, showing good agreement with conventional laboratory techniques [15,16]. When coupled with appropriate data-processing strategies, such as signal averaging and mathematical fitting, low-cost optical systems can achieve greater robustness and quantitative reliability, even with simple photodetectors.

Among these approaches, oxidation reactions involving dichromate ions have been widely used in analytical chemistry for the detection of easily oxidizable organic substances. In strongly acidic media, dichromate (Cr₂O₇²⁻) can oxidize several organic compounds, producing Cr³⁺ species that generate a characteristic color change in the visible region. The intensity of this colorimetric response can be correlated with the amount of oxidized material present in the solution. Although the reaction is not selective for a single compound and may respond to different oxidizable species, it has been historically employed in analytical procedures for rapid screening of organic content in relatively simple matrices. In the specific case of ethanol-containing systems, this reaction has been widely explored for indirect ethanol determination through spectrophotometric measurements [17].

Within this framework, the present work reports the design, construction, and validation of a low-cost, portable colorimeter for the determination of oxidizable organic compounds in aqueous solutions via dichromate oxidation, with ethanol as a model analyte. The device integrates open, accessible hardware components with open-source software for data acquisition and processing, emphasizing reproducibility, portability, and low fabrication costs. By combining a simple optical design with computational data analysis, this study aims to contribute to the development of accessible analytical hardware suitable for educational use, in situ monitoring, and rapid process screening.

The scientific novelty of this work lies not only in the construction of a cost-effective portable colorimeter but also in the integration of RGB LED-based spectral emulation, open-hardware architecture, and open-source computational signal processing using Gaussian fitting to obtain reliable analytical responses from simplified optical components. This combination enables indirect ethanol determination using a reproducible, portable, and accessible platform that extends previous low-cost colorimetric approaches toward a fully documented, replicable analytical hardware system.

2. Design

2.1. Design Rationale and Principle of Operation

The proposed colorimeter was designed as a low-cost, portable, and reproducible analytical device aimed at the indirect determination of ethanol concentration in aqueous solutions. Ethanol is widely used in beverages, disinfectants, fuels, solvents, and pharmaceutical products, creating a demand for rapid, accessible analytical methods [18,19]. However, ethanol lacks intrinsic UV–Vis absorbance bands, making its direct spectrophotometric determination impractical [20]. In this study, ethanol was selected as a model analyte to evaluate the proposed system, although the underlying dichromate oxidation reaction may also occur with other readily oxidizable organic compounds.

The initial tests for ethanol concentration determination were carried out using an indirect colorimetric method based on the oxidation of ethanol in a strongly acidic medium provided by concentrated sulfuric acid (~98%, analytical grade) in the presence of potassium dichromate, as previously described in the literature and adopted in the present study [20,21,22]. The methodology relies on the oxidation of ethanol to acetic acid under strongly acidic conditions, concomitantly with the reduction in dichromate ions (Cr₂O₇²⁻) to trivalent chromium (Cr³⁺). The overall reaction is represented as follows:

$$3\hspace{0.17em}\mathrm{C}{\mathrm{H}}_3\mathrm{C}{\mathrm{H}}_2\mathrm{O}\mathrm{H}+2\hspace{0.17em}\mathrm{C}{\mathrm{r}}_2{\mathrm{O}}_7^{2-}+16\hspace{0.17em}{\mathrm{H}}^{+} \to 3\hspace{0.17em}\mathrm{C}{\mathrm{H}}_3\mathrm{C}\mathrm{O}\mathrm{O}\mathrm{H}+4\hspace{0.17em}\mathrm{C}{\mathrm{r}}^{3+}+11\hspace{0.17em}{\mathrm{H}}_2\mathrm{O}$$

(1)

After the reduction process, Cr³⁺ species are formed in solution. At pH values above approximately 5.5–6.0, trivalent chromium may form insoluble hydroxides or oxides, which can affect the solution’s optical properties. Therefore, the reaction must be maintained under strongly acidic conditions to prevent precipitation and ensure stable colorimetric measurements.

The reduction in dichromate ions results in a pronounced color change of the solution, which evolves from yellow-orange to green, with a characteristic absorption maximum around 595 nm associated with Cr³⁺ species. Within the linear range of the method, the intensity of the formed color is proportional to the ethanol concentration present in the sample, enabling its quantification by spectrophotometric or colorimetric techniques. Although the analytical signal is not specific to ethanol and may be influenced by other oxidizable compounds, this reaction provides a robust and widely used basis for indirect ethanol determination in relatively simple matrices.

To address this limitation, the device employs an indirect colorimetric strategy that relies on the oxidation of ethanol by dichromate ions in an acidic medium, producing Cr³⁺ species and a characteristic color change with a maximum absorbance at 595 nm [20,23]. The intensity of the optical response is proportional to the amount of oxidized ethanol, enabling quantitative analysis. Although the method is not selective and may be affected by other oxidizable compounds, it has been successfully applied to ethanol determination in relatively simple matrices and process-monitoring applications [20,24].

Instead of relying on a conventional UV–Vis spectrophotometer, the proposed system emulates visible-range spectral scanning using low-cost electronic components. The principle of operation is based on modulating an RGB LED to generate discrete wavelengths between 400 and 700 nm, combined with intensity-based detection using a simple photodetector. This approach allows the device to reproduce spectrophotometer-like spectral scanning behavior while maintaining low cost, simplicity, and ease of replication [21,25].

2.2. Electronic Design

Figure 1 presents two complementary representations of the proposed circuit. Figure 1A provides a simplified and illustrative diagram intended to facilitate understanding for readers with limited experience in electronics. In this representation, a single push button (P1) was included, which is sufficient for the basic operation of the device. Figure 1B presents the complete electrical schematic of the circuit, including an additional optional push button (P2), which can be used to implement auxiliary control functions if desired. This distinction reflects the flexibility of the proposed design while maintaining clarity in both representations. The schematic provides a simplified representation of the circuit architecture, highlighting the functional relationships between the microcontroller, the RGB LED light source, and the LDR photodetector. The RGB LED (common cathode configuration) is driven by PWM signals generated by the microcontroller, allowing controlled modulation of light intensity for each color channel. The transmitted light is detected by the LDR sensor, and the resulting signal is acquired through an analog input.

Figure 1. Circuit representation of the proposed portable colorimeter. (A) Illustrative diagram of the system showing the main components and their interconnections, including the Arduino Nano, RGB LED (common cathode), LDR sensor, resistors, and push button. (B) Electrical schematic of the circuit, providing a formal representation of the component connections and signal flow. In (B), filled circles indicate electrical connections (merged wires), while crossing lines without filled circles represent non-connected wires.

Detailed information regarding component specifications, including part numbers and manufacturers, is provided in Table 1 to ensure reproducibility of the system. All files required for the reproduction of the circuit, including the Arduino firmware, circuit design, and fabrication files, are provided in the Supplementary Materials. These materials enable readers to examine the circuit in detail, access the embedded code, and support printed circuit board (PCB) prototyping.

Table 1. Bill of materials (BoM) for the construction of the low-cost portable colorimeter, including component type, quantity, and estimated cost.

Quantity	Component	Manufacturer	Part Number/Model	Material Type	Cost Per Unit *	Total Cost *
1	Arduino Nano Rev 3.0 (ATmega328P)	Arduino (Turin, Italy)/Compatible	A000005 (or compatible Nano V3.0)	Microcontroller board	US$ 20.00	US$ 20.00
1	RGB LED (common cathode, 5 mm)	Kingbright (Issum, Germany) (or equivalent)	L-154A4SURKQBDZGW	Electronic component	US$ 0.20	US$ 0.20
3	10 kΩ resistor	Yageo (Taipei City, Taiwan) (or equivalent)	CFR-25JB-52-10K	Electronic component	US$ 0.03	US$ 0.09
3	330 Ω resistor	Yageo (or equivalent)	CFR-25JB-52-330R	Electronic component	US$ 0.03	US$ 0.09
1	Photoresistor (LDR sensor)	Advanced Photonix (Camarillo, CA, USA)/Generic	GL5528	Electronic component	US$ 0.39	US$ 0.39
1	Push button (tactile switch)	Omron (Langenfeld Germany) (or equivalent)	B3F-1050	Electronic component	US$ 0.84	US$ 0.84
20	Jumper wires	Generic	Male–male jumper wires	Electronic component	US$ 0.10	US$ 2.00
1	Phenolic PCB board	Generic	FR-2 phenolic board	PCB substrate	US$ 1.00	US$ 1.00
1	3D-printed case (main body)	Generic/Local service	STL file (provided)	Polymer/resin prototype	US$ 0.50	US$ 0.50
1	3D-printed case (top cover)	Generic/Local service	STL file (provided)	Polymer/resin prototype	US$ 1.00	US$ 1.00

* Cost Approximate, which varies depending on time and location.

This electronic configuration enables intensity-based colorimetric measurements rather than high-resolution spectral analysis. Although true monochromatic radiation is not generated, the approach is sufficient for quantitative applications based on relative absorbance changes, particularly when combined with appropriate data-processing strategies [25,26]. Similar architectures have been successfully employed in portable analytical devices for chemical and biochemical sensing [10,27].

2.3. Printed Circuit Board (PCB) Design

To improve mechanical stability, electrical reliability, and reproducibility, a dedicated printed circuit board (PCB) was developed. Two alternative PCB layouts were designed to accommodate different fabrication strategies while maintaining identical electrical functionality. The first layout, shown in Figure 2A, was developed using Autodesk Eagle software and implemented as a single-layer PCB compatible with standard low-cost fabrication services. In Figure 2A, a schematic representation of the PCB is presented together with the connections to the Arduino microcontroller and the main circuit components. This representation is intended to facilitate understanding of system integration, as the Arduino is not physically mounted on the PCB but connected externally via jumper wires.

Figure 2. Printed circuit board (PCB) designs of the portable colorimeter. (A) PCB layout and schematic representation showing the connections between the board, the Arduino microcontroller, and the main components via jumper wires; this version is compatible with standard low-cost PCB fabrication. (B) Alternative PCB layout optimized for ultra-low-cost fabrication, featuring wider traces and increased spacing to facilitate manual production techniques.

The complete PCB schematic and fabrication files are provided in the Supplementary Materials, allowing users to reproduce the circuit and assemble the system with the appropriate connections. This version follows conventional electronic design rules and is suitable for commercial PCB manufacturing.

In parallel, an alternative PCB layout was created using general-purpose graphic design software, as shown in Figure 2B. This layout was specifically optimized for ultra-low-cost fabrication techniques, such as manual toner transfer or direct printing, by employing wider conductive traces and increased track spacing. The use of thicker and more widely spaced traces reduces the risk of fabrication defects and improves robustness when non-industrial PCB production methods are employed.

The PCB was manufactured from a one-sided copper-clad board using a direct heat-transfer method, followed by chemical etching with ferric chloride to remove unprotected copper areas. All resistors and pin headers were soldered directly to the PCB, while jumper wires connected external components such as the RGB LED and LDR sensor. The final PCB dimensions are 24.76 mm × 70.6 mm, allowing compact integration inside the device enclosure. The PCB design files are provided as supplementary material to ensure full reproducibility.

2.4. Mechanical Design and Enclosure

The mechanical enclosure of the colorimeter was designed to house the electronic components, define the optical path, and minimize the influence of ambient light. The enclosure design is shown in Figure 3. It consists of two main parts: a main body and a removable top cover.

Figure 3. Mechanical design of the colorimeter enclosure showing the main body, showing internal compartments for the Arduino Nano, PCB, and optical cuvette, and the removable top cover. The aligned apertures define the fixed optical path between the RGB LED and the LDR sensor.

Internal slots were incorporated to securely accommodate the Arduino Nano and the PCB on opposite sides of the enclosure. A central compartment was designed to hold a standard optical cuvette, positioned between aligned apertures for the RGB LED and the LDR sensor. This alignment defines a fixed optical path and ensures that the emitted light passes through the sample before reaching the detector.

The enclosure was fabricated by fused deposition modeling (FDM) 3D printing using opaque polyethylene terephthalate glycol (PETG) filament. The use of opaque material minimizes internal reflections and stray light, improving measurement reproducibility. The enclosure dimensions were designed to accommodate conventional cuvettes used in commercial spectrophotometers, facilitating comparison with reference instruments.

2.5. Software Design

The system’s software architecture comprises firmware running on the microcontroller and data-processing software running on an external computer. The Arduino firmware controls RGB LED modulation, synchronizes signal acquisition from the LDR sensor, and transmits raw intensity data via serial communication.

The raw optical data are processed using open-source Python (version 3.12.2) scripts that perform signal averaging, Gaussian fitting of absorbance profiles, and the construction of calibration curves. Mathematical treatment of the data is essential to compensate for noise and variability inherent to low-cost optical components, significantly improving the quantitative performance of the device [25,26]. This integration of simple hardware with computational data processing reflects a broader trend in analytical instrumentation toward software-assisted enhancement of cost-effective sensing platforms [10,27].

2.6. Bill of Materials

A detailed bill of materials (BoM), including component specifications, quantities, and estimated costs, is presented in Table 1. All components were selected based on availability, low cost, and ease of replacement, resulting in a total hardware cost compatible with educational, laboratory, and field applications.

3. Build Instructions

This section describes the step-by-step procedure for assembling the low-cost portable colorimeter. All files required for device construction, including electronic schematics, PCB layout files, firmware source code, and 3D-printable enclosure models, are provided as Supplementary Materials to ensure full reproducibility. The Arduino firmware, Python scripts for data acquisition and processing, and all technical files required for device replication are hosted in Supplementary Materials. This ensures transparency and reproducibility, facilitating future adaptations or improvements by the research and educational communities.

3.1. Assembly of the Electronic Circuit

The electronic circuit should be assembled following the schematic shown in Figure 1. Initially, the components are mounted on the printed circuit board (PCB) to ensure mechanical stability and reliable electrical connections. The Arduino Nano microcontroller is mounted using male pin headers, allowing easy replacement or reprogramming if necessary.

The resistors and pin headers are soldered directly onto the PCB according to the layout presented in Figure 2. After soldering, jumper wires are used to connect the RGB LED and the LDR sensor to the corresponding terminals on the PCB. The RGB LED (common cathode) must be connected to Arduino Nano’s PWM digital pins via 330 Ω resistors. In contrast, the LDR sensor is connected to the analog input (A0) using a voltage divider with a 10 kΩ resistor.

Two push buttons are connected to the microcontroller’s digital input pins and configured with pull-up resistors. These buttons initiate spectral scanning and data acquisition during device operation. After completing the soldering process, all electrical connections should be visually inspected and, if possible, verified using a multimeter to avoid short circuits or loose contacts.

3.2. Fabrication and Preparation of the Enclosure

The mechanical enclosure of the colorimeter is fabricated using fused deposition modeling (FDM) 3D printing. The enclosure design consists of two parts: a main body and a removable top cover, as shown in Figure 3. The device’s STL files, available on Supplementary Materials, allow straightforward replication with standard desktop 3D printers.

Opaque polyethylene terephthalate glycol (PETG) filament is recommended to minimize internal light reflections and reduce interference from ambient light. Printing parameters such as layer height, infill percentage, and printing speed can be adjusted according to the printer specifications; however, a moderate infill (≥20%) is recommended to ensure mechanical rigidity.

After printing, the enclosure parts should be cleaned to remove any residual filament or support material. The main body’s internal compartments are designed to accommodate the Arduino Nano and the PCB on opposite sides, with a central slot reserved for the optical cuvette.

3.3. Integration of Electronics and Optical Components

Once the PCB and enclosure are prepared, the electronic components are integrated into the case. The Arduino Nano and the PCB are inserted into their respective slots inside the main body of the enclosure, as illustrated in Figure 4A. The RGB LED and LDR sensor are positioned in aligned apertures on opposite sides of the cuvette compartment, defining the device’s optical path.

Figure 4. Assembly of the portable colorimeter. (A) Integration of the PCB, Arduino Nano, RGB LED, and LDR sensor inside the enclosure. (B) Fully assembled device with the top cover in place.

Care must be taken to ensure proper alignment between the LED, the cuvette, and the photodetector to guarantee consistent light transmission through the sample. The optical cuvette should fit securely in the central compartment without lateral movement. After confirming correct alignment and positioning, the top cover is placed and fixed onto the main body, completing the mechanical assembly of the colorimeter (Figure 4B).

The RGB LED source and the LDR photodetector are positioned in dedicated cavities within the device’s 3D-printed enclosure. These cavities were designed to ensure fixed positioning of the optical components and to maintain a consistent optical path between the light source, the sample holder, and the detector. This mechanical design reduces alignment variability during device assembly. However, preliminary tests using multiple hardware replicas showed small variations in measurements from identical samples, attributed to minor differences in component positioning during manual assembly and to small tolerances in the 3D printing process. Two aspects of the measurement protocol mitigate these effects. First, the device performs multiple spectral scans for each sample, and the analytical signal is obtained from an averaged response, reducing fluctuations associated with hardware variability. Second, each experiment includes a blank reference measurement, allowing all sample signals to be normalized relative to the specific device’s reference. This procedure improves measurement consistency across different hardware replicas.

3.4. Firmware Upload and System Check

Once the hardware is assembled, the firmware is uploaded to the Arduino Nano. This process is performed via a USB connection to a computer, using the source code available in the Supplementary Materials.

Once the firmware upload is complete, a preliminary system check should be performed. The device is powered via USB, and the RGB LED emission should be verified to ensure all color channels are functioning correctly. The LDR sensor’s response can be confirmed by observing changes in the transmitted signal when a cuvette is inserted or removed from the optical path.

If the device responds as expected, the colorimeter is ready for operation and data acquisition following the procedures described in the next section.

4. Operation Instructions

The operation of the portable colorimeter involves three integrated stages: preparation of ethanol standards and samples, acquisition of optical data using the embedded firmware, and computational processing of the acquired data to construct calibration curves and estimate ethanol concentration. The complete operational workflow adopted in this study is summarized in Figure 5.

Figure 5. Operating workflow for ethanol determination using the portable colorimeter. Ethanol standards, samples, and the reference solution (blank, 0% ethanol) are prepared using the same colorimetric protocol. Optical data are acquired using the Arduino firmware (espec.ino), which prints wavelength–signal pairs to the Serial Monitor. The data are saved as structured text files and processed using Python scripts (etoh_concentrations.py for calibration and etoh_sample.py for sample analysis) to construct calibration curves and estimate ethanol concentration.

Ethanol determination is based on an indirect colorimetric reaction in which ethanol is oxidized by dichromate ions in an acidic medium, producing Cr³⁺ species and a characteristic color change in the visible region. All solutions, including calibration standards, unknown samples, and the reference (blank), are prepared following the same chemical protocol to ensure consistency. The reference solution corresponds to a blank sample containing all reagents except ethanol, i.e., a solution with 0% (v/v) ethanol, and is used to account for background absorption and instrumental contributions.

All measurements were performed using standard plastic cuvettes with a 1 cm optical path length, which are commonly employed in visible-range spectrophotometric analyses. Plastic cuvettes were selected because the measurements were conducted in the visible spectral region and because they offer a low-cost, practical option compatible with the proposed portable device.

The assembled colorimeter is connected to a computer via a USB interface that provides both power and serial communication. The embedded firmware, implemented in the Arduino environment (espec.ino), controls the sequential modulation of the RGB LED to emulate discrete wavelengths across the visible spectrum and synchronizes signal acquisition from the light-dependent resistor (LDR). During each scan, the firmware prints wavelength–signal pairs to the Arduino IDE Serial Monitor, where the signal corresponds to the light intensity transmitted through the sample.

For each solution (reference, calibration standards, and unknown sample), multiple consecutive scans are performed to improve signal stability through averaging. The output displayed in the Serial Monitor is copied and saved as plain-text files, preserving the wavelength–signal structure. Separate files are created for each measurement and subsequently used as input for computational processing.

The calibration procedure is performed using the Python script etoh_concentrations.py. This script requires a set of input text files generated during data acquisition. The reference measurement must be saved in a file named ref.txt, corresponding to the blank solution (0% ethanol), and containing wavelength–signal pairs for the reference measurement. Each calibration standard is saved in an individual text file (e.g., c1.txt, c2.txt, …), with the same internal structure as the reference file. Additionally, a file named concentrations.txt is required; it contains one ethanol concentration value per line, in the same order as the corresponding calibration files. In all data files, each line consists of two comma-separated numerical values: the first represents the wavelength (in nm) and the second represents the measured signal intensity.

Using these input files, the calibration script averages the signals from repeated scans, computes an absorbance-like response by subtracting the sample signal from the blank (reference) signal, and fits the resulting spectral profiles with a Gaussian. The maximum absorbance extracted from the fitted curves is used as the analytical signal to construct a linear calibration model relating absorbance to ethanol concentration. The script generates graphical outputs illustrating the fitted absorbance spectra and the calibration curve, and it writes auxiliary text files containing the calibration coefficients and the wavelength interval used for peak evaluation. These files are automatically saved and later reused during sample analysis.

A blank reference measurement must be performed before each calibration experiment, i.e., before the acquisition of calibration curves and subsequent sample measurements. This procedure is recommended because the proposed device is assembled from low-cost optical and electronic components, and repeated handling may introduce small variations in the positioning of the RGB LED and LDR sensor. Performing a blank measurement before each experimental set normalizes the analytical signal to the device’s specific baseline conditions, improving measurement reproducibility.

Estimation of ethanol concentration in an unknown sample is carried out using the script etoh_sample.py. This script reads the reference data (ref.txt, blank at 0% ethanol), the sample measurement file (sample.txt), and the previously generated calibration parameters. As with the calibration files, the sample file contains wavelength–signal pairs organized as comma-separated values, with one measurement per line. The script computes the sample absorbance spectrum, restricts the analysis to the wavelength interval defined during calibration, and applies Gaussian fitting to extract the peak absorbance. The ethanol concentration is then calculated using the stored calibration coefficients. The output of this procedure includes a graphical representation of the fitted absorbance spectrum and the estimated ethanol concentration.

Throughout the operation, it is essential to maintain consistent reaction times, reagent volumes, and measurement conditions, as the method relies on an indirect chemical reaction and is sensitive to deviations in experimental protocol. When these conditions are controlled, the described operating procedure enables reproducible acquisition and processing of optical data using the portable colorimeter, allowing indirect determination of ethanol concentration in aqueous solutions.

5. Validation

The validation of the proposed portable colorimeter was conducted by evaluating the method’s chemical principle using a commercial UV–Vis spectrophotometer, followed by a detailed assessment of the portable device’s analytical performance, including calibration behavior, signal processing, analysis of real samples, and discussion of methodological limitations.

5.1. Validation of the Colorimetric Method Using UV–Vis Spectrophotometry

The dichromate-based colorimetric method was first evaluated using a commercial UV–Vis spectrophotometer (UV-M51, Bel Engineering, single-beam, 190–1000 nm wavelength range, 2 nm spectral bandwidth, silicon photodiode detector, equipped with a 10 mm cuvette holder) to validate the chemical reaction underlying ethanol determination. As shown in Figure 6A, the absorption spectra obtained for ethanol standard solutions in the concentration range of 0.5–1.5% (v/v), recorded between 500 and 700 nm, exhibited a well-defined absorption band centered at approximately 595 nm. This band is associated with the formation of Cr³⁺ species resulting from the reduction in dichromate ions during ethanol oxidation [28,29]. Figure 6B shows the calibration curve constructed from the maximum absorbance values, which reveals a linear relationship between absorbance and ethanol concentration over the investigated range. In parallel, Figure 6C shows the progressive visual color change in the reaction medium as a function of ethanol concentration, confirming the system’s pronounced colorimetric response.

Figure 6. Validation of the dichromate-based colorimetric method using a commercial UV–Vis spectrophotometer. (A) Absorption spectra of ethanol standard solutions in the concentration range of 0.5–1.5% (v/v). (B) Calibration curve obtained by plotting maximum absorbance versus ethanol concentration. (C) Visual color change in the dichromate reagent as a function of ethanol concentration.

The relationship between maximum absorbance and ethanol concentration showed linear behavior within the investigated range, as indicated by the calibration equation: Abs = 0.08345 + 0.37436 C_EtOH, with Adj. R² = 0.9887. Ethanol concentrations above 1.5% (v/v) resulted in absorbance values exceeding 1.0, indicating signal saturation and deviation from linearity. This behavior is consistent with the Beer–Lambert law and justifies the selected working range. The analytical sensitivity of the reference UV–Vis method was assessed by determining the limits of detection (LOD) and quantification (LOQ), calculated according to IUPAC recommendations [30]. The LOD and LOQ values obtained were 0.27% and 0.82% (v/v), respectively. Considering the density of ethanol (0.789 g mL⁻¹) and its molar mass (46.07 g mol⁻¹), these values correspond to approximately 2.13 g L⁻¹ (46.2 mmol L⁻¹) and 6.47 g L⁻¹ (140.4 mmol L⁻¹), respectively. These results indicate that the dichromate-based colorimetric approach provides sufficient sensitivity for applications such as quality control, fermentation monitoring, and educational experiments. Comparable detection limits have been reported for similar ethanol determination methods based on oxidation reactions [28,31].

5.2. Performance of the Portable Colorimeter and Signal Processing

Following validation of the chemical method using the reference spectrophotometer, the same experiments were conducted with the portable colorimeter developed in this work.

The raw optical data acquired using the portable colorimeter are presented in Figure 7A. As expected for a system based on low-cost electronic and optical components, the raw spectra exhibit noticeable instrumental noise, particularly at low ethanol concentrations where absorbance differences are small. To mitigate these effects, the measurement protocol and data-processing workflow incorporate two main strategies. First, the device performs multiple spectral scans for each sample, which helps reduce random fluctuations in the raw data. Second, the RGB LED modulation used to emulate the visible spectrum produces smooth intensity variations across the scanning sequence. As described by Magro et al. [25], this variation can be approximated by Gaussian-shaped intensity profiles in the wavelength domain. Consequently, the signals recorded by the LDR sensor also follow Gaussian-like behavior. Based on this property, the Python-based processing scripts perform Gaussian fitting of the measured intensity values as a function of wavelength, as shown in Figure 7B. This processing step enabled reliable identification of the region of maximum absorbance, and the fitting procedure allows extraction of the absorbance peak from a smoothed curve, thereby reducing the influence of noise in the raw measurements.

Figure 7. Performance of the portable colorimeter. (A) Raw absorbance-like spectra obtained using the portable device. (B) Processed spectra after Gaussian fitting, highlighting noise reduction and peak definition. (C) Calibration curve constructed from the portable colorimeter data, showing linear behavior in the investigated concentration range.

The processed absorbance spectra obtained with the portable device showed qualitative agreement with those measured using the commercial UV–Vis spectrophotometer, displaying a consistent increase in absorbance with increasing ethanol concentration. The calibration curve constructed from the portable colorimeter data (Figure 7C) was linear over the investigated concentration range (0.5–1.5% v/v), with a coefficient of determination (R²) of 0.99.

The comparison between the two systems also highlights differences in their optical architectures. Commercial UV–Vis spectrophotometers typically operate over a broad spectral range in the UV–visible region (≈200–800 nm) with high spectral resolution provided by monochromators. In contrast, the portable device developed in this work operates within the visible region using RGB LED spectral emulation (≈400–700 nm) combined with an LDR detector. Despite this simplified configuration, the portable colorimeter can provide reliable quantitative information when combined with appropriate computational methods.

According to Beer–Lambert law, absorbance is proportional to the concentration of the absorbing species when monochromatic radiation is used, and the system operates within the linear response region [32,33,34]. Deviations from linearity may arise at higher concentrations due to chemical, optical, or instrumental effects. In this work, the linear relationship between absorbance and ethanol concentration observed for both the reference spectrophotometer (Figure 6) and the portable colorimeter (Figure 7) indicates that the system operates within the expected linear regime over the selected concentration range.

In this context, the results of the present work are strongly supported by the study reported by Magro et al. [22], which serves as a key reference for this research. In that work, the authors demonstrated that low-cost colorimeter-like systems based on RGB LEDs and microcontrollers can provide reliable quantitative information from visible-range absorbance profiles when appropriate calibration and data treatment strategies are applied. The present study extends those findings by integrating an open-hardware, fully portable device with embedded control and open-source computational processing, demonstrating that comparable analytical performance can be achieved using simplified optical components and mathematical signal extraction. The agreement between the present results and those reported by Magro et al. [22] reinforces the feasibility of translating classical colorimetric methodologies, such as dichromate-based ethanol oxidation, into modern, cost-effective, and reproducible hardware platforms suitable for decentralized and in situ applications.

5.3. Analysis of Real Samples

The applicability of the proposed system was further evaluated by analyzing real samples of commercial distilled alcoholic beverages, namely sugarcane distilled spirit (cachaça) and vodka. These matrices were selected because they are relatively simple compared with more complex beverages that contain higher levels of sugars, pigments, and other oxidizable compounds. The ethanol concentrations determined using the portable colorimeter were compared with those obtained using the commercial UV–Vis spectrophotometer, as summarized in Table 2.

Table 2. Determination of ethanol concentration in commercial alcoholic beverages using the portable colorimeter and comparison with results obtained by a commercial UV–Vis spectrophotometer. * Relative error: (C_LCPC − C_commercial)/C_commercial × 100%.

Sample	Ethanol Concentration (% v/v)		* Relative Error (%)
	Ccolorimeter	Ccommercial
Sugarcane distilled spirit (cachaça)	0.812	0.740	9.76
Vodka	0.668	0.602	10.95

Relative errors of 9.76% for cachaça and 10.95% for vodka were observed. Given the device’s low cost, portability, and simplified construction, these values are acceptable for applications such as rapid screening, educational use, and preliminary quality control. Similar levels of accuracy have been reported for other low-cost, portable colorimetric systems used for ethanol determination [31,35].

5.4. Method Limitations

An important limitation of the proposed approach is that ethanol concentration is not directly measured but inferred from the products of its chemical oxidation. As a result, the analytical signal reflects the extent of dichromate reduction rather than ethanol concentration alone. Therefore, the presence of other oxidizable species in the sample may lead to overestimation of ethanol concentration [28,29]. This characteristic is inherent to the chemical assay itself rather than to the hardware platform.

No dedicated interference study was performed in this work. To reduce this constraint, the method was evaluated only in relatively simple alcoholic beverage matrices, and the results were compared with those obtained using a commercial UV–Vis spectrophotometer. Although similar results were obtained for the tested samples, interference from other oxidizable compounds remains a relevant issue, especially in more complex matrices.

In addition, the low cost and portability of the proposed system come at the cost of analytical trade-offs compared with conventional UV–Vis instrumentation, particularly in terms of selectivity and overall analytical refinement. For this reason, the proposed portable colorimeter is better suited for rapid screening, educational applications, and preliminary analysis in relatively simple or previously characterized samples, rather than as a replacement for high-performance laboratory instrumentation.

It is also important to emphasize that the RGB LED does not generate truly monochromatic radiation across the entire simulated visible spectrum. Instead, intermediate wavelengths correspond to mixtures of the red, green, and blue emission bands. However, in the present study, the maximum absorbance peak of the dichromate reaction product occurred at approximately 665 nm, which falls within the emission region of the red LED channel. Therefore, the influence of polychromatic light mixing on the analytical signal is minimal for this application. Nevertheless, this effect may become relevant when analyzing compounds with broader absorption bands spanning multiple RGB emission regions, and this limitation should be considered when applying the device to other analytical systems.

The LDR sensor used in the proposed hardware has inherent limitations, including nonlinearity, hysteresis, and sensitivity to temperature variations. Although the oxidation reaction between dichromate and ethanol is exothermic, it does not occur in the cuvette during the optical acquisition step. Instead, the reaction is completed before measurement, and the resulting solution is diluted before spectral acquisition. Consequently, the heat generated by the chemical reaction does not directly affect the sensor during scanning. In addition, the device’s spectral acquisition occurs over a relatively short time interval, reducing the influence of ambient temperature fluctuations and LED self-heating. While small thermal effects may contribute to minor baseline variations in the LDR signal, the measurement protocol mitigates them by using a blank reference measurement for each experiment. Because the analytical signal is calculated relative to this reference, device-specific baseline shifts and small thermal drifts are effectively normalized. Nevertheless, the implementation of temperature-compensation circuits or reference-beam correction strategies could further improve measurement robustness and represents a promising direction for future development of the system.

Despite these limitations, the proposed device demonstrates that low-cost electronic components, combined with appropriate signal processing strategies, can yield analytically useful results for selected applications. Future developments may further improve the platform’s robustness and analytical performance by incorporating alternative photodetectors (e.g., photodiodes), temperature-compensation strategies, or dual-beam optical configurations. In addition, evaluating the device with other colorimetric reactions and analytes represents an important direction for expanding the applicability of the proposed system.

6. Conclusions

In this work, a low-cost and portable colorimeter was successfully designed, built, and validated for the indirect determination of ethanol concentration in aqueous solutions. The proposed device integrates simple optical components, a microcontroller-based control system, and open-source data processing to emulate spectrophotometric measurements in the visible range, while maintaining low cost, portability, and ease of replication.

The analytical strategy is based on the oxidation of ethanol by dichromate ions in an acidic medium, producing Cr³⁺ species with a characteristic absorption band around 595 nm. Although ethanol is not directly measured, the results demonstrate that the indirect colorimetric approach provides reliable quantitative information when applied to controlled matrices and within an appropriate concentration range. Validation experiments showed good agreement between the portable colorimeter and a commercial UV–Vis spectrophotometer, with linear calibration behavior (R² ≈ 0.99) and relative errors of approximately 10% for real alcoholic beverage samples. While laboratory spectrophotometers provide broader spectral coverage and higher spectral resolution, the proposed device operates within the visible region using simplified RGB LED spectral emulation, demonstrating that reliable quantitative measurements can still be achieved using cost-effective optical components.

An important contribution of this study lies in combining low-cost hardware with computational signal processing. The use of RGB LED spectral emulation and Gaussian fitting of absorbance-like profiles proved effective in compensating for the limited spectral resolution inherent to simplified optical systems. This approach enables the translation of classical colorimetric methods into modern, compact, and reproducible analytical devices.

Despite its limitations in selectivity and indirect measurement, the proposed colorimeter offers a practical alternative for applications where rapid analysis, low cost, and portability are prioritized. Potential applications include undergraduate chemistry and analytical chemistry laboratories for teaching basic spectrophotometry and colorimetric analysis, as well as secondary school classrooms, where simplified experimental demonstrations of analytical techniques can be performed without complex laboratory infrastructure. The device may also be useful for preliminary quality control of alcoholic beverages or fermentation processes, and for screening measurements of oxidizable organic compounds in relatively simple aqueous systems during field or educational experiments. The method was validated using aqueous ethanol solutions and relatively simple alcoholic beverage matrices; therefore, applications involving complex biological fluids may require additional sample preparation and interference studies. Furthermore, the open-hardware and open-source nature of the device, including the availability of design files, electronic schematics, and data-processing scripts, facilitates adaptation, customization, and future improvements by the scientific and educational communities.

Overall, this work demonstrates that accessible analytical instrumentation can be achieved through the integration of simple hardware and computational methods, contributing to the broader dissemination of low-cost analytical technologies and supporting decentralized chemical analysis.