Fourier Transform Raman Spectroscopy Research Articles

Filter-processing-assisted Fourier transform Raman spectroscopy for forensic discrimination lubricant machinery oils

The primary objective of this study was to investigate the potential value of filtering algorithms in enhancing spectral model performance. 290 mechanical lubricants oils samples from various applications underwent measurement using Fourier transform Raman spectroscopy (FT-Raman). Subsequently, three discrimination models were developed employing C5.0, Bayes discriminant analysis, and support vector machine algorithms. The emphasis was on evaluating the efficacy of four filter algorithms—Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), Finite Impulse Response (FIR), and Hilbert Transform (HT)—for enhancing model performance. Among these, the FFT filter-SVM model, DWT filter-SVM model, and FIR (low-pass or band-stop filter)-SVM model emerged as optimal choices for identification. These models demonstrated outstanding performance, achieving 100 % accuracy across all 290 samples. Modelling using FT-Raman and chemometrics offered a simpler, more robust, and valuable approach for identifying mechanical lubrication oils across diverse applications, exploiting the potential of filtering algorithms in forensic spectroscopy.

Binary Mixtures of Meloxicam and L-Tartaric Acid for Oral Bioavailability Modulation of Pharmaceutical Dosage Forms.

Binary mixtures of active pharmaceutical ingredients (API) are researched to improve the oral bioavailability of pharmaceutical dosage forms. The purpose of this study was to obtain mixtures of meloxicam and L-tartaric acid because tartaric acid improves intestinal absorption and meloxicam is more soluble in a weakly basic environment. The mixtures in the 0-1 molar fraction range, obtained from solvent-assisted mechanosynthesis, were investigated by differential scanning calorimetry (DSC), Fourier Transform Infrared (FTIR) spectroscopy, Fourier Transform Raman spectroscopy (FT-Raman), X-ray powder diffraction (XRD) and solubility tests. The physicochemical characteristics of the compounds obtained from DSC data reveal, for the first time, the formation of a co-crystal at meloxicam molar fraction of 0.5. FTIR spectroscopy data show the existence of hydrogen bonds between the co-crystal components meloxicam and L-tartaric acid. FT-Raman spectroscopy was used complementary with FT-IR spectroscopy to analyze the pure APIs and their mixtures, to emphasize the appearance/disappearance and the shifts of the position/intensity of vibrational bands, following the formation of hydrogen-bonded structures or van der Waals interactions, and to especially monitor the crystal lattice vibrations below 400 cm-1. The experimental results obtained by X-ray powder diffraction confirmed the formation of the co-crystal by the loss and, respectively, the apparition of peaks from the single components in the co-crystal diffractogram. The solubility tests showed that the co-crystal product has a lower aqueous solubility due to the acidic character of the other component, tartaric acid. However, when the solubility tests were performed in buffer solution of pH 7.4, the solubility of meloxicam from the co-crystal mixture was increased by 57% compared to that of pure meloxicam. In conclusion, the studied API mixtures may be considered potential biomaterials for improved drug release molecular solids.

Agar and Chitosan Hydrogels' Design for Metal-Uptaking Treatments.

In the field of cultural heritage, the use of natural gels is rising for the application of active agents. Here, two natural polymers are assessed: agar, a pioneer hydrogel for conservation treatments, and chitosan, a rather novel and metal-binding gel. For chitosan, a state-of-the-art based formulation (CS-ItA-LCys) is evaluated as it was reported for silver-complexing properties. It is evaluated whether these polymers can withstand the addition of the chelating compound deferoxamine, which is a bacterial siderophore. This allows for the obtainment of completely bio-sourced gel systems. A Fourier-transformed (FT) infrared spectroscopy characterization is performed, completed with rheological measurements and Cryo-Scanning Electron Microscopy (cryo-SEM) to investigate the physico-chemical properties of the gels, as well as their interaction with deferoxamine. Both polymers are also tested for their inherent complexing ability on silver ions using FT-Raman spectroscopy. A multi-analytical comparison shows different microstructures, in particular, the presence of a thick membrane for chitosan and different mechanical behaviors, with agar being more brittle. Neither hydrogel seems affected by the addition of deferoxamine; this is shown by similar rheological behavior and molecular structures in the presence or absence of the chelator. The intrinsic abilities of the chitosan formulation to make silver complex are demonstrated with the observation of two peaks characteristic of Ag-S and Ag-O bonds. Agar and chitosan are both proven to be reliable gels to act as carriers for bio-based active agents. This paper confirms the potential asset of the chitosan formulation CS-ItA-LCys as a promising gel for the complexation of soluble silver.

Screening for pigment production and characterization of pigment profile and photostability in cold-adapted Antarctic bacteria using FT-Raman spectroscopy

Microbial pigments can replace synthetic organic pigments which often produced in unsustainable way and can be toxic. Therefore, search for new pigment producing microorganisms is of high interest for industry. In this study, a screening and characterization of pigment profile and photostability in seventy-four newly isolated Antarctic bacteria using Fourier-transform (FT) Raman spectroscopy and HPLC-MS was performed. Screening of the bacterial biomass by FT-Raman identified thirty-seven bacterial strains from the genera Agrococcus, Arthrobacter, Brachybacterium, Cryobacterium, Leifsonia, Micrococcus, Paeniglutamicibacter, Rhodococcus, Salinibacterium and Flavobacterium as having relatively high pigment content. The impact of growth temperature on the pigment production in the studied Antarctic bacteria was species - specific, while blue light exposure triggered pigment production in majority of the studied bacteria. HPLC-MS analysis of a biomass of a set of ten pigmented Antarctic bacteria identified eighteen different carotenoids and precursors. FT-Raman spectroscopy showed to be suitable for both, semi-qualitative library-independent identification of pigment producing bacteria and determination of pigment profile using spectral library of reference pigment standards. This study provides valuable insights into the pigment production capabilities of Antarctic bacteria and highlighting the potential of FT-Raman spectroscopy for characterizing microbial pigments.

Structural elucidation by Raman spectroscopy and analysis of luminescence quenching by the Inokuti-Hirayama model in the Pr3+ doped multi-component silicate photonic films

Thin films of multi-component silica glasses doped with Ca2+ and Pr3+ modifiers were fabricated by the spin coating technique. Surface micrographic images extracted by the Field Emission Scanning Electron Microscope revealed a homogeneous texture of the films. Detailed structural analysis by Fourier Transform Raman spectroscopy confirmed the existence of Si-O-Si and polyphosphate groups in the glass matrix. The Burstein-Moss shift was evidenced with doping, by an increase in the band gap of the glass films, evaluated by Tauc’s plots. The films exhibit red and near infra-red emissions (NIR), corresponding to the transitions: 3P0→3F2 and 3P0→3F4 respectively. The decay analysis by the Inokuti-Hirayama (I-H) model validated the contributions of multi-polar interactions particularly that of dipole-quadrupole mechanisms, leading to significant quenching in the highly doped film. The energy transfer efficiency between the sensitizer and activator ions, determined by the formulations of the model was 51.8 %. The decreasing lifetime of the metastable state observed in the glass films could be considered to be prospective for NIR waveguide lasers and red laser sources for optical display screens.

Effect of consumption of sheep and cow milk on rat brain fatty acid and phospholipid composition

The effect of sheep milk and cow milk on the lipid composition of rat brain was investigated in two feeding experiments of 28-days duration. Total lipids of the rat brain were extracted using ethanol-hexane, and the fatty acids and phospholipid contents analysed using gas chromatography with flame ionization detection (GC-FID) and phosphorus-31 nuclear magnetic resonance (31P NMR). Furthermore, freeze-dried pooled samples were analysed using attenuated total reflectance Fourier Transform Infrared and Fourier Transform Raman Spectroscopy and analysed with multivariate methods. A significantly (P < 0.05) higher C18:2 content was found in the cow milk group compared with sheep milk-treated groups in Study one. In Study two, a significantly (P < 0.05) lower C16:0 content was present in the sheep milk-treated group compared to the control low Ca/P group. No significant (P > 0.05) differences were observed in the spectroscopy analyses. It is concluded that sheep and cow milks fed to rats for 28-days had a low effect on the brain lipidome.

Influence of graphene oxide in the hydration mechanism by reinforcing mechanical strength and microstructural Characterization of ultra-high-performance concrete (UHPC)

In the past few years, one of the most promising graphite-based nanomaterials in the construction industry has been Graphene Oxide (GO) due to its outstanding performance combined with cementitious composites. Introducing extensive Engineering Cementitious Materials (ECMs) improves Ultra-High-Performance Concrete (UHPC) mechanical, durability, and microstructural characteristics. Very few studies have been concentrated on cement pastes, mortars, and regular concrete, high strength concrete. Limited studies on UHPC with large volumes of ECMs done. The present investigation mainly focuses on improving the UHPC in fresh, mechanical, and microstructural behavior. Four mixes were prepared with GO (0.00%, 0.03%, 0.06%, and 0.1% by weight of cement) and a water-cement ratio of 0.20. Results indicated that the mix with 0.06% GO had a better outcome and improved the compressive, split tensile, and flexural strength compared with other test mixes. Microstructural analysis carries out using x-ray fluorescence (XRF), x-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy-dispersive x-ray Spectroscopy (EDS), Thermogravimetric Analysis (TGA), Fourier-Transform Infrared Spectroscopy (FTIR), Fourier-Transform Raman Spectroscopy (FT-RAMAN) on 28 days UHPC mixes and quality of the concrete mixes analyzed with Ultrasonic Pulse Velocity (UVP) test. They developed and established the fundamental step toward the cost-effective, eco-friendly, sustainable UHPC.

Detection of carbon nanotubes in bovine raw milk through Fourier transform Raman spectroscopy

The potential use of carbon-based methodologies for drug delivery and reproductive biology in cows raises concerns about residues in milk and food safety. This study aimed to assess the potential of Fourier transform Raman spectroscopy and discriminant analysis using partial least squares (PLS-DA) to detect functionalized multiwalled carbon nanotubes (MWCNT) in bovine raw milk. Oxidized MWCNT were diluted in milk at different concentrations from 25.00 to 0.01 µg/mL. Raman spectroscopy measurements and PLS-DA were performed to identify low concentrations of MWCNT in milk samples. The PLS-DA model was characterized by the analysis of the variable importance in projection (VIP) scores. All the training samples were correctly classified by the model, resulting in no false-positive or false-negative classifications. For test samples, only one false-negative result was observed, for 0.01 µg/mL MWCNT dilution. The association between Raman spectroscopy and PLS-DA was able to identify MWCNT diluted in milk samples up to 0.1 µg/mL. The PLS-DA model was built and validated using a set of test samples and spectrally interpreted based on the highest VIP scores. This allowed the identification of the vibrational modes associated with the D and G bands of MWCNT, as well as the milk bands, which were the most important variables in this analysis.

Graphene oxide-alginate hydrogel-based indicator displacement assay integrated with diaper for non-invasive Alzheimer's disease screening

Pyrocatechol violet/copper ion-graphene oxide/alginate (PV/Cu2+-GO/Alg) hydrogel was fabricated and applied as a colorimetric sensor for monitoring urinary cysteine via an indicator-displacement assay (IDA) and Cu2+-cysteine affinity pair. The hydrogel-based sensor was formed by Ca2+ cations cross-linked PV/Cu2+-GO/Alg. The morphologies of hydrogel were characterized by field-emission scanning electron microscopy with energy-dispersive X-ray spectroscopy and Fourier-transform Raman spectroscopy. Incorporating GO into the hydrogel improved its uniformity of porosity, large surface area, and compressive strength, leading to amplified colorimetric signals of the hydrogel sensor. Under optimal conditions, this sensor offered a linear range of 0.0–0.5 g/L with a detection limit of 0.05 g/L for cysteine without interfering effects in urine. Furthermore, this hydrogel-based sensor was applied for urinary cysteine detection and validated with laser desorption ionization mass spectrometry. This platform could be used to determine cysteine at its cutoff (0.25 g/L) in human urine, which was distinguishable between normal and abnormal individuals, to evaluate an early stage of Alzheimer's disease. Eventually, this system was integrated with diapers for a wearable cysteine sensor.

Quantitative analysis of blood glucose by FT‐Raman spectroscopy and multivariate statistical analysis

AbstractDiabetes is one of the common chronic diseases in worldwide and increasing among young children. Testing glycated hemoglobin levels as well as blood glucose levels is a method for detecting diabetes. In this article, with multivariate statistical analysis was used to monitor the blood glucose levels by the Fourier Transform Raman spectroscopy. Principal component regression with direct orthogonal signal correction is developed and applied to analyze the glucose concentration with the blood Raman spectroscopy. The root means square error of calibration is 3.0824 mg/dL (0.1712 mmol/L), the root means square error of prediction is 3.2688 mg/dL (0.1816 mmol/L), the correlation coefficients (R2) is .9946 and ratio of performance to deviation is 6.4789 and, respectively. The results show that this method can be used as a strong potential diagnostic tool for diabetes mellitus.

High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm

Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive identification and minimal interference from water. However, the challenge lies in how to accurately predict blood glucose concentrations in human blood using Raman spectroscopy. This paper researches a novel integrated machine learning algorithm called Bagging-ABC-ELM. The optimal input weights and biases of extreme learning machine (ELM) model are obtained by artificial bee colony (ABC) algorithm. The bagging algorithm is used to obtain a better the stability of the model and higher performance than ELM algorithm. The results show that the mean value of coefficient of determination is 0.9928, and root mean square error is 0.1928. Compared to other regression models, the Bagging-ABC-ELM model exhibited superior prediction accuracy, robustness, and generalization capability. The Bagging-ABC-ELM model presents a promising alternative for analyzing blood glucose levels in clinical and research settings.

Preparation of 82Se thin films with trigonal hexagonal crystal structure for in-beam nuclear structure experiments

We report a novel approach in producing and characterizing enriched isotopic selenium-82 (82Se) thin films with trigonal hexagonal crystal structure (t-82Se), the most thermodynamically stable form of the element. The obtained t-82Se thin films are used as targets in accelerator based nuclear structure experiments. Several 82Se thin films with thicknesses around 5 mg/cm2 (10.4 μm) were deposited on 5 mg/cm2 (3 μm) tantalum (Ta) foils by vacuum evaporation-condensation method. The condensed 82Se films exhibit unstable amorphous structure (a-82Se), therefore were converted to t-82Se by means of an appropriate vacuum heat treatment developed in the target laboratory of IFIN-HH. After the thermal treatment, the microstructure, morphology and composition of the 82Se films were evaluated before and after the vacuum thermal treatment using Fourier Transform Raman Spectroscopy (FT-Raman), X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM) and Energy-Dispersive X-Ray Spectroscopy (EDX) techniques. Furthermore, an in-beam γ-spectroscopy experiment performed at the 9-MV tandem accelerator of IFIN-HH confirmed that the thermally treated t-82Se films possess high durability and high purity with no detectable contamination and no mass loss.

Novel highly stable conductive polymer composite PEDOT:DBSA for bioelectronic applications

In this work, a novel conductive polymer composite consisting of poly(3,4-ethylenedioxythiophene) doped with dodecylbenzenesulfonic acid (PEDOT:DBSA) for bioelectronic applications was prepared and optimized. The novel PEDOT:DBSA composite possesses superior biocompatibility toward cell culture and electrical characteristics comparable to the widely used PEDOT:PSS. The cross-linking processes induced by the cross-linker glycidoxypropyltrimethoxysilane (GOPS), which was investigated in detail using Fourier transform Raman spectroscopy and XPS analysis, lead to the excellent long-term stability of PEDOT:DBSA thin films in aqueous solutions, even without treatment at high temperature. The electrical characteristics of PEDOT:DBSA thin films with respect to the level of cross-linking were studied in detail. The conductivity of thin films was significantly improved using sulfuric acid posttreatment. A model transistor device based on PEDOT:DBSA shows typical transistor behavior and suitable electrical properties comparable or superior to those of available conductive polymers in bioelectronics, such as PEDOT:PSS. Based on these properties, the newly developed material is well suited for bioelectronic applications that require long-term contact with living organisms, such as wearable or implantable bioelectronics.

Carbonization of self-reduced AuNPs on silk as wearable skin patches for non-invasive sweat urea detection

Flexible conductive skin patches were readily fabricated on silk fabric by in situ deposition of gold nanoparticles (AuNPs) followed by carbonization. The carbonized AuNPs-silk with high flexibility was characterized by field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM) and Fourier transform Raman spectroscopy (FT-Raman) to verify the well arrangement surface and desired chemical binding. The conductivity of silk skin patch, measured by a four-point probe, was found to be 109.24 ± 13 S cm−1 × 10−3, verifying the potential application as a working electrode in electrochemical sensor and a sweat collection patch for direct detection by laser desorption/ionization mass spectrometry (LDI-MS). This silk skin patch offered a linear range of 0–100 mM with a detection limit (LOD) of 20 mM for electrochemical sensor and 8 mM for LDI-MS, respectively. Ultimately, this skin patch is successfully applied for the detection of sweat urea at its cut-off value (60 mM) for indicating chronic kidney disease (CKD) in artificial sweat with satisfactory results. By using dual-detection technique on single silk substrate, this platform might be an alternative approach for a non-invasive sweat urea detection with high precision.

Characterization of Synthesized NiCo2O4 with Trisodium Citrate for Supercapacitor Material: A Preliminary Study

Supercapacitors can be called electrostatic double-layer capacitors (EDLCs) or pseudo-capacitors based on their energy storage mechanism. Pseudo-capacitors with metal oxide electrodes that transmit electric charge offer great application power but low stability. This study aims to characterize trisodium citrate (TSC) modified NiCo2O4/rGO electrodes as a preliminary study for the NiCo2O4 nanoparticle pseudo-capacitor. The materials were characterized using SEM (Scanning Electron Microscopy), XRD (X-Ray Diffractometer), FT-Raman (Fourier Transform Raman Spectroscopy), and FTIR (Fourier Transform Infrared Spectroscopy). All of these analyses confirmed that NiCo2O4 was manufactured successfully using TSC. At XRD, the angles of 2????, namely 45.04 and 53.34°, matched the plane of the cubic phase nanorod crystals of NiCo2O4 with values of 400 and 511, respectively. In the Raman examination, the presence of rGO, which increased the crystallinity of NiCo2O4 nanoparticles, was confirmed. FTIR analysis indicated that the 1550-1600 cm−1 corresponds to a C=C functional group in an aromatic ring or a C=O ????-???? structure, and the wavenumber of 2300 cm−1 corresponds to the OH group in TSC, an alkanoate derivative. SEM analysis determined that NiCo2O4 nanoparticles with 1 mmol TSC are the ideal material for supercapacitor electrodes, as the structure is the most uniform, soft, and tidy. Further analysis is needed to confirm the stability of the modified material.

Graphene oxide-doped poly(styrene-co-maleic anhydride) for high-energy supercapacitors

Reliable energy-storage materials that can provide enhanced capacitance with good cycling stability along with improved energy and power densities are exceedingly relevant in the commercial arena to attenuate the prevalent energy shortage. Polymers with structural flexibility and good mechanical and thermal stability can be coupled with carbon-based additives to obtain an electrochemical platform for energy storage without compromising on the required thermal and mechanical attributes. Here, a styrene–maleic anhydride copolymer was modified with a diamine to form a polyimide. The samples were characterized using ultraviolet–visible spectroscopy, carbon-13 (13C) nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, Fourier transform Raman spectroscopy, thermogravimetric analysis, differential scanning calorimetry, Brunauer–Emmett–Teller analysis, scanning electron microscopy, transmission electron microscopy and X-ray diffraction to understand and investigate the spectral, morphological and electrochemical characteristics of the polymer nanocomposites. Efficacious intercalation of graphene oxide resulted in the formation of polymer nanocomposites that can act as excellent supercapacitor electrodes with a high specific capacitance of 700 F/g at 0.5 A/g and an energy and a power density of 129.23 Wh/kg and 5572 W/kg, respectively.

Comparison of three cyclodextrins to optimize bisphenol A extraction from source water: Computational, spectroscopic, and analytical studies.

Computationally and spectroscopically assisted analytical comparative investigation into the extraction of bisphenol A using three cyclodextrins, that is, α, β, and γ respectively, were performed. A simple, self-tailored μ-solid-phase extraction podium was used to extract bisphenol A from water samples, and high-performance liquid chromatography-ultraviolet was used for the qualitative and quantitative analysis of bisphenol A. Density functional theory first principle calculations, attenuated total reflectance Fourier-transform infrared spectroscopy and Fourier-transform Raman spectroscopy data supports the analytical selection of β-cyclodextrin as the adsorbent for bisphenol A extraction. Analytical optimization of various parameters including sample volume, sample pH, eluting solvent and its volume was performed to discover the most proper conditions for maximum extraction. Under the optimized conditions, a limit of detection value of 0.70ng/ml and a limit of quantification value of 2.31ng/ml was achieved with β-cyclodextrin, with recovery (%) values over 98.40-102.50 in real source water samples. Overall, well assisted by comprehensive computational and spectroscopic studies, a novel, simple, sensitive and economic analytical method was developed for the extraction of bisphenol A from source water using cyclodextrin.

Bactericidal Properties of Natural Fibers Hybrid Functionalized with ZnO/Cu2+ and ZnO/Cu0

Multifunctional natural fibers with antimicrobial properties have been applied as a viable strategy to prevent microorganism contamination and proliferation on the surface of clothes and personal protection equipment marketed and used by health professionals, patients, and the general population. They present intrinsic antimicrobial capacity, providing effective protection preventing the transmission and contagion of diseases caused by pathogenic microorganisms. Herein, we successfully functionalized cotton fibers with ZnO/Cu2+ and ZnO/Cu0 hybrid systems via a hydrothermal routine. Rietveld refinement from X-ray Diffractometry (XRD) data and Fourier-Transform Raman Spectroscopy (FT-Raman) indicate alterations on the cellulose crystallinity index in the cotton fibers after functionalization, mainly on the proportion of cellulose Iβ polymorph crystal. Scanning Electron Microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) indicate adequate ZnO nanoparticles fixation and in-situ reduction of copper ions. Antimicrobial tests confirm that the multifunctional fibers present bactericidal activity against Gram-negative and Gram-positive bacteria under electromagnetic irradiation (440–480 nm). Self-disinfection capability and UV blocking properties of wipes with fibers after ZnO/Cu2+ and ZnO/Cu0 functionalization were improved.

Growth parameters and investigations on the structural, optical, mechanical, thermal and electrical properties of an l-proline guanidine carbonate single crystal

Single crystal of l-proline guanidine carbonate (LPGC) was grown by adapting most important method of slow evaporation technique by using double distilled water as a solvent at room temperature. Single crystal X-ray diffraction determined that the crystal structure of LPGC as orthorhombic non-centro symmetric system with the P212121 space group and the lattice parameters are confirmed to be a = 8.3580(4) Å, b = 10.3479(4) Å, c = 15.1833(5) Å, α = β = γ = 90°, Volume V = 1313.17(9) A3. The diffraction pattern of powder X-ray diffraction describes the factors of the crystallinity nature and the purity of the LPGC crystal. The optical absorption spectrum of LPGC crystal has been recorded and the linear optical constants such as the absorption coefficient (α), Energy band gap (Eg), extinction coefficient (K), refractive index (n) and Urbach energy (Eu) have been calculated. The active functional groups of the grown crystal were identified and confirmed by Fourier transform infrared spectroscopic study (FTIR) and Fourier transform Raman spectroscopy (FT-RAMAN). The thermal behavior and the thermal stability of the crystal were investigated by the thermogravimetric-differential thermal analysis (TG-DTA). Vickers micro hardness test was carried out to determine the mechanical stability and the hardness parameters of the crystals such as stiffness constant (C11), yield strength (σy), hardness number (Hv) and work hardening coefficient (n). The luminescence activity of the grown crystal was determined by the photoluminescence (PL) spectroscopy. The dielectric properties of the LPGC crystal were analyzed at various temperature and frequency. The presence of active chemical compounds in LPGC crystal was confirmed by energy dispersive analysis (EDAX). The Z-scan analysis of the grown crystal determines the Q-switching behavior of the grown LPGC crystal.

An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman spectroscopy

Raman spectroscopy, with its advantages of non-contact nature, rapid detection, and minimum water interference, is promising for non-invasive blood detection or diagnosis in clinic applications. However, there is a critical issue that how to accurately analyze blood composition by Raman spectroscopy. In this study, we apply extreme learning machine (ELM) algorithm and a multivariate calibration regression model to analyze the results from Raman spectroscopy and determine the component’s concentrations in blood samples, including glucose, cholesterol, and triglyceride. Self-adaption differential evolution artificial bee colony (SADEABC) algorithm was further applied to increase the data’s accuracy and robustness. The obtained data for coefficient of determination, root mean square error of calibration, root mean square error of prediction, and relative percent deviation, were 0.9822, 0.3993, 0.3827, and 6.6679 for glucose, 0.9786, 0.2104, 0.2088 and 5.9533 for cholesterol, and 0.9921, 0.2744, 0.3433 and 10.5075 for triglyceride, respectively. Results demonstrated that the model based on SADEABC-ELM show much better prediction data than those models based on the ELM and ABC-ELM.