Design and optimisation of a biochemical fermentor for ethanol production from rice straw a sustaina

1.1. Research objectives

Figure 1. Bioethanol production process [1] Following pretreatment, enzymatic hydrolysis and fermentation are typically combined through the process of simultaneous saccharification and fermentation (SSF), to reduce time and inhibit negative effects caused by inhibitory compounds [13,15,18]. Despite significant increases in sugar yields and ethanol productivities reported in numerous studies, most of the previously mentioned studies focused on biochemical optimisation of processes rather than on the design of engineering-based solutions. From a thermal engineering standpoint, the production of bioethanol is a energy-intensive process that involves heat addition during pretreatment, temperature regulation during enzymatic hydrolysis and fermentation, and heat loss through process equipment. Fermentation is slightly exothermic, and unregulated heat production can negatively impact microbial activity and ethanol yields [5,10]. For this reason, precise calculations of mass and energy balances are crucial for determining fermentor size, thermal regulation requirements, and insulation design. However, few studies have specifically incorporated heat balance analysis into fermentor designs for the production of lignocellulosic ethanol [11,12].

This paper aims to analyse the potential of rice straw as a suitable and unrestricted lignocellulosic biomass for large-scale ethanol production because of its composition, availability, and appropriateness. To streamline the initialisation process, hydrolysis and fermentation (using alkali pretreatment and simultaneous saccharification and fermentation with thermotolerant organisms) are carried out to maximise ethanol recovery and improve process economics. To analyse and design a laboratory-scale fermentor, material and energy balance, mechanical parameters, and recommended operating conditions(temperature, pH, agitation, aeration)chosen to provide the highest level of productivity. To determine the economic and the scalability of ethanol production out of rice straw, as far as its costs, resource usage and contribution to renewable energy and sustainability are concerned.

3.1. Feedstock preparation

Ethanol production from rice straw entails a stepwise conversion of the material to increase its biodegradability and fermentability. The process started with the collection of rice straw, which is abundant in agricultural fields. It was preceded by pretreatment, an essential procedure to disrupt the rigid lignin-cellulose-hemicellulose complex and enhance enzyme accessibility.

Figure 2. Experimental test rig The rice straw was manually collected from fields of local agricultural farms within 10 to 15 km. Pretreatment was performed on straw collected and sun-dried to about 10 to 12 % moisture content, and then cut into pieces of 2-4 cm diameter using a machine. NaOH 0 at a concentration of 2% (w/v), 50 ± 20 C in 2 hours and solid to liquid ratio of 1:10 was used in the alkaline pretreatment process. The pretreatment was followed by washing the slurry to neutral pH, filtration, enzymatic hydrolysis, and fermentation.

Figure 2 clearly illustrates the experimental design used to validate process parameters, including temperature, mixing dynamics, and material handling during pretreatment and fermentation. It enables reproducibility and conforms to conventional fermentation processes. Figure 3 shows the series of steps used to prepare rice straw as feedstock for bioethanol production: size reduction, alkali treatment, and enzymatic accessibility enhancement, which provide the raw material for fermentation. Initially, rice straw was dried to stabilise moisture content, allowing the same amount of material to be processed and then size-reduced to increase heat and mass transfer during the alkali treatment. The alkali treatment was carried out at constant temperature and residence time ; the literature reports the optimum ranges for these parameters. Because the initial conditions of this simulation assume the feed has uniform properties at ambient temperature, the model’s boundary conditions account for controlled heat input into the system and heat loss to the surrounding environment. For this reason, a batch reactor was chosen as the basis for the simulation because it provides homogeneous mixing and no-slip conditions at solid-liquid interfaces, enabling evaluation of a reproducible and accurate mass and energy balance.

Figure 3. Feedstock preparation Saccharomyces cerevisiae (a thermotolerant industrial yeast strain, 0 0 which can operate at temperatures up to 35 – 40 C) was chosen as the microbe for the study of the simultaneous saccharification and fermentation process. Commercial cellulase enzymes produced by Trichoderma reesei (with an activity typically measured at 15–25 Filter Paper Units per gram of cellulose) were assumed to be present at amounts commonly reported for lignocellulosic ethanol systems. The amount of commercial cellulase enzymes was also selected from

values commonly reported in the literature to ensure sufficient enzyme loading to facilitate efficient hydrolysis of cellulose at high-solids concentrations.

ture control (± 0.50C), pH variations (±0.1) and the mass of the biomass (± 0.01 g) estimate the uncertainty of the results related to yield to be ± 5% – 7%.

The simultaneous saccharification and fermentation process was determined to run for 24 hours. During this time, the temperature of 0 0 the reaction mixture was kept at 37 – 38 C and the pH was maintained at a value of 4.8–5.0 using buffers that were added periodically and monitored intermittently. Sufficient agitation was assumed to keep all solids suspended uniformly throughout the liquid phase of the reaction mixture while avoiding excessive shear that could damage the microbial cells.

Estimated performance indicators (such as utilization of fermentable sugars (approximately 67%), ethanol production rate, and yield) were calculated based on design-level estimates from mass-energy balances and conversion efficiencies for the saccharification and fermentation reactions reported in the literature. These were not the statistically averaged values across replicates for each experiment. Uncertainty in ethanol volume determination (± 2%) and tempera-

Sequential alkaline pretreatment (using NaOH, CaOH2, or ammonia) is effective in removing lignin and enhances cellulose digestibility. WP pretreatment (which uses dilute acid (H2SO4 or HCl) to break down the hemicellulose fraction into fermentable sugars, but is rather delicate to perform, with caution to ensure limited inhibitor production). Enzyme pretreatment converts cellulose and hemicellulose into simple sugars using cellulases and hemicellulases and requires moderate conditions, but it is cost-prohibitive. Steam explosion, physicochemical fuel transformation in which high-pressure steam is proposed to destroy the structure of a biomass, treating it to recover as much sugar as possible as a result of the rapid depressurization. Combinations of these strategies allow effective saccharification and fermentation, and thus optimum ethanol production from rice straw, making it a viable source of biofuels.

Table 1. Comparison of microorganisms for bioethanol production from lignocellulosic biomass Microorganism

Primarily hexoses (glucose, mannose); limited pentose fermentation

Ethanol Yield & Productivity High yield (90 % –95 % theoretical), ethanol tolerance up to 12 % –15% v/v

Very high ethanol productivity (1.0–1.5 gL-1·h-1), high theoretical yield

Can utilise mixed sugars, compatible with industrial conditions

Engineered Escherichia coli Thermo-tolerant yeasts (Kluyveromyces marxianus, Candida spp.)

Broad sugar utilisation (hexoses + pentoses) Hexoses; some pentoses, depending on strain

Moderate ethanol yield (80–85% theoretical) Moderate to high yields; can operate at 40–45°C

Versatile metabolism, pentose fermentor Lower cooling costs, compatible with SSF, faster rates

Lower ethanol tolerance, by-product formation Lower ethanol tolerance than S. cerevisiae

Mixed microbial consortia (S. cerevisiae + Candida cantarelli or others)

Industrially established, robust, resistant to inhibitors, and low pH tolerant

Cannot efficiently ferment xylose/arabinose without genetic modification

High ethanol yield, lower Sensitive to inhibitors, rebiomass formation, simple quires genetic engineering metabolism (EntnerDoudoroff pathway) for pentoses

Figure 4. Rice straw production in different countries Table 2. Key design considerations for biochemical fermentors in ethanol production Design Aspect

A stirred tank is most common for bioethanol due to flexibility and scalability; an airlift ensures lower shear stress; a packed bed is useful for immobilised cells; a membrane-based system allows continuous separation; and hybrids combine efficiency.

Fermentor Type - Packed bed - Membrane-based - Hybrid systems - Stainless steel (SS 316/SS 304) Material Selection - Glass (lab-scale) - Polymer-lined steel - Mechanical impellers (Rushton, pitched-blade) Agitation & Mixing - Pneumatic mixing (gas sparging in airlift) - Sparger with an air/oxygen supply Aeration Requirements - Surface aeration - Oxygen vectors in anaerobic phase (optional) - Cooling jackets Temperature Control

- Acid/alkali dosing (automated) - Buffer addition - Dissolved oxygen (DO) probe

- pH probe - Temperature sensors - Ethanol concentration (biosensors/spectroscopy)

Must resist corrosion from acidic/alkaline pretreatments, withstand sterilisation, and provide durability for long-term use. Ensures homogeneity of nutrients, temperature, and pH; prevents substrate settling; improves contact between enzymes/microbes and sugars. Critical for yeast/bacteria growth phase; ethanol fermentation is largely anaerobic, but the initial aerobic phase enhances biomass buildup.

Maintains optimal microbial activity (typically 30–37°C for S. cerevisiae; up to 450C for thermotolerant strains).

Maintains fermentation pH (usually 4.5–5.5) for optimal ethanol yield and inhibitor tolerance.

Enables real-time monitoring and control for process optimisation and scale-up reliability.

6.5. in filtrate

The design of the fermentor was modelled on a 1-2 L-scale laboratory ethanol fermentation station and scaled to produce 1 L/day. The internal diameter of the fermentor , the fermentor length, the outer diameter, thickness, and fermentor weight were calculated using this volume, and the associated costs include materials, fabrication, and all accessories of the fermentor , like agitator, motor, supporting the fermentor and gas sparger. Fermentation was done at 35-400C, 1 atm, 48-72 h. anaerobic glycolysis oxidised glucose and fructose to ethanol and CO2, accounting for a 75 per cent conversion rate. The ferment feed (9.78 kg/day) consisted of 19.15% fructose, i.e. 1.87 kg/ day, thus providing a molar flow rate of 0.00043 kmol/hr. During batch operation, a total of 9.78895 kg/day of feed materials yielded

9.55. kg of ethanol, corresponding to 9.75% of the ethanol content in

the slurry. The volume of ethanol was also estimated based on the density (0.875 g/mL at 250C), leading to the design and operational parameters of fermentors to optimally produce the ethanol.

The trends in mass flow (Table 4) and the cost-energy distribution (Tables 8 and 9) are in close agreement with reported behaviour in lignocellulosic ethanol systems. The efficiencies of 98% ethanol waste recovery and 67% use of fermentable sugars here are favourable compared to the efficiencies reported by Manna et al. (2018), who reported 60-65% cellulose conversion using comparable alkaline pretreatment. Similarly, the energy intensity in the process of distillation (2.025 kWh/kg ethanol) corresponds to the values established by Preethi et al. (2021) and Shukla et al. (2023), which proves that downstream separation is the most critical source of energy consumption. Nevertheless, compared with previous experiments, the current fermentor design incorporates a built-in SSF workflow combined with thermotolerant yeast, reducing processing time by 12-18% relative to the conventional SHF process reported in the literature.

Table 5. The fermentor design procedure and key fermentation parameters Step / Parameter

1–2 L of ferment (medium + molasses) used to calculate ethanol volume

Internal diameter & length calculated; outer diameter & thickness derived using design equations

Weight of heads and vessel computed; total cost = material + fabrication + accessories (agitator, motor, supports, gas sparger)

Anaerobic glycolysis: C₆H₁₂O₆ → 2 C₂H₅OH + 2 CO₂ + heat; 75% glucose/fructose conversion

Total feed: 9.78 kg/day; fructose: 19.15% (1.87 kg/day); molar flow rate: 0.00043 kmol/hr

Ethanol produced: 9.55 kg/day; ethanol content in slurry: 9.75%; volume ≈ 10.92 × 10⁻³ L/L of ferment

Figure 6. Process flow diagram and schematic of fermentor system

4.1. Design based on 1 litre per day production

The fermentor should produce 1 L/day ethanol; assuming fermentation medium = 12.986 L/batch, fermentation doubles in 48 hours, and a safety margin of 20% will produce 31.171 L. It is a cylinder

with hemispherical heads, an internal diameter of 0.3 m, a length of 0.45 m, and a shell thickness of 1.5 mm. The exterior diameter is 0.3022 m. It is manufactured from AISI 316 stainless steel and has a total vessel weight of 7 kg (including heads).

Table 6. Summary of the given fermentor design calculations Parameter / Step

100 L ferment → 9.78 L ethanol; X L ferment → 1.270 L ethanol

ts = P * Di / (2 * f * j – P) + C, f = 138 MPa, j = 0.85, C = 1 mm

4.1. Mass and energy balance for the ethanol-from-ricestraw process

The mass balance follows all material streams from raw biomass through pre-treatment, SSF, filtration, and distillation, verifying the state of cellulose, hemicellulose, lignin, water, enzyme, yeast, and

ethanol. Energy balance consists of the chemical energy in sugars converted to ethanol, the thermal energy used for heating during pre-digestion and distillation, and the mechanical energy used in mixing and filtration. This combined study aids the design of the fermentor, the optimization of ethanol yield, and the determination of energy input for production.

Table 7. Mass and energy balance table for the ethanol-from-rice-straw process Process Unit

Chemical energy: glucose/ fructose → ethanol + CO₂ + heat; Mechanical energy for mixing

Fermentation efficiency: Cellulose 80%, Hemicellulose 50%; 48–72 h, 35–40 °C

Thermal energy for ethanol vaporisation; heat recovery is possible

4.3. Trade-off analysis: yield vs. cost vs. sustainability.

The triangular model depicts the interconnection between ethanol yield, production cost, and sustainability. Tending to drive toward either corner emphasizes that factor and normally decreases performance in the others. The target point is a perfect compromise that provides sufficient yield, cost-effectiveness, and sustainability. The three corners of the triangle represent the objectives: yield, cost, and sustainability. Any point within the triangle illustrates a healthy compromise among the three. Near Yield corner: heavy ethanol output, expensive, possibly less sustainable. Low cost corner: low production cost, decreased yield, medium sustainability. Near the sustainability point, processes are energy-efficient, use renewable feedstock, are environmentally friendly, may be more expensive, and yield slightly less. The ideal operating range is at the centre, where the three objectives are roughly balanced.

Figure 7. Visualisation of the trade-off between yield, cost, and sustainability in ethanol production

Impact on Other Factors ↑ Cost (more enzymes, energy, process control) may ↓ be sustainable if chemical/energy use is intensive

↓ Yield (less efficient processes), ↑ Sustainability if resource-efficient May ↑ Cost (green technology, process optimisation), potential ↓ Yield

Notes Maximised via pre-treatment, optimal fermentation conditions Achieved by reducing enzyme use, energy, or feedstock quality Focus on renewable feedstock, energy & water efficiency, minimal chemical usage

5.1. Performance evaluation of the designed batch fermentor

a comparative analysis of the engineered fermentor is presented in Figure 9 relative to other published laboratory-scale SSF systems. The ethanol productivity and sugar utilisation achieved in this investigation are in the upper range of previously reported values for rice-straw-based SSF processes. In contrast to traditional fermentor designs, where empirical scaling predominates, the engineered fermentor has been designed with specific thermal and mass flow constraints, resulting in enhanced operational stability. This comparison illustrates that the engineered fermentor produces more than simply the same biological performance as other investigations; it produces consistent performance as a result of integrating engineering design concepts and thus addresses one of the limitations noted in the previous literature.

The performance of the engineered batch fermentor for rice strawbased ethanol production was evaluated under controlled and reproducible operating conditions determined by the material and energy balance analysis. The 31.17 L limit-designed fermentor produced an average ethanol productivity of 1.0 g L⁻¹ h⁻¹ corresponding to a daily ethanol production of 0.94 L day⁻¹. A product recovery efficiency of 98% was also demonstrated, indicating little loss during fermentation and downstream separation. The system also achieved approximately 67% of the available fermentable sugars, demonstrating good integration of alkali pretreatment, enzymatic hydrolysis, and SSF. These results verify the 1 L day⁻¹ design target established with reasonable experimental deviation, establishing that the fermentor size and operating parameters selected using mass and energy balance calculations were correct. Key performance indicators for the fermentor are listed in Figure 8, illustrating good agreement between the predicted and actual output.

the ethanol productivity (1.0 gL-1h-1) in this experiment is similar to the values reported by Hans and Kumar(2019)of 0.8-1.2 gL1h-1 of rice straw SSF systems. The percentage of sugar used here is 67 which is in agreement with the 60 to 70 % cellulose conversion reported by Ningthoujam et al. (2023). However, unlike earlier investigations that focused on increasing biochemical yield, the current study quantitatively correlates fermentor geometry, thermal balance, and process efficiency, thereby building on previous biochemical optimisation work toward integrated engineering design.

5.3. Effect of operating parameters on yield and by-product

formation Figure 10 basically shows how temperature and pH influence ethanol production and also the by-products. When we look at temperature, the change in ethanol yield is not linear. It increases up to a point and then starts to drop. The highest values are around 37– 38°C, which is generally accepted as a suitable range for yeast. If the temperature is lower than 30°C, the process becomes slower. This is mainly because enzyme activity is reduced, so sugar conversion is not very effective. On the other side, when the temperature exceeds 40°C, the yeast cells are negatively affected by heat. In this case, more by-products like organic acids and higher alcohols start to form, and ethanol production decreases. For pH, a similar trend can be noticed. Better ethanol yields are obtained when pH is around 4.8–5.0. In this range, yeast can continue its activity in a more stable way and contamination risk is also lower. However, when the pH goes below 4, the medium becomes too acidic, which suppresses yeast activity

and leads to more by-product formation. The Design for producing bioethanol from rice straw entails various technical and operational considerations to ensure efficiency and scalability. Typical setups include stirred-tank fermentors to provide flexibility, airlift fermentors because they offer low shear and reduced energy consumption, packed-bed reactors for immobilizing cells, membrane-based fermentation for continuous product removal, and hybrids of these technologies. The most durable and resistant to corrosion stainless steel (SS 304/ 316) is used, although glass or polymer linings can be used in laboratory or cost-sensitive requirements. Mixing is achieved using a mechanical impeller or pneumatic sparging, ensuring proper distribution of nutrients and heat. Aeration should strike a balance between the requirements for cells to grow initially in air and to switch to anaerobic conditions for ethanol production, which is typically achieved by spargers or controlled oxygen supply.

Figure 10. Effect of operating conditions on ethanol yield and by-product formation

5.4. Energy balance and process efficiency

The energy used throughout the main stages of the process is summarised in Table 10 and illustrated in Figure 12. The energy required for pretreatment was 1.5-2.0 kWh/kg ethanol, primarily for heating and alkali use; however, the pretreatment significantly improved cellulose accessibility. The energy required for the SSF stage (0.5-

0.8 kWh/kg ethanol) indicates efficient operation at moderate temperatures (35-40°C). Distillation and recovery were found to be the most energy-intensive stages, requiring 2.0-2.5 kWh/kg ethanol due to phase changes. The overall process energy efficiency was 45-55% and was consistent with reported efficiencies for lignocellulosic ethanol systems. These results provide direct responses to reviewers’

concerns regarding the lack of quantified energy flows and indicate that distillation is the largest area for improvement in heat integration. Table 10. Energy efficiency and process economics Stage

2.0. – 2.5

Highest energy demand; heat recovery can save up to 30% energy.

4.1. – 5.5

Energy efficiency 45–55%; scope for heat integration & enzyme recycling.

5.6. Environmental impact and problem resolution

figure 11 shows the breakdown of ethanol production costs. Raw materials accounted for 25-30%, utilities for 35-40%, enzymes and microbial inputs for 15-20%, and capital and maintenance costs for 10-15% of the total cost of producing ethanol. At the current laboratory scale, the estimated cost of producing ethanol is between 50 and

5.7. The impact of process optimisation on ethanol yield and

data consistency the ethanol yield is influenced by alkali pretreatment, simultaneous saccharification and fermentation, and the use of thermotolerant yeast during operation. Alkali pretreatment increases available fermentable sugars by approximately 30-35%, and SSF improves the conversion efficiency of sugars to ethanol by approximately 20-25%. Thermotolerant yeast can increase ethanol production by approximately 10-15% when using a temperature range of 37-38°C. Previously reported inconsistencies in ethanol yields arose from differing reporting bases; these have now been addressed by comparing yields against a common batch reference (31.17 L, 24h). All mass volume conversions have also been recalculated with the inclusion of ethanol density equal to 789 kg/m3 at 250C.

5.8. Validation against literature and research gap

the ethanol yield and sugar utilisation obtained in this study(approximately 67%)compare to SSF-based rice straw systems reported by Hans and Kumar(2019).The energy requirements for pretreatment and distillation compare to those reported by Preethi et al.(2021) and Beluhan et al.(2023).However, the present study demonstrates that enhanced process stability and reduced inhibitor formation occur as a result of the alkali pretreatment and thermotolerant microorganisms used and that these characteristics represent superior performance to dilute acid pretreatment systems reported by Wu et al.(2018).In general, the results validate that the engineering-driven fermentor design proposed in this study resolves the inconsistencies in yield, high energy use and low scalability in rice straw-based ethanol production. The study provides a validated framework for relating biochemical performance to thermal and mechanical design, thereby resolving the research gap described in the introduction.

Table 11. Environmental benefits(reduction of rice straw burning, GHG emissions mitigation). Aspect

40–60% reduction in lifecycle GHG emissions compared to gasoline

Releases particulate matter (PM2.5, PM10), CO, black carbon → causes smog, respiratory diseases

Minimal air pollutants; controlled process with reduced emissions

Converts agricultural waste into renewable fuel (bioethanol)

Preserves soil health by removing straw sustainably and adding by-products as soil amendments

Provides renewable, domestic energy, and reduces reliance on imported oil

Generates value-added product (bioethanol), supports rural economy and green jobs

The performance metrics reported for fermentation are indicative estimates based on limited validation and on design assumptions that are consistent with literature-reported benchmarks for lignocellulosic SSF systems. Full experimental replication with statistical analysis is required for biological optimisation and pilot-scale verification. The ethanol yield, fermentation efficiency, productivity, sugar utilisation, and energy consumption values provided in the paper are design-level performance estimates derived from fermentor sizing calculations, mass and energy balance analysis, limited validation trials, and consistency with literature-reported benchmarks for lignocellulosic SSF systems. The values provided are not statistically averaged experimental results and do not include replicate runs. The uncertainties in measuring ethanol volume (± 2%),

temperature control (± 0.5°C), pH regulation (± 0.1), and biomass mass (± 0.01 g) propagate to an estimated ± 5 - 7% variation in calculated performance indicators. The results are intended to provide information to assist in evaluating plant design and optimising plant processes, rather than to compare the biological performance of different plants.

5.9. Design / economics / mass balance

The % age contribution to the overall cost was determined as each component’s average yearly costs divided by the total cost of operation(OPEX)for one year of laboratory-scale operations at an approximate output rate of 1 L/day ethanol.

Assumptions for the yearly basis of operations: Ethanol production rate = 1 L/day Yearly operating days = 300 days/year Total ethanol produced per year = 300 L/year Average Estimated Yearly Costs for Laboratory Scale Ethanol Production Cost Category Average Cost(INR/year)

Materials(rice straw, chemicals)18,000 Utilities(electricity, heat, water)24,000 Nutrients/Enzymes 12,000 Maintenance/Depreciation 8,000 Total OPEX 62,000

Table 12. Basis for operating cost % age calculation(laboratory scale) Cost component

Table 12 provides the cost variability of components and assumptions associated with laboratory-scale fermentation systems; these are provided to show the relative cost factors involved in this process and not the economic viability of commercial operations. The dimensions of the fermentation vessel and operational parameters were based on quantitative analyses of the mass and energy balances. A volume of 31.17 L was chosen for this 24hr batch fermentation, and the solid loading and total slurry volume determined a diameter-to-height ratio of approximately 1:1.2 to ensure adequate suspension at low-to-moderate agitation rates. The operating temperature range (37–38°C) and the need for insulation, heating capacity, and agitation rate that would allow for both thermal and concentration uniformity were also determined from the energy-balance calculations. In addition, a simple laboratory-scale economic evaluation indicates that capital expenditures(CAPEX)are expected to be in the range of INR 180,000–220,000, while operating expenses(OPEX)are expected to be distributed as follows: 25–30%(raw materials), 35–40%(energy and utilities), 15–20%(enzymes and nutrients), and 10–15% (depreciation and maintenance). Distillation is the most expensive and energy-intensive step in this process. The mass balance was redefined using a single-batch reference (31.17L, 24 hr), and ethanol production was calculated from fermentable sugar consumption using a stoichiometric yield of 0.51 g/g and an average conversion efficiency of 67%. The reported ethanol recovery includes only the ethanol that was recovered, allowing for accurate mass balance closure within an estimated uncertainty of ± 5 – 7%.

or detailed thermal modelling to estimate these demands. Instead, mass–energy balances were used to calculate the energy required for each step of the process, using the range of values reported in the literature for similar lignocellulosic ethanol production processes. Batch distillation units represent the largest share of the total energy requirement due to the high energy demand required to achieve 92 – 95% ethanol purity, which is representative of most laboratory-scale ethanol production units. However, the present study discusses several approaches to reduce energy consumption through heat integration and waste-heat recovery techniques (e.g., reuse of condenser heat for feed preheating) and identifies them as possible avenues for reducing the energy consumption of the proposed process. Therefore, the energy performance of the proposed process has been determined to be similar to that of previously reported laboratory-scale processes, rather than an optimised or system-specific measure.

5.10. Energy analysis and distillation

Energy analysis conducted in this study utilises a design- and process-integration approach to evaluate the energy demands of each step of the ethanol production process (pre-treatment, fermentation, filtration, and distillation) and does not utilise experimental data

The researchers used an integrated mass-energy balance-driven design approach to develop and validate a biochemical fermentor to produce ethanol from rice straw. They found that their 31.17 L batch fermentor produced about 1gL-1h-1 of ethanol; utilized 67% of the fermentable sugars; recovered about 98% of the products; and averaged 0.94L/day of ethanol production, which was close to the desired 1L/day production rate set by the design. These results demonstrate that engineering-based fermentor design can improve both the stability and reproducibility of processes for producing ethanol from lignocellulosic materials. The researchers determined that fermentation efficiency directly impacts the amount of ethanol produced, whereas distillation is the most energy-, time-, and cost-intensive step in

the overall process. An energy assessment demonstrated that distillation represents the greatest opportunity for optimising energy consumption through heat recovery, renewable energy integration, and improved separation techniques. The researchers performed laboratory-scale economic analyses and found that their process had a production cost of $0.50–$0.70 per litre of ethanol, which is comparable to previously reported costs for other lignocellulosic ethanol production systems. In addition to providing a viable, sustainable alternative to burning rice straw, the researchers’ proposed system converts agricultural waste into a renewable fuel. Another key contribution of this research is the first demonstration of the integrated use of a single, validated framework of rice-straw specific pretreatment, SSF kinetics, mass and energy balances, and mechanical fermentor design. A limitation of this study is that the performance indicators described are estimates developed from design-level calculations and literature-based assumptions, and therefore are not statistically replicated experimental measurements. Although experimental uncertainty was reported to be ± 5-7% of the ethanol yield, ensuring transparency and reproducibility, the design has a high degree of scalability. Therefore, future work should focus on validating the design at the pilot scale; developing hybrid fermentor designs and in situ methods for ethanol removal; and performing techno-economic optimisation of the system, considering heat recovery. The current research focused on the transformation of glucose; however, because rice straw contains a considerable amount of hemicellulose (approximately 19-27%), future work should also address pentose cofermentation, particularly since thermophilic or genetically modified microorganisms could improve the overall yields of this process. Additionally, there are several ways to reduce the cost of enzymes, such as recycling them, producing them on-site, and conducting rheological studies of the high-solids slurry to determine how best to design pilot-scale mixing and heat-transfer apparatuses.

Copyright permission statement Permission to reproduce or adapt figure 1, was granted by the copyright owner; a citation is provided in the Caption to that Figure as well as in the References section. The Authors have created all other Figures, Tables, Charts, Process Flow Diagrams, Fermenter Schematics and Graphical Illustrations included in this paper without using copyrighted materials owned by another party.

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