Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “research methods”

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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CROCUS High-Frequency Measurements of CO₂, H₂O, Wind, and Temperature at University of Illinois Chicago

As of April 9, 2026: this dataset is currently being versioned to include data up to March 31, 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. Raw atmospheric measurements collected at the University of Illinois Chicago (UIC) as part of the Community Research on Climate and Urban Science (CROCUS) project. The data includes high-frequency measurements of carbon dioxide (CO₂) concentration, water vapor (H₂O) concentration, wind speed (U, V, W components), temperature, and atmospheric pressure. These raw data are recorded by the LI-7500DS Open Path CO₂/H₂O Analyzer and a sonic anemometer at a 10 Hz acquisition frequency, providing the necessary inputs for calculating fluxes of CO₂, H₂O, heat, and momentum. In addition to gas concentration measurements, the dataset includes diagnostic information from the instruments, including absorptance, sample and reference signals, and diagnostic values. The data were collected to study urban atmospheric conditions and contribute to flux calculations for urban climate research. These measurements form the basis for calculating 30-minute average fluxes of key atmospheric variables using the eddy covariance method. This dataset provides critical raw input data for researchers interested in atmospheric fluxes, urban air quality, and the interaction between the urban environment and atmospheric processes. The data is part of the U.S. Department of Energy’s Biological and Environmental Research (BER) program, under the CROCUS Urban Integrated Field Laboratory (UIFL) project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Synthesis and characteristics of porous ceramic tubes: a comparison of centrifugal casting and cold isostatic pressing methods

Short porous ceramic tubes in small quantities are needed for membrane-related research and development efforts and can be synthesized by centrifugal casting (CC) or cold isostatic pressing (CIP) methods. Here, this work evaluates the characteristics of porous ceramic tubes prepared by both methods and provides a strategy for selecting the proper method for ceramic tube fabrication, depending on its application. Samarium-doped ceria (SDC) with an average crystallite size of 10 nm was synthesized by a citrate method and used to make porous SDC tubes by the CC and CIP methods under different conditions. Porous SDC tubes were prepared from an aqueous suspension of the SDC powder with polyvinyl alcohol (PVA) using a cylindrical metallic mold, centrifugated at 4000–6000 rpm, followed by sintering in 1200–1500 °C. SDC tubes were also made by the CIP method from the SDC powder placed inside a cylindrical rubber bag followed by isostatic compression at 1379 bar. The pore structure of the SDC tubes was characterized by helium permeation and liquid nitrogen Archimedes method. Due to high compression pressure giving a low porosity green tube, the CIP method with lower sintering temperature produces SDC tubes with much lower porosity and average pore size and similar tortuosity compared to the CC methods. The CIP method should be used to prepare low porosity or dense ceramic tubes, and the CC method should be used for preparing high-porosity ceramic tubes or tubes with pore gradient tube wall.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Application of deep learning methods for beam size control during user operation at the Advanced Light Source

Past research at the Advanced Light Source (ALS) provided a proof-of-principle demonstration that deep learning methods could be effectively employed to compensate for the significant perturbations to the transverse electron beam size induced by user-controlled adjustments of the insertion devices. However, incorporating these methods into the ALS’ daily operations has faced notable challenges. The complexity of the system’s operational requirements and the significant upkeep demands has restricted their sustained application during user operation. Here, we introduce the development of a more robust neural network (NN)-based algorithm that utilizes a novel online fine-tuning approach and its systematic integration into the day-to-day machine operations. Our analysis emphasizes the process of NN model selection, demonstrates the superior performance of the NN-based method over traditional feedback methods, and examines the effectiveness and resilience of the new algorithm during user-operation scenarios. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Flash Heating of a Hollow Rod to Determine Thermal Properties

In a nuclear reactor, prolonged exposure to high neutron flux levels can change material properties of reactor components. Due to the danger posed to personnel by highly radioactive components such as spent fuel, noncontact methods must be used to determine these properties. The objective of the current research is to test the viability of using a flash-heating method to determine the thermal diffusivity of a silicon carbide (SiC) tube, which could be used as cladding for a nuclear fuel rod. The flash-heating experiment was conducted at Oak Ridge National Laboratory and temperature results were analyzed as a two-Dimensional cross section which assumed axial symmetry. The model was fitted iteratively to the temperature measurements using nonlinear regression which required values for thermal diffusivity, Biot number and a term to determine the magnitude of the heat absorbed by the flash. The method could be expanded in the future to estimate the thermal diffusivity of spent nuclear fuel rods in an effort to increase the certainty of new reactor designs using precise thermal properties throughout the core life. A statistical analysis of the results of this work is provided as part of the analysis.

McMasters, Robert L [Virginia Military Institute, ↗
DOE OSTI2020

Structure and Dynamics of Domains in Ferroelectric Nanostructures – Phase-Field Modeling (Final Technical Report)

Domain pattern formation is one of the most common phenomena in nature and is a topic of immense interest in many fields ranging from materials science and physics to chemistry and biology. This DOE sponsored research project explored the basic science concerning the thermodynamic stability of mesoscale polarization domain patterns and their temporal evolution mechanisms during formation and subsequent switching in ferroelectric nanostructures and heterostructures. The project employed the computational phase-field method in combination of microelasticity and electrostatic theories. The research was carried out in close collaboration with a number of experimental groups who used High Resolution Transmission Electron Microscopy (HRTEM), in situ TEM with Scanning Probe Microscopy (SPM), or Piezoresponse Force Microscopy (PFM) to characterize the domain structures and dynamics of ferroelectric thin films and heterostructures and who grow high-quality ferroelectric and multiferroic thin films using advanced growth techniques such as Molecular Beam Epitaxy (MBE), Pulsed Laser Deposition (PLLD), and sputtering. The research efforts of the project help establish the phase-field method as the most powerful method for understanding and predicting domain structures in ferroelectric thin films and nanostructures. The findings of the project led to the basic understanding of stability and switching mechanisms of ferroelectric domains under different mechanical boundary conditions and under either homogeneous capacitor configurations or local fields using metallic probes as electrodes and the emergence of charged domain walls during domain switching. The project predicted the spatial length scales, temperature ranges, and electromechanical conditions for different polar states in heterostructures and guided the discovery of both transient and stable novel polarization states containing vortex lattices in oxide superlattices. The project resulted in 134 journal publications and 6 PhD theses with all the PhD graduates currently working in either academia or industry within the United States. The basic understanding on the stability of mesoscale polar states and pattern evolution achieved by the project improved our ability to control and engineer properties of ferroelectric thin films and heterostructures for potential applications in nanoscale electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Conceptual monopile and tower sizing for the IEA Wind Task 37 Borssele reference wind farm

This paper explores the preliminary design of the support structures for the IEA Wind Task 37 reference wind farm at the Borssele site III and IV. The study looks at two different design methods that might be used within larger wind farm system design optimization (i.e. lay-out, electrical systems, etc.). The first consists of a scaling tool that scales a detailed design according to the rated power, water depth, hub height and rotor diameter. The second is a physics-based optimization approach that relies on the WISDEM® design tool. This research compares the results of these two methods for the design of both the tower and monopile of the IEA 10-MW and 15-MW reference wind turbines at a range of sea depths (25 m, 30 m, 35 m, 40 m). The two tools yield very similar results in terms of monopile base diameter, support structure natural frequency and mass. WISDEM is then used to also investigate the sensitivity of the design to the tower top forces, wave conditions and the soil conditions. It is shown that tower top forces dominate the design. In general, large diameter structures can carry additional costs associated with manufacturing and transportation requirements. Thus, the paper is concluded with a trade-off study between mass and diameter that quantifies the effect of the reduction in monopile diameter with the increase in structural mass.

WIND ENERGY↗
DOE OSTI2026

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗
DOE OSTI2021

Zirconium-diboride silicon-carbide composites: A review

Zirconium diboride (ZrB 2 ) and silicon carbide (SiC) composites have long been of interest since it was observed that ZrB 2 improved the thermal shock resistance of SiC. However, processing of these materials can be difficult due to high and different sintering temperatures and differences in the thermodynamic stability of each material. ZrB 2 –SiC composites have been processed in a variety of ways including hot-pressing, spark-plasma sintering, reactive melt infiltration, pack cementation, chemical vapor deposition, chemical vapor infiltration, stereolithography, direct ink writing, selective laser sintering, electron beam melting, and binder jet additive manufacturing. Each manufacturing method has its own pros and cons. This review serves to summarize more than 60 years of research and provide a coherent resource for the variety of methods and advancements in development of ZrB 2 –SiC composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies

Changing power system configuration may result in load shed recovery (LSR) because topology change can provide power flow control in meshed network. Some topologies may favor generation redispatch as compared to others and can eliminate line congestion which leads to LSR. One of the known methods for topology change is called transmission switching (TS) and research conducted in the past showed that TS is an effective means of mitigating load shedding. Another method of topology control is intentional islanding (IIS). In this manuscript, we explore IIS as a potential solution for LSR. IIS based on generator coherency has been presented in literature for mitigating cascading failures. However, IIS has not been explored solely as a LSR mechanism. In this paper, we compare the LSR based on IIS with well known LSR algorithm based on TS. The comparison is performed for IEEE 39-bus system and IEEE 118- bus system. The results show that IIS has a potential to perform better than TS in terms of computational efficiency and LSR.

42 ENGINEERING↗
DOE OSTI2025

Predicting soot and radiation in pool fires using flamelet methods

This work provides an overview of the ongoing research to better estimate radiation and soot in large-scale pool fires. The core focus of this presentation is on improvements to models for novel physics at larger scales.

Meehan, Michael Alexander [Sandia National Laborat↗
DOE OSTI2022

A Framework for Effective Science Communication and Outreach Strategies and Dissemination of Research Findings for Marine Energy Projects

Marine energy is an emerging renewable energy industry with the potential to produce 2300 terawatt-hours per year from resources within the United States. As development and testing of marine energy devices advance, regulatory and permitting decision-makers are concerned about the uncertainty surrounding the potential environmental effects resulting from the introduction of these novel devices in coastal and riverine environments. The Triton Initiative researches and provides recommendations for environmental monitoring technologies and methods to inform industry stakeholders with the data necessary to permit the testing of marine energy systems. Effective dissemination of the research findings is essential for improving the accessibility of data to stakeholders who may use the results to inform policy decisions, yet few frameworks for conducting science communications for marine energy projects exist. In this paper, we present tools, channels, and tactics for developing a science communication framework for marine energy projects, or similar areas of study, using the Triton Initiative’s pilot science communication program as a case study. By leveraging existing bodies of work in disciplines such as communications theory, marketing, public relations, and social science, the presented framework includes audience identification and analysis; channel development, including a website, blog, newsletter, social media, and webinars and presentations; and metrics for determining success. Outcomes from one year of Triton’s case study are presented, including the most effective tactics and lessons learned.

communication framework↗
DOE OSTI2022

Application of Manufacturing Quality Management Principles to PV System Installations

To help SETO/DOE achieve its goals, the IBTS team proposed a project addressing system reliability by improving installation standards and quality management. The proposed approach was designed to help achieve measurable reductions in installation defect density and improvements in the performance of PV systems by optimizing design and installation of residential and commercial PV systems. This approach addressed the soft costs associated with installations and quality management. The project demonstrated improved system reliability and reduced PV system installation costs. The software developed improved operations, decreased risk, and increased the overall value of PV systems across their lifecycle. The project used several data collection methods, including extensive industry surveys, face-to-face high-level interviews at industry conferences, stakeholder teleconferences, and in-depth interviews conducted by IBTS staff. Results from the research found the industry needs a uniform assessment method for national providers to be more efficient; the software should support both code officials and installers; most industry stakeholders would find value in a centralized software system that allows them to collect, report, and review information on in-process and completed solar installations; and mobile solutions that bridge existing knowledge gaps with inspectors and integrate with existing methodologies (such as permitting software) are of great value. The software solution developed is web-based, allowing for national access, and is built on a Google Firebase platform that can handle significant users and data. It can be used onsite or remotely, allowing for code compliance to continue despite ongoing pandemic related delays or shutdowns for local economies. The information provided by the software tool allows users to uniformly assess a system for compliance and use that aggregated data to identify training topics or create internal process designed to improving issues and reducing occurrence. This solution has multiple benefits in managing quality at time of use and promoting an increase in future safety and quality through education. Perhaps most importantly, this software increases public safety by ensuring compliance of installed systems and allows for local AHJs to remotely engage specialized and qualified solar specific expertise for oversite of the installation in their jurisdictions. Data analysis provides the quality feedback loop identifying the root cause of failure and drives installation practices to improve through training and education, resulting in systems with higher performance, greater reliability, and reduced operations and maintenance costs. With the successful completion of this project, the industry can expect reduced soft costs and increased performance and safety and will ultimately benefit from longer performing systems that cost less to operate.

14 SOLAR ENERGY↗
DOE OSTI2025

Explaining word embeddings with perfect fidelity: a case study in predicting research impact

The best-performing approaches for scholarly document quality prediction are based on embedding models. In addition to their performance when used in classifiers, embedding models can also provide predictions even for words that were not contained in the labelled training data for the classification model, which is important in the context of the ever-evolving research terminology. Although model-agnostic explanation methods, such as Local interpretable model-agnostic explanations, can be applied to explain machine learning classifiers trained on embedding models, these produce results with questionable correspondence to the model. We introduce a new feature importance method, Self-Model Entities Rated (SMER), for logistic regression-based classification models trained on word embeddings. We show that SMER has theoretically perfect fidelity with the explained model, as the average of logits of SMER scores for individual words (SMER explanation) exactly corresponds to the logit of the prediction of the explained model. Quantitative and qualitative evaluation is performed through five diverse experiments conducted on 50,000 research articles (papers) from the CORD-19 corpus. In conclusion, through an AOPC curve analysis, we experimentally demonstrate that SMER produces better explanations than LIME, SHAP and global tree surrogates.

Coarse-grained models↗
DOE OSTI2023

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Alternate Methods for Cleaning Zirconium Plate

The United States High Performance Research Reactor Conversion Program identified the need to transition from highly enriched uranium fuel to lowly enriched uranium fuel for high power research and civil reactors. One of the fuel configurations selected for these reactors was a uranium (U) foil alloyed with 10% molybdenum (Mo). The U-10Mo fuel foil was then covered with a zirconium (Zr) interlayer and pressed into an aluminum cladding. Idaho National Laboratory prescribed a need to remove surface oxidation on the Zr prior to bonding it with U-10Mo fuel foil. To determine the best method of oxidation removal, a variety of polishing methods, including hand polishing with a diamond paste or Scotch-Brite™ pads, mechanically wet-polishing with abrasive belts, and chemical etching with hydrofluoric/nitric acid mixtures, were investigated on pre-polished Zircaloy 702 sheets purchased directly from the manufacturer. No change in surface roughness was detected using any of these methods relative to the as-received material. In fact, scanning electron microscopy detected grit from hand polishing with Amplex Grade 30 waste soluble diamond paste and Scotch-Brite™ pads. Visible staining was found, and fluorine detected via X-ray photoelectron spectroscopy on the flash etching samples. These contaminants were not seen on the as-received material. In addition to the need to remove the oxide layer on the Zr prior to co-rolling, there are concerns that the Neolube debonding agent on the co-rolling can may contaminate the Zr surface after co-rolling. The experimental results found that zirconium in contact with Neolube coated steel plates was easily cleaning with ethanol wiping after heat treated and no carbide inclusions remained on the surface. Overall, all cleaning methods tested did not significantly change the surface roughness of the plates or reduce the oxide layer present on the zirconium. Carbon was found on all the samples, before and after cleaning, except for the flash etch samples which detected fluorine instead. The insignificant changes seen in the cleaned plates relative to the as received plates question the need for cleaning prior to rolling. Further investigation in the requirements for cleaning at this step is recommended. Current methods for cleaning the surface after hot rolling with alcohol appear sufficient. After hot rolling, if Neolube does peel off the can and onto the zirconium coated foil surface, a dry abrasive or diamond paste polish is not recommended due to the chance of abrasive being embedded into the surface. However, the ability of an etchant to lift the lubricant off the zirconium surface indicates that a spot etch method could work to clean specific spots where Neolube is present, if the need arises.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2021

Easier Access to Functional Furans

Traditional furan alkylation utilizes catalyst materials are unsafe, produce hazardous waste, and yield low reaction products. Researchers at Los Alamos National Laboratory have developed a new method to enable industries to produce valuable chemicals from biomass more safely with higher yields and less waste. This method has been successfully demonstrated on the benchtop, and is ready for testing to scale up for industrial synthesis applications. Los Alamos is seeking a licensee to scale this technology in-house, or a Cooperative Research and Development Agreement (CRADA) partner to scale the method within the Laboratory for a specific purpose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity)

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity) project aims to demonstrate a novel, scalable method for removing carbon dioxide (CO 2 ) directly from ambient air and delivering it to cyanobacterial cultures to produce commodity biofuel, mid-value protein for supplements, and high value phycocyanin (PC), a natural blue colorant (Figure A). This approach uses low-cost, reusable anion exchange polymers embedded in modular mesh packets, which capture CO 2 during drying cycles when exposed to ambient air, and release concentrated CO 2 into aqueous cultivation systems. The project addresses a critical challenge in energy research needed for developing sustainable, economically viable methods of Direct Air Capture (DAC) that can be integrated with bio-based systems for fuel and chemical production. AUDACity contributes to scientific understanding by integrating materials chemistry, cyanobacterial biology, and system engineering to create a distributed CO 2 delivery platform. Key insights have emerged around the design of biocompatible sorbents, optimization of CO 2 capture-release cycles, and durability of packet-based delivery systems under outdoor conditions. Notably, the team has synthesized and tested a range of polymer sorbents, identified mechanisms of material degradation and fouling, and advanced both lab- and pilot-scale cultivation systems to evaluate performance. From a technical and economic standpoint, AUDACity shows promise for achieving cost-effective CO 2 capture and delivery into aqueous media and biofuel production. Preliminary techno-economic analysis (TEA) indicates that the DAC system based on current performance can reach $\$$680/tonne CO 2 delivered into aqueous solution; with reasonable improvements to sorbent lifetime, sorbent capacity, reducing water uptake the approach could reach $\$$66/tonne by avoiding the need for energy-intensive sorbent regeneration and CO 2 compression, making it more feasible for decentralized deployment. With these costs for CO 2 and by extracting and selling high-value PC ($\$$50/kg) and mid-value protein supplement ($\$$6/kg), the remaining biomass can be hydrothermally treated into biofuel for $\$$2.50/gallon, and would support a small first-of-a-kind biorefinery capable of producing 500 barrels per day of biofuel. The project offers meaningful public benefits by advancing carbon removal technologies that are low-energy, modular, and adaptable to non-arable land and brackish water use. It aligns with national goals to develop advanced biotechnology and supports future pathways for bio-based fuels and products. By enabling direct coupling of CO 2 transfer into aqueous medium and biological carbon utilization, AUDACity lays the groundwork for effective algae cultivation without wasteful CO 2 delivery and is a promising and innovative solution for low-carbon fuel and bioproduct generation contributing to a vigorous bioeconomy.

09 BIOMASS FUELS↗