Set Of Experimental Conditions Research Articles

Automated Optimization of a Multistep, Multiphase Continuous Flow Process for Pharmaceutical Synthesis.

Flow synthesis is becoming increasingly relevant as a sustainable and safe alternative to traditional batch processes, as reaction conditions that are not usually achievable in batch chemistry can be exploited (for example, higher temperatures and pressures). Telescoped continuous reactions have the potential to reduce waste by decreasing the number of separate unit operations (e.g., crystallization, filtration, washing, and drying), increase safety due to limiting operator interaction with potentially harmful materials that can be reacted in subsequent steps, minimize supply chain disruption, and reduce the need to store large inventories of intermediates as they can be synthesized on demand. Optimization of these flow processes leads to further efficiency when exploring new reactions, as with a higher yield comes higher purity, reduced waste, and a greener synthesis. This project explored a two-step process consisting of a three-phase heterogeneously catalyzed hydrogenation followed by a homogeneous amidation reaction. The steps were optimized individually and as a multistep telescoped process for yield using remote automated control via a Bayesian optimization algorithm and HPLC analysis to assess the performance of a reaction for a given set of experimental conditions. 2-MeTHF was selected as a green solvent throughout the process, and the heterogeneous step provided good atom economy due to the use of pure hydrogen gas as a reagent. This research highlights the benefits of using multistage automated optimization in the development of pharmaceutical syntheses. The combination of telescoping and optimization with automation allows for swift investigation of synthetic processes in a minimum number of experiments, leading to a reduction in the number of experiments performed and a large reduction in process mass intensity values.

A Factorial Design Assessment of Marine Exoskeleton-Based Bio-sorption of Relevant Electroplating Metals

A preliminary assessment of the capacity of pulverized crab shells to function as bio-sorbents for the removal of selected metals, zinc, cadmium, and chromium was analyzed according to a factorial experimental design. These metals were chosen because they have little precedent in past sorption studies and represent metals discharged into receiving waters by the electroplating industry. The design was done to assess parameters that have the highest impact on adsorption capacity and removal efficiency. Validation with other heavy metal ion removals was performed for comparison followed by a factorial 33 DOE using JMP®. It was found that for zinc, adsorbent amount, pH, time and the interaction of adsorbent amount*time and pH*adsorbent amount have the highest significance. For cadmium, only adsorbent amount is significant. Finally, chromium uptake was strongly dependent on adsorbent amount and pH. According to ionic radius theory, the favorability for adsorption is according to the following trend: chromium > cadmium > zinc; however, under our set of experimental conditions, the order was: cadmium > zinc > chromium because the presence of calcium carbonate exerts a major role in their sequestration.

Platinum Nanoparticles Supported by Carbon Nanotubes: Improvement in electrochemical sensor performance for caffeine determination.

Platinum nanoparticles supported by carbon nanotubes were obtained by a simple chemical route and used for preparation of electrochemical sensor towards caffeine determination. Carbon nanotubes were used before and after an acid treatment, yielding two different materials. Morphological and structural characterization of these materials showed platinum nanoparticles (size around 12 nm) distributed randomly along carbon nanotubes. Modified electrodes were directly prepared through a dispersion of these materials. Voltammetric studies in the presence of caffeine revealed an electrocatalytic effect of platinum oxides, electrochemically produced from the chemical oxidation of the platinum nanoparticles. This behavior was explored in the development a selective method for caffeine determination based on platinum oxide reduction at a lower potential value (+0.45 V vs. Ag/AgCl). Using the best set of experimental conditions, it was shown a linear relationship for the caffeine concentration ranging from 5.0 to 25 µmol L-1 with a sensitivity of 449 nA L µmol-1. Limits of detection and quantification of 0.54 and 1.80 µmol L-1 were calculated, respectively. Recovery values for real samples of caffeine pharmaceutical formulations between 98.6% and 101.0% (n = 3) were obtained using the proposed procedure. Statistical calculations showed good concordance (95% confidence level) between the added and recovery values.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Experimental Research of Triple Inertial Navigation System Shearer Positioning.

In order to improve the positioning accuracy of shearers, the overground experimental device based on the positioning model of TINS (Triple Inertial Navigation System) was built. The influence of TINS installation parameters on positioning accuracy was discussed through two sets of experiments: the inter-INS (Inertial Navigation System) distances influence experiments and the tri-INS plane spatial position influence experiments. The results show that the positioning accuracy of the shearer is improved to a different extent under the two sets of experimental conditions. When the inter-INS distances are 0.2 m, the positioning accuracy is the highest and the positioning accuracy improvement effect is also the best. When the negative plane α3 is 45°, the positioning accuracy is the highest, and the positioning accuracy improvement effect is also the best. The analysis shows that the main factor affecting the positioning accuracy is the precision of the evaluated values outputs of TINS from EKF (Extended Kalman Filter). Considering the positioning accuracy, equipment installation convenience and so on, the optimum installation parameters are 90° (horizontal installation) α3 for the positive plane and 0.2 m inter-INS distances.

A computer simulation study of extended DLVO interactions between calcite nanoparticles and real rough surfaces

The interaction energy between calcite nanoparticles and real rough surfaces in calcium carbonate supersaturated solutions was numerically calculated according to the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory and the surface element integration method. Three different surfaces, namely polished stainless steel, plasma-treated stainless steel, and fluorine-doped diamond-like carbon film, were prepared by mechanical polishing, plasma sputtering and film deposition, and characterized by atomic force microscopy. These images were then used as inputs in numerical simulations, where particle radius, solution concentration, surface electric potential, and surface tension components were varied. A total of 4052 simulations were performed. It was obtained that smaller particles interact more strongly with the surface and therefore are more attracted or repelled by the surface than larger ones. The effect of surface roughness on the particle interaction, however, depends on the physicochemical properties of the system and, therefore, a given surface may change its fouling behavior when the set of experimental conditions is changed. The effect of particle size on particle-surface interaction was found to be dependent on the relative sizes of the particle and the typical roughness features of the surface. A new local roughness metric – the minimum distance between the south pole of the particle and the rough substrate – can be used to predict the contact energy. These results may be important to engineer better antifouling surfaces for a wide range of applications, such as oil and gas exploitation and water treatment and desalination.

Assessment of the Dimensionless Groups-Based Scale-Up of Gas–Solid Fluidized Beds

The most common scale-up approach for gas–solids fluidized beds is based on matching the governing dimensionless parameters. In the literature, this approach has been validated only by means of measuring global parameters between different sizes of fluidized beds. However, such global measurements are not sufficient to depict all the interplaying hydrodynamic phenomena and hence verify the scale-up relationships. Therefore, to assess this approach, an advanced gas–solids optical probe and pressure transducer measurement techniques have been applied to quantify local hydrodynamic parameters in two different sized fluidized beds. Four different sets of experimental conditions were designed and conducted to examine the assessment of the scaling approach with matched and mismatched dimensionless groups between the two beds. The results indicated that the reported dimensionless groups are not adequate for achieving similarity between the two gas–solids fluidized beds in terms of solids holdup, gas holdup, particle velocity, mass flux, and pressure fluctuation. This finding demonstrates the importance of local measurements of the hydrodynamic parameters of fluidized beds in order to evaluate scale-up relationships. Finally, the results further advance the understanding of the gas–solids fluidized beds and present deeper insight into their solids dynamics.

Reference genes selection for expression studies in Maconellicoccus hirsutus (Green) (Pseudococcidae: Hemiptera) under specific experimental conditions.

Maconellicoccus hirsutus is a destructive pest which causes severe losses of agricultural and horticultural crops. For the management of M. hirsutus, many insecticides have been used and it has been exposed to insufficient dosage or uneven spray coverage which resulted in the development of insecticide resistance. Xenobiotic metabolism can be better understood with the help of gene expression studies by unveiling the underlying molecular mechanisms. The qRT-PCR is the simplest method to analyse gene expression, however, it highly relies on suitable reference genes concerning the different experimental conditions. We evaluated the stability of five reference genes in two sets of experimental conditions viz. developmental stages (nymphs and adults) and agrochemical stress (GA3 and Buprofezin sprayed) against M. hirsutus, using different softwares-NormFinder, geNorm, BestKeeper, and RefFinder. The study revealed that ATP51a and GAPDH can be used as reference genes for gene expression studies when exposed to Gibberellic acid. Additionally, the study revealed that the ideal pair of reference genes for data validation in M. hirsutus treated with Buprofezin was GAPDH and β-tubulin. The ideal reference gene combination for various developmental stages was found to be 28S and Actin. According to the study, GAPDH can be utilized as a reliable reference gene in the agrochemical (GA3 and Buprofezin) exposure set. The genes can be utilized as a suitable reference for qRT-PCR gene expression studies of xenobiotic metabolism to understand the underlying molecular mechanism, which will help further to design suitable management strategies.

Dynamic salinity‐induced phase‐inversion conductivity measurements used to characterize alcohol ethoxylate based surfactant/oil/water systems

AbstractDynamic conductivity measurements proved to be an effective and rapid method to determine the optimal experimental conditions for a salinity‐induced phase‐inversion from surfactant/oil/water (SOW) systems consisting of nonionic surfactants, more specifically alcohol ethoxylates. This emerging methodology can be used as a rapid screening tool to determine the impact of alcohol ethoxylate surfactants in a SOW solution and was demonstrated to be not only repeatable, but highly comparable to the traditional static method, in which the solutions are added to flat bottom tubes and allowed to equilibrate at a given temperature for extended time periods. Given a set of experimental conditions (oil‐type, temperature, etc.), these dynamic salinity‐induced phase‐inversion (Dy‐SPI) conductivity measurements can be used to determine the optimal salinity (S*) for a given surfactant at a set concentration, as well as its characteristic curvature via a series of experiments with varying oil types. Additionally, Dy‐SPI was used to confirm the previously observed inverse relationship between the concentration of an alcohol ethoxylate and S* under a given set of conditions. What makes this method so unique is the amount of time (30 min to 1 h) and the simplicity of the equipment needed for these Dy‐SPI conductivity measurements, allowing for a rapid screening tool for these SOW parameters.

Biochar: An environmentally friendly platform for construction of a SARS-CoV-2 electrochemical immunosensor

Waste management is a key feature to ensure sustainable consumption and production patterns, and to combat the impacts of climate change. In this scenario, the production of biochar from different biomasses results in environmental and economic advantages. In this study, biochar was produced from sugarcane bagasse pyrolysis, to immobilize biomolecules, in order to assemble an electrochemical immunosensor to detect antibodies against SARS-CoV-2. For this, screen-printed carbon electrodes (SPCE) were modified with a dispersion of biochar and used to immobilize the receptor-binding-domain (RBD) against virus S-protein, through EDC/NHS crosslinking reaction. Under the best set of experimental conditions, negative and positive serum samples responses distinguished based on a cutoff value of 82.3 %, at a 95 % confidence level. The immunosensor showed selective behavior to antibodies against yellow fever and its performance was stable up to 7 days of storage. Therefore, biochar yielded from sugarcane bagasse is an ecofriendly material that can be used as a platform to immobilize biomolecules for construction of electrochemical biosensors.

Graphene-Binding Peptide in Fusion with SARS-CoV-2 Antigen for Electrochemical Immunosensor Construction.

The development of immunosensors to detect antibodies or antigens has stood out in the face of traditional methods for diagnosing emerging diseases such as the one caused by the SARS-CoV-2 virus. The present study reports the construction of a simplified electrochemical immunosensor using a graphene-binding peptide applied as a recognition site to detect SARS-CoV-2 antibodies. A screen-printed electrode was used for sensor preparation by adding a solution of peptide and reduced graphene oxide (rGO). The peptide-rGO suspension was characterized by scanning electron microscopy (SEM), Raman spectroscopy, and Fourier transform infrared spectroscopy (FT-IR). The electrochemical characterization (electrochemical impedance spectroscopy—EIS, cyclic voltammetry—CV and differential pulse voltammetry—DPV) was performed on the modified electrode. The immunosensor response is based on the decrease in the faradaic signal of an electrochemical probe resulting from immunocomplex formation. Using the best set of experimental conditions, the analytic curve obtained showed a good linear regression (r2 = 0.913) and a limit of detection (LOD) of 0.77 μg mL−1 for antibody detection. The CV and EIS results proved the efficiency of device assembly. The high selectivity of the platform, which can be attributed to the peptide, was demonstrated by the decrease in the current percentage for samples with antibody against the SARS-CoV-2 S protein and the increase in the other antibodies tested. Additionally, the DPV measurements showed a clearly distinguishable response in assays against human serum samples, with sera with a response above 95% being considered negative, whereas responses below this value were considered positive. The diagnostic platform developed with specific peptides is promising and has the potential for application in the diagnosis of other infections that lead to high antibody titers.

A new improved Liu-type estimator for Poisson regression models

The Poisson Regression Model (PRM) is commonly used in applied sciences such as economics and the social sciences when analyzing the count data. The maximum likelihood method is the well-known estimation technique to estimate the parameters in PRM. However, when the explanatory variables are highly intercorrelated, unstable parameter estimates can be obtained. Therefore, biased estimators are widely used to alleviate the undesirable effects of these problems. In this study, a new improved Liu-type estimator is proposed as an alternative to the other proposed biased estimators. The superiority of the new proposed estimator over the existing biased estimators is given under the asymptotic matrix mean square error criterion. Furthermore, Monte Carlo simulation studies are executed to compare the performances of the proposed biased estimators. Finally, the obtained results are illustrated in real data. Based on the set of experimental conditions which are investigated, the proposed biased estimator outperforms the other biased estimators.

Locomotor Challenges of Waterfall-Climbing Gobies during Transitions between Media.

An amphidromous goby, Sicyopterus japonicus, migrates from the ocean to upstream regions of many streams and rivers in the Pacific coasts of Japan and Taiwan. Using its mouth and fused pelvic fins (pelvic sucker), this gobiid species exhibits a rock-climbing behavior and surmounts sizable waterfalls, which block the upstream movement of many of its competitors and predators. When gobies emerge from the water to commence their climbing behavior, the change in effective density (i.e., lack of buoyancy) that occurs in this transition substantially increases the force required for adhesion. Consequently, these fish must exert adhesive suction strong enough to support their body weight against gravity during climbing on the rock surface. Suction performance for adhesion and modulatory capacity of S. japonicus were evaluated with two different sets of experimental conditions: climbing on the vertical surface with no water flow versus climbing on a 60°-inclined surface with 2 L/min flow. Individuals of S. japonicus showed 50.7% greater mean safety factor (suction force for adhesion/gravitational force) and 56.6% shorter time to reach maximum pressure differential during climbing on the 60°-inclined surface with water rushing over their bodies than during climbing on the vertical surface with no water flow. These results indicate that when climbing with drag force from flowing water, greater functional demands are imposed and therefore, S. japonicus is required to increase neuromuscular stimulation of the pelvic muscles to elevate suction performance. In addition, S. japonicus individuals at different ontogenetic stages modulate their climbing behaviors and strategies to accommodate changing functional demands as they make transitions between different inclines, as well as media, while ascending waterfalls.

The impact of placement, experimental conditions, and injections on mass flow measurements in supercritical fluid chromatography

In supercritical fluid chromatography (SFC), the variation of pressure, temperature and volumetric flow-rate is most noticeable when the mobile phase contains only neat carbon dioxide. This can be explained by the compressibility of CO2 and introduces several difficulties to the work of chromatographers. The only flow parameter that is considered to be constant across the SFC system is the mass flow-rate. It has been shown that the Coriolis flow meter (CFM) provides different types of information depending on its placement in the instrument. Therefore, the goal of this paper is to investigate several factors affecting the variation of mass flow-rate in SFC, including four different configurations around the column, four sets of experimental conditions along with two columns and a zero-volume union. The effect of disturbances introduced by injections are studied as well. The results show different mass flow-rates when taken at the inlet or the outlet of the column. In addition, different columns produced different tendencies of variations. Study of the injections showed that the initial severe drop of mass flow is reduced when the averages are taken until the elution times of the chosen compounds. Additional testing related to possible leaks and CFM calibration showed that even if all standard operating procedures are strictly followed, reproducibility of the mass-flow rate can still be an issue.

Delamination ASSESSMENT during MACHINING OF laminated POLYMER nanocomposite

Nanomaterials are gaining extensive application in the manufacturing sector due to favorable properties. Its rapid growth in highly sensitive, robust, and lightweight sensors and biomedical components has attracted considerable attention worldwide. Nanomaterial uses with fiber-reinforced polymeric material have increased significantly. In order to manufacture structural components in a near-net shape, laminated nanocomposite machining is required. Due to the need for product assembly in mechanical structures, Milling is the primarily machining process in the manufacturing industry to create slots, channels, etc. The present work optimized the process variables affecting the Milling process by adopting the minimize criterion to control the delamination factor using the Taguchi method. The process parameters include cutting speed, feed, depth of cut, and filler material Graphene Oxide. The optimized conditions were found as cutting speed (Vc) 37.12 m/min, spindle feed (F) 80 mm/min, depth of cut (D) 0.5 mm and filler material Graphene Oxide (G) 1 wt.%. The percentage contribution of the process parameter on the delamination factor (Fd) was determined using the Analysis of Variance (ANOVA) method, and it has been found the feed rate (62.60%) is the most influencing factor. The delamination factor obtained in the confirmatory experiments carried out under optimized conditions was found lower than the Taguchi design test runs. The findings indicate that process parameter optimization under the given set of experimental conditions is effective for a manufacturing environment.

Sub-pixel high-resolution imaging of high-energy x-rays inspired by sub-wavelength optical imaging.

We have developed and demonstrated an image super-resolution method-XR-UNLOC: X-Ray UNsupervised particle LOCalization-for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μm of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of "nearly-dark" instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community ("droplet analysis") showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome.

Identification of 20 polymer types by means of laser-induced breakdown spectroscopy (LIBS) and chemometrics

Over the past few years, laser-induced breakdown spectroscopy (LIBS) has earned a lot of attention in the field of online polymer identification. Unlike the well-established near-infrared spectroscopy (NIR), LIBS analysis is not limited by the sample thickness or color and therefore seems to be a promising candidate for this task. Nevertheless, the similar elemental composition of most polymers results in high similarity of their LIBS spectra, which makes their discrimination challenging. To address this problem, we developed a novel chemometric strategy based on a systematic optimization of two factors influencing the discrimination ability: the set of experimental conditions (laser energy, gate delay, and atmosphere) employed for the LIBS analysis and the set of spectral variables used as a basis for the polymer discrimination. In the process, a novel concept of spectral descriptors was used to extract chemically relevant information from the polymer spectra, cluster purity based on the k-nearest neighbors (k-NN) was established as a suitable tool for monitoring the extent of cluster overlaps and an in-house designed random forest (RDF) experiment combined with a cluster purity–governed forward selection algorithm was employed to identify spectral variables with the greatest relevance for polymer identification. Using this approach, it was possible to discriminate among 20 virgin polymer types, which is the highest number reported in the literature so far. Additionally, using the optimized experimental conditions and data evaluation, robust discrimination performance could be achieved even with polymer samples containing carbon black or other common additives, which hints at an applicability of the developed approach to real-life samples.Graphical abstract

Power density modulated ultrasonic degradation of perfluoroalkyl substances with and without sparging Argon

The power density modulates the dynamics of the chemical reactions during the ultrasonic breakdown of organic compounds. We evaluated the ultrasonic degradation of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) at various power densities (30 W/L–262 W/L) with and without sparging Argon. We observed pseudo-first-order degradation kinetics at an initial PFASs concentration of 100 nM over a range of power density. The rate kinetics of degradation shows a non-linear increase with an increase in power density. We proposed a four-parameter logistic regression (4PLR) equation that empirically fits the degradation rate kinetics with the power density. The 4PLR equation predicts that the maximum achievable half-life of PFOA and PFOS sonochemical degradation are 1 and 10 min under a given set of experimental conditions. The high bulk-water temperature (i.e., 30 °C) of the aqueous sample helps increase the degradation rate of PFOA and PFOS. The addition of oxidants such as iodate and chlorate help enhance PFOA degradation in an argon environment at an ultrasonic frequency of 575 kHz.

Gunshot residue detection in stagnant water: SEM-EDX or ICP-MS? A preliminary study.

The identification of gunshot residue (GSR) on wounds enables the differentiation of entry and exit wounds. Unfortunately, studies analyzing GSR on degraded bodies have been poorly documented, and no data exist regarding GSR detection after stagnant water immersion. The aim of this preliminary experimental study was to detect GSR on wounds altered in stagnant water, using scanning electron microscopy coupled with energy-dispersive X (SEM-EDX) and inductively coupled plasma mass spectrometry (ICP-MS). Shots were performed on sheep limbs with a 22LR at a distance of 20cm. The limbs were then submerged in stagnant water and analyzed on days 0, 6, and 14. SEM-EDX was performed on previously dehydrated wounds. For ICP-MS analysis, the wounds were rubbed with a cotton swab that was then analyzed. In the SEM studies, a higher number of particles were detected in entry wounds compared to exit wounds under every set of experimental conditions. Unfortunately, SEM-EDX failed to detect GSR particles, even on day 0. ICP-MS enabled the detection of Pb, Sb, and Ba at every stage with higher quantities on entry than in exit. These elements remained detectable following limb immersion. ICP-MS enabled differentiate entry from exit wounds, even after immersion in stagnant water. Nevertheless, when manually swabbing the wounds, quantities of matter collected is highly variable. ICP-MS is a more suitable technique than SEM-EDX for GSR identification of wounds after decomposition in stagnant water; however, standardization is needed.

Label-free aptasensor for p24-HIV protein detection based on graphene quantum dots as an electrochemical signal amplifier

Human immunodeficiency virus (HIV) is still considered a pandemic, and the detection of p24-HIV protein has an important role in the early diagnosis of HIV in adults and newborns. The accessibility of these trials depends on the price and execution difficulty of the method, which can be reduced using electrochemical methods by using enzymeless approaches, disposable and accurate devices. In this work, graphene quantum dots were acquired by a simple synthesis and employed as an electrochemical signal amplifier and support for the aptamer immobilization through a feasible and stable modification of disposable screen-printed electrodes. The device has been easily assembled and used to detect p24-HIV protein without the interference of similar proteins or sample matrix. Using the best set of experimental conditions, a linear correlation between analytical signal and log of p24-HIV concentration from 0.93 ng mL−1 to 93 μg mL−1 and a limit of detection of 51.7 pg mL−1 were observed. The developed device was applied to p24 determination in spiked human serum and provided distinct levels of signal for positive and negative samples, successfully identifying real samples with the target protein. This sensor is a step towards the development of point-of-care devices and the popularization of electrochemical methods for trials and diagnostics of relevant diseases.