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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 181 records · Page 10

Supply chain system for a centralized biorefinery system based on switchgrass grown on marginal land in Michigan

The feedstock supply chain of a biorefinery is critical in determining the economic and environmental performance of biofuels. This study investigated various feedstock supply chains for a centralized biorefinery based on different objective functions and how the biorefinery responds to supply chain volatility. For the analysis, a hypothetical centralized biorefinery was supplied by switchgrass grown on marginal lands in Michigan. From an economic standpoint, the minimum biofuel selling price is an important metric of the objective function, and the greenhouse gas mitigation potential is a similarly important metric for global warming impact. A trade-off therefore exists between the economic and environmental performance of biofuels under this system configuration. However, when a carbon tax credit is applied to soil organic carbon sequestration in switchgrass production, the metric of the objective function may not be the key factor in establishing a supply chain as long as it is associated with biorefinery capacity as well as economic or environmental values. Year-to-year fluctuations in cellulosic biomass yield (supply chain volatility) might also prevent the biorefinery from operating at full capacity. Cellulosic biomass pellets can serve as an auxiliary feedstock for the centralized cellulosic biorefinery system to minimize the impacts of supply chain volatility.

09 BIOMASS FUELS↗

Clean Energy Manufacturing: Renewable Energy Technology Benchmarks

The manufacturing of clean energy technologies has become a global enterprise. An analysis of four clean energy technology manufacturing processes—wind turbine components, crystalline silicon solar photovoltaic modules, light-duty vehicle lithium-ion battery cells, and light-emitting diodes—was conducted to provide a reference point for comparison over time as this sector evolves. The manufacturing supply chain analysis included processing of raw materials, making required subcomponents, and assembling final products, using benchmarks that crossed 12 economies: Brazil, Canada, China, Germany, India, Japan, Malaysia, Mexico, South Korea, Republic of China (Taiwan), the United Kingdom, and the United States. Larger economies, with extensive manufacturing supply chains and high prevailing wages, tend to retain more value added from clean energy manufacturing than small economies. Manufacturing of clean energy technologies drives extensive trade among economies to support the widely distributed supply chain links. Production of wind turbine components and photovoltaic modules is more centralized than production of light-emitting diodes and lithium-ion battery cells. Across the four clean energy technologies evaluated, there was generally an excess of manufacturing capacity relative to global supply.

benchmarks↗

Verifying status of a termination end cap of a microinverter chain

A photovoltaic (PV) system includes a system control module that determines the presence of a microinverter chain termination end cap. The end cap includes an embedded circuit. The embedded circuit includes components having resistive, reactive, or impedance values. A signal source provides a signal through the microinverter chain. A parameter for a sensed signal detected by the system control module is used to determine the presence of the end cap using a change between the parameter for the sense signal and a reference parameter.

Chapman, Patrick L.↗

Kinetic model-based group contribution method for derived cetane number prediction of oxygenated fuel components and blends

A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.

42 ENGINEERING↗

On decoupling the integrals of cosmological perturbation theory

ABSTRACT Perturbation theory (PT) is often used to model statistical observables capturing the translation and rotation-invariant information in cosmological density fields. PT produces higher order corrections by integration over linear statistics of the density fields weighted by kernels resulting from recursive solution of the fluid equations. These integrals quickly become high dimensional and naively require increasing computational resources the higher the order of the corrections. Here, we show how to decouple the integrands that often produce this issue, enabling PT corrections to be computed as a sum of products of independent 1D integrals. Our approach is related to a commonly used method for calculating multiloop Feynman integrals in quantum field theory, the Gegenbauer Polynomial x-Space Technique. We explicitly reduce the three terms entering the 2-loop power spectrum, formally requiring 9D integrations, to sums over successive 1D radial integrals. These 1D integrals can further be performed as convolutions, rendering the scaling of this method Nglog Ng with Ng the number of grid points used for each fast Fourier transform. This method should be highly enabling for upcoming large-scale structure redshift surveys where model predictions at an enormous number of cosmological parameter combinations will be required by Monte Carlo Markov Chain searches for the best-fitting values.

Slepian, Zachary↗

Simple Autoignition Model for the Derived Cetane Number of Oxygenated Compounds and Fuel Blends

A simple four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a given compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the explicit dependence of the measured ignition delay on each functional group. The new model was able to successfully describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model could naturally be modified into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).

09 BIOMASS FUELS↗

Simple Autoignition Model for the Derived Cetane Number of Oxygenated Compounds and Fuel Blends

A four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the dependence of the measured ignition delay on each functional group. The new model was able to describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model was transformed into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).

Witkowski, Dustin↗

Which Combinations of Environmental Conditions and Microphysical Parameter Values Produce a Given Orographic Precipitation Distribution?

This study applies an idealized modeling framework, alongside a Bayesian Markov chain Monte Carlo (MCMC) algorithm, to explore which combinations of upstream environmental conditions and cloud microphysical parameter values can produce a particular precipitation distribution over an idealized two-dimensional, bell-shaped mountain. Simulations focus on orographic precipitation produced when an atmospheric river interacts with topography. MCMC-based analysis reveals that different combinations of parameter values produce a similar precipitation distribution, with the most influential parameters being relative humidity (RH), horizontal wind speed (U), surface potential temperature (θ sfc ), and the snow fall speed coefficient (A s ). RH, U, and A s exhibit interdependence: changes in one or more of these factors can be mitigated by compensating changes in the other(s) to produce similar orographic precipitation rates. The results also indicate that the parameter sensitivities and relationships can vary for spatial subregions and given different environmental conditions. In particular, high θ sfc values are more likely to produce the target precipitation rate and spatial distribution, and thus the ensemble of simulations shows a preference for liquid precipitation at the surface. The results presented here highlight the complexity of orographic precipitation controls, and have implications for flood and water management, observational efforts, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical simulation of axisymmetric turbulent flow in combustors and diffusers

Numerical studies of turbulent flow in an axisymmetric 45-deg-expansion combustor and bifurcated diffuser are presented. The Navier-Stokes equations incorporating a k-epsilon model were solved in a nonorthogonal curvilinear coordinate system. A zonal-grid method, where the flow field was divided into several subsections, was developed. This approach permitted different computational schemes to be used in the various zones. In addition, grid generation was made a more simple task. Boundary overlap and interpolating techniques were used, and an adjustment of the flow variables was required to assure conservation of mass flux. Three finite-differencing methods (hybrid, quadratic upwind, and skew upwind) were used to represent the convection terms. Results were compared with existing experimental data. In general, good agreement between predicted and measured values was obtained.

Yung, Chain-Nan↗

Dynamics of Single Chains of Suspended Ferrofluid Particles

We present an experimental study of the dynamics of isolated chains made of super-paramagnetic particles under the influence of a magnetic field. The motivation of this work is to understand if the chain fluctuations exist and, if it does, how does the fluctuation affect chain aggregation. We find that single chains strongly fluctuate and that the characteristic frequency of their fluctuations is inversely proportional to the magnetic field strength. The higher the field the lower the characteristic frequency of the chain fluctuations. In the high magnetic field limit, chains behave like rigid rods without any internal motions. In this work, we used ferrofluid particles suspended in water. These particles do not have any intrinsic magnetization. Once a magnetic field is applied, a dipole moment is induced in each particle, proportional to the magnetic field. A dipolar magnetic interaction then occurs between particles. If dipole-dipole magnetic energy is higher than the thermal energy, the result is a structure change inside the dipolar fluid. The ratio of these two energies is expressed by a coupling constant lambda as: lambda = (pi(a(exp 3))(chi(exp 2))(mu(sub 0))(H(sub 0))(exp 2))/18kT Where a is the particle radius, mu(sub 0) is the vacuum magnetic permeability, H(sub 0) the applied magnetic field, k the Boltzmann constant and T the absolute temperature. If lambda > 1, magnetic particles form chains along the field direction. The lateral coalescence of several chains may form bigger aggregates especially if the particle volume fraction is high. While many studies and applications deal with the rheological properties and the structural changes of these dipolar fluids, this work focuses on the understanding of the chain dynamics. In order to probe the chain dynamics, we used dynamic light scattering (DLS) in self-beating mode as our experimental technique. The experimental geometry is such that the scattering plane is perpendicular to the magnetic field. Therefore, only motions in this plane are probed. A very dilute sample of a ferrofluid emulsion with a particle volume fraction of 10(exp -5) is used in this experiment. We chose such a low volume fraction to avoid multiple light scattering as well as lateral chain-chain aggregation. DLS measures the dynamic structure factor S(q,t) of the sample (q is the scattering wave vector, t is the time). In the absence of the magnetic field, identical particles of ferrofluid droplets are randomly distributed and S(q,t) reduces to exp(-q(exp 2)2D(sub 0)t). D(sub 0)=(kT/(6(pi)(eta)(a)) is the diffusion coefficient of Brownian particles (where Xi = (6(pi)(eta)(a)) is the Stokes frictional coefficient of a spherical particle in a fluid of viscosity eta). If interactions or polydispersity can not be ignored, an effective diffusion coefficient is introduced. Formally, D(sub eff) is defined as: D(sub eff) = - q(exp -2) partial derivative of (ln(S(q,t)) with respect to time, as t goes to 0. D(sub eff) reduces to D(sub 0) if no interactions and only a few particles size are present. Therefore, we can use DLS to measure particle size. The particle radius was found to be a=0.23 mu m with 7% of polydispersity. In this case, if we vary the scattering angle theta (and so q) we do not have any change in the measured diffusion coefficient: it is q-independent. When a magnetic field is applied, particles aggregate into chains if lambda > 1. We first studied the kinetics of the chain formation when lambda = 406. At a fixed scattering angle, we measured diffusion coefficient D(sub eff) as a function of time. Experimentally, we find that D(sub eff) decreases monotonously with time. Physically, this means that chains are becoming longer and longer. Since we are only sensitive to motions in the scattering plane and since chains have their main axis perpendicular to this plane, the measured diffusion coefficient is the trans-verse diffusion coefficient. We can relate D(sub eff) to the mean number of particles per chain N(t) at a given time and to the diffusion coefficient of an isolated particle D(sub 0) as D(sub eff)=f(N(t))D(sub 0). Since f(N) is known from other recent work, N can be expressed as a function of the time. We found a square root dependency: N(t) proportional to the square root of t. As expected for very low volume fraction, this behavior is characteristic of a diffusion-limited aggregation as suggested by several authors and by our previous work. In this study, we focus on the dependence of the effective diffusion coefficient on the scattering angle and the magnetic field strength. After the magnetic field is applied (lambda = 406) for a long time, typically 6 hours, kinetics of chain formation becomes very slow. Chain size does not vary much over the next hour period. Thus, we can perform different interesting experiments. First, at a fixed magnetic field, we measure the effective diffusion coefficient as a function of the scattering angle (from 5 to 130 deg). Our results show that the measured diffusion coefficient increases linearly with the scattering angle: D(sub eff) proportional to q. If we do the same experiment for different lambda values, D(sub eff) depends on lambda as D(sub eff) proportional to lambda(exp -1/2). We also find for different lambda values that the same asymptotic D(sub eff) value is obtained when q approaches zero. The angle dependency of D(sub eff) suggests that an additional motion exists besides chain drifting. Chain size is constant during experiment, which was verified by measuring the same diffusion coefficient at the beginning and at the end of the angle switching. If chains are rigid, D(sub eff) is independent of q. Therefore, we found that D(sub eff) not only measures the motion of the entire chain but also its internal fluctuations. These internal motions are the fluctuations of the particles in the chain. To understand the q dependency of D(sub eff), let us look at the probing length used. In our study, the characteristic length scale probed is l=2pi/q which is in the range of 0.9<l/a<20. When l is much larger than the particle radius (l/a going to infinity) we are mainly sensitive to the center of mass diffusion of the chain. D(sub eff) is then the diffusion of the entire chain and depends only on N but not on q and lambda. The value D(sub eff) allows us to obtain the number of particles per chain N. In the opposite limit (i.e. l/a < 1), we are sensitive to motions on the size of individual particles. The main contributions to the measured diffusion coefficient come from internal motions of the chains (i.e. particles' fluctuations inside the chain). We investigated also the effect of the chain size on D(sub eff). For the same value of the magnetic interaction lambda and different chain sizes, we found that the slope of D(sub eff) versus q decreases when N increases as a power law D(sub eff) proportional to N(exp -0.7). This is an important behavior because this means that the longer the chain the slower its internal fluctuations besides the whole chain motion.

Cutillas, S.↗

Control of Peptide Amphiphile Supramolecular Nanostructures by Isosteric Replacements

Supramolecular nanostructures with tunable properties can have applications in medicine, pharmacy, and biotechnology. In this work, we show that the self-assembly behavior of peptide amphiphiles (PAs) can be effectively tuned by replacing the carboxylic acids exposed to the aqueous media with isosteres, functionalities that share key physical or chemical properties with another chemical group. Transmission electron microscopy, atomic force microscopy, and small-angle X-ray scattering studies indicated that the nanostructure’s morphologies are responsive to the ionization states of the side chains, which are related to their pK a values. Circular dichroism studies revealed the effect of the isosteres on the internal arrangement of the nanostructures. The interactions between diverse surfaces and the nanostructures and the effect of salt concentration and temperature were assessed to further understand the properties of these self-assembled systems. These results indicate that isosteric replacements allow the pH control of supramolecular morphology by manipulating the pK a of the charged groups located on the nanostructure’s surface. Theoretical studies were performed to understand the morphological transitions that the nanostructures underwent in response to pH changes, suggesting that the transitions result from alterations in the Coulomb forces between PA molecules. Furthermore, this work provides a strategy for designing biomaterials that can maintain or change behaviors based on the pH differences found within cells and tissues.

36 MATERIALS SCIENCE↗

Role of tunable polymer flexibility in controlling wetting behavior and thermal properties of poly(1,3-cyclohexadiene)-silica nanocomposites

We present how altering the chain flexibility affects the nanoscale organization of polymer-grafted nanoparticles (PGNPs) and its ultimate impact on macroscale thermal properties. To isolate the role of chain flexibility on wetting behavior in athermal polymer nanocomposites (PNC), the graft and matrix chemistry is kept identical by utilizing 1,3-cyclohexadiene-based polymer materials. Increasing the rigidity and molecular weight of both the graft and matrix is found to favor mixing of poly(1,3-cyclohexadiene) PCHD-grafted silica NPs with the matrix, supported by a concomitant increase in glass transition temperatures of the PNCs. Further, the associated entropic factors that drive wetting behavior and dispersion of PGNPs are discussed, emphasizing the dominant role-played by chain flexibility. Alterations in graft flexibility had the strongest impact on dispersion and Tg values of the PNC, while molecular weight (MW) plays a secondary role. This investigation is a unique demonstration of how chain flexibility alteration in athermal semiflexible systems can be used to alter NP organization by altering filler-matrix wettability which also impacts thermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Combining Reclaimed PET with Bio-Based Monomers Enables Plastics Upcycling

Less than 30% of PET plastic is recycled in the United States. The low reclamation rate may be due to mechanical recycling accounting for the majority of commercial PET recycling. Mechanical recycling yields a lower-quality recycled plastic than the process of chemically recycling back to the monomer phase, which can be energetically and economically expensive. In this work, recently published in Joule, reclaimed PET bottles are chemically recycled and converted into higher-value fiberglass-reinforced plastics (FRPs).This presentation will focus on the supply-chain level energy and greenhouse gas emissions intensities associated with this novel upcycling route. The Materials Flows through Industry supply chain analysis tool, developed at NREL, is used to estimate these impacts. Depending on the extent and speed of adoption, this strategy for plastic upcycling could lead to significant energy usage and emissions reductions over the traditional FRP supply chain. Overall, this approach may provide an economic incentive for plastics recycling and renewable feedstock use through the creation of higher-value FRPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chain Formation as a Mechanism for Mass-Independent Fractionation of Sulfur Isotopes in the Archean Atmosphere

The anomalous abundances of sulfur isotopes in ancient sediments provide the strongest evidence for an anoxic atmosphere prior to ∼2.45 Ga, but the mechanism for producing this 'mass-independent' fractionation pattern remains in question. The prevailing hypothesis has been that it is created by differences in the UV photolysis rates of different SO2 isotopologues. We investigate here a recently proposed additional source of fractionation during gas-phase formation of elemental sulfur (S4 and S8). Because two minor S isotopes rarely occur in the same chain, the longer S4 and S8 chains should be strongly, and roughly equally, depleted in all minor isotopes. This gives rise to negative ∆(sup 33) S values and positive ∆(sub 36) S values in elemental sulfur-just the opposite of (and much larger than) what is predicted from SO2 photolysis itself. Back-reactions during chain formation, specifically photolysis of S2 and S3, pass sulfur having the opposite fractionation back to atomic S, and thence to other sulfur species, causing H2S, SO2, sulfate, and short-chain elemental sulfur to have positive ∆(sup 33) S and negative ∆(sup 36) S. Positive ∆(sup 33) S values in elemental sulfur produced in laboratory SO2 photolysis experiments could be caused by the initial fractionation during photolysis, combined with rapid condensation of short-chain sulfur species on the walls of the reaction chamber, along with a scarcity of back-reactions. The simulated fractionations produced by the chain formation mechanism do not directly match fractionations from the rock record. The mismatch might be explained if the isotopic signals leaving the atmosphere were significantly modulated by life, by uncertainties in the rates of reactions of both major and minor isotopic sulfur species, or by the relatively large potential range of atmospheric parameters. Further work is needed to better constrain these uncertainties, but this novel mechanism suggests new avenues to explore in our search for a explanation for the S-MIF record.

Great Oxidation Event↗

Majorana modes with side features in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) systems represent promising platforms to host Majorana zero modes (MZMs), the elemental building blocks for fault-tolerant quantum computers. Theoretical description of such MSH structures is mostly based on simplified models, not accounting for the complexity of real materials. Here, based on density functional theory, we derive a superconducting 80-band model to study an MSH system consisting of a magnetic manganese chain on the s wave superconductor niobium. For a wide range of values of the superconducting order parameter, the system is a topological superconductor, with MZMs exhibiting non-universal spatial patterns and a drastic accumulation of spectral weight on both sides along the magnetic chain. These side feature states can be explained by an effective model which is guided by the ab initio results. Performing scanning tunneling spectroscopy experiments on the same system, we observe a spatial structure in the low-energy local density of states that is consistent with the theoretical findings. Our results open a first-principle approach to the discovery of topological superconductors.

36 MATERIALS SCIENCE↗

Colorado State University (CSU) X-Band Precipitation Radar Plan Position Indicator Data Processed with Corrected Moments in Antenna Coordinates (CMAC) Value-Added Product Report

In 2010 the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility procured 3- and 5-cm wavelength radars for documenting the macrophysical, microphysical, and dynamical structure of precipitating systems. To maximize the scientific impact, ARM supported the development of an application chain to correct for various phenomena in order to retrieve the “point” values of moments of the radar spectrum and polarimetric measurements. We have now used the lessons learned from the processing of the 3- and 5-cm wavelength radars obtained by ARM to help process X-band radar data from the Surface Atmospheric Integrated Field Laboratory (SAIL) field campaign. This report details the motivation, science, and progress to date as well as charting a path forward.

54 ENVIRONMENTAL SCIENCES↗

Chain Formation as a Mechanism for Mass-Independent Fractionation of Sulfur Isotopes in the Archean Atmosphere

The anomalous abundances of sulfur isotopes in ancient sediments provide the strongest evidence for an anoxic atmosphere prior to ∼2.45 Ga, but the mechanism for producing this ‘mass-independent’ fractionation pattern remains in question. The prevailing hypothesis has been that it is created by differences in the UV photolysis rates of different SO2 isotopologues. We investigate here a recently proposed additional source of fractionation during gas-phase formation of elemental sulfur (S4 and S8). Because two minor S isotopes rarely occur in the same chain, the longer S4 and S8 chains should be strongly, and roughly equally, depleted in all minor isotopes. This gives rise to negative Δ(exp 33)S values and positive Δ(exp 33)S values in elemental sulfur—just the opposite of (and much larger than) what is predicted from SO2 photolysis itself. Back-reactions during chain formation, specifically photolysis of S2 and S3, pass sulfur having the opposite fractionation back to atomic S, and thence to other sulfur species, causing H2S, SO2, sulfate, and short-chain elemental sulfur to have positive Δ(exp 33)S and negative Δ(exp 33)S. Positive Δ(exp 33)S values in elemental sulfur produced in laboratory SO2 photolysis experiments could be caused by the initial fractionation during photolysis, combined with rapid condensation of short-chain sulfur species on the walls of the reaction chamber, along with a scarcity of back-reactions. The simulated fractionations produced by the chain formation mechanism do not directly match fractionations from the rock record. The mismatch might be explained if the isotopic signals leaving the atmosphere were significantly modulated by life, by uncertainties in the rates of reactions of both major and minor isotopic sulfur species, or by the relatively large potential range of atmospheric parameters. Further work is needed to better constrain these uncertainties, but this novel mechanism suggests new avenues to explore in our search for a explanation for the S-MIF record.

C. E. Harman↗