The Optical Approaches to Monitor Biomass Ethanol Productions with Optical Microscopic Methods

Abstract

Oil and natural gas continue to dominate global energy consumption, though a supply gap of 2 million barrels per day (b/d) was reported in the fourth quarter of 2023. Despite a projected increase in global oil supply by 1.2 million b/d in 2023, reaching 101.1 million b/d compared to 2022, reliance on fossil fuels poses challenges for energy security and sustainability. For China, transitioning to clean and renewable energy sources is essential. Biofuel ethanol, with its high octane rating and anti-knock properties, is a promising alternative. This bioenergy sector is expanding globally, with cellulosic ethanol production emerging as a key objective. However, the high production cost of cellulosic ethanol presents a significant challenge to its large-scale adoption. To overcome this barrier, various techniques are being explored to reduce production costs. Among them, advanced characterization methods are used to monitor changes in cellulose, lignin, and hemicellulose during ethanol production in situ, quickly and without surface labeling. These methods provide insights into the factors driving high production costs, enabling targeted improvements. This review focuses on the potential of these characterization techniques to optimize ethanol production processes and improve efficiency. The findings may offer a strategic direction for scaling up cellulosic ethanol production and contribute to the sustainability of energy resources by reducing dependency on fossil fuels.

1. Introduction

Cellulosic ethanol is a type of biofuel that is derived from organic matter containing cellulose [1,2]. It is produced by converting biomass into raw materials that can be fermented into bioethanol. Several companies, such as Iogen, POET, DuPont, and Abengoa, are constructing refineries that can handle this process. Cellulosic ethanol has the advantage of using non-food crops, such as straw and agricultural residues, as feedstocks. It can also reduce greenhouse gas emissions and oil dependence. However, the main challenge for cellulosic ethanol is the high cost of collecting, processing, pretreating, and enzymatically hydrolyzing the biomass [3,4].

To produce fuel ethanol from straw efficiently and cost-effectively, it is essential to understand the production process, which involves the following steps: pretreatment [5,6], which removes and degrades lignin and hemicellulose molecules in straw by chemical or thermal treatment [3]; hydrolysis, which breaks down cellulose into glucose using enzymes; and fermentation, which converts glucose into ethanol [7] using yeast or bacteria [8]. Various straw production processes have been investigated by domestic and foreign researchers, and some progress has been made. In the research process, different instruments and equipment are required to evaluate each production step in order to enhance production efficiency and lower costs. Some of the commonly used equipment are atomic force microscopy [9,10], scanning electron microscopy [11,12,13], transmission electron microscopy [10,12,13], atomic force microscopy [9,10,11,12], confocal microscopy [14,15], microscopic Raman spectroscopy [16,17], and Fourier-transform infrared spectroscopy [18]. These devices can directly or indirectly observe the changes in the surface structure of the cell walls during pretreatment and hydrolysis and analyze their impacts on ethanol production. However, except for Raman microscopy, none of them can perform real-time in situ detection of biomass changes, while Raman spectroscopy itself has a weak signal and is prone to fluorescence interference.

Nonlinear optical microscopy is a sophisticated form of scanning optical microscopy that harnesses the power of ultra-fast laser light sources to capture intricate details at the microscopic level. One of its most significant advantages lies in its ability to operate in a label-free manner, meaning it can visualize biological samples without the need for fluorescent markers or dyes, which can alter the properties of the samples. Additionally, this technique is nondestructive, allowing researchers to observe live samples without causing damage, making it an invaluable tool for in situ analysis. In the context of biomass ethanol production, nonlinear optical microscopy enables real-time, in situ, and high-resolution observation of key components, such as cellulose, hemicellulose, and lignin—three vital structural polysaccharides found in plant materials. By providing detailed insights into the composition and structure of these materials, researchers can identify optimal conditions for the conversion process, thus enhancing production efficiency and reducing the costs associated with generating fuel ethanol from agricultural residues like straw. The subsequent section will delve deeper into the specific applications and advantages of nonlinear optical microscopy within the straw ethanol production process, highlighting how this innovative imaging technique contributes to the advancement of biofuel technologies. It will explore case studies, discuss the technical methodologies employed, and illustrate the potential for improving yield and sustainability in the production of renewable energy sources.

2. Linear Optics Microscopy

The invention of the linear optical microscope can be traced back to the end of the 16th century, marking a significant milestone in the realm of scientific exploration and discovery. Since then, these microscopes have enabled researchers and scientists to observe a wide array of microscopic structures, including cells, fibers, vessels, and wood rays in materials such as wood and straw [19,20]. The ability to magnify and examine these tiny components has revolutionized fields like biology, materials science, and medicine. As technology progressed, scientists developed confocal microscopes based on traditional optical microscopes, which offered enhanced imaging resolution and the capability to capture three-dimensional structures with greater clarity [21,22]. This advancement facilitated more detailed studies of complex specimens, allowing for a deeper understanding of their spatial arrangement and functional properties. To further refine the analysis of wooden structures, researchers introduced Raman imaging [14], a technique that combines the principles of Raman spectroscopy with the high-resolution capabilities of confocal microscopy. This innovative approach enables the characterization of chemical compositions and molecular structures within the wood, providing valuable insights into its properties, behavior, and potential applications in various industries, including construction, furniture design, and conservation.

2.1. Optics Microscopy

The confocal microscope reveals penetration depth, distribution patterns, and voids/aggregates of the coating within the wood cells and straw cells that are not visible under conventional microscopy [19,20]. Detailed lignin structure is revealed using phloroglucinol. Maüle staining shows the presence of more diffuse lignin in the secondary cell wall. UV fluorescence microscopy combined with Maüle staining enhances lignin detection. The article demonstrates how simple and inexpensive histochemical staining techniques, when used together with light/fluorescence microscopy, can provide valuable insights into lignin localization in different lignocellulosic biomass samples, as shown in Figure 1 [23].

2.2. Confocal Laser Scanning Microscope, CLSM

The CLSM reveals penetration depth, distribution patterns, and voids/aggregates of the coating within the wood cells and straw cells that are not visible under conventional microscopy [24]. CLSM, which has the ability to light a section and recombine in three dimensions, shows three-dimensional images of coating buildup in cell corners and cavities that are clearly demarcated from the underlying wood. It allows for the quantitative analysis of coating properties at the microstructural level and can also be used to study the distribution of lignin in plant materials. It provides the high-resolution spatial distribution of lignin in wheat straw and enables the quantitative analysis of its composition, offering crucial insights for applications in biofuel production and research [15,25].

In studies of cellulose reactions with catabolic enzymes, confocal microscopy revealed that the enzymes were concentrated in the outer hyphal sheath and degraded cell walls. This study utilized CLSM techniques to provide new insights into the cellulolytic systems of an ecologically important mushroom species. As shown in Figure 2, it improved the understanding of fungal lignocellulose degradation mechanisms. It also characterized the cellulolytic enzyme system of V. volvacea and localized enzyme production/activity sites microscopically [20].

2.3. Raman Microscopy

Compared with traditional CLSM, Raman microscopy has the characteristics of high spectral resolution, is label-free, and can obtain images of the components of the sample [26]. Raman setup and mapping capabilities enable spatially resolved chemical analysis down to the level of straw cells, revealing redistribution patterns that provide insights into cryoprotectant behavior during straw freezing that cannot be observed with other techniques. The Raman spectroscopy system with the LN-cooled sample holder is presented in Figure 3a. The typical Raman spectrum from a frozen sample is shown in Figure 3b [27].

Confocal Raman microscopy has the high spatial resolution of traditional confocal microscopy and the surface label imaging capability of Raman spectroscopy. Research shows it can achieve chemically specific imaging of poplar cell walls. Chemical selectivity images are obtained by plotting the intensities of specific Raman bands on the image. There are distributions of cellulose, lignin, and hemicellulose in secondary cell walls and interlayers of different cell types (fibers, vessels, and rays). This groundbreaking work demonstrates the ability of confocal Raman microscopy to chemically image plant cell wall components without the need for labels, as shown in Figure 4 [14].

3. Nonlinear Optics Microscope

3.1. Fundamentals of Nonlinear Optical Microscopy

Nonlinear optical microscopy encompasses a suite of imaging techniques that leverage the nonlinear optical properties of biological samples to achieve high-resolution, label-free imaging. Techniques such as multiphoton microscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, two-photon excited fluorescence (TPEF) microscopy, and second harmonic generation (SHG) microscopy have revolutionized our ability to visualize biological structures and processes with exceptional clarity and specificity. These techniques utilize the nonlinear interactions between photons and biological molecules, providing contrast mechanisms that are particularly well-suited for studying biomass components and their transformations during ethanol production.

3.2. Coherent Anti-Stokes Raman Scattering, CARS

CARS is a nonlinear optical process that generates an anti-Stokes signal after interaction. It is enhanced by resonance through vibrational transitions [28,29]. CARS is a third-order nonlinear optical process that involves the interactions of the three ultrafast laser beams. The energy levels of the pump light ω_p, the Stokes light ω_S, and the anti-Stokes light ω_pr during CARS are shown in Figure 5. These ultrafast lasers produce a Stokes signal (ω_as = ω_pr + ω_p − ω_S). When the frequency difference between the pump light and the Stokes light (vib = ω_p − ω_S) matches the Raman natural frequency of the sample, the anti-Stokes signal is resonantly amplified.

Zeng et al. used CARS microscopy to image wild-type and lignin-downregulated alfalfa lines [30,31]. The purpose of the study was to evaluate the impact of lignin modification on the overall cell wall structure. The Raman mode at 1600 cm⁻¹ was chosen for CARS imaging to specifically target the lignin signal in the plant cell wall. The CARS signal intensity followed the general trend of lignin content in the cell walls of the wild-type and lignin-downregulated alfalfa lines. The study also showed that CARS microscopy can provide high-resolution and chemical specificity to image high-concentration species such as lignin in plant cell walls. CARS imaging has high chemical selectivity and high sensitivity, enabling each frame to be acquired in seconds. The optical layout of the CARS measurement system is indicated in Figure 6a. Therefore, CARS is a promising tool to monitor the changes in chemical pretreatment and enzymatic hydrolysis during biomass conversion. Figure 6b presents the bottom corresponding line profiles of the CARS intensities showing different lignin contents on the cell wall layer.

3.3. Stimulated Raman Scattering, SRS

SRS is a nonlinear optical process in which the pump and Stokes light interact with the sample and excite the vibrational state at the Raman frequency [32,33]. When the pump and Stokes light coincide with the molecule, the molecular vibration is driven coherently, and the Raman process is amplified. The pump light is converted into the Stokes light. The depletion of the pump light is called stimulated Raman loss (SRL), and the enhancement of the Stokes light is called stimulated Raman gain (SRG). Both SRL and SRG effects can be measured in the experiments. Therefore, CARS is a promising tool to monitor the changes in chemical pretreatment and enzymatic hydrolysis during biomass conversion, as shown in Figure 6 [30].

The enzymatic digestibility of the plant cell wall is affected by various factors, and it is important to study how the complex 3D nanostructure of the plant cell wall influences the accessibility and degradability of cellulose by microorganisms and cellulolytic enzymes in order to improve the conversion of cellulose into sugars for subsequent fermentation. Currently, cellulases are used to hydrolyze cellulose and produce glucose. Ding et al. employed several different types of microscopes, especially SRS microscopy, to understand how cellulase works [8]. The authors used two-channel SRS microscopy, in which the Raman peak at 1600 cm⁻¹ (aromatic ring breathing mode) represented lignin, and the Raman peak at 2900 cm⁻¹ (C-H stretch) represented polysaccharides. Based on their findings, fungal cellulases digested cellulose from the pore structure more efficiently than bacterial-derived multienzyme complexes after a better removal of lignin. To achieve cost-efficient production of cellulosic ethanol, a better understanding of the plant cell wall chemistry and enzymatic hydrolysis is essential. The SRS images of untreated cell walls are shown in Figure 7a. The typical instrumentation of an SRS microscope is also shown in Figure 7b.

3.4. Two-Photon Excited Fluorescence, TPEF

TPEF microscopy is based on the two-photon excitation of a fluorescent group in a single quantum event. The wavelength of each photon is twice the wavelength needed for excitation by a single photon, and each photon carries about half the energy required to excite the molecule [34,35]. TPEF microscopy is a sophisticated imaging technique that relies on the principle of two-photon excitation to induce fluorescence in a sample. In this process, two photons are simultaneously absorbed by a fluorescent molecule, resulting in the excitation of the molecule in a single quantum event. Notably, the wavelength of each photon used in TPEF is precisely twice that required for excitation by a single photon, allowing for deeper tissue penetration and reduced photodamage, compared to conventional fluorescence microscopy. This is particularly advantageous when imaging living tissues, as it minimizes the effects of phototoxicity and photobleaching, significantly enhancing the viability of the sample during prolonged observations. Each photon in TPEF carries approximately half the energy needed to excite the molecule, which means that the effective excitation occurs only at the focal point of the laser beam, creating a highly localized excitation volume. This localized excitation leads to improved spatial resolution and enables the acquisition of high-contrast images with minimal background noise. TPEF microscopy is especially valuable in biological and biomedical research, as it allows for the visualization of dynamic processes at the cellular and subcellular levels. Researchers can observe cellular interactions, track the movement of molecules, and study the morphology of complex tissues in real time [8].

Moreover, TPEF can be combined with other imaging modalities, such as SHG microscopy, to provide additional information about the structural properties of biological samples. This versatility makes TPEF a powerful tool for investigating a wide range of applications, including developmental biology, neurobiology, and cancer research. Overall, the development of two-photon excitation fluorescence microscopy has profoundly advanced our ability to study biological systems, paving the way for new discoveries and insights into the intricate workings of life at the molecular level. The energy level diagram is shown in Figure 5. The sample is then imaged by a laser scanning microscope to obtain a TPEF microscopic image.

Fovo et al. [36] used two nonlinear optical imaging modes, namely SHG and TPEF, to investigate the structural and chemical changes in cellulose fibers treated with flame-retardant materials. The treatment targeted the hydroxyl groups in the ordered and disordered regions of the fiber, leading to swelling and changes in the crystallinity ratio. The study revealed that the flame retardant treatment induced significant alterations in the structure and chemical composition of the cellulose fiber. Additional results confirmed the reduction of crystallinity in microfibers, mainly due to the decrease in hydrogen bonds between cellulose macromolecules, while the increase in fluorescence might be related to the introduction of ester groups, which facilitate the decomposition of cellulose chains and lignin into fluorescent by-products. This study contributed to the understanding of the chemical changes in the cell wall during straw pretreatment. The mosaics of nine SHG/TPEF merged images are shown in Figure 8.

3.5. Second Harmonic Generation, SHG

SHG is a nonlinear optical process in which two photons with the same frequency interact with a nonlinear material and generate a new photon with twice the energy and half the wavelength of the initial photons [37,38,39]. The process is instantaneous and does not involve intermediate steps, such as photon absorption or reemission. The energy level diagram is shown in Figure 5. The sample is then imaged by a laser scanning microscope to obtain an SHG microscopic image. Only non-centrosymmetric structures can produce SHG light, such as cellulose in plants.

Fovo et al. used TPEF and SHG microscopy to examine the microstructures of different wood species in the artwork. They found that TPEF and SHG imaging modes provided valuable information on the microstructure of the different wood species used in the artwork. The imaging modes can distinguish different components of the wood structure, such as cellulose, lignin, and hemicellulose. The information about these experiments is shown in Figure 8 [36].

3.6. Comparison with Other Methods

In this study, we provide a comparative assessment of the key features of various optical microscopy techniques, including conventional linear optical microscopy and nonlinear optical microscopy. Particular aspects of comparison include microscope design configurations, detection methodologies, and their respective abilities to image lignin, hemicellulose, and cellulose components.

The principal points of distinction are summarized in Table 1. Generally, nonlinear optical microscopy offers advantages over conventional approaches by enabling label-free, high-resolution visualization of all three components simultaneously without staining. Conventional microscopy is limited to surface-level observations and cannot differentiate between the components. Among nonlinear techniques, second harmonic generation selectively detects cellulose microstructures and uniquely permits real-time characterization of architectural changes. The CARS and SRS probe chemically specific vibrations and have been widely applied for plant tissue imaging.

Detector selection varies according to signal intensity. Traditional and Raman spectroscopy approaches with relatively higher intensities can employ conventional cryogenically cooled, charge-coupled device/complementary metal-oxide-semiconductor detectors to improve the signal-to-noise ratio. Weaker signals from confocal and nonlinear modalities necessitate the use of photomultiplier tube detectors. Notably, stimulated Raman scattering microscopy monitors pump light intensity fluctuations, favoring photodiode detectors with high sensitivity and resolution capabilities.

While most microscopes detect both forward- and backward-scattered emissions, forward scatter typically dominates, owing to excitation and sample properties. Some configurations are limited to backward detection due to experimental design constraints, such as signal generation mechanisms and specimen thickness.

4. Conclusions

Nonlinear optical microscopy is an innovative optical imaging technique that can be applied in biological imaging, offering researchers a powerful tool to explore complex biological systems. It can also be effectively utilized for the imaging of biomass ethanol, providing insights into its composition and structure. This technique interacts with the sample through a laser beam to produce nonlinear effects, enabling the acquisition of high-resolution images that reveal intricate details at the microscopic level. One of the standout advantages of nonlinear optical microscopy is its label-free nature, allowing for in situ, real-time observations without the need for fluorescent tags or dyes that can alter the sample. Additionally, its rapid imaging capabilities facilitate the study of dynamic processes, making it an invaluable asset in both research and industrial applications. The application of nonlinear optical microscopy in biomass ethanol research can significantly enhance our understanding of the structural and compositional characteristics of biomass materials. For instance, this technique can be employed to study the distribution and morphology of key biomass components, such as cellulose, lignin, and hemicellulose, which are critical for optimizing biofuel production processes. By providing detailed insights into these components, nonlinear optical microscopy can contribute to more efficient and sustainable approaches to biomass utilization and energy production. Ultimately, this emerging technology holds great promise for advancing our knowledge in various fields, including bioenergy, materials science, and environmental studies.

Author Contributions

Conceptualization, H.G.; methodology, X.L.; formal analysis, X.Z. and R.L.; resources, Q.Z.; funding acquisition, Q.Z.; writing—original draft preparation, R.L.; writing—review and editing, H.-C.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available in the article.

Conflicts of Interest

Author Huipeng Gao and Quan Zhang were employed by the company SINOPEC Dalian Research Institute of Petroleum and Petrochemicals Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

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Figures and Table

Figure 1. Tylosis showed a green fluorescence (arrow), and the innermost layer of the vessel cell wall showed a red fluorescence (arrowhead) [23].

Figure 2. Dual WGA, Alexa Fluor® 488 conjugate, and propidium iodide staining revealed the fungal cell wall (green fluorescence) and wheat straw cell wall (red fluorescence), respectively. Representative micrographs are shown for each treatment. Fungal detection on the wheat straw surface on day 14. Inocula correspond to: (A) anaerobic sludge, (B) native microflora, (C) soil, and (D) ruminal fluids [20].

Figure 3. (a) Experimental setup of the Raman spectroscopy system: 1—mirror; 2—beam splitter (small aluminum mirror sputtered on glass plate); 3—lens; 4—glass dewar; 5—edge-filter; 6—lens; 7—spectrometer; 8—sample (frozen cryoprotector solution in the straw); 9 and 10top and bottom air bubbles, respectively; 11—central column (region measured); 12—column bottom side; (b) representative Raman spectrum from a frozen sample [27].

Figure 4. Raman images of poplar latewood cross-sections from Raman confocal microscopy. The cell corner (CC) and the compound middle lamella (CML) [14]. (A–D), Raman images (30 × 20 μm) of a cross section of poplar latewood by integrating over defined wavenumber areas. (A), Intensity of the aromatic lignin band (1550–1640 cm−1). (B), C–H str.region (2780–3060 cm−1). (C,D), Intensity of bands in the carbohydrate region from 1026 to 1195 cm−1 (C) and intensity of the 1096 cm−1 band (1090–1105 cm−1; (D)).

Figure 5. The transition diagrams of infrared, Raman, CARS, TPEF, SHG, and SRS. The arrows represented as the electron transitions between the energy states.

Figure 6. (a) Schematic diagram of the multimodal nonlinear optical imaging platform. DM—dichroic mirror, M—mirror, BS—beam splitter, BBO—barium boron oxide, GM—galvo mirror, X-/Y-Mirror—X/Y axis scanning mirror, SL—scanning lens, TL—tube lens, OBJ—objective lens, CL—condensing lens, PMT—photomultiplier tube, PC—programmed computer. (b) Top CARS micrographs of lignin distribution in cross-sections of wild-type (WT) and lignin-downregulated alfalfa lines (HCT and C3H). Bottom corresponding line profiles of CARS intensities show different lignin contents across the cell wall layers in the direction shown by the blue arrows [30,31].

Figure 7. (a) The SRS images of untreated cell walls. (A) represents the polysaccharides at 2900 cm−1 (blue), and (B) represents the lignins at 1600 cm−1 (red). After delignification, (C), the signal at 2900 cm−1, is slightly reduced, and (D), the 1600 cm−1 signal, is eliminated [8]. (b) The typical instrumentation of an SRS microscope (electro-optic modulators, EOM) [32].

Figure 8. Mosaics of nine SHG/TPEF merged images. F—not treated. AF—aged and not treated. C—COEX®-treated. CA—COEX®-treated and aged [36].

Table 1

Contrasts between the different optical microscopes. (C (cellulose), L (lignin), H (hemicellulose); F (forward), B (backward)).

Method	Primary Information	Illumination Source	Emission Direction	Resolution	Detector	Representative Refs.
Traditional microscope	(C, L, H) Structural	White light	F/B	Low	CCD/CMOS	[23]
CLSM	(C, L, H) Structural	C-W laser	B	High	PMT	[25]
Raman	(C, L, H) Spectrum, Chemical	C-W laser	F/B	Low	CCD/CMOS	[27]
Raman confocal	(C, L, H) Structural/Chemical	C-W laser	B	High	PMT	[15,26]
CARS	(C, L, H) Structural/Chemical	ps/fs + OPO	F/B	High	PMT	[30,31]
SRS	(C, L, H) Structural/Chemical	ps/fs + OPO	F/B	High	Photodiodes	[8]
TPEF	(C, L, H) Structural	ps/fs	F/B	High	PMT	[31,36,40]
SHG	C Structural	ps/fs	F/B	High	PMT	[36,40]

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