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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Ushering in the New Age of Laboratories: Smart Labs in Practice; Preprint

Ventilation is the first line of defense against airborne hazards produced during research activities in laboratories. A vital component to maintaining healthy, safe, indoor air quality, laboratory ventilation systems are often victim to ineffective operation, posing a risk to an organization's most important asset - the researchers. Furthermore, system inefficiencies can lead to up to 50% wasted energy. By providing a framework to improve the safety and energy efficiency through optimized ventilation and operations, the Smart Labs Toolkit guides laboratory stakeholders through a straight-forward, holistic approach to achieving a dynamic Smart Labs program. A Smart Labs program employs a combination of physical, administrative, and management techniques to plan, assess, optimize, and manage high-performance laboratories. Grounded in the Smart Labs methodology, the National Renewable Energy Laboratory (NREL) implemented a successful Smart Labs program to oversee the design, construction, maintenance, and operations of its laboratories. To accomplish this effort, NREL's key stakeholders created an internal partnership to align NREL's existing laboratories with Smart Labs principles and solidify organizational roles for the safe and efficient operation of laboratory assets. The program provides the groundwork for decarbonization strategies centered around building operation. This paper outlines best practices employed by NREL to develop a cross-cutting Smart Labs team, garner managerial support, and effectively communicate of goals around safety and energy. Strategies include specific Smart Labs best practices, such as implementing a Laboratory Ventilation Risk Assessment - a systematic process for identifying risk due to airborne hazards and informing dynamic, demand-based ventilation to optimize safety and efficiency.

decarbonization↗

DOE OSTI2020

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Optimizing the fuel efficiency of an opposed piston engine for electric power generation

This paper investigates the optimal crankshaft motion for an opposed piston (OP) engine in a novel hybrid architecture to maximize fuel efficiency. The OP engine was selected for this work due to its inherent thermodynamic benefits and the balanced nature of the engine which can achieve downsizing through reducing the number of cylinders rather than the individual cylinder volume. The typical geartrain required on an OP engine was exchanged for two electric motors, reducing friction loss and decoupling the crankshafts. Using the motors to control the crankshaft motion profiles, this architecture introduces capabilities to dynamically vary compression ratio, combustion volume, and scavenging dynamics. To leverage these opportunities, an optimization scheme was developed utilizing nonlinear optimization of a 0-D model to compute the crankshaft motion profile that maximizes the work generated by the system. This optimization was then iteratively coupled with a high fidelity model which supplies the cylinder flow boundary conditions. This iterative approach reduces the model complexity used in the optimal control problem (OCP) while capturing the gas exchange dynamics critical to the 2-stroke cycle of the OP engine. By using the rate of change of motor torque as the input to the OCP, the torque fluctuation in a single cycle can be limited to ensure tracking feasibility. The results show crankshaft velocity slows during the compression stroke and conversely accelerates during the expansion stroke, reducing the peak motor torque required for control and thus reducing the motor losses. The extended residence time at top dead center, however, leads to an increase in heat transfer, illustrating the trade-off between the work extraction efficiency and the indicated engine efficiency.

Engineering↗

DOE OSTI2020

Improving AHU Performance by Minimizing Approach Temperature, Reducing Air Maldistribution, and Efficiently Handling Sensible and Latent Loads (Phase 1 Interim Final Technical Report)

Residential air handling units (AHUs) have stayed the same in form and efficiency for the past 30+ years, with incremental improvements made to address safety, functionality, and energy-efficiency. The purpose of this research in Phase I, Topic 9a: Next Generation Residential Air Handlers, was to improve AHU performance by minimizing heat exchanger (HX) approach temperature, reducing air maldistribution, and developing alternative system configurations which more efficiently handle sensible and latent loads. In this research Optimized Thermal Systems (OTS) developed, modeled, and evaluated multiple alternative system concepts. A dual vapor compression system separate sensible and latent cooling (SSLC) concept was studied to inform work on alternative concepts and to show best-case performance benefit. System concepts included ejector enhanced vapor compression cycles, desiccant assisted dehumidification, dual evaporator SSLC, and alternative AHU HX configurations. A dual vapor compression system showed COP improvement of 20%, however, required additional components, increased unit size, and increased cost. Two types of ejector enhanced vapor compression cycles with dual evaporators improved system COP by 9 to 11%, and reduced AHU losses by as much as 18%, with design changes limited to the AHU, no unit physical size increase, and a moderate increase to system first cost. Desiccant assisted air-conditioning required increased air flow rate resulting in higher fan power and the desiccant wheel increased sensible heat load leading to increased compressor power and reduced system COP. Dual evaporator cycles were found to degrade performance due to increased expansion losses. Optimized single slab HX designs used in place of the traditional A-coil HX led to 44–49% reduction in aluminum, 47–60% less refrigerant charge, and improved HX velocity distribution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2016

Global Optimization of Low-Thrust Interplanetary Trajectories Subject to Operational Constraints

Low-thrust electric propulsion provides many advantages for mission to difficult targets-Comets and asteroids-Mercury-Outer planets (with sufficient power supply)Low-thrust electric propulsion is characterized by high power requirements but also very high specific impulse (Isp), leading to very good mass fractions. Low-thrust trajectory design is a very different process from chemical trajectory.

optimization↗

DOE OSTI2025

A two-dimensional numerical study of the magneto-Rayleigh–Taylor instability with FLASH: Application to the staged Z-pinch concept

Magnetically driven implosions involving a liner collapsing onto a target are inherently vulnerable to the magneto-Rayleigh–Taylor instability (MRTI). Among the various approaches proposed to achieve fusion conditions within the target, the staged Z-pinch (SZP) concept employs a high-Z liner, the advantages of which remain an active area of investigation. Consequently, ongoing design optimization efforts are essential, while critical physical processes such as magnetic field (B-field) diffusion and radiation transport increase the complexity of required simulations. In this study, we utilize the new capabilities of the FLASH code to simulate in 2D, for the first time using this code, staged Z-pinch configurations (designated SZP1 and SZP1*), focusing on their stability. First, a comparison of simulation results with theoretical predictions of MRTI growth provide new insights into the often-overlooked influences of high mesh resolution and initial perturbation seeding on instability dynamics. These findings then lead to a discussion on potential improvements for future SZP experiments. These include the use of an axial B-field stabilization and the optimization of radiation transport processes during the implosion. The results presented herein establish the framework for simulating multi-dimensional Z pinches using the FLASH code and pave the way for the development of innovative experimental configurations leveraging its advanced simulation capabilities.

Adaptive mesh refinement↗

NASA NTRSDate not supplied

Space Exploration Applications for Development of High Capacity Cryocoolers

Long term storage of cryogens is necessary to enable NASAs long duration crewed missions to both the lunar and Martian surfaces. Such missions require in-space transport systems such as Nuclear Thermal Propulsion (NTP), and descent/ascent vehicles for transportation to and from the lunar and Martian surfaces. NTP systems and Lunar/Martian landers utilize cryogenic fluids to minimize architectural volume and mass. To further enhance the capability of these cryogenic systems, the Agency is putting emphasis on reusability, which requires the NTP and ascent/descent elements be replenished on-orbit via tankers or propellant depots, or on the lunar or Martian surface using liquefied in-situ produced propellants. NTP is one of the leading propulsion option for human Mars missions and requires liquid hydrogen to be stored on-orbit for over four years. For such a long duration mission, near “Zero Boil-Off” (ZBO) must be achieved which requires an optimized suite of passive Cryogenic Fluid Management technologies and active cooling (cryocoolers). Tens of Watts of 20K cooling is required to achieve ZBO conditions for NTP, however two-stage cooling using both 20K and 90K systems can lead to a significant reduction in both active cooling mass and power. The use of in-situ resources for lunar and Martian missions will require 150 Watts of 90K cooling for oxygen liquefaction and 300 Watts of 20K cooling for hydrogen liquefaction (lunar only). Descent/Ascent vehicles, propellant depots, and tankers will also require the use of cryocoolers to achieve ZBO conditions. To support these programs, NASA is developing high capacity 20K and 90K reverse turbo-Brayton cycle cryocoolers which offer a scalable, high efficiency, low vibration solution.

cryocooler↗

DOE OSTI2022

Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling

Multi-channel, nonlinear predictions of core temperature and density profiles are performed for the SPARC tokamak accounting for both kinetic neoclassical and fully nonlinear gyro-kinetic turbulent fluxes. A series of flux-tube, nonlinear, electromagnetic simulations using the CGYRO code with six gyrokinetic species are coupled to a nonlinear optimizer using Gaussian process regression techniques. The simultaneous evolution of energy sources, including alpha heat, radiation, and energy exchange, coupled with these high fidelity models and techniques, leads to a converged solution in electron temperature, ion temperature and electron density channels with a minimal number of expensive gyrokinetic simulations without compromising accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Global optimization of harmonic oscillator basis in covariant density functional theory

The present investigation focuses on the improvement of the accuracy of the description of binding energies within moderately sized fermionic basis. Using the solutions corresponding to infinite fermionic basis it was shown that in the case of meson exchange (ME) covariant energy density functionals (CEDFs) the global accuracy of the description of binding energies in the finite $N_F$ = 16 - 20 bases can be drastically (by a factor ranging from ~3 up to ~9 dependent on the functional and $N_F$) improved by a global optimization of oscillator frequency of the basis. This is a consequence of the unique feature of the ME functionals in which with increasing fermionic basis size fermionic and mesonic energies approach the exact (infinite basis) solution from above and below, respectively. As a consequence, an optimal oscillator frequency $\hbar\omega_0$ of the basis can be defined which provides an accurate reproduction of exact total binding energies by the ones calculated in truncated basis. This leads to a very high accuracy of the calculations in moderately sized $N_F=20$ basis when mass dependent oscillator frequency is used: global rms differences $\delta B_{rms}$ between the binding energies calculated in infinite and truncated bases are only 0.025 MeV and 0.031 MeV for the NL5(Z) and DD-MEZ functionals, respectively. Optimized values of the oscillator frequency $\hbar\omega_0$ are provided for three major classes of CEDFs, i.e. for density dependent meson exchange functionals, nonlinear meson exchange ones and point coupling functionals.

Binding energy & masses↗

DOE OSTI2026

SimH 2 : an integrated techno-economic modeling framework for hydrogen pipeline infrastructure and network optimization

Large-scale hydrogen (H 2 ) pipeline transport design and network optimization have seldom been reported due to the lack of a cost model accounting for the relationship between transport cost and hydrogen mass flow rate. Here, this work introduced a system-level cost model for hydrogen pipeline transport at supercritical state and integrated it with an existing CO 2 pipeline network tool, SimCCS, for hydrogen-specific pipeline design and optimization. The Intermountain West (I-West) region of the U.S., historically dependent on fossil fuel-based economies, is chosen to demonstrate the capabilities of our H 2 pipeline cost model and transport network optimization platform called SimH 2 . Two scenarios are examined: one where the pipeline is not allowed to pass through disadvantaged communities and the other where it is permitted. The results highlight that incorporating disadvantaged-community constraints lead to longer pipeline routes and increased transport costs, reflecting the trade-offs involved in equitable infrastructure development. It is demonstrated that the newly developed SimH 2 tool not only enables the efficient design of H 2 transportation pipelines but also optimizes the network by accounting for local terrain and the presence of disadvantaged areas.

08 HYDROGEN↗

DOE OSTI2021

Optimization of TAM16, a Benzofuran That Inhibits the Thioesterase Activity of Pks13; Evaluation toward a Preclinical Candidate for a Novel Antituberculosis Clinical Target

With increasing drug resistance in tuberculosis (TB) patient populations, there is an urgent need for new drugs. Ideally, new agents should work through novel targets so that they are unencumbered by preexisting clinical resistance to current treatments. Benzofuran 1 was identified as a potential lead for TB inhibiting a novel target, the thioesterase domain of Pks13. Although, having promising activity against Mycobacterium tuberculosis, its main liability was inhibition of the hERG cardiac ion channel. This article describes the optimization of the series toward a preclinical candidate. Despite improvements in the hERG liability in vitro, when new compounds were assessed in ex vivo cardiotoxicity models, they still induced cardiac irregularities. Further series development was stopped because of concerns around an insufficient safety window. However, the demonstration of in vivo activity for multiple series members further validates Pks13 as an attractive novel target for antitubercular drugs and supports development of alternative chemotypes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing

Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to a single layer and/or small number of particles. Therefore, results from such model configurations may not be generalized to multiple layer processes. In this study, a computationally efficient multi-layer powder spreading DEM simulation model is proposed. The model is calibrated experimentally using static Angle of Repose measurements. The adhesion model parameter, cohesive energy density is related to adhesive surface energy and strain energy release rate parameters. The model results show that interaction between particle and the powder spreading rake leads to noticeable variation in packing density, surface roughness, dynamic angle of repose (AOR), particle size distribution, and particle segregation. Finally, the powder model is experimentally validated using a recoater spreading rig to measure the dynamic AOR at spreading speeds consistent with recoating speeds and layer heights used in AM processes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules

The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.

McKeon, Caroline A. (ORCID:0000000217373503)↗

DOE OSTI2024

Effects of Calcination Conditions on the Structural and Electrochemical Behaviors of High‐Nickel, Cobalt‐Free LiNi 0.9 Mn 0.1 O 2 Cathode

Abstract Eliminating cobalt from high‐nickel layered oxide cathodes lowers the cost of lithium‐ion batteries for electric vehicles. However, cobalt‐free cathodes with high Mn 4+ and Ni 2+ contents are prone to Li/Ni mixing after synthesis, potentially compromising battery energy density, rate capability, and cycling stability. Without cobalt facilitating cation ordering in the layered structure, the degree of Li/Ni mixing in cobalt‐free cathodes depends heavily on the calcination conditions. In this study, a systematic exploration of calcination temperatures and LiOH ratio for LiNi 0.9 Mn 0.1 O 2 (NM‐90) provides detailed insights into the optimal synthesis conditions for high‐capacity cobalt‐free cathodes with extended cycle life. Surprisingly, high Li/Ni mixing does not necessarily lead to poor cycling stability whereas low Li/Ni mixing does not guarantee a long cycle life. More importantly, although excessive calcination temperature can further decrease Li/Ni mixing, it does not necessarily enhance capacity. Instead, the pernicious effects from the H2 → H3 phase transition are amplified due to a pronounced two‐phase reaction. An extensive suite of chemical and structural characterization methods uncovers a correlation between elevated calcination temperature, phase transformation, cation ordering, and capacity fading behavior: “overcooking” high‐nickel, cobalt‐free cathodes induce structural arrangement toward that of LiNiO 2 , with exacerbated lattice distortion and surface instability accelerating capacity fade.

Lee, Steven↗

DOE OSTI2021

Range-separated hybrid functionals for mixed dimensional heterojunctions: Application to phthalocyanines/MoS 2

We analyze the electronic structure and level alignment of transition-metal phthalocyanine (MPc) molecules adsorbed on two-dimensional MoS 2 employing density functional theory (DFT) calculations. We develop a procedure for multi-objective optimal tuning of parameters of range-separated hybrid functionals in these mixed-dimensional systems. Using this procedure, which leads to the asymptotically-correct exchange-correlation potential between molecule and two-dimensional material, we obtain electronic structures consistent with experimental photoemission results for both energy level alignment and electronic bandgaps, representing a significant advance compared to standard DFT methods. We elucidate the MoS 2 valence resonance with the transition-metal phthalocyanine non-frontier 3d orbitals and its dependence on the transition metal atomic number. Based on our calculations, we derive parameter-free, model self-energy corrections that quantitatively accounts for the effects of the heterogeneous dielectric environment on the electronic structure of these mixed-dimensional heterojunctions.

2D materials↗

DOE OSTI2023

Shadow energy functionals and potentials in Born–Oppenheimer molecular dynamics

In Born–Oppenheimer molecular dynamics (BOMD) simulations based on the density functional theory (DFT), the potential energy and the interatomic forces are calculated from an electronic ground state density that is determined by an iterative self-consistent field optimization procedure, which, in practice, never is fully converged. The calculated energies and forces are, therefore, only approximate, which may lead to an unphysical energy drift and instabilities. Here, we discuss an alternative shadow BOMD approach that is based on backward error analysis. Instead of calculating approximate solutions for an underlying exact regular Born–Oppenheimer potential, we do the opposite. Instead, we calculate the exact electron density, energies, and forces, but for an underlying approximate shadow Born–Oppenheimer potential energy surface. In this way, the calculated forces are conservative with respect to the approximate shadow potential and generate accurate molecular trajectories with long-term energy stabilities. We show how such shadow Born–Oppenheimer potentials can be constructed at different levels of accuracy as a function of the integration time step, δt, from the constrained minimization of a sequence of systematically improvable, but approximate, shadow energy density functionals. For each energy functional, there is a corresponding ground state Born–Oppenheimer potential. These pairs of shadow energy functionals and potentials are higher-level generalizations of the original “zeroth-level” shadow energy functionals and potentials used in extended Lagrangian BOMD. The proposed shadow energy functionals and potentials are useful only within this extended dynamical framework, where also the electronic degrees of freedom are propagated as dynamical field variables together with the atomic positions and velocities. The theory is quite general and can be applied to MD simulations using approximate DFT, Hartree–Fock, or semi-empirical methods, as well as to coarse-grained flexible charge models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Design and Analysis of a Mutual Inductance Level Sensor for Liquid Metals

Here, this article describes the design and analysis of an electromagnetic level sensor for use in high-temperature liquid metal systems. The mutual inductance level sensor (MILS) described in this work was fabricated using two single-conductor mineral insulated cables wrapped in a bifilar fashion around a stainless steel tube core and was housed in an isolating thimble that preserved the pressure boundary of the test vessel. Two sensor variations were fabricated that differ only in active length, 1016 and 1778 mm. Experimental data were collected using the 1016-mm sensor (MILS-MKII-040) that demonstrated a sensitivity of 9.2 μ V/mm in a room temperature testing stand that used solid aluminum as a surrogate for liquid metal. Experimental data were collected using the 1778-mm sensor (MILS-MKII-070) that demonstrated a sensitivity of 6.9 μ V/mm in the high-temperature (300 ° C) liquid sodium environment at the mechanisms engineering test loop (METL) of Argonne National Laboratory. The sensor performance was found to be repeatable over the course of several months, with roughly ±1% deviation from nominal output. Finite element models were developed in COMSOL Multiphysics that fully describe each test setup, and the models were validated using experimental data. The validated COMSOL models were used to perform an array of analyses that examined the performance of the sensor in differing environments. Maximizing the coil diameter inside the isolating thimble was found to maximize the signal and sensitivity of the sensor. An optimal operating frequency was found near 1000 Hz using both experimental data and COMSOL. The influence of a metallic thimble surrounding the sensor and a metallic sensor core was quantified and found to be negligible at the optimal operating frequency. The sensitivity of the sensor was quantified when monitoring the level of additional liquid metals. These include lead, lead-bismuth eutectic (LBE), sodium-potassium alloy (NaK), and lithium (in addition to sodium). The sensitivities were quantified using liquid metal properties at 350 ° C and 650 ° C. The geometry of the test stand model, all material properties used in the model, and the results are presented in a manner that allows the reader can replicate the model and perform additional analyses.

COMSOL↗

DOE OSTI2023

Promising approaches for the assembly of the catalytically active, recombinant Desulfomicrobium baculatum hydrogenase with substitutions at the active site

Background: Hydrogenases (H2ases) are metalloenzymes capable of the reversible conversion of protons and electrons to molecular hydrogen. Exploiting the unique enzymatic activity of H2ases can lead to advancements in the process of biohydrogen evolution and green energy production. Results: Here we created of a functional, optimized operon for rapid and robust production of recombinant [NiFe] Desulfomicrobium baculatum hydrogenase (Dmb H2ase). The conversion of the [NiFeSe] Dmb H2ase to [NiFe] type was performed on genetic level by site-directed mutagenesis. The native dmb operon includes two structural H2ase genes, coding for large and small subunits, and an additional gene, encoding a specific maturase (protease) that is essential for the proper maturation of the enzyme. Dmb, like all H2ases, needs intricate bio-production machinery to incorporate its crucial inorganic ligands and cofactors. Strictly anaerobic, sulfate reducer D. baculatum bacteria are distinct, in terms of their biology, from E. coli. Thus, we introduced a series of alterations within the native dmb genes. As a result, more than 100 elements, further compiled into 32 operon variants, were constructed. The initial requirement for a specific maturase was omitted by the artificial truncation of the large Dmb subunit. The assembly of the produced H2ase subunit variants was investigated both, in vitro and in vivo. This approach resulted in 4 recombinant [NiFe] Dmb enzyme variants, capable of H 2 evolution. The aim of this study was to overcome the gene expression, protein biosynthesis, maturation and ligand loading bottlenecks for the easy, fast, and cost-effective delivery of recombinant [NiFe] H2ase, using a commonly available E. coli strains. Conclusion: The optimized genetic constructs together with the developed growth and purification procedures appear to be a promising platform for further studies toward fully-active and O 2 tolerant, recombinant [NiFeSe] Dmb H2ase, resembling the native Dmb enzyme. It could likely be achieved by selective cysteine to selenocysteine substitution within the active site of the [NiFe] Dmb variant.

59 BASIC BIOLOGICAL SCIENCES↗