High interfacial thermodynamic and contact stabilities are two key factors to suppress dendrite growth in solid‐state sodium metal batteries (SSSBs). However, a thermodynamical stable interface often features with sodiophobic character to aggravate interfacial contact affinity, thus making the two key factors paradox with each other. Herein, a new strategy is reported to resolve the intrinsic contradictions between high sodiophobicity and interfacial contacts with a “kinetic‐driven alloy sinking” process. Specifically, the sodiophilic and electronic conductive alloy (e.g., KNa 2 ) is spontaneously “sunk” into bulk Na metal, thus remaining a sodiophobic/ionic conductive but intimately contacted interface (e.g., NaF). Unlike conventional concept of sodiophilic interface, this work demonstrates the advantage of sodiophobic modification with an in situ formed ionic conductive interphase, which establishes a foundational distinction from prior literatures. Consequently, an ultrahigh time‐constant mode critical current density (CCD) of 4.0 mA cm −2 is achieved, surpassing the state‐of‐the‐art values in existing literature. The fundamental understanding on interfacial sodiophobicity and conduction types of interphases will provide new insight for designing high‐performance SSSBs.

Considering the lower acquisition value and the practicality of obtaining data using a portable instrument (NIR-Portable), it is crucial to verify whether it offers spectra with prediction quality at least equal to those on a bench (NIR-Bench), which achieve higher spectral resolution. This study aimed to compare a NIR-Bench and a NIR-Portable to build and validate multivariate calibration models to predict sucrose in chocolate products. In Experiment 1, we evaluated cocoa mixtures with different concentrations of sucrose; in Experiment 2, fructose was added to the mixture. We built prediction models from the sample spectra via PLS regression. Considering both instruments and experiments, there were equivalent performances for the sucrose prediction models (RMSEP from 0.0597 to 0.0811 and rp2 from 0.9797 to 0.9943). A linear correlation existed between actual and predicted values ​​(0.9898 < rp < 0.997). The NIR-Portable presented, on average, greater relative errors (RE) without a predominance of greater RE per sample (p-value = 0.125). In the same spectral range, the rp was greater than 0.9874. There is no predominance of larger REs for the portable NIR (p-values ​​= 0.453 and 1 – Experiments 1 and 2, respectively). In commercial chocolate products, considerable values ​​were obtained for RMSE (0.1079 and 0.1478), r2 (0.9154 and 0.9301), and r (0.9568 and 0.9644) in Experiments 1 and 2, respectively. The fitted models allowed the detection of sucrose in both experiments. Portable NIR can replace bench-top NIR with good predictive capacity in commercial chocolate products.

Combinatorial Order Pre-processing Search (COPS), a novel approach for optimizing data pre-processing is proposed in this work. Unlike simultaneous hyperparameter optimization, COPS employs a priori optimization to reduce computational time while refining the search space for preprocessing sequences and combinations. It allows for setting a maximum number of pre-processing methods, while efficiently searching through combinations of methods with chemically relevant knowledge. In this work, 67 calibration datasets across various analytical techniques, including fluorescence spectroscopy, gas chromatography (GC), near-infrared spectroscopy (NIR), mid-infrared spectroscopy (MIR), visible-near-infrared spectroscopy (Vis-NIR), Raman spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and voltammetry were evaluated. COPS yielded significant improvements over existing methodologies based on design of experiment and compounded pre-processing approaches. The COPS outperformed the other methods, resulting in an average root mean square error of prediction (RMSEP) reduction of 31.7%, while also reduced the complexity (number of latent variables) of the model which allows for easier interpretation. This underscores the importance of combinatorial order set theory for the search of pre-processing method combinations (without fixing the sequence of pre-processing methods) to enhance model performance and interpretation. The novel COPS approach can be employed in process analytical technology (such as inline, online or at-line chemical sensing analytics) to enhance predictive accuracy and operational efficiency, fundamentally transforming the quality and reliability of chemical process monitoring and control.

This study proposes a rapid and straightforward method for determining total recoverable sugars (TRS) in sugar cane juice using near-infrared spectroscopy (NIR) and partial least-squares (PLS) regression. PLS models were built using NIR spectra obtained directly from sugar cane juice as independent variables and TRS values as dependent variables. TRS was obtained via two estimations: (i) technological analysis (TRSTA), indirectly determined using CONSECANA equations, and (ii) high-performance liquid chromatography, used to quantify sucrose, glucose, and fructose to calculate TRS, defined as TRSLC. The estimated values for TRSTA and TRSLC ranged from 82.08 to 180.03 kg ton-1 and from 116.14 to 216.83 kg ton-1, respectively. A high correlation coefficient (R = 0.90) and a consistent bias of 24.75 kg ton-1 were observed between TRSTA and TRSLC. Thus, a median bias correction was proposed to improve the alignment. To enhance model performance, variable selection was applied by using the ordered predictor selection (OPS) algorithm. PLS models built with the OPS showed improved accuracy compared to models using the full spectral range. The best PLS-OPS model for TRSTA and TRSLC presented root-mean-square errors of prediction of 7.8 and 9.8 kg ton-1 and R of 0.91 and 0.86, respectively. Finally, the models were successfully applied in a practical genotype screening scenario, showing a high selection efficiency and strong agreement with HPLC-based rankings. These findings demonstrate the potential of NIR-PLS models as reliable, low-cost, and scalable alternatives for TRS prediction in sugar cane breeding and industrial decision-making.

The COVID-19 pandemic has highlighted the urgent need for rapid, accurate, and cost-effective diagnostic alternatives to conventional methods such as RT-qPCR and immunoassays. In this study, we explored the potential of vibrational spectroscopy, specifically near-infrared (NIR) and mid-infrared (MID) spectroscopy, for detecting SARS-CoV-2 infection in dried plasma samples. Spectral data were obtained from 83 patients (45 COVID-19 positive and 38 negative) and analyzed using partial least squares discriminant analysis (PLS-DA), with and without variable selection by the ordered predictors selection for discriminant analysis (OPSDA) method. While initial models using full spectra showed moderate classification accuracy, the application of OPSDA significantly enhanced model performance. For the NIR dataset, OPSDA-based models achieved 100% sensitivity and specificity in both training and test sets (n = 25). For the MID dataset, the test set (n = 25) sensitivity reached 86%, with 100% specificity. These results demonstrate that NIR and MID spectroscopy, when combined with advanced chemometric approaches, can provide reliable, rapid, and low-cost screening for COVID-19. This platform holds promise for broader applications in clinical diagnostics beyond the current pandemic.

This work aims to comprehensively study the optimal conditions for hydrothermal pretreatment, which selectively solubilizes hemicellulose without using chemicals for sugarcane bagasse (SCB), sugarcane straw (SCS), and energy cane (EC). Raw SCB, SCS, and EC were submitted to hydrothermal pretreatments at temperatures and time ranging from 180 to 300 oC and 0 to 180 min. Glucose, xylose, arabinose, furfural, hydroxymethyl furfural, and acids were analyzed in collected liquor. The solid materials, i.e., biomass and cellulignin, were characterized using X-ray diffraction, mid-infrared, thermogravimetric analysis, and scanning electron microscopy. The characterizations were helpful in identifying changes in solid materials in the different pretreatments. Best pentose and furfural yields were obtained from SCB pretreatment, reaching respectively 98.8 g kg− 1 and 30.6 g kg− 1 at 90 min and 180 ºC. SCS reached at 170 ºC and 165 min, 60.7 g kg− 1 and 24.7 g kg− 1 of pentoses and furfural, respectively. EC provided 50.6 and 28.5 g kg− 1 of pentose and furfural, respectively, at 180 ºC and 90 min. However, it was not possible to achieve higher pentose yields in shorter times, which requires further study with the addition of catalysts to improve pentoses’ conversion rate to furfural.

This review presents the development stages of Ni-based cathode materials for second-generation lithium-ion batteries (LIBs). Due to their high volumetric and gravimetric capacity and high nominal voltage, nickel-based cathodes have many applications, from portable devices to electric vehicles. A discussion of the most commonly used methods for cathode synthesis and the standard and advanced characterizations of synthesized materials is presented. The methods for preparing LIBs for electrochemical characterizations for obtaining electricity are also analyzed. The progress of synthesis methods is highlighted, connecting them to the mitigation strategies to overcome the failure mechanisms in Ni-rich cathodes. This review summarizes the state-of-the-art of Ni-based cathode for LIBs through high-impact scientific references.

Near-infrared (NIR) spectroscopy and hyperspectral imaging allow the study of spectral and spatial distribution of multiple chemical components in large sample areas. This technique is fast, non-destructive, contactless, and does not require sample preparation. The NIR spectrum of each sample pixel is acquired, resulting in a data cube that contains two spatial dimensions (x and y) and one spectral dimension (z), providing the spectral profiles of every part of the sample. This technique, for example, can provide significant information about the distribution of additives into polymer matrices with potential to be used as a tool for real-time quality control. Herein, the stepwise application of this method is demonstrated for determination of spatial and spectral distributions of film components, showcasing the plasticization of a biodegradable packaging.

O3-type layered oxides are highly promising cathodes for sodium-ion batteries (SIBs), however they undergo complex phase transitions and exhibit high sensibility to air, leading to subpar cycling performance and commercial viability. In this work, we report a layered cathode material (NaNi 0.29 Cu 0.1 Mg 0.05 Li 0.05 Mn 0.2 Ti 0.2 Sn 0.11 O 2 ) with a sate-of-the-art high-entropy compositional design. We unveil that such a configuration featuring inhomogeneous coordination environment of transition metal (TM) elements, can enable enhanced gliding energy (−0.38 vs −0.58 eV) of TMO 2 slabs upon desodiation both theoretically and experimentally, which underlies the fundamental origin of the outstanding structural stability of HEO materials. As a consequence, the complex phase transitions (O3−O′3−P3−P′3−P3′−O3′) of conventional O3-type cathode have been eliminated, and the as-obtained material demonstrates exceptional structural robustness and integrity with an ultra-long cycle life in a quasi-solid-state cell (maintaining 73.2 % capacity after 1000 cycles at 2 C). Moreover, the material presents satisfactory air stability, with minimal structural and electrochemical degradation when directly exposed to the air. An Ah-scale pouch cell based on the cathode material is constructed, demonstrating a capacity retention of 83.6 % after 500 cycles, signaling substantial promise for commercial applications.

Ni-based layered oxide materials are among the most promising cathode materials for the next generation of lithium-ion batteries due to their higher energy capacity. However, capacity decay occurs due to degradation mechanisms that reduce the electrochemical performance of this type of material. This work aims to synthesize Nb-doped LiNi0.55Mn0.25Co0.20O2 (Nb-NCM) materials via the solvothermal method to enhance the cyclability and energy density of the layered oxide cathode. The effects of Nb doping on the microstructure and the electrochemical performance of the cathodes are investigated. The introduction of the contents of Nb expands the structural lattice parameters and decreases the Li+/Ni2+ cation mixing degree of the NCM cathode. Furthermore, the Nb doping enhances the electrochemical activity of LiNi0.55Mn0.25Co0.20O2, increasing its initial discharge capacity to 169.61 mAhg- 1 when 1% of Nb was used as a dopant (1%Nb-NCM) in contrast to the capacity of 149.45 mAhg-1 presented by the pristine material. The modified 1.0%Nb-NCM material also exhibits remarkable cycling performance with a capacity retention of 92.7% after 100 cycles at the rate of 1 C (2.8-4.3 V). This work suggests a rational strategy for high-performance cathode for lithium-ion batteries, proposing the extension of Nb doping to enhance Ni-mid material's cyclability.

Pretreatment of bagasse, straw, and energy sugarcane using niobium phosphate catalyst. Adviser: Reinaldo Francisco Teófilo. The optimization of hydrothermal pretreatment (HTP) of sugarcane bagasse (SCB), sugarcane straw (SCS), and energy cane (E.C.) using niobium phosphate (NbP) catalyst is the aim of this work. The biomasses were characterized by chemical composition, moisture, and granulometry. The experiments were designed following a face-centered composite design (FCCD), using, as independent variables, temperature (140-180 °C), NbP catalyst load (1-100 %), and time. Dur- ing HTP, aliquots were taken each 15 minutes and analyzed until they reached 135 minutes. After HTP, the amounts of xylose, arabinose, and furfural (HMF) were determined in the liquor using high-performance liquid chromatography (HPLC). The use of NbP as a catalyst proved to be very effective in the hemicellulose solubilization and the pentoses conversion in furfural. The maximum xylose productivity and best level for temperature and catalyst load were for SCB, SCS, and E.C., respectively 115 g/kg (180 °C and 1%), 71 g/kg (160 °C and 50.5 %), and 61 g/kg (180 °C and 1%). The results showed that furfural production is favored in a high temperature and catalyst load. The maximum furfural productivity predicted by the models were 95 g/kg, 75 g/kg, and 65 g/kg for SCB, SCS, and E.C., respectively. Keywords: Design of experiments. Bagasse. Catalyst. Energy cane. Sugarcane biomass. Xylose. Furfural.

The COVID-19 pandemic that affected the world between 2019 and 2022 showed the need for new tools to be tested and developed to be applied in global emergencies. Although standard diagnostic tools exist, such as the reverse-transcription polymerase chain reaction (RT-PCR), these tools have shown severe limitations when mass application is required. Consequently, a pressing need remains to develop a rapid and efficient screening test to deliver reliable results. In this context, near-infrared spectroscopy (NIRS) is a fast and noninvasive vibrational technique capable of identifying the chemical composition of biofluids. This study aimed to develop a rapid NIRS testing methodology to identify individuals with COVID-19 through the spectral analysis of swabs collected from the oral cavity. Swab samples from 67 hospitalized individuals were analyzed using NIR equipment. The spectra were preprocessed, outliers were removed, and classification models were constructed using partial least-squares for discriminant analysis (PLS-DA). Two models were developed: one with all the original variables and another with a limited number of variables selected using ordered predictors selection (OPS-DA). The OPS-DA model effectively reduced the number of redundant variables, thereby improving the diagnostic metrics. The model achieved a sensitivity of 92%, a specificity of 100%, an accuracy of 95%, and an AUROC of 94% for positive samples. These preliminary results suggest that NIRS could be a potential tool for future clinical application. A fast methodology for COVID-19 detection would facilitate medical diagnoses and laboratory routines, helping to ensure appropriate treatment.

Compressing supercapacitor（SCs） electrode is essential for improving the energy storage characteristics and minimizing ions’ distance travel, faradaic reactions, and overall ohmic resistance. Studies comprising the ion dynamics in SC electrodes under compression are still rare. So, the ionic dynamics of five aqueous electrolytes in electrodes under compression were studied in this work for tracking electrochemical and structural changes under mechanical stress. A superionic state is formed when the electrode is compressed until the micropores match the dimensions with the electrolyte’s hydrated ion sizes, which increases the capacitance. If excessive compression is applied, the accessible pore regions decrease,and the capacitance drops. Hence, as the studied hydrated ions have different dimensions, the match between ion/pore sizes differs. To the LiOH and NaClO 4 electrolytes, increasing the pressure from 60 to 120 and 100 PSI raised the capacitance from 13.5 to 35.2 F g -1 and 30.9 to 39.0 F g -1 ,respectively. So,the KOH electrolyte with the lowest and LiCl with the biggest combination of hydrated ion size have their point of maximum capacitance(39.5 and 36.7F g -1 ) achieved at 140 and 80 PSI, respectively. To LiCl and KCl electrolytes, overcompression causes a drop in capacitance higher than 23%.

The reuse study of niobium phosphate catalyst (NbOPO4.nH2O, abbreviated as NbP) in furfural production from sugarcane bagasse (SCB) in an aqueous medium is the aim of this project. The heterogeneous NbP catalyst was exploited to hydrolize the SCB biopolymers and dehydrate the major released carbohydrate, i.e., xylose, into furfural. The compounds were separated and quantified by high-performance liquid chromatography (HPLC). At the end of each reaction, the catalyst was separated from the SBA by sieving and pre-treated with water (A), 5 ml of acetone (B), 10 ml of acetone (C) or calcined at 550 °C (D). After pretreatment, the catalyst was reused for another cycle. An analysis of variance was performed to compare the difference in productivity between cycles statistically. The catalyst was analyzed for its morphology by SEM images and XEDS. For the release of xylose, at a significance level of 0.01, the pretreatments A, B, and D in the reactions at 150 °C were efficient to reactivate the catalyst’s active sites. Cycles 1 and 2 produced about 15 g kg-1 xylose at 110 °C and 80 g kg-1 furfural at 150 °C. The results with pretreatment A at 150 °C are promising from an economic and environmental point of view since the other pretreatments either use a toxic, more costly solvent or consume electricity.

The aim of this work was to study dehydration as a way to improve the prediction of sucrose, glucose, and fructose in sugarcane juice using near-infrared (NIR) spectroscopy and partial least squares (PLS) regression models. The temperature, time, and sample volume involved in the dehydration process were optimized using design of experiments. Six different sample supports were assessed, being the thick couche paper the best support. NIR spectra from liquid (LSJ) and dehydrated sugarcane juice (DSJ) were obtained. Sucrose, glucose, and fructose in LSJ were analyzed using high-performance liquid chromatography with an evaporative light scattering detector (HPLCELSD). Sucrose, glucose, and fructose ranged from 99.29 to 249.27 mg/mL, 5.96-14.94 mg/mL and 3.99-16.10 mg/mL. PLS models were built using the sugars content and NIR spectra collected from a benchtop and a portable instrument. Ordered predictors selection (OPS) was applied to select the most informative variable. The results indicated better predictions for all sugars using the DSJ for both instruments, being the benchtop statistically better than the portable instrument. On the benchtop instrument, the PLS-OPS models presented root mean square error of prediction (RMSEP) respectively for sucrose, glucose, and fructose 7.98, 0.82, and 1.00 mg/mL using the DSJ against 12.75, 1.00, and 1.35 mg/mL using the LSJ. For the portable instrument, the RMSEP were respectively 15.90, 1.18, and 1.65 mg/mL using DSJ against 23.23, 1.40, and 2.08 mg/mL using LSJ. To sum up, the dehydration approach showed to be a great technique to improve the predictability of PLS-OPS models for sugarcane juice sugars using NIR spectra by removing the water and concentrating the analytes.

Optimization procedures such as experimental designs (DOE) improve pretreatment efficiency, and chemical characterization of the starting material becomes necessary to assess the efficiency. Hydrothermal pretreatment (HTP), also called auto-hydrolysis (AH), is one of the most economically interesting pretreatments since only water work as reactant. AH pretreatment optimization can reach a liquor rich in monosaccharide units at the same time that a low content of toxic compounds to biological processes (i.e., 2-furfuraldeído (FUR) e 5-hidroximetil-2-furfuraldeído (HMF). Early, AH pretreatment variables temperature (T), time (t), solid-liquid ratio (SLR) and stirring (RPM) were studied by a 24 factorial design. A new HPLC analytical method for quantifying acids that can be formed during AH (i.e., formic, acetic, glucuronic and levulinic acids) has been developed using Bio-Rad Aminex HPX-37H column in a Shimadzu Prominence HPLC. In general, the most significant factors were T and t; higher levels of T improved hemicellulose depolymerization whereas lower levels of t disfavoured pentoses degradation to FUR. At 220 ºC, 60 min, 20 % of SCB and 60 rpm it was possible to achieve a yield of 109.84 g kg-1 of pentoses (i.e., xylose and arabinose) with only 14.42 g kg-1 of FUR. Under these same conditions, the acid content in the liquor was 15.1 g kg-1, 12.2 g kg-1, 39.8 g kg-1 and 55.5 g kg-1 for glucuronic, formic, acetic and levulinic acids, respectively.

Identifying compounds present in the sugarcane epicuticular wax and using these compounds to classify the genotypes susceptible and resistant to the initial attack of sugarcane borer (Diatraea saccharalis) was the aim of this study. A greenhouse experiment was performed in a factorial scheme with and without borer infestation using genotypes previously characterized as resistant or susceptible in field-based experiments. Sugarcane whorls of six-month-old plants were collected before (BI) and after (AI) 72 h of sugarcane borer infestation. The sugarcane epicuticular wax was extracted in both times, i.e., BI and AI and its chemical composition was assessed by gas chromatography coupled to mass spectrometry (GC-MS). Twenty-five compounds were identified for both BI and AI. Classification models were built using partial least squares for discriminant analysis (PLS-DA) and linear discriminant analysis (LDA). Variable selection methods were used to improve the classification models. Ordered predictors selection for discriminant analysis (OPSDA) selected compounds that correctly classified all the test samples before borer infestation (Error = 0.000), and exhibited the most suitable classification parameters for the test set after borer infestation (Error = 0.111). The C30 pentacyclic triterpene friedelin and a high alcohol/aldehyde ratio were associated with the classification of resistant genotypes. Our findings have applicability in developing a screening methodology for breeding programs interested in identifying genotypes resistant to the initial feeding of sugarcane borer.

Lignocellulosic biomasses have some characteristics that hinder their use as fuel. Further, the biodegradation processes that can occur during storage can affect their energy properties. Torrefaction can improve their energy properties while reducing the impacts of storage. Near-infrared (NIR) spectroscopy could be a promising tool to estimate changes to biomass properties during storage. A series of waste feedstocks, including: sugarcane bagasse, coffee husk, eucalyptus, and pine were torrefied at 290 C in a screw reactor, over 5, 7.5, 10, 15, or 20 min. Then, raw and torrefied biomasses were submitted to leaching and to white and brown-rot fungi, to simulate storage conditions. The weight loss (WL) due to fungal degradation after 2, 4, 8, and 12 weeks was measured and the high heating value (HHV) of all biodegradation steps, including raw and torrefied samples after leaching, were determined. All the samples were analysed by NIR spectroscopy and chemometric models were then developed. Firstly, partial least squares for discriminant analysis (PLS-DA) models successfully classified the four different residual biomasses into raw and torrefied forms according to fungal decomposition. Secondly, partial least squares regression (PLSR) models showed potential utility in an industrial context as a standardized continuous method to predict the HHV during biomass storage steps. While, PLSR models did not present good accuracy when estimating WL resulting from fungal degradation, they can be useful for screening during decision making. Further studies are required to improve and develop more efficient models to predict the fungal degradation level of stored biomasses. For exemple, in considering the class of torrefied biomasses, the model could show better predictive capacity due to less variability in the data. These results highlight the potential of NIR spectroscopy as a simple, fast, and efficient tool to analyze the degradation process over time. Such a rapid and non-destructive characterization tool could be very useful in industry to assess biomass property changes during storage.

The analyzes of micro-, meso- and macro-porous carbon electrodes in a symmetrical supercapacitor filled with a 1.0 M TEABF(4) EC-DMC electrolyte were reported in this work. The activated carbon (AC), multi-walled carbon nanotubes, and graphite materials were studied. The results indicate AC is the best electrode material for the application with high specific capacitance and energy. The Raman operando analyzes of AC show that the D- and G- bands shift their positions and intensities. The cause of this phenomenon is the electrostatic ionic adsorption inside very narrow pores, affecting the vibrational mode and the work function of the material, resulting in the shift of the Fermi level of the material. For mesoporous carbon, this phenomenon is much less pronounced. In principle, graphite has enough specific capacitance for competitive application. However, its overall surface area is reduced. Graphite's Raman operando analyzes revealed the BF4- insertion into graphene layers. The G-band splits while the in-situ electrochemical data support a capacitance with three orders of magnitude higher than expected for a purely electrostatic adsorption process on graphite. Overall, this fundamental study evidences that in-situ electrochemistry and Raman spectroscopy combined could offer important information on the energy storage process for supercapacitors.

In this work, some physical mixtures of Nb2O5·nH2O and NbOPO4 were prepared to study the role of phosphate groups in the total acidity of samples and in two reactions involving carbohydrate biomass: hydrolysis of polyfructane and dehydration of fructose/glucose to 5-hydroxymethylfurfural (HMF). The acid and catalytic properties of the mixtures were dominated by the phosphate group enrichment. Lewis and Brønsted acid sites were detected by FT-IR experiments with pyridine adsorption/desorption under dry and wet conditions. Lewis acidity decreased with NbP in the composition, while total acidity of the samples, measured by titrations with phenylethylamine in cyclohexane (~3.5 μeq m−2) and water (~2.7 μeq m−2), maintained almost the same values. Inulin conversion took advantage of the presence of surfaces rich in Brønsted sites, and NbOPO4 showed the best hydrolysis activity with glucose/fructose formation. The catalyst with a more phosphated surface showed less deactivation during the dehydration of fructose/glucose into HMF.