Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computer model”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Experimental and Computational Evaluation of Nicotinamide Cofactor Biomimetics

Oxidoreductase enzymes are widely used biocatalysts due to their high enantioselectivity and broad substrate compatibility in useful transformations. Many oxidoreductases require nicotinamide cofactors (i.e., NAD(P)H). To replace this costly natural cofactor, synthetic nicotinamide cofactor biomimetics (NCBs) offer different shapes, binding affinities, and reducing potentials that exceed the capabilities of wild-type NAD(P)H. However, the ill-defined structure–activity relationships (SARs) of various NCBs slow rationally guided innovation, such as customized reducing potentials. Here, we dissect two essential elements of NCB design, holding the nicotinamide invariant. First, the linker length between the nicotinamide and an unconjugated aromatic ring uncovered unexpected benefits to redox activity for two or three carbon linkers. Second, substitution on this unconjugated aryl group (Ring 2) might not be expected to affect activity. However, SAR trends demonstrate substantial benefits to reductive potential conferred by electron-donating functionalities on Ring 2. Furthermore, catalysis by two enzymes demonstrates enzyme-dependent tolerance or sensitivity to the NCB structures. Density functional theory (DFT) and computational modeling provide a theoretical framework to understand and build upon these observations. Ring 2 reaches up to the nicotinamide to stabilize its positive charge after oxidation through π–π stacking and charge transfer. Thus, the systematic examination of NCB’s stability, electrochemical redox potentials, and kinetics uncovers trends for the improved design of NCBs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electrochemical Routes for the Valorization of Biomass-Derived Feedstocks: From Chemistry to Application

The drive to reduce consumption of fossil resources, coupled with expanding capacity for renewable electricity, invites the exploration of new routes to utilize this energy for the sustainable production of fuels, chemicals, and materials. Biomass represents a possible source of platform precursors for such commodities due to its inherent ability to fix CO2 in the form of multi-carbon organic molecules. Electrochemical methods for the valorization of biomass are thus intriguing, but there is a need to objectively evaluate this field and define the opportunity space by identifying pathways suited to electrochemistry. In this contribution we offer a comprehensive, critical review of recent advances in low-temperature (liquid phase), electrochemical reduction and oxidation of biomass-derived intermediates (polyols, furans, carboxylic acids, amino acids, and lignin), with emphasis on identifying the state-of-the-art for each documented reaction. Progress in computational modeling is also reviewed. We further suggest a number of possible reactions that have not yet been explored but which are expected to proceed based on established routes to transform specific functional groups. We conclude with a critical discussion of technological challenges for scale-up, fundamental research needs, process intensification opportunities (e.g., by pairing compatible oxidations and reductions), and new benchmarking standards that will be necessary to accelerate progress toward application in this still-nascent field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Oxygenate Production from Plasma-Activated Reaction of CO 2 and Ethane

Upgrading ethane with CO 2 as a soft oxidant represents a desirable means of obtaining oxygenated hydrocarbons. This reaction is not thermodynamically feasible under mild conditions and has not been previously achieved as a one-step process. Non-thermal plasma was implemented as an alternative means of supplying energy to overcome activation barriers, leading to the production of alcohols, aldehydes, and acids as well as C 1 -C 5+ hydrocarbons under ambient pressure, with a maximum total oxygenate selectivity of 12%. A plasma chemical kinetic computational model was developed and found to be in good agreement with the experimental trends. Results from this study illustrate the potential to use plasma for the direct synthesis of value-added alcohols, acids, and aldehydes from ethane and CO 2 under mild conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Architecting the Third Dimension of Electrochemical Energy Storage

Three-dimensional (3D) architectural design has emerged as a powerful strategy to push electrochemical energy storage (EES) devices beyond the intrinsic limitations of conventional two-dimensional (2D) electrodes. While planar architectures enable high packing density and mature manufacturing, they suffer from limited ion transport and low active-material loading. In contrast, 3D architectures introduce low-tortuosity networks and high surface area that enhance charge and mass transport while supporting thick, high mass-loading electrodes. However, their practicality remains hindered by challenges in volumetric density, mechanical stability, and large-scale manufacturability. Here, this Perspective examines the key evaluation and design principles that govern 3D device performance. We discuss the fundamental trade-offs between porosity, volumetric density, and mechanical stability that shape 3D design and highlight emerging strategies for integrating materials engineering, structural optimization, device integration, computational modeling, and scalable manufacturing. By aligning structural functionality with manufacturability, 3D architectures can evolve from laboratory prototypes to commercially viable energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

Biology shows many examples of spatially controlled assembly of cells and biomacromolecules into hierarchically organized structures, to which many of the complex biological functions are attributed. While such biological structures have inspired the design of synthetic materials, it is still a great challenge to control the spatial arrangement of individual building blocks when assembling multiple types of components into bulk materials. Here, in this study, we report self-assembly of multilayered, ordered protein arrays from mixed populations of virus-like particles (VLPs). We systematically tuned the magnitude of the surface charge of the VLPs via mutagenesis to prepare four different types of VLPs for mixing. A mixture of up to four types of VLPs selectively assembled into higher-order structures in the presence of oppositely charged dendrimers during a gradual lowering of the ionic strength of the solution. The assembly resulted in the formation of three-dimensional ordered VLP arrays with up to four distinct layers including a central core, with each layer comprising a single type of VLP. A coarse-grained computational model was developed and simulated using molecular dynamics to probe the formation of the multilayered, core-shell structure. Our findings establish a simple and versatile bottom-up strategy to synthesize multilayered, ordered materials by controlling the spatial arrangement of multiple types of nanoscale building blocks in a one-pot fabrication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Spherical Congeners of Polyaromatic Compounds Approaching C 20 - and C 60 -Fullerene-Type Structures

A series of three symmetric, hollow spherical, and shape-persistent molecular organic cages analogous to C 20 and C 60 were examined by computational modeling, analyzing structural elements, strain indicators, and physical properties relevant for potential applications. The compounds are covalent aromatic cages based on 1,3,5-substituted benzene nodes linked by paraphenylene or para-pyrenylene-connectors, with diameters varying from 2.3 to 4.2 nm. The apertures in the cage interior are varied by virtue of the cage type (C 20 - or C 60 -type cage) and the linear connectors placed between the C 6 H 3 -units. NBO and MESP analyses indicate the presence of electrophilic and nucleophilic sites in the molecular skeleton. In the cages with the phenylene-connectors, the HOMO−LUMO gaps are close to 4.0 eV. In the cage coated with an enlarged polyaromatic spacer (pyrene-unit), the gap is reduced by approximately 0.4 eV.

Aromatic compounds↗
DOE OSTI2025

Investigating Np(VI) Nitrate Speciation Control through Temperature and Optical Spectroscopy

Numerous areas of nuclear processing, such as radioisotope production, nuclear waste remediation, and separations, depend upon the speciation of f-elements in the solution state. However, fundamental knowledge of the actinides─particularly Np─lags behind most of the elements on the periodic table. Despite the importance of Np(VI) chemistry in separations and nuclear processing, its speciation in HNO 3 remains uncertain. This work addresses some of these gaps by investigating the effect of HNO 3 concentration and temperature on the spectra and speciation of the Np(VI) nitrate system. Six samples of Np in 1 to 10 M HNO 3 were prepared and treated with (NH 4 ) 2 [Ce(NO 3 ) 6 ] to stabilize the hexavalent oxidation state. The absorbance spectrum of the 10 M HNO 3 is drastically different from the spectra of the other samples; the 10 M spectrum indicates coordination of nitrate ligands to the Np(VI)O 2 2+ ion to form a complex with high symmetry. Additionally, absorbance spectra were recorded over the temperature range of 15 to 40 °C, and systematic increases and decreases in certain spectral features of the ultraviolet–visible (UV–vis)–near-infrared (NIR) spectra are present in the spectra. The difference in spectral features suggests that Np(VI) nitrate speciation depends on temperature. Dilution studies of this sample were monitored with UV–vis–NIR and Raman spectroscopies. Spectral data indicate the presence of multiple complexes with different symmetries, including a high-symmetry complex with an inversion center. As samples are diluted and aquo ligands replace nitrate ligands bound to the Np(VI) neptunyl cation, changes in spectroscopic signals indicate a decrease in the high-symmetry nitrate complex and an increase in the lower-symmetry aquo complex. Additionally, the Raman band associated with the Np(VI)O 2 2+ symmetric stretch broadens with dilution and is fitted with two peaks. These peaks are assigned to Np(VI) aquo and nitrato complexes, indicating that this vibrational mode is sensitive to the coordination environment of the Np(VI) neptunyl cation and that contributions from these two Np(VI) complexes can be distinguished. This unique experimental data could be used to advance computational models describing the electronic transitions of complex actinyl ions.

Absorption↗
DOE OSTI2021

Metal–Organic Framework Based Hydrogen-Bonding Nanotrap for Efficient Acetylene Storage and Separation

The removal of carbon dioxide (CO 2 ) from acetylene (C 2 H 2 ) is a critical industrial process for manufacturing high purity C 2 H 2 . However, it remains challenging to address the trade-off between adsorption capacity and selectivity, on account of their similar physical properties and molecular sizes. To overcome this difficulty, here we report a novel strategy involving the regulation of hydrogen-bonding nanotrap on the pore surface to promote the separation of C 2 H 2 /CO 2 mixtures, in three isostructural metal-organic frameworks (MOFs, named as MIL-160, CAU-10H, and CAU-23, respectively). Among them, MIL-160, which has abundant hydrogen-bonding acceptors as nanotraps, can selectively capture acetylene molecules and demonstrates ultra-high C 2 H 2 storage capacity (191 cm 3 g –1 , or 213 cm 3 cm –3 ) but much less CO 2 uptake (90 cm 3 g –1 ) under ambient conditions. The C 2 H 2 adsorption amount of MIL-160 is remarkably higher than the other two isostructural MOFs (86 cm 3 g –1 and 119 cm 3 g –1 for CAU-10H and CAU-23 respectively) under the same conditions. More importantly, both simulation and experimental breakthrough results show that MIL-160 sets a new benchmark for equimolar C 2 H 2 /CO 2 separation in terms of the separation potential (Δq break = 5.02 mol/kg) and C 2 H 2 productivity (6.8 mol/kg). In addition, in-situ FT-IR experiments combined with computational modeling further reveal that the unique host-guest multiple hydrogen-bonding interactions between the nanotrap and C 2 H 2 is the key factor for achieving extraordinary acetylene storage capacity and superior C 2 H 2 /CO 2 selectivity. Furthermore, this work provides a novel and powerful approach to address the trade-off of this extremely challenging gas separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cooperative Activation of CO 2 and Epoxide by a Heterobinuclear Al–Fe Complex via Radical Pair Mechanisms

Activation of inert molecules like CO 2 is often mediated by cooperative chemistry between two reactive sites within a catalytic assembly, the most common form of which is Lewis acid/base bifunctionality observed in both natural metalloenzymes and synthetic systems. Here, we disclose a heterobinuclear complex with an Al–Fe bond that instead activates CO 2 and other substrates through cooperative behavior of two radical intermediates. The complex L dipp (Me)AlFp (2, L dipp = HC{(CMe)(2,6- i Pr 2 C 6 H 3 N)} 2 , Fp = FeCp(CO) 2 , Cp = η 5 -C 5 H 5 ) was found to insert CO 2 and cyclohexene oxide, producing L dipp Al(Me)(μ:κ 2 -O 2 C)Fp (3) and L dipp Al(Me)(μ-OC 6 H 10 )Fp (4), respectively. Detailed mechanistic studies indicate unusual pathways in which (i) the Al–Fe bond dissociates homolytically to generate formally Al II and Fe I metalloradicals, then (ii) the metalloradicals add to substrate in a pairwise fashion initiated by O-coordination to Al. The accessibility of this unusual mechanism is aided, in part, by the redox noninnocent nature of L dipp that stabilizes the formally Al II intermediates, instead giving them predominantly Al III -like physical character. The redox noninnocent nature of the radical intermediates was elucidated through direct observation of L dipp Al(Me)(OCPh 2 ) (22), a metalloradical species generated by addition of benzophenone to 2. Complex 22 was characterized by X-band EPR, Q-band EPR, and ENDOR spectroscopies as well as computational modeling. As a result, the “radical pair” pathway represents an unprecedented mechanism for CO 2 activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mapping the Morphology of DNA on Carbon Nanotubes in Solution Using X-ray Scattering Interferometry

Single-walled carbon nanotubes (SWCNTs) with adsorbed single-stranded DNA (ssDNA) are applied as sensors to investigate biological systems, with potential applications ranging from clinical diagnostics to agricultural biotechnology. Unique ssDNA sequences render SWCNTs selectively responsive to target analytes such as (GT)n-SWCNTs recognizing the neuromodulator, dopamine. It remains unclear how the ssDNA conformation on the SWCNT surface contributes to functionality, as observations have been limited to computational models or experiments under dehydrated conditions that differ substantially from the aqueous biological environments in which the nanosensors are applied. We demonstrate a direct mode of measuring in-solution ssDNA geometries on SWCNTs via X-ray scattering interferometry (XSI), which leverages the interference pattern produced by AuNP tags conjugated to ssDNA on the SWCNT surface. We employ XSI to quantify distinct surface-adsorbed morphologies for two (GT) n ssDNA oligomer lengths (n = 6, 15) that are used on SWCNTs in the context of dopamine sensing and measure the ssDNA conformational changes as a function of ionic strength and during dopamine interaction. Here, we show that the shorter oligomer, (GT) 6 , adopts a more periodically ordered ring structure along the SWCNT axis (inter-ssDNA distance of 8.6 ± 0.3 nm), compared to the longer (GT) 15 oligomer (most probable 5'-to-5' distance of 14.3 ± 1.1 nm). During molecular recognition, XSI reveals that dopamine elicits simultaneous axial elongation and radial constriction of adsorbed ssDNA on the SWCNT surface. Our approach using XSI to probe solution-phase morphologies of polymer-functionalized SWCNTs can be applied to yield insights into sensing mechanisms and inform future design strategies for nanoparticle-based sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modulating CO 2 Electrocatalytic Conversion to the Organics Pathway by the Catalytic Site Dimension

Electrochemical reduction of carbon dioxide to organic chemicals provides a value-added route for mitigating greenhouse gas emissions. Here, we report a family of carbon-supported Sn electrocatalysts with the tin size varying from single atom, ultrasmall clusters to nanocrystallites. High single-product Faradaic efficiency (FE) and low onset potential of CO 2 conversion to acetate (FE = 90% @ –0.6 V), ethanol (FE = 92% @ –0.4 V), and formate (FE = 91% @ –0.6 V) were achieved over the catalysts of different active site dimensions. The CO 2 conversion mechanism behind these highly selective, size-modulated p-block element catalysts was elucidated by structural characterization and computational modeling, together with kinetic isotope effect investigation.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Covalency-Driven Differences in the Hydrogenation Chemistry of Lanthanide- and Actinide-Based Frustrated Lewis Pairs

The electronic organization of Frustrated Lewis Pairs (FLPs) allows them to activate strong bonds in mechanisms that are usually free of redox events at the Lewis acidic site. The unique 6d/5f manifold of uranium could serve as an interesting FLP acceptor site, but to date FLP-like catalysis with actinide ions is unknown. In this paper, the catalytic, FLP-like hydrogenation reactivity of trivalent uranium complexes is explored in the presence of base-stabilized silylenes. Comparison to isoelectronic, isostructural lanthanide and thorium complexes lends insight into the electronic factors governing dihydrogen activation. Mechanistic studies of the uranium- and lanthanide-catalyzed hydrogenations are presented, including discussion of likely intermediates. Computational modeling of the f-element complexes, combined with experimental comparison to p-block Lewis acids, elucidates the relevance of steric hindrance to productive reactivity with dihydrogen. As a result, consideration of the complete experimental and theoretical evidence provides a clear picture of the electronic and steric factors governing dihydrogen activation by these FLPs.

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

Circularity in Sequence-Controlled Copolyamides Enabled by Regioselective Enzymatic Hydrolysis

Sequence-controlled polymers enable precise control over macromolecular structures and function, but both their synthesis and end-of-life management remain fundamental challenges. Achieving high sequence fidelity is synthetically demanding, and conventional depolymerization methods lack regioselectivity, leading to irreversible loss of encoded molecular information and limiting polymer circularity. Enzymatic catalysis offers a potential solution by combining substrate specificity with selective bond cleavage. Here, we report the synthesis, characterization, and regioselective enzymatic depolymerization of poly- (X,AMA), a sequence-controlled copolyamide composed of alternating hexamethylenediamine−adipic acid (MA) and pxylylenediamine− adipic acid (XA) repeat units. Poly(X,AMA) was synthesized via solid-state polycondensation (SSP) of sequence-defined oligomers, enabling precise control over repeat-unit order. Polymer microstructure and sequence fidelity were confirmed by 13 C NMR spectroscopy and MALDI−TOF mass spectrometry. Comparison with a statistical copolymer analogue and Nylon-66 demonstrated pronounced differences in crystallinity, morphology, and thermal behavior arising from sequence control. Screening of 96 Nylon hydrolase homologues against poly(X,AMA) revealed strongly enzyme-dependent depolymerization profiles. While tetrad formation was generally favored, enzymes displayed pronounced sequence selectivity, preferentially releasing distinct sequence-defined tetrads XAMA or MAXA. SSP of sequence-defined tetrad MAXA produced a copolyamide with near identical monomer ordering as poly(X,AMA). Computational modeling of enzyme−substrate complexes identified structural features consistent with the observed regioselectivity. Together, these results establish selective enzymatic depolymerization as a viable strategy for the circular recycling of sequence-controlled polymers and provide a foundation for the rational engineering of enzymes for programmable polymer deconstruction.

Amides↗
DOE OSTI2020

Deep neural network improves the estimation of polygenic risk scores for breast cancer

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. Here, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA, and LDpred. In the test cohort with 50% prevalence, the Area Under the receiver operating characteristic Curve (AUC) were 67.4% for DNN, 64.2% for BLUP, 64.5% for BayesA, and 62.4% for LDpred. BLUP, BayesA, and LPpred all generated PRS that followed a normal distribution in the case population. However, the PRS generated by DNN in the case population followed a bimodal distribution composed of two normal distributions with distinctly different means. This suggests that DNN was able to separate the case population into a high-genetic-risk case subpopulation with an average PRS significantly higher than the control population and a normal-genetic-risk case subpopulation with an average PRS similar to the control population. This allowed DNN to achieve 18.8% recall at 90% precision in the test cohort with 50% prevalence, which can be extrapolated to 65.4% recall at 20% precision in a general population with 12% prevalence. Interpretation of the DNN model identified salient variants that were assigned insignificant p values by association studies, but were important for DNN prediction. These variants may be associated with the phenotype through nonlinear relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Direct insights into the role of epoxy groups on cobalt sites for acidic H 2 O 2 production

Hydrogen peroxide produced by electrochemical oxygen reduction reaction provides a potentially cost effective and energy efficient alternative to the industrial anthraquinone process. In this study, we demonstrate that by modulating the oxygen functional groups near the atomically dispersed cobalt sites with proper electrochemical/chemical treatments, a highly active and selective oxygen reduction process for hydrogen peroxide production can be obtained in acidic electrolyte, showing a negligible amount of onset overpotential and nearly 100% selectivity within a wide range of applied potentials. Combined spectroscopic results reveal that the exceptionally enhanced performance of hydrogen peroxide generation originates from the presence of epoxy groups near the Co–N 4 centers, which has resulted in the modification of the electronic structure of the cobalt atoms. Computational modeling demonstrates these electronically modified cobalt atoms will enhance the hydrogen peroxide productivity during oxygen reduction reaction in acid, providing insights into the design of electroactive materials for effective peroxide production.<

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Anomalous size effect on yield strength enabled by compositional heterogeneity in high-entropy alloy nanoparticles

High-entropy alloys (HEAs), although often presumed to be random solid solutions, have recently been shown to display nanometer-scale variations in the arrangements of their multiple chemical elements. Here, we study the effects of this compositional heterogeneity in HEAs on their mechanical properties using in situ compression testing in the transmission electron microscope (TEM), combined with molecular dynamics simulations. We report an anomalous size effect on the yield strength in HEAs, arising from such compositional heterogeneity. By progressively reducing the sample size, HEAs initially display the classical “smaller-is-stronger” phenomenon, similar to pure metals and conventional alloys. However, as the sample size is decreased below a critical characteristic length (~180 nm), influenced by the size-scale of compositional heterogeneity, a transition from homogeneous deformation to a heterogeneous distribution of planar slip is observed, coupled with an anomalous “smaller-is-weaker” size effect. Atomic-scale computational modeling shows these observations arise due to compositional fluctuations over a few nanometers. These results demonstrate the efficacy of influencing mechanical properties in HEAs through control of local compositional variations at the nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A unique Co@CoO catalyst for hydrogenolysis of biomass-derived 5-hydroxymethylfurfural to 2,5-dimethylfuran

The development of precious-metal-free catalysts to promote the sustainable production of fuels and chemicals from biomass remains an important and challenging target. Here, we report the efficient hydrogenolysis of biomass-derived 5-hydroxymethylfurfural to 2,5-dimethylfuran over a unique core-shell structured catalyst, Co@CoO that affords the highest productivity among all catalysts, including noble-metal-based catalysts, reported to date. Surprisingly, we find that the catalytically active sites reside on the shell of CoO with oxygen vacancies rather than the metallic Co. The combination of various spectroscopic experiments and computational modelling reveals that the CoO shell incorporating oxygen vacancies not only drives the heterolytic cleavage, but also the homolytic cleavage of H 2 to yield more active H δ- species, resulting in the exceptional catalytic activity. Co@CoO also exhibits excellent activity toward the direct hydrodeoxygenation of lignin model compounds. This study unlocks, for the first time, the potential of simple metal-oxide-based catalysts for the hydrodeoxygenation of renewable biomass to chemical feedstocks.

09 BIOMASS FUELS↗