SEARCH · Engineering Papers

Results for “Improved”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Applying design principles to improve hydrogen storage capacity in nanoporous materials

Hydrogen is an attractive option for energy storage because it can be produced from renewable sources and produces environmentally benign byproducts. However, the volumetric energy density of molecular hydrogen at ambient conditions is low compared to other storage methods like batteries, so it must be compressed to attain a viable energy density for applications such as transportation. Nanoporous materials have attracted significant interest for gas storage because they can attain high storage density at lower pressure than conventional compression. Here, we examine how to improve the cryogenic hydrogen storage capacity of a series of porous aromatic frameworks (PAFs) by controlling the pore size and increasing the surface area by adding functional groups. We also explore tradeoffs in gravimetric and volumetric measures of the hydrogen storage capacity and the effects of temperature swings using grand canonical Monte Carlo simulations. We also consider the effects of adding functional groups to the metal–organic framework NU-1000 to improve its hydrogen storage capacity. We find that highly flexible alkane chains do not improve the hydrogen storage capacity in NU-1000 because they do not extend into the pores; however, rigid chains containing alkyne groups do increase the surface area and hydrogen storage capacity. Finally, we demonstrate that the deliverable capacity of hydrogen in NU-1000 can be increased from 40.0 to 45.3 g/L (at storage conditions of 100 bar and 77 K and desorption conditions of 5 bar and 160 K) by adding long, rigid alkyne chains into the pores.

08 HYDROGEN↗

DOE OSTI2020

Improved pore network models to simulate single-phase flow in porous media by coupling with lattice Boltzmann method

In this paper, different pore network models to simulate single-phase flow in porous media are built and their accuracy is evaluated. In addition to the conventional pore network model (CPNM) which consists of regular pore bodies and throat bonds, three improved pore network models (IPNMs) are developed allowing to better describing the real pore and throat geometry. The first improved pore network model (IPNM1) replaces the regular throat bond with a throat bond showing the real throat cross section. The second improvement (IPNM2) uses a series of sub-throat bonds with varying cross sections to better describe the real throat geometry, which is firstly proposed in this paper. The third model (IPNM3) extracts the real pore-throat-pore geometry without simplification. The conductance of fluid flow through these more realistic throat bonds is calculated by the lattice Boltzmann method (LBM). The accuracy and computational efficiency of the different pore network models are evaluated taking the LBM simulation over the whole porous medium as reference solution. The global permeability and detailed pressure distributions in the pores for the different pore network models are validated. The results show that the accuracy of the pore network model increases from CPNM to IPNM3, but at the expense of increasing computational cost. This study suggests that IPNM3 can replace a whole-domain LBM simulation with similar accuracy but much lower computational cost. As a first-order approximation the newly proposed IPNM2 is suggested as good compromise between accuracy and computational cost.

42 ENGINEERING↗

DOE OSTI2025

Improved Bayesian regularization of inverse problems in vibrations and acoustics using noise-only measurements

Here, this paper studies Tikhonov regularization (ridge regression) parameter selection for problems in vibrations and acoustics. The selection method is based on a popular Bayesian method, but it incorporates measurements of sensor noise. The regularization parameter is closely related to the ratio of system input energy to noise energy, so noise measurements inform the inference procedure and improve parameter identification. In cases where standard Bayesian regularization identifies zero as the optimal regularization parameter, noise measurements guarantee a unique nonzero optimum. Sufficient theoretical criteria are developed for this guarantee. The method is verified in even-determined and under-determined configurations in an acoustic source localization simulation and a vibration load identification experiment. It is shown to yield significant improvements over existing empirical Bayesian regularization. Improvements are larger in the even-determined case and smaller in the under-determined case, wherein the inverse solution is less sensitive to the regularization parameter.

42 ENGINEERING↗

DOE OSTI2023

Precisely doping the surface of tin-based electrocatalysts for improved CO 2 conversion to liquid chemicals

Doping tin catalysts with sulfur can improve the electrochemical CO 2 conversion into formate/formic acid, but the lack of composition-dependent activity trends hinders further catalyst development. Here, we precisely controlled the composition of sulfur-doped Sn catalysts to show that sulfur doping only improves CO 2 conversion over a very narrow composition range, achieving maximum activity at 1.4 at% S. In situ Raman spectroscopy indicted working catalysts were in a primarily metallic state (e.g. S-Sn), and we achieved some of the highest reported partial current densities in both H-cell and full-cell electrolyzer configurations. Density Functional Theory calculations predicted S atoms preferentially occupied the catalyst surface and improved CO 2 reduction by localizing charge density at the catalyst/intermediate interface, which stabilized the *OCOH intermediate and lowered the CO 2 conversion thermodynamic barrier. Our work quantifies the composition-dependent influence of S dopants on Sn-based CO 2 reduction catalysts and provides a pathway for maximizing their CO 2 conversion activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Incremental Interval Assignment by Integer Linear Algebra with Improvements

Interval Assignment (IA) is the problem of selecting the number of mesh edges (intervals) for each curve for conforming quad and hex meshing. The intervals x is fundamentally integer-valued. Many other approaches perform numerical optimization then convert a floating-point solution into an integer solution, which is slow and error prone. We avoid such steps: we start integer, and stay integer. Incremental Interval Assignment (IIA) uses integer linear algebra (Hermite normal form) to find an initial solution to the meshing constraints, satisfying the integer matrix equation Solving for reduced row echelon form provides integer vectors spanning the nullspace of A. Here we add vectors from the nullspace to improve the initial solution, maintaining Ax = b Heuristics find good integer linear combinations of nullspace vectors that provide strict improvement towards variable bounds or goals. IIA always produces an integer solution if one exists. In practice we usually achieve solutions close to the user goals, but there is no guarantee that the solution is optimal, nor even satisfies variable bounds, e.g. has positive intervals. We describe several algorithmic changes since first publication that tend to improve the final solution. The software is freely available.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Simultaneously improved J sc and V oc achieving 19.15% efficiency in ternary blend polymer solar cell containing a Y-type acceptor with thiophene based end groups

Simultaneously enhancing the short-circuit current density (J sc ) and open-circuit voltage (V oc ) of current state-of-the-art polymer solar cells (PSCs) containing wide bandgap polymers as donors and Y6 derivatives as acceptors is of great challenge but essential for further improvement of the photovoltaic performances. Here, in this work, two Y-type non-fullerene acceptors of BTP-T and BTP-TCl were designed and successfully synthesized with relatively weak electron-accepting thiophene based end groups, where blue-shifted absorption and upshifted LUMO energy levels were achieved to fill the well-known absorption gap at 700 nm of typical binary devices based Y-type molecules and rise the output voltage, respectively. Simultaneously increased J sc and V oc were achieved in ternary blend devices containing D18:BTP-eC9:BTP-TCl with a significantly improved PCE up to 19.15 %, which is over 7 % increase compared to the binary device. Our results illustrated the great potential of rational design of Y6 derivatives for constructing ternary PSCs to improve their performances.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Graphene nanoplatelets reinforced cement as a solution to leaky wellbores reinforcing weak points in hydrated Portland cement with graphene nanoparticles improves mechanical and chemical durability of wellbore cements

In this work, to improve the performance of wellbore cement under subsurface environments, graphene nanoplatelets (GNPs) were added in various percentages to Class-H cement slurry. Microstructural characterization of cement slurries cured at 90 °C and 95% RH indicates that GNP modifies the microstructure of hydrated cement by reinforcing pore spaces. As a result, the mechanical properties, such as Young's modulus and axial peak stress, obtained from high temperature triaxial compression tests are significantly improved based on different percentages of added GNPs. Furthermore, the hydrated 1 × 2 inch GNP- Portland cement cores tested under simulated deep wellbore conditions of high-temperature and high pressure (HTHP), appear to have a ductile-like behavior, when compared to a typical brittle nature of Portland cement pastes. From our observations and published data on graphene resistance to fracture, GNP addition to cement is evidently enhancing the flexibility of cement. These improvements would reduce the risks associated with wellbore cement deterioration and a consequent leakage in fossil fuel production, geothermal energy production, CO 2 storage as well as long-term sealing materials in plugging and abandonment of all wellbores at the end of their service life.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Bending and shear improvements in 3D-printed core sandwich composites through modification of resin uptake in the skin/core interphase region

Fused deposition modeling (FDM) printed polymers are rarely used as a structural material due to anisotropic and low mechanical properties compared with conventional composites. In recent years, greater need has been expressed for recycling of materials, such as recyclable FDM, at the end of service life to reduce environmental pollution and manufacture cost. However, how the amount of resin uptake in the skin and skin/core interphase affects the bending and shear performance of the sandwich composites when replacing the low strength and ductile core (conventional core) with a high strength and brittle core (FDM printed PLA (polylactic acid) core) still remains unclear. A new manufacturing routine is needed to improve the incorporation of FDM printed polymers in composite structures. In this work, FDM printed PLA was used as core material and sandwiched between two unidirectional glass fiber reinforced polymer (GFRP) skins to form a sandwich composite by compression-molding (CM) process, which provides a good manufacturing strategy for skin/core interphase modification. The significance of the CM process is proved by investigating the effect of resin uptake on bending and in-plane/out-of-plane shear performances. Current first order shear deformation (FSDT) theory lacks a direct connection between the in-plane shear stress and out-of-shear stress in the core region of sandwich composites. With the help of DIC, a connection between the in-plane shear and the out-of-plane shear strain was built and in-plane shear properties can acquire through out-of-plane shear properties, hence reducing the redundancy of sample preparation or the need for simulation. A significant improvement was found compared with the optimized resin uptake (Optimized resin uptake range: 20.43%–22.86 wt%) 3D-printed PLA core sandwich composite and lowest performance sandwich composite (Improvement: in-plane shear strength (~34%)/modulus (~29%), out-of-plane shear strength (~25%)/modulus (~31%), specific peak bending load (~19%)). Finally, compared with balsa core sandwich composites, the 3D-printed cores are suitable for use in composite sandwich structures in many applications with a satisfactory strength-to-weight ratio.

3D-printed core sandwich composite↗

DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗

DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Two trillion gallons: Fuel savings from fuel economy improvements to US light-duty vehicles, 1975–2018

Since 1975, the fuel economy of new light-duty vehicles sold in the U.S. has almost doubled. Fuel economy improvements on laboratory tests gradually became real improvements on the road as newer, more efficient vehicles replaced older less efficient ones. Fleet-wide fuel economy gains produced large fuel savings. In this paper, we show that fuel economy gains measured on laboratory test cycles, adjusted for on-road conditions and weighted by the distribution of vehicles by age and their relative use, closely match estimates by the Federal Highway Administration based primarily on traffic counts and motor fuel tax records. Furthermore, adjusting for the rebound effect of fuel economy on vehicle miles traveled, we estimate the fuel savings, CO 2 emissions reductions and dollars saved on fuel due to fuel economy improvements over the past 43 years. Through the end of 2018, estimated cumulative fuel savings amount to approximately 2 trillion gallons of gasoline. We estimate that roughly one-fifth of the savings can be attributed to gasoline price increases over the period and four-fifths to fuel economy and greenhouse gas (ghg) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information

Reliable near real-time precipitation estimates are essential for monitoring and managing of natural disasters such as floods. Quality of inputs and capability of the retrieval algorithm are two important aspects for developing satellite-based precipitation datasets. Most retrieval algorithms utilize infrared (IR) information as their input due to its fine spatiotemporal resolution and near-instantaneous availability. However, their sole reliance on IR information limits their capability to learn different mechanisms of precipitation during training, resulting in less accurate estimates. Moreover, recent advances in the field of machine learning offer attractive opportunities to improve the precipitation retrieval algorithms. This work investigates the effectiveness of adding geographical information (i.e. latitude and longitude) to IR information and the application of a U-Net-based convolutional neural network for improving the accuracy of retrieval algorithms. This research suggests that applying an appropriate CNN architecture on geographical and IR information provides an opportunity to improve the satellite-based precipitation products.

42 ENGINEERING↗

DOE OSTI2022

Improving energy performance metrics to maximize the benefits of disruptive technologies

Advances in appliance and equipment systems' technologies also cause changes in their technical characteristics that can affect energy consumption and associated greenhouse gas emissions. Energy performance evaluation methods that use testing and metrics can evolve to account for energy consumption contributed from new technological characteristics. However, there is no systematic effort to enable the advancement of test procedures and performance metrics to maximize the energy, climate, and financial benefits of disruptive technologies. Therefore, it is important for countries to regularly update their energy-efficiency policy programs, such as standards and labels, by improving test procedures and metrics to reflect the innovation in emerging technologies as well as to mitigate the risk of deploying obsolete technology. This paper shows how energy performance metrics have been improving in selected appliances and equipment and provides insights to design a systematic effort to improve metrics and test procedures at the speed of ongoing changes in technologies and markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Retrofitting stoves with forced jets of primary air improves speed, emissions, and efficiency: Evidence from six types of biomass cookstoves

Incorporating jets of forced air into biomass cookstove combustion has been shown to potentially decrease harmful emissions, leading to a variety of designs in recent years. These have shown mixed success in terms of real-world performance, usability, and durability. The Jet-Flame forced draft retrofit accessory was recently developed to implement forced jets of primary air at a low cost into a wide range of types of cookstoves using a small 1.5-W fan housed in a low-cost cast iron body to be inserted beneath the fuel bed of a biomass cooking fire. This research sought to quantify the potential efficiency and emissions performance impacts of the Jet-Flame when installed in six different types of biomass cookstoves (three open or shielded fires and three rocket stoves) versus the natural draft performance of each. The effect of the operating fan voltage was also measured. A series of tests following a modified ISO 19867-1:2018 protocol were performed in the laboratory using the Aprovecho Laboratory Emissions Measurement System (LEMS) equipped with additional oxygen and temperature sensors. Results for each stove carefully tended with a single layer of sticks showed that the global average PM 2.5 reduction with the Jet-Flame was 89 % relative to the natural draft cases, with larger relative improvements seen in the most rudimentary stoves. CO was reduced by a global average of 74 %, reaching tier 4 or 5 for all stoves. Thermal efficiency was also improved by 34 % when calculated without taking into account the energy content of the remaining char (or 21 % with char), illustrating the value of burning char to provide cooking energy rather than leaving it unburned in the combustion chamber as is common in many natural draft stoves. Time to boil was also reduced by 8 %. In addition, adjusting the voltage of the jet-flame assisted in modulating firepower, improving the usability of the stove. These results indicate a strong potential for the Jet-Flame to help reduce emissions and fuel consumption in a wide range of cookstove designs at a relatively low cost or need for changes in behavior, fuel, or cooking device. The unit also provides enhanced usability in terms of ease of startup, cooking speed, low PM emissions at high power, and burning char. Additional studies are needed to measure performance in the field and under a variety of operational conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Improving chiller performance and energy efficiency in hydrogen station operation by tuning the auxiliary cooling

In a hydrogen station that operates with direct fueling through the use of a 700 bar boost compressor, the outlet hydrogen temperature can significantly increase, stressing the chiller system. Here, this paper evaluates improvements that can be made to the auxiliary cooling system integrated with the compressor. Both theoretical modeling and experiments were performed at Cal State LA Hydrogen Research and Fueling Facility. The findings suggest that adjusting the auxiliary closed-loop cooling system from 15 °C to 10 °C reduced the station energy consumption and decreased the demand on the station chiller that needed to provide –20 °C hydrogen at the hose. The overall energy consumption for a single fueling reduced by between 2.86 and 9.43% for the set of experiments conducted. After the temperature of the closed-loop cooling system was reduced by 5 °C, the boost compressor outlet temperature dropped from 46-50 °C–40 °C and consequently at the hose the hydrogen temperature declined by 3 °C. Results were scaled up with a forecast on the number of daily refueling events. With a low number of daily fuelings, the proposed set-up showed a minor influence on the overall station energy consumption. However, the benefits were more pronounced for a connector station with sales at 180 kg/day, where the energy efficiency improved by between 1.4 and 5.5%, and even more so for a higher capacity station at 360 kg/day, where the improvement was between 2.9 and 8%.

08 HYDROGEN↗

DOE OSTI2021

Multi-objective optimization of low-GWP mixture composition and heat exchanger circuitry configuration for improved system performance and reduced refrigerant flammability

The recently introduced hydrofluoroolefin (HFO) refrigerants, including R1234yf and R1234ze(E), have significantly lower global warming potentials (GWPs) than traditional hydrofluorocarbon (HFC) refrigerants like R410A. However, prior tests show that direct drop-in of pure R1234yf or R1234ze(E) into equipment designed for R410A results in a decrease in heat exchanger capacity and the system coefficient of performance. The primary reason is the lower in-tube heat transfer performance of R1234yf and R1234ze(E) compared with that of R410A. To address this issue, previous studies have mixed the mildly flammable HFC R32 with HFOs to improve system performance, with HFC R125 also added to suppress flammability. Previous studies selected compositions based on simple cycle analyses and did not consider modifications of the heat exchanger circuitry configuration to adapt to the new refrigerants. This study presents a novel multi-objective optimization approach to design a refrigerant composition that maximizes energy efficiency within flammability and GWP limits. The approach in this work simultaneously optimizes mixture composition and heat exchanger circuitry configuration. A case study on a rooftop unit indicates that, compared with mixture-only optimization, simultaneous optimization of mixture and heat exchanger circuitry yields a 5.9% improvement in cycle efficiency and a 48.6% reduction in refrigerant flammability with a GWP of 268. Circuitry optimization using refrigerants with different temperature glides shows that the larger the temperature glide is, the larger EER improvement is obtained. The results show that zeotropic blends with a large temperature glide are more sensitive to the refrigerant circuitry than pure refrigerants and may suffer significant performance degradation with subpar heat exchanger circuitry design. The proposed optimization approach is generally applicable to mixtures with any number of components. Using this approach to design a HVAC system can yield higher system efficiency within flammability and GWP constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Recycled polyethylene and crumb rubber composites modified asphalt with improved aging resistance and thermal stability

Crumb rubbers (CR) and recycled Polyethylene (PE) are commonly used as modifiers to improve the asphalt properties. However, the addition of these modifiers individually may result in phase separation of PE and inadequate degradation of CR, which may not simultaneously satisfy the rheological and aging resistance of the binder blends. In this study, a type of CR/PE composites manufactured through melt extrusion procedures was adopted for the improvement of the modified binder blends. The modified binder blends after short-term (RTFO) and long-term (PAV) aging were collected for dynamic shear rheometer and bending beam rheometer tests. FTIR tests were also used to quantify the aging resistance, while differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were applied to evaluate the thermal behaviors of the binder blends. Optical microscopy tests were used to explore the modification mechanism and visualize the microstructures of original and PAV aged binder blends. Test results showed that CR/PE composites could significantly improve the aging resistance of the binder blends. The dispersed PE particles still interacted with each other and meanwhile worked with the diffused rubbery phase, which could form a similar TPEs network. The oxidation and high-temperature aging of such binder blends would strengthen the network that resisted the aging severity of the binder blends. Furthermore, it was also revealed that CR/PE modified asphalt could sustain more heat before a rapid degradation and the well-dispersed PE particles could interact with the diffused CR particles to form a network to resist aging.

02 PETROLEUM↗

DOE OSTI2024

Improving dairy manure hydrolysis and acidification through microbial community restructuring by adaptation to hyperthermophilic conditions

Dairy manure (DM) contributes significantly to greenhouse gas emissions and ecosystem degradation, yet its resistance to biodegradation hinders widespread bioprocessing applications. Lignocellulosic materials in DM pose a particular challenge because of their recalcitrance. Bioprocessing under hyperthermophilic (≥70 °C) conditions potentially offers an advantage over traditional fermentation temperatures due to enhanced activity of enzymes and the kinetics of enzymatic reactions. This can lead to a higher conversion rate and a greater extent of biomass hydrolysis and acidification. To test the validity of this hypothesis, the current study evaluated the efficacy of anaerobic hydrolysis and acidogenic fermentation of DM under mesophilic, thermophilic, and hyperthermophilic conditions. All inocula were adapted to corresponding temperatures but were derived from the same mesophilic source. Hyperthermophilic conditions resulted in superior DM hydrolysis efficiency (53%) compared to mesophilic (34%) and thermophilic (42%) conditions. The hyperthermophilic environment was particularly favorable to the decomposition of crude proteins and hemicellulose, which were reduced by 64% and 54%, respectively. Furthermore, hyperthermophilic fermentation also yielded the highest volatile fatty acid (VFA) production rate of 460 mg/L/day during the first four days, representing improvements of 50% and 90% over mesophilic and thermophilic conditions. In part, this was attributed to the enhanced production of branched-chain VFAs, including an increase of 6–10% in isobutyric acid and 12–13% in isovaleric acid. At hyperthermophilic conditions, however, there was no accumulation of VFAs during the days 5–8 of fermentation, which could be due to acetate conversion by the syntrophic acetate-oxidizing bacteria. A considerable gain in hydrolysis efficiency and VFA production rate were accompanied by a reduction in microbial diversity, which suggests that hyperthermophilic temperature is a favorable environment for the selection of organisms with enhanced DM hydrolysis and fermentation capabilities. A significantly increased relative abundance of xylanolytic Caldicoprobacter (23% of population) and proteolytic Thermovirga (9% of population) could be the major contributors to improved decomposition of hemicellulose and protein. As revealed by the techno-economic analysis, acidogenic fermentation of DM at 70 °C and a retention period of 4 days provides the greatest positive net present value, highest internal rate of return of 9.2%, and shortest investment payback period of 9 years. Furthermore, this study demonstrates that hyperthermophilic conditions enable superior deconstruction and bioconversion of lignocellulose-containing biomass into VFAs under reduced retention times, offering a promising approach for improving DM management and generating bioproducts.

09 BIOMASS FUELS↗