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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.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Porous potassium tantalate-reduced graphene oxide nano cube architecture for high performance hybrid supercapacitors

Energy storage has always been a major concern in the present-day situation. Advanced energy storage devices are batteries, supercapacitor and solar cells. However, advancements have been noteworthy in the field of high-performance hybrid supercapacitors. On this note, we have fabricated a hybrid supercapacitor electrode material Potassium tantalate nano cube (KT NCs) and its reduced graphene oxide composite (KT-rGO NCs) and tested its electrochemical performance. The materials showed high performances with specific capacitance of 565 F/g for KT NCs and 850 F/g for KT-rGO NCs respectively. Energy densities of both KT NCs & KT-rGO NCs are 28.24 Wh/Kg and 29.50 Wh/kg with good retention capacities. Further detailed study of both KT NCs and KT-rGO NCs are carried out with characterization techniques like XRD, FTIR, BET, Raman and HRTEM for structural analysis and electrochemical measurements to analyse various parameters pertaining to its charge storage capacity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Insights into catalyst degradation during alkaline water electrolysis under variable operation

Energy conversion technologies that are key to decarbonization efforts face significant durability challenges due to variable operation. Understanding the impact of variable operation on catalytic stability and identifying the key variables that dictate degradation is crucial for developing robust technologies. Here, we present a comprehensive investigation of the effects of variable operation on liquid alkaline water electrolysis. Our findings reveal that variable operation induces severe degradation of Ni, Fe, and Co catalytic films that is not observed during steady-state operation. By systematically interrogating the electrode discharge during simulated shutdown tests using Raman spectroscopy and mass spectrometry techniques, we uncover significant alterations caused by reverse currents in real time. These include changes in crystal structure, composition, film thickness, electronic conductivity, and dissolution rates. Lab-scale electrolyzer experiments further highlight the impact of variable operation on catalyst materials under relevant conditions. Finally, we provide guidelines for leveraging these insights to advance electrocatalysis research. This work underscores the importance of integrating realistic stressors into stability testing and offers practical guidelines for catalyst design, performance evaluation, and industrial implementation. Collectively, insights from this study will drive the development of more resilient energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗
DOE OSTI2025

Earlier snowmelt increases the strength of the carbon sink in montane meadows unequally across the growing season

1. Warming temperatures are changing winters, leading to earlier snowmelt. This shift can lead to an earlier and potentially longer growing season, which in turn may affect various plant-mediated ecosystem functions. Despite its relevance in the carbon cycle, we still know little about how earlier snowmelt impacts the carbon balance in ecosystems over the growing season, for example, does it only shift phenology, or does it affect the overall carbon uptake? Most studies rely on interannual variability in snowmelt timing, making it difficult to isolate snowmelt effects from other confounding variables, for example, temperature and moisture anomalies. To address this uncertainty, we investigated how experimentally advancing snowmelt affects the carbon cycling of montane meadows across the growing season. 2. We experimentally advanced the snowmelt date in a montane meadow by approximately 12 days and collected data every 2 weeks throughout the growing season, including net ecosystem exchange (NEE), gross primary productivity (GPP), ecosystem respiration (ER), plant composition, and shrub, graminoid, and forb biomass. 3. Early in the growing season, GPP was higher in the early snowmelt plots, though this effect decreased as the growing season progressed. Our modelling of cumulative NEE showed a possible 22% increase in the carbon sink strength with earlier snowmelt. The effect was strongest in the early spring and diminished as the growing season progressed, with control plots being a greater carbon sink in the later season. Graminoid biomass was 47% higher in plots with earlier snowmelt, but there was no change in total biomass. 4. Synthesis. As winters warm and snowmelt occurs earlier, plant productivity will shift earlier in the growing season, and montane meadows may become a stronger carbon sink. However, this effect will differ seasonally, altering the carbon balance in montane meadows.

carbon cycle↗
DOE OSTI2020

NEAMS Milestone Report: M2MS–20OR030102 FW–CADIS PWR Ex-Core Analysis with Shift Through VERA

This report presents the work completed for the NEAMS milestone M2MS–20OR030102 titled "FW–CADIS PWR Ex-Core Analysis with Shift through VERA." The work completed for this milestone includes the implementation, integration, and optimization of memory and performance improvement methods in Shift for fully coupled ex-core calculations through Virtual Environment for Reactor Applications (VERA). Fully coupled in this context means the transfer of moderator boron concentration, pin-wise fission source, depleted compositions, temperatures, and moderator densities from MPACT (with COBRA-TF (CTF)) to Shift. The ability to run ex-core calculations with VERA has been enabled and used for several years by Consortium for Advanced Simulation of Light Water Reactors (CASL) partners. However, this implementation was limited and potentially computationally burdensome. This work has enabled the ability to run higher-fidelity ex-core calculations on moderate computing clusters by focusing on multithreading, domain decomposition, and Forward-Weighted CADIS (FW-CADIS) variance reduction. Tests performed on small cores, a small modular reactor (SMR), and CASL progression problems show very promising memory reduction and computational performance. Recommendations for settings when running fully coupled high-fidelity ex-core calculations with VERA are documented. Without these optimization methods, many processors on a compute node would be left unused for the entire ex-core calculation. Therefore, these methods enable the user to better use the resources available and reduce computation time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha –1 ). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R 2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R 2 = 0.88). Cellulose was best predicted using the NDRE (R 2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R 2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.

09 BIOMASS FUELS↗
DOE OSTI2025

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improved irradiation resistance of accident-tolerant high-strength FeCrAl alloys with heterogeneous structures

In this work, post–neutron irradiation examination is performed on advanced accident-tolerant fuel (ATF) cladding iron-chromium-aluminum (FeCrAl) alloys with ~10–13at. % Cr, ~10–12 at. % Al, ~1 at. % Mo, and minor alloying elements including Y irradiated to a damage level of 7 displacements per atom (dpa) at irradiation temperatures of 267–282 °C. A compositional dependency of the Cr and Al content is observed on the ratio of sessile and glissile dislocation loops, where the density of a$\langle$100$\rangle$ type loops is somewhat higher than the a/2$\langle$111$\rangle$ type loops. The α' precipitate number density is inversely correlated to the starting Cr concentration of the alloys of interest. The irradiation to a higher dose of 7 dpa results in a higher density of dislocation loops and α' precipitates for the same alloys at a lower irradiation dose, such as 1.8 dpa. In this work, the effect of α' precipitates on the dislocation loop density is discussed, and the presence of α' appears to inhibit the nucleation of loops. Compared with first-generation FeCrAl alloys, these advanced alloys with heterogeneous structure exhibit a lower Cr concentration in α' precipitation at the same dose level; they act as weaker obstacles deviating from the primary hardening contribution from the mature α'. Hence, the overall irradiation-induced hardening decreases; our alloys show improved radiation resistance because of their stronger sink strengths. The results presented in this paper could provide insights for the design and optimization of ATF cladding materials for future fission and space applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Above‐T g Annealing Benefits in Nanoparticle‐Stabilized Carbon Molecular Sieve Membrane Pyrolysis for Improved Gas Separation

Nanoparticles can suppress asymmetric precursor support collapse during pyrolysis to create carbon molecular sieve (CMS) membranes. This advance allows elimination of standard sol-gel support stabilization steps. Here we report a simple but surprisingly important thermal soaking step at 400 °C in the pyrolysis process to obtain high performance CMS membranes. The composite CMS membranes show CO 2 /CH 4 (50 : 50) mixed gas feed with an attractive CO 2 /CH 4 selectivity of 134.2 and CO 2 permeance of 71 GPU at 35 °C. Furthermore, a H 2 /CH 4 selectivity of 663 with H 2 permeance of 240 GPU was achieved for promising green energy resource-H 2 separation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Scale-dependent enhancement of productivity and stability in xenic Nannochloropsis cultures

Although bacterial amendments can enhance algal productivity and stability, the development of algal-bacteria consortia for commercial-scale utilization is limited. Here, for this work, we used an established high-throughput approach to generate algal-bacteria consortia, and tested consortia performance at spatial scales from microplates to 320 L raceway ponds. We used both lab and field-reared strains of Nannochloropsis oceanica to build consortia. In some experiments, we imposed environmental perturbations to test the ability of bacteria to enhance algal culture stability. In repeated assays at the scale of well plates, flasks, and bioreactors, strong effects of bacterial amendments on N. oceanica were observed. These effects were most dramatic when cultures experienced stressors such as temperature perturbations or removal of CO 2 augmentation. Isolates that were advanced for field testing included species in the genera Algoriphagus, Oceanicaulis, and Marinobacter. When consortia were generated in the field, positive effects of bacterial amendments were not observed. The amended bacteria were outcompeted, and bacterial community composition across treatments converged after the first grow out. These results highlight the complexity of using consortia in open systems, where interactions between the existing bacterial community, inoculated bacteria, and changing environmental conditions are layered upon other differences in scale and cultivation regimes. Moreover, functionally redundant bacteria are likely present in the field. Following this work, we hypothesize that tight interactions (e.g., obligate relationships between partners) will scale more predictably to outdoor systems. We suggest relying on true synthetic ecological approaches in which the relationships between bacteria and algae partners are well understood, or synthetic ecological approaches coupled with high throughput approaches to design and test consortia. We also recommend future work to examine the effect of algae-bacteria inoculation ratios on productivity and stability, track dynamics of partners through time, and manage ponds to retain beneficial symbioses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploiting Saturation Regimes and Surface Effects to Tune Composite Design: Single Platelet Nanocomposites of Peptoid Nanosheets and CaCO 3

Mineral-polymer composites found in nature exhibit exceptional structural properties essential to their function, and transferring these attributes to the synthetic design of functional materials holds promise across various sectors. Biomimetic fabrication of nanocomposites introduces new pathways for advanced material design and explores biomineralization strategies. This study presents a novel approach for producing single platelet nanocomposites composed of CaCO 3 and biomimetic peptoid (N-substituted glycines) polymers, akin to the bricks found in the brick-and-mortar structure of nacre, the inner layer of certain mollusc shells. The significant aspect of the proposed strategy is the use of organic peptoid nanosheets as the scaffolds for brick formation, along with their controlled mineralization in solution. Here, we employ the B28 peptoid nanosheet as a scaffold, which readily forms free-floating zwitterionic bilayers in aqueous solution. The peptoid nanosheets were mineralized under consistent initial conditions (σ calcite = 1.2, pH 9.00), with variations in mixing conditions and supersaturation profiles over time aimed at controlling the final product. Nanosheets were mineralized in both feedback control experiments, where supersaturation was continuously replenished by titrant addition and in batch experiments without a feedback loop. Complete coverage of the nanosheet surface by amorphous calcium carbonate was achieved under specific conditions with feedback control mineralization, whereas vaterite was the primary CaCO 3 phase observed after batch experiments. Thermodynamic calculations suggest that time-dependent supersaturation profiles as well as the spatial distribution of supersaturation are effective controls for tuning the mineralization extent and product. We anticipate that the control strategies outlined in this work can serve as a foundation for the advanced and scalable fabrication of nanocomposites as building blocks for nacre-mimetic and functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Sediment Mineralogy Data Review for the Hanford Central Plateau

The compendium of Hanford site sediment mineralogy data provided in this report was initiated in 2012 to support flux mitigation technologies and real-time monitoring that could limit contaminant fluxes to the groundwater in the Central Plateau. Recent efforts in advancing spectral induced polarization as a method for monitoring contaminant transformations for active biogeochemical remedies have underscored the need for a published compendium of sediment characterization data. Although the data are primarily focused on the mineralogical composition of Hanford sediments, other soil measurements such as particle size distribution such as particle size distribution and carbon content are provided. The data have been reproduced from the original reports and are provided here for information only (FIO).

58 GEOSCIENCES↗
DOE OSTI2024

Graph-Based Modeling for the Detection and Tracking of Sarin-Surrogate-Induced Neurotoxicity Using a Human-Relevant, In-Vitro Brain Model

Organophosphorus (OP) nerve agents are a chemical threat to the United States, to the civilian population (e.g., pesticides) and historically weaponized (e.g., sarin) as chemical warfare agents. The unprecedented, accelerated process from “bench-to-bedside” during the SARSCov2 pandemic has made it clear that technology and tools need to be readily available for immediate response. Advances in human organ tissue mimetic systems are a promising technology to evaluate the human-relevant response in vitro for basic and applied research and drug screening. In particular, current brain microphysiological systems (MPS) have the capability to monitor and detect changes in engineered human neural circuit activity. However, current data analytics approaches for these systems lack the granularity to functionally detect and distinguish the different mechanisms that occur in the brain following neurotoxicity, injury, and disease. The goal of this project was to advance the computational analytical capabilities of the brain MPS to detect functional changes in neural circuit structure at different stages of Sarin surrogate-induced neurotoxicity. We developed graph-based models to (1) identify the composition of the neural circuit structure; (2) detect and monitor how this structure changes following sarin-induced neurotoxicity; and (3) evaluate the analytical pipeline using known/promising oxime reactivators. Through experiments on the bMPS where in vitro neuronal cultures were exposed to a sarin surrogate, we demonstrated the capabilities of our computational pipeline to identify different responses in the functional networks of brain cells exposed to low and high concentrations of the nerve agent. We identified a biphasic response of human neural network activity following exposure to a sarin-surrogate that had not been reported in the literature before. The graph-based models and software developed in this project can be used for future studies that leverage the brain MPS technology, such as treatment efficacy assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Rationally Designed Lithium Ion Batteries Towards Displacing Internal Combustion Engines

Group14 Technologies is leading a word-class team composed of Cabot Corporation, Silatronix, Arkema, Pacific Northwest National Laboratories, and Farasis Energy to research, fabricate, test and demonstrate lithium-ion batteries (LIB) implementing ≥30% silicon-carbon (Si-C) composite anode material achieving aggressive next generation automotive energy targets.

25 ENERGY STORAGE↗
DOE OSTI2026

Mechanical Solution for Existing Conductors

The rapid growth in energy demand, driven by advancements in AI technology, renewable energy integration, and increased industrial activity, highlights the need for innovative solutions to improve the resiliency and efficiency of the power grid. This report details the fire testing of GridWrap’s Composite WiRe Wrap, to evaluate the wrap's ability to enhance conductor performance under wildfire-simulated conditions. Conductors were prepared and tested in a controlled environment at 400°C for 18 minutes, during which sag and temperature data were recorded. The results demonstrated that the unwrapped conductor sagged 3/16ths of an inch, while the WiRe Wrapped conductor sagged only 1/16th of an inch under identical conditions, indicating a significant improvement in mechanical performance. This project, conducted as part of a collaborative effort between BEA (Idaho National Laboratory’s managing contractor) and GridWrap, Inc., demonstrates the potential of grid-enhancing technologies like WiRe Wrap to reduce sag, increase grid resiliency, and support the future energy landscape. By validating the performance of such technologies in real-world scenarios, this work provides critical insights for industry adoption, benefiting both grid operators and U.S. taxpayers through improved reliability, reduced emissions, and enhanced energy delivery.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2022

Wood combustion nanoparticles emitted by conventional and advanced technology cordwood boilers, and their interactions in vitro with human lung epithelial monolayers

Biomass-burning boilers and stoves are widely used in many parts of the world, producing combustion emissions linked with health risks. Here, combustion emission nanoparticles (NPs) were collected from four representative wood burning boilers using oak cordwood at specific times in the burn cycle. The morphology and composition of the NPs was characterized using transmission electron microscopy and energy dispersive X-ray analysis. To determine the degree of NP cytotoxicity with human lung tissue, the combustion NPs were introduced to incubated lung bronchial epithelial monolayers (NCI-H292) in vitro at doses of 0.1×10 -6 and 3.0×10 -6 kg/L for 2 and 4 h. Histochemical analysis showed that cell death increased by a factor of 3.5 for both doses after 4 h when compared to the control. Ultrapure NPs prepared by wet chemical methods were also introduced to the epithelial lung cells for similar doses and exposure times and the cultures exhibited significantly reduced mortality. Electron microscopy was used to study the mechanism of cell mortality for the synthesized and combustion-based NPs by examining how the NP byproducts interacted with individual cell organelles. It was found that cell survival was strongly correlated with the absence of contaminants (salts, heavy metals, poly aromatic hydrocarbons) associated with the NPs entering the cells. Synthesized NPs consisting of pure carbon were relatively well tolerated and could be excreted without damaging the cell ultrastructure. Thus, careful removal of extraneous contaminants by controlling the burn cycle with a catalyst is essential to minimize the health and environmental effects of wood biofuel combustion. In better words, optimized advanced technology wood-burning boilers and stoves can provide a CO 2 -neutral energy source and significantly contribute to a future where fossil fuels have a reduced role.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗