Linear symmetric self-selecting 14-bit kinetic molecular memristors.

Artificial Intelligence (AI) is the domain of large resource-intensive data centres that limit access to a small community of developers1,2. Neuromorphic hardware promises greatly improved space and energy efficiency for AI but is presently only capable of low-accuracy operations, such as inferencing in neural networks3-5. Core computing tasks of signal processing, neural network training and natural language processing demand far higher computing resolution, beyond that of individual neuromorphic circuit elements6-8. Here we introduce an analog molecular memristor based on a Ru-complex of an azo-aromatic ligand with 14-bit resolution. Precise kinetic control over a transition between two thermodynamically stable molecular electronic states facilitates 16,520 distinct analog conductance levels, which can be linearly and symmetrically updated or written individually in one time step, substantially simplifying the weight update procedure over existing neuromorphic platforms3. The circuit elements are unidirectional, facilitating a selector-less 64 × 64 crossbar-based dot-product engine that enables vector-matrix multiplication, including Fourier transform, in a single time step. We achieved more than 73 dB signal-to-noise-ratio, four orders of magnitude improvement over the state-of-the-art methods9-11, while consuming 460× less energy than digital computers12,13. Accelerators leveraging these molecular crossbars could transform neuromorphic computing, extending it beyond niche applications and augmenting the core of digital electronics from the cloud to the edge12,13.

Gas sensing behavior of metal-catecholates based MOFs.

We report on the usability aspect of triphenylene ligand-based metal-organic frameworks (MOF) as the potential gas sensing element in chemiresistive devices. Among various possibilities, we explored mono-metallic (Nickel-based) and bi-metallic (Nickel and copper-based) in room temperature gas sensing. Our investigations suggest that the chemiresistive device based on nickel catecholate MOFs were highly sensitive to ethyl alcohol gas in the concentration range of 5-100 ppm with decent sensing parameters such as response time, recovery time, repeatability, stability, etc. We also investigated bimetallic (Nickel and copper) catecholate based MOFs in gas sensing with different metallic content ratios (Cu: Ni:: 60:40 and 40:60). We found that the 1D Cu0.6Ni0.4-CAT nanostructures-based gas sensor to be selective towards H2gas (0.2-7 ppm) at room temperature. We further explored the gas sensing abilities of Cu0.4Ni0.6-CAT based devices, and we found them to be selective towards NO2gas. However, it was not possible to obtain the current versus concentration curve due to the gas molecules' aggressive chemisorption. However, the device could perform well (with a hysteresis error of ∼10%) for detecting NO gas (which has the 2nd best absolute response after NO2). These results indicate that the ratio of metal ions in the MOF directly influences the sensing capabilities. Hence, rational synthetic variations in the metal content in MOF can lead to the design and develop highly selective and sensitive chemiresistive sensors.

Precursor to Gas Sensor: A Detailed Study of the Suitability of Copper Complexes as an MOCVD Precursor and their Application in Gas Sensing.

There are very few p-type semiconductors available compared to n-type semiconductors for positive sensing response for oxidizing gases and other important electronic applications. Cupric oxide (CuO) is one of the few oxides that show p-type conductivity, useful for sensing oxidizing gases. Many researchers obtained CuO using the chemical and solid-state routes, but uniformity and large-area deposition have been the main issues. Chemical vapor deposition is one such technique that provides control on several deposition parameters, which allow obtaining thin films having crystallinity and uniformity over a large area for the desired application. However, CuO-chemical vapor deposition (CVD) is still unfathomed due to the lack of suitability of copper precursors based on vapor pressure, contamination, and toxicity. Here, to address these issues, we have taken four Cu complexes (copper(II) acetylacetonate, copper(II) bis(2,2,6,6-tetramethyl-3,5-heptanedionato), copper(II) ethylacetoacetate, and copper(II) tert-butylacetoacetate), which are evaluated using thermogravimetry for suitability as a CVD precursor. The decomposition behavior of the complexes was also experimentally confirmed by depositing CuO thin films via CVD. Phase purity, decomposition, volatility, growth rate, and morphological characteristics of the films are investigated in detail. Analysis suggests that copper(II) tert-butylacetoacetate has the highest vapor pressure and growth rate at a low temperature, making it the most suitable precursor for high-throughput CVD. Further, to investigate the role of these precursors, films deposited using Cu complexes were subjected to gas sensing. The CuO gas sensor fabricated on glass shows pronounced NO2 sensing. The sensing results of CuO films have been explained from the standpoint of roughness, morphology, and unpassivated bonds present on the surface of films and vapor pressure of precursors. The higher density of surface state and the lower resistivity of the Cu(tbaoac)2 film lead to a sensor with higher responsivity and sensitivity (down to 1 ppm). These precursors can probably be utilized to improve the performance of other metal oxide gas sensors, especially Cu2O and Cu-III-O2.

Performance tunability of field-effect transistors using MoS2(1-x)Se2xalloys.

Ultra-thin channel materials with excellent tunability of their electronic properties are necessary for the scaling of electronic devices. Two-dimensional materials such as transition metal dichalcogenides (TMDs) are ideal candidates for this due to their layered nature and great electrostatic control. Ternary alloys of these TMDs show composition-dependent electronic structure, promising excellent tunability of their properties. Here, we systematically compare molybdenum sulphoselenide (MoS2(1-x)Se2x) alloys, MoS1Se1and MoS0.4Se1.6. We observe variations in strain and carrier concentration with their composition. Using them, we demonstrate n-channel field-effect transistors (FETs) with SiO2and high-kHfO2as gate dielectrics, and show tunability in threshold voltage, subthreshold slope (SS), drain current, and mobility. MoS1Se1shows better promise for low-power FETs with a minimum SS of 70 mV dec-1, whereas MoS0.4Se1.6, with its higher mobility, is suitable for faster operations. Using HfO2as gate dielectric, there is an order of magnitude reduction in interface traps and 2× improvement in mobility and drain current, compared to SiO2. In contrast to MoS2, the FETs on HfO2also display enhancement-mode operation, making them better suited for CMOS applications.

An ultralow power nanosensor array for selective detection of air pollutants.

Semiconducting metal oxide gas sensors typically operate at a high temperature and consume hundreds of milliwatts of power. Therefore there is great demand for the development of a low-power gas-sensing technology that can sensitively and selectively detect the gas analytes present in the atmosphere. We report an ultralow-power nanosensor array platform, integrated with an independently controlled nanoheater of size 4 µm × 100 nm, which consumes ∼1.8 mW power when operated continuously at 300 °C. The heaters exhibit a fast thermal response time of less than 1 µs, and can be utilized to operate in duty cycle mode, leading to power saving. The active area of the nanosensor is 1 µm × 200 nm, defined by sensing electrodes with a nanogap of ∼200nm, leading to small form factor. As a proof of concept, each of the sensing elements in the array is functionalized with different sensing materials to demonstrate a low-power, sensitive and selective multiplexed gas-sensing technology for the simultaneous detection of CO (∼93.2% for 3 ppm at 300 °C), CO2 (∼76.3% for 1000 ppm at 265 °C), NO2 (∼2301% for 3 ppm at 150 °C) and SO2 (∼94% for 3 ppm at 265 °C). The technology described here uses scalable crossbar architecture for sensor elements, thus enabling the integration of additional sensing materials and making it customizable for specific applications.

Colloidal lithography nanostructured Pd/PdO x core-shell sensor for ppb level H2S detection.

In this work we report on plasma oxidation of palladium (Pd) to form reliable palladium/palladium oxide (Pd/PdO x ) core-shell sensor for ppb level H2S detection and its performance improvement through nanostructuring using hole-mask colloidal lithography (HCL). The plasma oxidation parameters and the sensor operating conditions are optimized to arrive at a sensor device with high sensitivity and repeatable response for H2S. The plasma oxidized palladium/palladium oxide sensor shows a response of 43.1% at 3 ppm H2S at the optimum operating temperature of 200 °C with response and recovery times of 24 s and 155 s, respectively. The limit of detection (LoD) of the plasma oxidised beam is 10 ppb. We further integrate HCL, a bottom-up and cost-effective process, to create nanodiscs of fixed diameter of 100 nm and varying heights (10, 15 and 20 nm) on 10 nm thin Pd beam which is subsequently plasma oxidized to improve the H2S sensing characteristics. The nanostructured Pd/PdO x sensor with nanodiscs of 100 nm diameter and 10 nm height shows an enhancement in sensing performance by 11.8% at same operating temperature and gas concentration. This nanostructured sensor also shows faster response and recovery times (15 s and 100 s, respectively) compared to the unstructured Pd/PdO x counterpart together with an experimental LoD of 10 ppb and the estimated limit going all the way down to 2 ppb. Material characterization of the fabricated Pd/PdO x sensors is done using UV-vis spectroscopy and x-ray photoemission spectroscopy.

Spotting 2D atomic layers on aluminum nitride thin films.

Substrates for 2D materials are important for tailoring their fundamental properties and realizing device applications. Aluminum nitride (AIN) films on silicon are promising large-area substrates for such devices in view of their high surface phonon energies and reasonably large dielectric constants. In this paper epitaxial layers of AlN on 2″ Si wafers have been investigated as a necessary first step to realize devices from exfoliated or transferred atomic layers. Significant thickness dependent contrast enhancements are both predicted and observed for monolayers of graphene and MoS2 on AlN films as compared to the conventional SiO2 films on silicon, with calculated contrast values approaching 100% for graphene on AlN as compared to 8% for SiO2 at normal incidences. Quantitative estimates of experimentally measured contrast using reflectance spectroscopy show very good agreement with calculated values. Transistors of monolayer graphene on AlN films are demonstrated, indicating the feasibility of complete device fabrication on the identified layers.

Exploring glycated sites in human serum albumin: impact of sample processing techniques on detection and analysis.

Glycation and the subsequent formation of advanced glycation end products (AGEs) disrupt and impair the physiological functions of proteins. This study presents a comprehensive glycation site mapping of human serum albumin (HSA) utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS). Both in vitro glycation experiments and patient samples were investigated, exploring various enzymes, processing techniques, and their impacts on glycation site detection. A pilot study was conducted, analyzing sixteen serum samples, which spanned from healthy individuals to severe diabetic patients (with HbA1c values ranging from 5.7% to 18.1%). The aim was to comprehend the progression of glycation on various sites of HSA with increasing levels of glycation. Their glycated albumin levels (GA) spanned from 19.7% to 62.3%. Trypsin-mediated proteolytic digestion unveiled 12 glycation sites through direct in-solution digestion of whole serum. However, isolating albumin from serum enabled the identification of a higher number of glycation sites in each sample compared to direct serum digestion. Boronate affinity chromatography facilitated the segregation of less glycated albumin (LGA) from the more glycated albumin (MGA) fraction. Subsequent proteolytic digestion of both LGA and MGA samples revealed similar glycation sites. The MGA fraction exhibited a greater number of identified glycation sites, thereby elucidating which sites are particularly prone to glycation in highly glycated albumin samples. Changes in relative glycation levels were noted in the tryptic digests of albumin samples following the sample enrichment steps, as opposed to direct in-solution digestion of whole serum. Two enzymes, trypsin and Glu-C, were evaluated for efficacy in sequence coverage and glycation site analysis of HSA, with trypsin demonstrating superior efficiency over Glu-C.

Albumin Oxidation and Albumin Glycation Discordance During Type 2 Diabetes Therapy: Biological and Clinical Implications.

Aims: Cys34 albumin redox modifications (reversible "cysteinylation" and irreversible "di/trioxidation"), besides being just oxidative stress biomarkers, may have primary pathogenetic roles to initiate and/or aggravate cell, tissue, and vascular damage in diabetes. In an exploratory "proof-of-concept" pilot study, we examined longitudinal changes in albumin oxidation during diabetes therapy. Methods: Mass spectrometric analysis was utilized to monitor changes in human serum albumin (HSA) post-translational modifications {glycation [glycated albumin (GA)], cysteinylation [cysteinylated albumin (CA) or human non-mercaptalbumin-1; reversible], di/trioxidation (di/trioxidized albumin or human non-mercaptalbumin-2; irreversible), and truncation (truncated albumin)} during ongoing therapy. Four informative groups of subjects were evaluated [type 1 diabetes (T1DM), type 2 diabetes (T2DM), prediabetes-obesity, and healthy controls] at baseline, and subjects with diabetes were followed for a period up to 280 days. Results: At baseline, T2DM was associated with relatively enhanced albumin cysteinylation (CA% total) compared with T1DM (P = 0.004), despite comparable mean hyperglycemia (P values: hemoglobin A1c = 0.09; GA = 0.09). T2DM, compared with T1DM, exhibited selectively and significantly higher elevations of all the "individual" glycated cum cysteinylated ("multimodified") albumin isoforms (P values: CysHSA+1G = 0.003; CysHSA+2G = 0.007; and CysHSA+3G = 0.001). Improvements in glycemic control and decreases in albumin glycation during diabetes therapy in T2DM were not always associated with concurrent reductions of albumin cysteinylation, and in some therapeutic situations, albumin cysteinylation worsened (glycation-cysteinylation discordance). Important differences were observed between the effects of sulfonylureas and metformin on albumin molecular modifications. Conclusions: T2DM was associated with higher oxidative (cysteinylation) and combined (cysteinylation plus glycation) albumin molecular modifications, which are not ameliorated by improved glucose control alone. Further studies are required to establish the clinical significance and optimal therapeutic strategies to address oxidative protein damage and resulting consequences in diabetes.

Differential Spectrum of Albumin Glycation, Oxidation, and Truncation in Type 2 and Type 1 Diabetes: Clinical and Biological Implications.

Background: Albumin, the most abundant and physiologically vital serum protein, accumulates a range of chemical modifications, as consequence of encounters with large number of reactive molecules whose concentrations increase in serum under pathological conditions. Methods: In a "proof of concept" study, mass spectrometric analysis was utilized to quantitate albumin post-translational modifications (glycation, oxidation, and truncation; individual isoforms and total) in four informative subject groups [type 1 diabetes (T1DM), type 2 diabetes (T2DM), prediabetes-obesity and healthy; all with estimated glomerular filtration rate ≥60 mL/(min·m2)]. Besides glycated albumin (GA/mass spectrometry), glycated serum protein (GSP/nitro blue tetrazolium colorimetry), and glycated hemoglobin (HbA1c/high-performance liquid chromatography) were also measured. Results: A wide spectrum of albumin molecular modifications was identified in diabetes, with significant differences between T2DM and T1DM. Albumin glycation: GA correlated more strongly with HbA1c in T1DM, compared to T2DM. Higher albumin glycation isoforms (human serum albumin +3G/2G) were more stable and discriminative markers of mean glycemia. Albumin oxidation: T2DM, in comparison with T1DM, showed enhanced oxidative and dual (glycation plus oxidation) modifications, representing extreme molecular pathology. Albumin truncation: There was dramatic reduction ("deficiency") of truncated albumin isoforms in T2DM, and significant reduction in T1DM. Albumin truncation negatively correlated with severity of albumin glycation (mean glycemia) and albumin oxidation (cysteinylation). Possible mechanisms of insulin resistance, with associated increased free fatty acids binding to albumin, in stimulating albumin oxidation and inhibiting albumin glycation ("metabolic cross talks") are reviewed. Conclusions: Albumin molecular modifications in diabetes, together with significant differences between T2DM and T1DM, suggest possible role for insulin resistance in their genesis and consequent cell, tissue, and vascular dysfunction/damage. Albumin molecular fingerprinting can provide valuable insights into pathogenesis, diagnosis, monitoring, and future therapies for diabetes. Identification of biomarker battery ("albuminomics," "diabetomics") driven diverse "healthy," prediabetes, obesity, and T2DM phenotypes represents additional novel step toward precision medicine in diabetes and related disorders.

Realizing avalanche criticality in neuromorphic networks on a 2D hBN platform.

Networks and systems which exhibit brain-like behavior can analyze information from intrinsically noisy and unstructured data with very low power consumption. Such characteristics arise due to the critical nature and complex interconnectivity of the brain and its neuronal network. We demonstrate a system comprising of multilayer hexagonal boron nitride (hBN) films contacted with silver (Ag), which can uniquely host two different self-assembled networks, which are self-organized at criticality (SOC). This system shows bipolar resistive switching between the high resistance state (HRS) and the low resistance state (LRS). In the HRS, Ag clusters (nodes) intercalate in the van der Waals gaps of hBN forming a network of tunnel junctions, whereas the LRS contains a network of Ag filaments. The temporal avalanche dynamics in both these states exhibit power-law scaling, long-range temporal correlation, and SOC. These networks can be tuned from one to another with voltage as a control parameter. For the first time, two different neural networks are realized in a single CMOS compatible, 2D material platform.

Energy and Space Efficient Parallel Adder Using Molecular Memristors.

A breakthrough in in-memory computing technologies hinges on the development of appropriate material platforms that can overcome their existing limitations, such as larger than optimal footprint and multiple serial computational steps, with potential accumulation of errors. Using a molecular switching element with multiple non-monotonic and deterministic transitions, the device count and the number of computational steps can be substantially reduced. With molecular materials, however, the realization of a reliable and robust platform is an unattained goal for decades. Here, crossbar arrays with up to 64 molecular memristors are fabricated to experimentally demonstrate 8-bit serial and 4-bit parallel adders that operate for thousands of measurement cycles with an estimated error probability of 10-16 . For performance benchmarking, a 32-bit parallel adder is designed and simulated with 268 million inputs including contributions from the peripheral circuitry showing a 47× higher energy efficiency, 93× faster operation, and 9% of the footprint, leading to 4390 times improved energy-delay product compared to a special purpose complementary metal-oxide-semiconductor (CMOS)-based multicore adder.

External bias dependent direct to indirect band gap transition in graphene nanoribbon.

In this work, using self-consistent tight-binding calculations, for the first time, we show that a direct to indirect band gap transition is possible in an armchair graphene nanoribbon by the application of an external bias along the width of the ribbon, opening up the possibility of new device applications. With the help of the Dirac equation, we qualitatively explain this band gap transition using the asymmetry in the spatial distribution of the perturbation potential produced inside the nanoribbon by the external bias. This is followed by the verification of the band gap trends with a numerical technique using Magnus expansion of matrix exponentials. Finally, we show that the carrier effective masses possess tunable sharp characters in the vicinity of the band gap transition points.

Growth-Temperature Dependent Unpassivated Oxygen Bonds Determine the Gas Sensing Abilities of Chemical Vapor Deposition-Grown CuO Thin Films.

CuO is a multifunctional metal oxide excellent for chemiresistive gas sensors. In this work, we report CuO-based NO2 sensors fabricated via chemical vapor deposition (CVD). CVD allows great control on composition, stoichiometry, impurity, roughness, and grain size of films. This endows sensors with high selectivity, responsivity, sensitivity, and repeatability, low hysteresis, and quick recovery. All these are achieved without the need of expensive and unscalable nanostructures, or heterojunctions, with a technologically mature CVD. Films deposited at very low temperatures (≤350 °C) are sensitive but slow due to traps and small grains. Films deposited at high temperatures (≥550 °C) are not hysteretic but suffer from low sensitivity and slow response due to lack of surface states. Films deposited at optimum temperatures (350-450 °C) combine the best aspects of both regimes to yield NO2 sensors with a response of 300 % at 5 ppm, sensitivity limit of 300 ppb, hysteresis of <20%, repeatable performance, and recovery time of ∼1 min. The work demonstrates that CVD might be a more effective way to deposit oxide films for gas sensors.

Glycation of albumin and its implication in Diabetes: A comprehensive analysis using mass spectrometry.

AIM: To understand the mechanism of glycation of albumin and effects on cysteinylation and methionine oxidation. METHODS: The in vitro glycation of HSA and BSA was studied with varying concentrations of glucose. Clinical blood samples of diabetic subjects with varying HbA1c values, were analyzed to assess in vivo glycation. All samples and their tryptic digests were analyzed using liquid chromatography/mass spectrometry. Glycation sites were mapped on to the three-dimensional structure of the HSA and BSA. RESULTS: A total thirty-one sites for glycation and eight sites of Nε-carboxymethyl-lysine (CML) modification were identified on albumin. The site selectivity of glycation was correlated with the environment of the reactive residue in the three-dimensional structure. CONCLUSIONS: The maximum percentage glycation under extreme conditions was in the range of ~55 to 88% in four weeks. Two major glycation sites K-233 and K-525 were identified, which together accounted for 40-50% of total glycation. A correlation was observed between glycation and oxidation of methionine residues in samples glycated in vitro. The role of spatially proximate residues in facilitating the glycation process is evident. The tri- and tetra-glycated isoforms of albumin can serve as biomarkers for the severe uncontrolled diabetic state.

Multicentric evaluation of a novel point of care electrochemical ELISA platform for SARS-CoV-2 specific IgG and IgM antibody assay.

New diagnostics technologies for the efficient detection and quantification of SARS-CoV-2 antibodies are very crucial to manage the COVID-19 pandemic, especially in the context of emerging vaccination paradigms. Herein, we report on a novel point-of-care Electrochemical ELISA platform with disposable screen printed electrodes functionalized with SARS-CoV-2 Spike Glycoprotein S1, to enable fast and accurate quantitative estimation of total antibody concentration (IgG and IgM) in clinical samples. The quantification is performed with a comparison of electrochemical redox current against the current produced by the spiked monoclonal antibodies with known concentration. The assay is validated through multicentric evaluation against 3 different FDA authorized Laboratory standard techniques, using both EDTA whole blood and serum samples. We demonstrate that the proposed assay has excellent sensitivity and specificity, making it a suitable candidate for epidemiological surveys and quantification of antibodies in COVID-19 vaccination programs.

Ultrasonication assisted fabrication of a tungsten sulfide/tungstite heterostructure for ppb-level ammonia detection at room temperature.

A heterostructure of WS2/WO3·H2O has been prepared by partial oxidation of WS2 nanosheets by exposing bulk WS2 micron powder to ultrasonic waves in a bath sonicator. The as-prepared nanomaterial was used as a sensing film in an interdigitated electrode-based gas detecting device. The device was found to be specific towards ammonia gas among a group oxidizing and reducing gases. In particular, a response of as high as 11.36-254.66% was recorded for ammonia concentrations of 50 ppb to 2 ppm with excellent repeatability and reproducibility at room temperature. The response time and recovery time of the device was found to be a few tens of seconds suggesting its practicability. A plausible mechanism based on different active sites present in the receptor film is proposed and a logical reason behind its specificity towards ammonia gas is also inferred based on the Lewis acidic centers on the nano-surfaces. Overall, this proposed nanomaterial has very high potential for practical use as a room temperature ammonia sensor.

Boron nanostructures obtained via ultrasonic irradiation for high performance chemiresistive methane sensors.

We report on a chemiresistive gas sensor using boron nanostructures as the sensing layer, to detect methane gas down to 50 ppm. The sensor showed an excellent response of 43.5-153.1% for a methane concentration of 50 ppm to 105 ppm, with linear behaviour and good response and recovery time. The stability, repeatability, reproducibility, and shelf life of the sensor are promising for next generation methane gas detection.

Serum Creatinine Electrochemical Biosensor on Printed Electrodes Using Monoenzymatic Pathway to 1-Methylhydantoin Detection.

The rising prevalence of Chronic Kidney Disease (CKD) has necessitated efforts towards the development of cost-effective and accurate biosensors for serum creatinine, which is a potent biomarker reflecting kidney function. This work presents a novel and cost-effective technique to estimate serum creatinine without any sample preprocessing. The technique involves the conversion of creatinine by a monoenzymatic pathway to 1-methylhydantoin. The concentration of 1-methylhydantoin is then quantified by utilizing its innate ability to form a complex with transition metals such as cobalt. The complex formation has been validated using optical spectroscopy and the transmittance at 290 nm wavelength is used to identify the optimum concentration of cobalt chloride in sensing chemistry. This chemical assay is shown to be robust against interference from serum albumin, the abundant plasma protein that can potentially influence the sensor response. The electrochemical biosensor developed using screen-printed electrodes thus provides highly selective creatinine estimation over the range of 0.2-4 mg/dL in a sample volume of 300 µL with no preprocessing and hence can be easily translated into a viable point-of-care (POC) device.

Biochemical assay for serum creatinine detection through a 1-methylhydantoin and cobalt complex.

Creatinine is a reliable indicator of renal function and degradation of muscular metabolism. Current analytical techniques for its measurement are limited by their cost and requirement of sophisticated instruments. In this work, we report a highly sensitive amperometric biosensor for creatinine by utilizing the one-step selective conversion of creatinine by creatinine deiminase. The novelty of the proposed sensor relies on the measurement of N-methylhydantoin produced in the reaction. The sensing chemistry comprises of creatinine deiminase as the receptor for creatinine, cobalt chloride as the electrochemically active recognition element, and methylene blue as the redox mediator. The sensing chemistry is immobilized on the glassy carbon electrode surface by physisorption. We have been able to provide a standalone device that reliably quantifies creatinine in serum and even whole blood, without any sample pre-processing. It is possible to measure creatinine in the clinically relevant range from 0.8 to 4 mg dL-1 with this approach.