Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “process performance”

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.

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

At least 505 records · Page 28

An Investigation into the Effects of Process Conditions on the Tribological Performance of Pack Carburized Titanium with Limited Oxygen Diffusion

In the present study, a new pack carburization technique for titanium has been investigated. The aim of this treatment is to produce a titanium carbide/oxycarbide layer atop of an extended oxygen diffusion zone [α-Ti(O)]. The effects of treatment temperature and pack composition have been investigated in order to determine the optimal conditions required to grant the best tribological response. The resulting structural features were investigated with particular interest in the carbon and oxygen concentrations across the samples cross section. The optimization showed that a temperature of 925 °C with a pack composition of 1 part carbon to 1 part energizer produced surface capable of withstanding a contact pressure of ≈ 1.5 GPa for 1 h. The process resulted in TiC surface structure which offers enhanced hardness (2100 HV) and generates a low friction coefficient (μ ≈ 0.2) when in dry sliding contact with an alumina (Al{sub 2}O{sub 3}) ball. The process also produced an extended oxygen diffusion zone that helps to improve the load bearing capacity of the substrate.

36 MATERIALS SCIENCE↗

SU-G-JeP2-07: Fusion Optimization of Multi-Contrast MRI Scans for MR-Based Treatment Planning

Purpose: To develop an image fusion method using multiple contrast MRI scans for MR-based treatment planning. Methods: T1 weighted (T1-w), T2 weighted (T2-w) and diffusion weighted images (DWI) were acquired from liver cancer patient with breath-holding. Image fade correction and deformable image registration were performed using VelocityAI (Varian Medical Systems, CA). Registered images were normalized to mean voxel intensity for each image dataset. Contrast to noise ratio (CNR) between tumor and liver was quantified. Tumor area was defined as the GTV contoured by physicians. Normal liver area with equivalent dimension was used as background. Noise was defined by the standard deviation of voxel intensities in the same liver area. Linear weightings were applied to T1-w, T2-w and DWI images to generate composite image and CNR was calculated for each composite image. Optimization process were performed to achieve different clinical goals. Results: With a goal of maximizing tumor contrast, the composite image achieved a 7–12 fold increase in tumor CNR (142.8 vs. −2.3, 11.4 and 20.6 for T1-w, T2-w and DWI only, respectively), while anatomical details were largely invisible. With a weighting combination of 100%, −10% and −10%, respectively, tumor contrast was enhanced from −2.3 to −5.4, while the anatomical details were clear. With a weighting combination of 25%, 20% and 55%, balanced tumor contrast and anatomy was achieved. Conclusion: We have investigated the feasibility of performing image fusion optimization on multiple contrast MRI images. This mechanism could help utilize multiple contrast MRI scans to potentially facilitate future MR-based treatment planning.

60 APPLIED LIFE SCIENCES↗

Application of Black Silicon for Nanostructure-Initiator Mass Spectrometry

Nanostructure-initiator mass spectrometry (NIMS) is a matrix-free desorption/ionization technique with high sensitivity for small molecules. Surface preparation has relied on hydrofluoric acid (HF) electrochemical etching which is undesirable given the significant safety controls required in this specialized process. Here in this study, we examine a conventional and widely used process for producing black silicon based on sulfur hexafluoride/oxygen (SF 6 /O 2 ) inductively coupled plasma (ICP) etching at cryogenic temperatures and we find it to be suitable for NIMS. A systematic study varying parameters in the plasma etching process was performed to understand the relationship of black silicon morphology and its sensitivity as a NIMS substrate. The results suggest that a combination of higher silicon temperature and oxygen flow rate gives rise to the formation of black silicon with fine pillar structures, whose aspect ratio are ~8.7 and depth are <1 μm resulting in higher NIMS sensitivity which is attributed to surface restructuring caused by their low melting point upon laser irradiation. Interestingly, we find selectivity of these black silicon substrates to different analytes depending on the etching parameters. Though, the sensitivity of the dry etching process is lower than the traditional "wet" electrochemical etching process, it is suitable for many applications and is prepared using conventional equipment without the use of HF.

36 MATERIALS SCIENCE↗

Pilger Mill Processing

The Nuclear Technology Research & Development program of the Office of Nuclear Energy has implemented a program to develop an advanced reactor cladding fabrication capability by using the extrusion and pilgering processes. Oxide-dispersion strengthened (ODS) steels are a promising class of advanced materials, but processes need to be developed to produce tubing for these advanced alloys. The Pacific Northwest National Laboratory (PNNL) has converted its rolling mill into a lab-scale pilger mill, which required designing pilger tooling and rolls that contained multiple pilgering grooves and designing a servo-driven feed mechanism. Upon assembling and checking out the system, pilgering runs on stainless steel, MA956, and 14YWT iron (Fe)-based alloys were completed. The feed rates and rotation rates were established, the reduction schedules were determined. This report will provide a description of the lab-scale pilger mill performance and processing results for the stainless steel, MA956, and 14YWT alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Shelf-life of ball-milled catalyst inks for the fabrication of fuel cell electrodes

A major factor driving fuel cell costs is the quantity of precious metal required. Therefore, it is important to understand a timeframe where inks can be reused. Here, in this work, we explore differences between a freshly prepared catalyst ink and one that has been stored for over a year – comparing ink properties, cathode catalyst layer microstructure, and their respective fuel cell performance. Ink studies revealed smaller agglomerate sizes and a decrease in shear viscosity for the aged ink. Longer storage time also results in fewer cracks and a more uniform ionomer distribution, as evidenced by microscopy characterization of rod-coated electrodes. Lastly, polarization curves show improved performance at higher current densities for the electrode prepared from the aged ink. We rationalize such effect in terms of enhanced ionomer adsorption onto the catalyst over time.

08 HYDROGEN↗

Slipstream pilot-scale demonstration of a novel amine-based post-combustion technology for carbon dioxide capture from coal-fired power plant flue gas

Post-combustion CO 2 capture (PCC) technology offers flexibility to treat the flue gas from both existing and new coal-fired power plants and can be applied to treat all or a portion of the flue gas. Solvent-based technologies are today the leading option for PCC from commercial coal-fired power plants as they have been applied in large-scale in other applications. Linde and BASF have been working together to develop and further improve a PCC process incorporating BASF’s novel aqueous amine-based solvent technology. This technology offers significant benefits compared to other solvent-based processes as it aims to reduce the regeneration energy requirements using novel solvents that are very stable under the coal-fired power plant feed gas conditions. BASF has developed the desired solvent based on the evaluation of a large number of candidates. In addition, long-term small pilot-scale testing of the BASF solvent has been performed on a lignite-fired flue gas. In coordination with BASF, Linde has evaluated a number of options for capital cost reduction in large engineered systems for solvent-based PCC technology. This report provides a summary of the work performed and results from a project supported by the US DOE (DE-FE0007453) for the pilot-scale demonstration of a Linde-BASF PCC technology using coal-fired power plant flue gas at a 1-1.5 MWe scale in Wilsonville, AL at the National Carbon Capture Center (NCCC). Following a project kick-off meeting in November 2011 and the conclusion of pilot plant design and engineering in February 2013, mechanical completion of the pilot plant was achieved in July 2014, and final commissioning activities were completed to enable start-up of operations in January 2015. Parametric tests were performed from January to December 2015 to determine optimal test conditions and evaluate process performance over a variety of operation parameters. A long-duration 1500-hour continuous test campaign was performed from May to August 2016 at a selected process condition to evaluate process performance and solvent stability over a longer period similar to how the process would operate as a continuously running large-scale PCC plant. The pilot plant integrated a number of unique features of the Linde-BASF technology aimed at lowering overall energy consumption and capital costs. During the overall test period including startup, parametric testing and long-duration testing, the pilot plant was operated for a total of 6,764 hours out of which testing with flue gas was performed for 4,109 hours. The pilot plant testing demonstrated all of the performance targets including CO 2 capture rate exceeding 90%, CO 2 purity exceeding 99.9 mol% (dry), flue gas processing capacity up to 15,500 lbs/hr (equivalent to 1.5 MWe capacity slipstream), regeneration energy as low as 2.7 GJ/tonne CO 2 , and regenerator operating pressure up to 3.4 bara. Excellent solvent stability performance data was measured and verified by Linde and BASF during both test campaigns. In addition to process data, significant operational learnings were gained from pilot tests that will contribute greatly to the commercial success of PCC. Based on a thorough techno-economic assessment (TEA) of the Linde-BASF PCC process integrated with a 550 MWe supercritical coal-fired power plant, the net efficiency of the integrated power plant with CO 2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 4], and is further increased to 31.4% using a Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced stripper interstage heater (SIH) configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the cost of electricity (COE) and cost of CO 2 captured from $147.25/MWh and $56.49/MT CO 2 , respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO 2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO 2 captured can be further reduced to $125.51/MWh and $39.90/MT CO 2 for a further optimized PCC process defined as LB1-CREB. Most notably, the Linde-BASF process options assessed have already demonstrated the potential to lower the cost of CO 2 captured below the DOE target of $40/MT CO 2 at the 550 MWe scale for second generation PCC technologies. Project organization, structure, goals, tasks, accomplishments, process criteria and milestones will be presented in this report along with highlights and key results from parametric and long-duration testing of the Linde-BASF PCC pilot. The parametric and long-duration testing campaigns were aimed at validating the performance of the PCC technology against targets determined from a preliminary techno-economic assessment. The stability of the solvent with extended operation in a realistic power plant setting was measured with performance verified. Additionally, general solvent classification information, process operating conditions, normalized solvent performance data, solvent stability test results, flue gas conditions data, CO 2 purity data in the gaseous product stream, steam requirements and process flow diagrams, and updated process economic data for a scaled-up 550 MWe supercritical power plant with CO 2 capture are presented and discussed in this report.

20 FOSSIL-FUELED POWER PLANTS↗

Electro-strengthening of the additively manufactured Ti–6Al–4V alloy

Structure-property-processing relationship has been studied in additively manufactured Ti–6Al–4V alloy. The processing was performed using in-situ electron microscope (EM) at a moderate current density of 5 × 105 A/cm2 applied for 5 min, and by suppressing Joule heating with massive heat sinks such that the temperature rise was <180 °C and the mechanical properties were not compromised. Overall, the results show that while the grain size increased by ~15%, the nanohardness increased by 16%. This is attributed to the pronounced dislocation generation, regeneration, and clustering as well as defect healing. Ultimately, there is a reduction in the residual strain and a significant increase in the intrinsic strength as evidenced by the high Taylor factor of the electric current processed specimen. This novel processing technique represents an alternative pathway for active controlling of microstructure and internal defects for parts that might be sensitive to high-temperature processing or conventional methods.

36 MATERIALS SCIENCE↗

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗

Impact of polymer additives on crack mitigation of rod-coated fuel cell cathode catalyst layers

Cracks in catalyst layers (CLs) are a potential source of long-term failure in a fuel cell membrane electrode assembly (MEA). While modifications to the CL ink formulation can affect the degree of cracking, these changes may lead to lower initial performance than their cracked analogues due to the established link between formulation and performance. In this work, we explored the use of polymeric additives to mitigate CL cracks. Small quantities of poly (acrylic acid), poly (ethylene oxide), poly (methyl methacrylate), or poly (vinyl alcohol) - 5 wt% relative to ionomer mass - were added to the ink prior to its final mixing. Poly (vinyl alcohol) resulted in crack-free CLs, whereas the other polymers resulted in CLs with similar crack percentages as the control CL. Through a combination of transmission electron microscopy, X-ray computed tomography, and infrared spectroscopy, we ascribed the crack-mitigating mechanism of poly (vinyl alcohol) to its ability to hydrogen-bond with Nafion, the ion conducting polymer binder in the catalyst ink. Initial performance of this non-cracked electrode exhibited nearly identical electrochemical behavior to its cracked counterpart, demonstrating that PVA additives successfully reduce cracks while maintaining cell initial performance.

30 DIRECT ENERGY CONVERSION↗

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗

Superplasticizer to layered calcium aluminate hydrate interface characterized using model organic molecules

Ten organic molecule models simulating the chemical functions of commercial superplasticizers used in the cement/concrete industry were intercalated into lamellar calcium aluminate hydrates to synthesize hybrid AFm phases. AFm phases, encountered in cement hydration chemistry, belong to the large Layered Double Hydroxide (LDH) family. The intercalation process was performed using the anion exchange method. The affinities of the model molecules toward the AFm mineral layers, [Ca{sub 2}Al(OH){sub 6}]{sup +}, were compared using several complementary techniques. They display the following tendencies: –PO{sub 3}{sup 2-} > –SO{sub 3}{sup -} > –CO{sub 2}{sup -} for the hydrophilic parts and heptyl-R > phenyl-R > pentyl-R > ethyl-R for the hydrophobic parts. The organic-inorganic interface of the hybrid AFm phases was achieved. The organic molecule arrangement is either perpendicular or parallel to the inorganic main layer, resulting in various connection modes, from intercalation to grafting. The results enable a better understanding of the chemical reactivity of the utilized superplasticizers during the concrete setting process.

36 MATERIALS SCIENCE↗

Consolidating WLCG topology and configuration in the Computing Resource Information Catalogue

Here, the Worldwide LHC Computing Grid infrastructure links about 200 participating computing centres affiliated with several partner projects. It is built by integrating heterogeneous computer and storage resources in diverse data centres all over the world and provides CPU and storage capacity to the LHC experiments to perform data processing and physics analysis. In order to be used by the experiments, these distributed resources should be well described, which implies easy service discovery and detailed description of service configuration. Currently this information is scattered over multiple generic information sources like GOCDB, OIM, BDII and experiment-specific information systems. Such a model does not allow to validate topology and configuration information easily. Moreover, information in various sources is not always consistent. Finally, the evolution of computing technologies introduces new challenges. Experiments are more and more relying on opportunistic resources, which by their nature are more dynamic and should also be well described in the WLCG information system. This contribution describes the new WLCG configuration service CRIC (Computing Resource Information Catalogue) which collects information from various information providers, performs validation and provides a consistent set of UIs and APIs to the LHC VOs for service discovery and usage configuration. The main requirements for CRIC are simplicity, agility and robustness. CRIC should be able to be quickly adapted to new types of computing resources, new information sources, and allow for new data structures to be implemented easily following the evolution of the computing models and operations of the experiments.

97 MATHEMATICS AND COMPUTING↗

Nonlinear dynamics of C–terminal tails in cellular microtubules

The mechanical and electrical properties, and information processing capabilities of microtubules are the permanent subject of interest for carrying out experiments in vitro and in silico, as well as for theoretical attempts to elucidate the underlying processes. In this paper, we developed a new model of the mechano–electrical waves elicited in the rows of very flexible C–terminal tails which decorate the outer surface of each microtubule. The fact that C–terminal tails play very diverse roles in many cellular functions, such as recruitment of motor proteins and microtubule–associated proteins, motivated us to consider their collective dynamics as the source of localized waves aimed for communication between microtubule and associated proteins. Our approach is based on the ferroelectric liquid crystal model and it leads to the effective asymmetric double-well potential which brings about the conditions for the appearance of kink–waves conducted by intrinsic electric fields embedded in microtubules. These kinks can serve as the signals for control and regulation of intracellular traffic along microtubules performed by processive motions of motor proteins, primarly from kinesin and dynein families. On the other hand, they can be precursors for initiation of dynamical instability of microtubules by recruiting the proper proteins responsible for the depolymerization process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Challenges of Monte Carlo Transport

These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and, finally, the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗

Microstructural evolution and intermetallic formation in Zn-3Mg (wt%) powder mixture processed by high-pressure torsion

Severe plastic deformation (SPD) techniques have been used extensively over the past 40 years for producing strong metals and alloys. High-pressure torsion (HPT) is one of the most promising SPD techniques for achieving high strength through nanoscale grain refinement and phase transformation. In this research, a mixture of pure zinc (Zn) and magnesium (Mg) powders, Zn-3Mg (wt%), was HPT-processed under a pressure of 6 GPa for 1, 5, 10, 20, and 30 turns at room temperature to achieve a high strength biodegradable material. In order to understand the effects of pre-consolidation on the resulting microstructure and hardness, HPT processing was performed on loose powders placed in the die and also on a pre-compacted powder mixture and the resulting HPT disks were characterized by X-ray diffraction, scanning electron microscopy, atom probe tomography, and Vickers microhardness. In both cases, the HPT disk microstructures contained nanoscale grains, and stable and metastable strain-induced intermetallics, but an unusual softening appeared at large shear strains. Grain size, grain morphology, and the formation of different intermetallics were analyzed to explain the unusual hardness distribution, and it was found that an inverse Hall-Petch relationship between hardness and grain size exists. It is suggested that thermally-activated phenomena such as grain boundary sliding contributed to the strain-induced softening of this nano-structured biomaterial due to its low melting point. Finally, the current results are compared with those for HPT-processed cast alloys and hybrids of the same composition.

36 MATERIALS SCIENCE↗

Theoretical insights into the selective oxidation of methane to methanol in copper-exchanged mordenite

Selective oxidation of methane to methanol is one of the most difficult chemical processes to perform. A potential group of catalysts to achieve CH 4 partial oxidation are Cu-exchanged zeolites mimicking the active structure of the enzyme methane monooxygenase. However, the details of this conversion, including the structure of the active site, are still under debate. In this contribution, periodic density functional theory (DFT) methods were employed to explore the molecular features of the selective oxidation of methane to methanol catalyzed by Cu-exchanged mordenite (Cu-MOR). We focused on two types of previously suggested active species, CuOCu and CuOOCu. Our calculations indicate that the formation of CuOCu is more feasible than that of CuOOCu. In addition, a much lower C–H dissociation barrier is located on the former active site, indicating that C–H bond activation is easily achieved with CuOCu. We calculated the energy barriers of all elementary steps for the entire process, including catalyst activation, CH 4 activation, and CH 3 OH desorption. Finally, our calculations are in agreement with experimental observations and present the first theoretical study examining the entire process of selective oxidation of methane to methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering of holocellulase in biomass-degrading fungi for sustainable biofuel production

Biofuels, such as bioethanol, are a clean and sustainable form of energy and have emerged as a viable alternative to fossil fuels. Plant biomass is an important raw material for the production of clean and renewable energy. The holocellulose contained in the composition of plants may be broken down into simple sugars, such as glucose, which are fermented by yeast to produce bioethanol. The conversion of glucose polymers into fermentable sugars is accomplished by enzymes known as holocellulases, which are produced by lignocellulolytic fungi. These enzymes act synergistically for the efficient degradation of cellulose polymers, and the fine and coordinated regulation of this process is performed by transcription factors (TFs). TFs are regulatory proteins that bind to the promoter region of their target genes (CAZymes, sugar transporters, signaling proteins, other TFs, etc.) to induce or repress their transcription. This review aims to understand the main regulatory mechanisms involved in plant biomass degradation by the most studied lignocellulolytic fungi Trichoderma sp., Aspergillus sp., Penicillium sp., and Neurospora crassa. In this context, the most studied TFs related to holocellulose degradation and genetic modification of TFs or promoters as a valuable tool to improve enzyme production for biotechnological purposes have been discussed. Furthermore, this review enables the expansion of knowledge on the regulation of the cellulolytic system of filamentous fungi and the application of this knowledge to the improvement of numerous bioproducts. Engineering TFs and promoters may yield more efficient strains that may be active in plant biomass hydrolysis. In this way, the technological processes for obtaining ethanol from lignocellulose may become more commercially viable.

09 BIOMASS FUELS↗