Spectroscopy Research Articles

Flakes and Nanoparticles from Waste Ru-Plated Fashion Items through Food Waste by-Products.

Ruthenium is relevant for a broad range of applications, including catalysis and electronics. Like other metals of the platinum group, ruthenium stands out as one of the rarest elements in the Earth's crust. The demand for Ru from the industry is putting pressure on its availability. Hence, its recovery from secondary sources is imperative. Fashion solid residues of the plating industry are an important waste stream for Ru. Within this context, we propose a novel approach to Ru recovery for its safe, sustainable, and economically affordable upcycling. The approach is based on peeling from waste metal wires by a green oxidizing agent, H2O2, in an environment acidic by lactic acid, a by-product of the food industry. Peeled flakes were characterized by scanning electron microscopy, energy dispersive spectroscopy, X-ray photoelectron spectroscopy, and atomic force microscopy for their structure and (surface) chemical composition and bonding. Inductively Coupled Plasma Optical Emission Spectroscopy shows the ultra-low concentration of noble metals in the leachate, thereby suggesting their quantitative recovery in their metallic state. Further, we observed the colloidal nature of the washing water of the peeled flakes. Therefore, we hypothesized the presence of nanoparticles in the washing water and went for their characterization.

First-principles molecular dynamics of exciton-driven initial stage of plasma phase transition in warm dense molecular nitrogen.

Understanding the properties of molecular nitrogen N2 at extreme conditions is the fundamental problem for atomistic theory and the important benchmark for the capabilities of first-principles molecular dynamics (FPMD) methods. In this work, we focus on the connection between the dynamics of ions and electronic excitations in warm dense N2. The restricted open-shell Kohn-Sham method gives us the possibility to reach relevant time and length scales for FPMD modeling of an isolated exciton dynamics in warm dense N2. Wannier localization sheds light on the corresponding mechanisms of covalent bond network rearrangements that stand behind polymerization kinetics. FPMD results suggest a concept of energy transfer from the thermal energy of ions into the internal energy of polymeric structures that form in warm dense N2 at extreme conditions. Our findings agree with the thermobaric conditions for the onset of absorption in the optical spectroscopy study of Jiang et al. [Nat. Commun. 9, 2624 (2018)].

Ground-Based MAX-DOAS Observations for Spatiotemporal Distribution and Transport of Atmospheric Water Vapor in Beijing

Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m2/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics.

Oxidative Dissolution and the Aggregation of Silver Nanoparticles in Drinking and Natural Waters: The Influence of the Medium on the Process Development.

Currently, there are quite a few data on the ways silver nanoparticles get into the aquatic environment, on their subsequent dissolution in water, and on the release of toxic Ag+ ions. Differences in the experimental conditions hinder the determination of the basic regularities of this process. In this study, the stages of oxidative dissolution of AgNPs were studied, starting from the formation of silver hydrosol in deaerated solution, the reaction of silver with oxygen and with drinking and natural waters, the analysis of intermediate species of the oxidized colloidal particles, and the subsequent particle aggregation and precipitation, by optical spectroscopy, DLS, TEM, STEM, and EDX. In the presence of oxygen, silver nanoparticles undergo oxidative dissolution, which gives Ag+ ions and results in the subsequent aggregation of nanoparticles. The carbonate hydrosol loses stability when mixed with waters of various origin. This is due to the destruction of the electric double layer, which is caused by an increase in the solution's ionic strength and the neutralization of the charge of the metal core. The environmental hazard of the silver nanoparticle hydrosol would noticeably change and/or decrease when the nanoparticles get into natural waters because of their fast precipitation and because the major part of released Ag+ ions form poorly soluble salts with ions present in water.

Green-Dyeing Processes of Plant and Animal Fibers Using Folium, an Ancient Natural Dye

In recent decades, fabric-dyeing processes involved greener processes because, since ancient times, dyers used mordants based on metals to make the color better adhere to the textile fibers, but this is the reason for their increased pollution. To develop new strategies, attention was focused on finding the best condition for a dyeing method for natural fibers of vegetable and animal origin (cotton and wool) using an ancient natural dye known as folium. Folium was used mostly in miniature painting in an attempt to avoid the use of classical mordants and solvents. To this purpose, plasma treatment and chitosan coating were employed. Firstly, the textile fibers were analyzed through infrared spectroscopies to verify surface modifications; subsequently, the post-treatment morphological variations were observed via scanning electron microscopy. Both techniques highlighted a significant variation of the surface functional groups due to plasma treatments with He-O2 mixtures, which allowed a greater adhesion of chitosan on the fiber’s surface. Finally, the color strength of samples dyed with folium was tested through fiber optic reflectance spectroscopy, and the folium absorbance peaks were still detected after fabric washing. It is thus shown how an ancient, traditional raw matter has become relevant for developing new modern technologies.

Evolution from a guided-streamer mode to a continuous-discharge mode in an atmospheric pressure argon plasma jet

Atmospheric pressure plasma jet (APPJ) has attracted much attention due to its versatile applications in various fields, which normally operates in either a guided-streamer mode or a continuous-discharge mode. In this paper, temporal evolution is observed from the guided-streamer mode to the continuous-discharge one in an argon APPJ excited by a sinusoidal voltage. Waveforms of voltage and current indicate that the voltage applied to the electrode is distorted severely from the ideal sine. For the guided-streamer mode, there is only one discharge pulse per half voltage cycle. For the mode transition or the continuous-discharge mode, there is only one discharge composed of a pulse and a hump per half voltage cycle. Fast photography implemented for the mode transition reveals that both the discharges in the positive and the negative voltage polarities evolve from the guided-streamer mode to the continuous-discharge one. In the guided-streamer mode of the mode transition, the discharge behaves as a positive streamer in the positive voltage polarity, while a negative streamer in the negative voltage polarity. In addition, the mode transition only occurs in a range of dissipated power and gap width. Based on optical emission spectroscopy, temporal evolutions of the mode transition are investigated for excited electron temperature, electron density, and field strength. Moreover, their spatial distributions along the argon stream are studied at different time instants. These results are of great importance for the discharge dynamics of APPJ.

Multiwavelength Surface-Enhanced Raman Scattering Fingerprints of Human Urine for Cancer Diagnosis.

Label-free surface-enhanced Raman spectroscopy (SERS) is capable of capturing rich compositional information from complex biosamples by providing vibrational spectra that are crucial for biosample identification. However, increasing complexity and subtle variations in biological media can diminish the discrimination accuracy of traditional SERS excited by a single laser wavelength. Herein, we introduce a multiwavelength SERS approach combined with machine learning (ML)-based classification to improve the discrimination accuracy of human urine specimens for bladder cancer (BCa) diagnosis. This strategy leverages the excitation-wavelength-dependent SERS spectral profiles of complex matrices, which are mainly attributed to wavelength-related vibrational changes in individual analytes and differences in the variation ratios of SERS intensity across different wavelengths among various analytes. By capturing SERS fingerprints under multiple excitation wavelengths, we can acquire more comprehensive and unique chemical information on complex samples. Further experimental examinations with clinical urine specimens, supported by ML algorithms, demonstrate the effectiveness of this multiwavelength strategy and improve the diagnostic accuracy of BCa and staging of its invasion with SERS spectra from increasing numbers of wavelengths. The multiwavelength SERS holds promise as a convenient, cost-effective, and broadly applicable technique for the precise identification of complex matrices and diagnosis of diseases based on body fluids.

Urine-based SERS and multivariate statistical analysis for identification of non-muscle-invasive bladder cancer and muscle-invasive bladder cancer.

Bladder cancer (BC) is an epidemiological urologic malignancy that continues to increase each year. Early diagnosis and prognosis monitoring is always significant in clinical practice, especially in distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC), due to the various depths of tumor invasion related to different therapeutic schedules and recurrence rates. Common diagnostic approaches are too invasive or generally inefficient in accuracy and specificity. In this work, a totally non-invasive and cost-effective method is established by investigating urine samples using surface-enhanced Raman spectroscopy (SERS) and multivariate statistical analysis. The comparison of urine SERS spectra shows the intensities of characteristic peaks for DNA/RNA, hypoxanthine, albumin, D-( +)-galactosamine, fatty acids, and some amino acids are distinguishable in BC occurrence and invasion progression. A PLS-LDA-based two-step binary classification scheme is performed on urine SERS spectra and the diagnostic accuracies were 97.7% and 96.3% for healthy individuals versus BC patients and NMIBC versus MIBC patients, respectively. Moreover, the impact of urine SERS spectral lengths in reaching high-precision recognition of BC is investigated. The results show that the Raman peaks at 803, 893, 1139, 1375, and 1466cm-1 play an essential role in correctly categorizing healthy control, NMIBC, and MIBC patients, and SERS spectra ranges from 400 to 1600cm-1 are enough for this identification task. These findings provide a sensitive, label-free, rapid, and totally non-invasive way for assessment of invasion depth of BC to its early diagnosis and prognosis monitoring, as well as valuable insights for selecting reasonable spectral range to enhance the measurement efficiency especially in large-scale sample datasets.

Dispersion and self-assembly of 2,5-dimercapto-1,3,4-thiadiazole (DMTD) functionalized silver QDs in 6 CHBT liquid crystal

ABSTRACT Silver nanoparticles were synthesised using silver nitrate and tri-sodium citrate and were functionalized with 2,5-Dimercapto-1,3,4-thiadiazole (DMTD) linking molecules. Functionalized silver nanoparticles dispersed within 4-(trans-4-n hexylcyclohexyl) isothiocyanatobenzoate (6CHBT) liquid crystal (LC) matrices have attracted significant attention because of their potential for tailoring tuneable surface plasmonic, optical, and electronic properties by controlling the self-assembly of silver dots. The unique combination of functionalized nanoparticles and 6CHBT LCs offers a versatile platform for manipulating interactions at the nanoscale. The dispersion of functionalized Ag nanoparticles within the LCs appears to substantially modify the plasmonic and opto-electronic properties of the Ag QDs. The formation and morphology of the self-assembled structures of silver nanoparticles were confirmed by Optical and Scanning Electron Microscopy. Optical microscopy (OM) and Scanning Electron Microscopy (SEM) images of Ag-doped 6CHBT confirmed the formation of nano-micro spheres, as well as ring and rod-like structures in LC media. We have used High-Resolution X-ray diffraction (HR-XRD), Fourier-Transform Infrared Spectroscopy (FTIR), Surface-Enhanced Raman Spectroscopy (SERS), Optical Microscopy (OM), Scanning Electron Microscopy (SEM), Ultraviolet-visible-near-infrared Spectroscopy (UV-Vis-NIR), and Fluorescence (FL) Spectroscopy. We calculated the electronic properties such as the bandgap of the synthesised Ag QDs and functionalized Ag QDs using UV-Vis-NIR and Tauc’s plot curves. Surface-enhanced Raman spectroscopy, Optical microscopy, SEM, and UV-Vis-NIR spectral data were used to correlate the properties of the LC and QDs hybrid systems.

A new homologous series of semi-conducting liquid crystals based on phenyl-anthracene: synthesis and effect of the alkyloxy terminal chain on charge transport and photoconductive properties.

π-Conjugated systems are the key to the charge transport properties of organic semiconductors. Four multifunctional mesogenic materials were designed and synthesised from 2-amino anthracene and para-hydroxybenzaldehyde. Each material contains a central, rigid phenyl-anthracene core and one flexible alkyloxy chain with different lengths based on the concept of combining liquid crystal (LC) materials featuring facile processability, highly ordered alignment, and effective charge transport. (E)-N-(Anthracen-2-yl)-1-(4-(alkyloxy)phenyl) methanimine (n-OPIA) with n = 8, 10, 12, and 16 was chemically characterized by nuclear magnetic resonance spectroscopy and high-resolution mass spectrometry. Their thermal behaviours were performed by means of differential scanning calorimetry and polarised optical microscopy and showed differences in mesomorphic behaviours with respect to the alkyloxy chain length. Concerning their frontier molecular energy levels, they were studied by optical spectroscopy and cyclic voltammetry and compared to values obtained via ab initio density-functional theory (DFT) calculations. LC field-effect transistors (LC-FETs) using a solvent vapour enhanced drop casting based n-OPIA material showed efficient electrical parameters and interesting photoconductive properties, indicating their potential applications in multifunctional integrated devices. As the alkyloxy chain length of the n-OPIA compounds increased, the hole mobility, on/off current ratio, and responsivity decreased. The 8-OPIA homologue exhibits a mobility one order of magnitude larger than the previously studied homologue, namely 10-OPIA.

Mixed-valence Sm-doped LaF3 crystals as ion-electron conductors: Crystal growth and impedance characterization

The single crystals with the composition La1−y(Sm3+1−xSm2+x)yF3−xyLa1−ySm1−x3+Smx2+yF3−xy(y = 0.04) were grown from melt by the vertical Bridgman technique. A part of the Sm3+ doping ions in LaF3 matrix is reduced to the Sm2+oxidation state due to interaction with carbon during the growth process. The crystals were studied by X-ray diffraction analysis, optical and impedance spectroscopy. The Sm-doped crystals LaF3 are single-phase, retaining the tysonite-type structure (sp. gr. P-3c1P3̄c1) and demonstrate a bipolar electrical conductivity mechanism. Both the ionic conductivity σi = 4.7 × 10−5 S/cm caused by heterovalent substitutions of La3+ for Sm2+ and the comparable electronic conductivity σe = 3 × 10−5 S/cm due to the variable oxidation states Sm2+/Sm3+ ions were detected for the grown crystals. The discovered mixed ionic-electronic conductivity of La0.96Sm3+0.004Sm2+0.036F2.964 crystals opens up a new direction for the practical application of the tysonite-type fluorides as a component of electrode materials for fluorine-ion current sources.

Applying Machine Learning and SERS for Precise Typing of DNA Secondary Structures.

Surface-enhanced Raman spectroscopy (SERS) has been demonstrated as an effective method for elucidating secondary structural characteristics of DNA. However, the inherent complexity of the DNA conformation and the lack of SERS samples pose challenges for identifying numerous secondary structures. To address these issues, a synergistic method integrating machine learning with SERS was proposed so as to analyze the SERS spectra of 54 well-defined conformational oligonucleotides, namely, G-quadruplex (G4), i-motif (iM), double-strand (DS), and single-strand (SS) configurations. Principal component analysis (PCA) effectively segregated the oligonucleotides into three distinct conformational groups (G4s, iMs, and others). Furthermore, linear discriminant analysis (LDA), K-nearest neighbor (KNN), and support vector machine (SVM) approaches were utilized to improve the typing accuracy of 54 trained sequences. This enabled the correct classification of the structures of five untrained sequences, as well as the identification of the predominant conformations including G4, iM, and DS formed by two complementary G-rich and C-rich sequences in acidic and neutral pH conditions. The results of this study demonstrated the potential of the proposed methodology for rapid screening and prediction of secondary DNA conformations.

Energy–dependent femtosecond LIPSS on germanium and application in explosives sensing

Abstract In this study, we fabricated laser-induced periodic surface structures (LIPSS) on a germanium surface through laser ablation in air using axicon and femtosecond (fs) pulses. This novel approach permitted the nanoscale material processing outcome refinement via an fs Bessel beam. Our investigations aimed at systematically understanding the formation of periodic structures under various experimental conditions, such as (i) different pulse energies ranging from 50 µJ to 1000 µJ at a constant scan speed and (ii) constant energy with different scan speeds (0.1–3 mm s−1). By adjusting the fluences and scan speeds, we were able to identify the parametric space and alter the periodicity of the low-spatial frequency LIPSS and high-spatial frequency LIPSS on germanium, which were analyzed using field emission scanning electron microscopy. An optimal LIPSS formation over a large area of germanium was achieved at an input energy of 250 µJ and a scan speed of 0.75 mm s−1. Additionally, we measured the contact angles of the Ge nanostructures (GeNSs) to demonstrate their hydrophobic nature and non-wetting properties, providing insights into the behavior of LIPSS. Subsequently, the GeNSs were coated with a ∼15 nm thick gold (Au) film using a thermal deposition method. Utilizing these, the surface-enhanced Raman spectroscopy (SERS) technique detected diverse analytes, such as tetryl (an explosive) at a concentration of 50 µM and thiram (a pesticide) at 500 nM. The SERS enhancement factors for tetryl and thiram molecules on GeNSs coated with a 15 nm-thick Au layer were determined to be 2.5 × 104 and 4.2 × 105, respectively.

SERS-Driven Ceftriaxone Detection in Blood Plasma: A Protein Precipitation Approach

Accurate detection of antibiotics in biological samples is essential for clinical diagnoses and therapeutic drug monitoring. This research examines how proteins and other substances in blood plasma affect the detection of the antibiotic ceftriaxone using surface-enhanced Raman spectroscopy (SERS). We detected ceftriaxone spiked in blood plasma without sample preparation within the range of 1 mg/mL to 50 µg/mL. By employing a pretreatment approach involving methanol-based protein precipitation to eliminate interfering substances from a spiked blood plasma solution, we could detect ceftriaxone down to 20 µg/mL. The comparative analysis demonstrates that the protein precipitation step enhances the sensitivity of SERS-based detection of drugs in the matrix blood plasma. The insights derived from this study are highly beneficial and can prove advantageous in developing new antibiotic detection methods that are both sensitive and selective in complex biological matrices. These methods can have important implications for clinical treatments.

Rapid detection of drugs in blood using “molecular hook” surface-enhanced Raman spectroscopy and artificial intelligence technology for clinical applications

Accurate detection of cardiovascular drugs in blood is complicated by interference from serum biomolecules. This study introduces a novel surface-enhanced Raman spectroscopy (SERS) platform incorporating “molecular hooks” to capture small drug molecules while excluding larger biomolecules selectively. The self-assembled nanoparticles with the A13 molecule enhance Raman signals by creating dense electromagnetic “hotspot” regions, achieving detection limits of 10 pg/mL for dobutamine hydrochloride and 10 ng/mL for milrinone-substantially below therapeutic thresholds. Artificial intelligence (AI) integration enables automated spectral analysis, allowing rapid and precise drug detection in clinical blood samples. This approach offers a transformative solution for real-time diagnostics, significantly advancing personalized treatment strategies in clinical settings.

Spectroscopic analysis of single and multiphase electrical discharge for clean energy conversion

Abstract In this study, we examined non-thermal atmospheric pressure plasma processes operating under varying conditions using different liquid and gaseous hydrocarbon materials. The light emission from the discharges were analyzed through optical emission spectroscopy to comprehend the products generated in different parameter space. The gaseous products from each of these analyses were also collected and analyzed through gas chromatography. Analysis of the optical emission from the discharge and concentration of the gaseous products show a linear trend between emission intensity ratio Hα/C2 and gas concentration ratio H2/C2Hx. Gas temperature and electronic excitation temperature of different experimental conditions were also compared and indicates that spark discharge relates to higher electronic excitation temperature compared to glow discharge of similar medium. Higher electronic excitation temperature leads to generation of different products from spark discharge compared to glow discharge. Glow discharge generates more of the intermediate products. Whereas spark discharge, because of its higher electronic excitation temperature, leads to higher rate of dissociation and therefore generates more of the dissociated products. Glow discharge, for example generates more of OH and H from the moisture present in the carrier gas as impurity, whereas spark discharge would generate more of Hα and O particles further breaking down the OH bonds. Finally, UV-Vis analysis was performed on the liquid products of the discharge and reveals that the photo-centers and the newly generated soot nano particles absorb the UV range lights and some of the visible range light emission mostly up to ~600nm.

Insights into Tetravalent Np Speciation in HNO3 through Spectroelectrochemistry and Multivariate Analysis.

In situ optical spectroscopy, spectropotentiometry, and multivariate analysis were applied to the Np(IV) nitrate system to better understand speciation and quantify HNO3 concentration. Thin-layer spectropotentiometry, or spectroelectrochemistry, was leveraged to isolate and stabilize Np(IV) without compromising the solution conditions and generate representative Vis-NIR absorption spectra from 0.5 to 10 M HNO3 and benchmark the corresponding Np(IV) molar absorptivity coefficients. Spectra were described with principal component analysis (PCA) to identify the purest Np(IV) absorbance spectra among other oxidation states [e.g., Np(V/VI)] at each acid concentration and then to identify the primary sources of variance within each Np(IV) spectrum with respect to Np(IV) nitrate complexes. Then, partial least-squares regression (PLSR) and support vector regression (SVR) models were built to predict HNO3 concentration from the Np(IV) spectral data. The nonlinear SVR model outperformed the linear PLSR model for the HNO3 concentration predictions. Finally, the inclusion of spectra collected in edge and center point HNO3 concentrations in the calibration set was determined to be crucial for producing models with strong predictive capabilities. The multivariate approach used in this study makes it possible to quantify HNO3 concentration solely based on Np(IV) absorption spectra, which is essential to quantifying processing streams in various online monitoring applications.

Multiplexed SERS Detection of Serum Cardiac Markers Using Plasmonic Metasurfaces.

Surface-enhanced Raman spectroscopy (SERS) possesses exquisite molecular-specific properties with single-molecule sensitivity. Yet, translation of SERS into a quantitative analysis technique remains elusive owing to considerable fluctuation of the SERS intensity, which can be ascribed to the SERS uncertainty principle, a tradeoff between "reproducibility" and "enhancement". To provide a potential solution, herein, an integrated multiplexed SERS biosensing strategy is proposed, which features two distinct advantages. First, a subwavelength-structured plasmonic metasurface consisting of alternately stacked metal-dielectric pyramidal meta-atoms is fabricated and could provide simultaneously enhanced electric and magnetic fields to enable spatially extended and weakly wavelength-dependent SERS. Second, nanomechanical perturbations are harnessed to transduce signals in the form of SERS frequency shifts, which are not directly affected by the SERS uncertainty principle. By also employing 3D printing methods, a proof-of-concept study of multiplexed detection of a panel of serum cardiac biomarkers for acute myocardial infarction is provided. Success in the development of both the electric and magnetic fields-active plasmonic metasurfaces could transform future designs of SERS substrates with newly endowed functionalities, and frequency shift-based SERS multiplexing could open new opportunities to develop innovative quantitative optical techniques for applications in chemistry, biology, and medicine.

Interpretable Machine Learning-Aided Optical Deciphering of Serum Exosomes for Early Detection, Staging, and Subtyping of Lung Cancer.

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, underscoring an urgent need for strategies that enable early detection and phenotypic classification. Here, we conducted a label-free surface-enhanced Raman spectroscopic (SERS) analysis of serum exosomes from 643 participants to elucidate the biochemical deregulation associated with LC progression and the unique phenotypes of different LC subtypes. Iodide-modified silver nanofilms were prepared to rapidly acquire SERS spectra with a high signal-to-noise ratio using 0.5 μL of patient exosomes. We performed interpretable and automated machine learning (ML) analysis of differential SERS features of serum exosomes to build LC diagnostic models, which achieved accuracies of 100% and 81% for stage I lung adenocarcinoma and its preneoplasia, respectively. In addition, the ML-derived exosomal SERS models effectively recognized different LC subtypes and disease stages to guide precision treatment. Our findings demonstrate that spectral fingerprinting of circulating exosomes holds promise for decoding the clinical status of LC, thus aiding in improving the clinical management of patients.

AN EX-VIVO SPECTRAL AND LIFETIME-DECAY ANALYSIS OF 5-ALA DERIVED PPIX flUORESCENCE: OBJECTIVE flUORESCENCE MAPPING IN GLIOMA SURGERY

Abstract AIMS 5ALA/Protoporphyrin IX (PpIX) fluorescence guided surgery (FGS) in high-grade glioma has been shown to increase resection and survival, despite this benefits are limited in low-grade glioma by low emission and subjective interpretation. Quantitative fluorescence could address these issues, however is challenging due to photobleaching and variations in tissue induced distortion and PpIX photochemical state that are poorly understood. Lifetime-decay measures intrinsic fluorophore properties and is not influenced by these factors, but is difficult to measure intra-operatively. We used paired optical and fluorescence spectroscopy with lifetime decay mapping to characterise PpIX emission within the glioma tissue microenvironment. METHOD Biopsies were collected from 20 patients undergoing glioma FGS, along with 4 controls from partial temporal lobectomies. Paired measurements of emission and lifetime were matched with optical property readings. Lifetime and emission ratios at 635 and 620nm were calculated (PpIX635/620), corresponding to the primary emission peak for the photochemical states of PpIX in tissue. Raw and optically corrected emission was correlated with lifetime decay. RESULTS 205 specimens were analysed by WHO grade (56 Grade4, 66 Grade3, 37 Grade2, 20 control). PpIX635/620 emission was 0.93 in control (CI 0.91-0.95), 1.03 in grade 2 tumours (CI 0.95-1.26), 1.56 in grade 3 (CI 1.22-1.91) and 6.99 (CI 5.78-8.20) in grade 4. PpIX635/620 lifetime correlated with emission (R2 =0.98, range 0.94-1.57). Correlation of emission with lifetime readings improved significantly following optical correction at 635nm (raw R2 =0.81, corrected R2 =0.90) and 620nm (raw R2 =0.44, corrected R2 =0.86). CONCLUSION PpIX620 and PpIX635 photochemical states are present in human glioma, with an increase in PpIX635/620 suggesting increased WHO grade. The ability to distinguish these forms holds the potential to provide real-time data for tumour differentiation and pathology. Accurate characterisation and correction of tissue induced distortion significantly improves the ability to detect, characterise and quantify PpIX intra-operatively.