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At least 397 records · Page 22

Bifacial Multilayer Graphene Float Transfer

A method for graphene transfer which is referred to as “bifacial transfer” that allows transfer of multilayer chemical vapor deposition (CVD) graphene from both sides of a native metal substrate, such as an as-received nickel catalyst, is presented. In traditional transfer methods, the graphene on the “non-preferred” side, that is, the bottom of the substrate, is removed with oxygen plasma before removal of the metal catalyst in etchant solution. Although this treatment prevents undesired aggregation of the graphene films, it fails to utilize both sides of CVD-grown graphene. The bifacial transfer method reduces the cost of multilayer graphene by allowing the transfer of graphene from both sides of the substrate. The quality of graphene transferred from both sides onto target glass and polymer substrates is compared. The results of optical microscopy, confocal Raman spectroscopy, atomic force microscopy, and electronic transport measurements suggest that the quality of the multilayer graphene on the “non-preferred” side does not differ significantly from that of the “preferred” side. Overall, this method will allow more efficient and cost-effective use of graphene by doubling the usable graphene per area of growth substrate, and by eliminating the need for intermediate sacrificial transfer substrates such as poly(methyl methacrylate).

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Scale bridging damage model for quasi-brittle metals informed with crack evolution statistics

Computationally efficient methods for bridging length scales, from highly resolved micro/meso-scale models that can explicitly model crack growth, to macro-scale continuum models that are more suitable for modeling large parts, have been of interest to researchers for decades. In this work, an improved brittle damage model is presented for the simulation of dynamic fracture in continuum scale quasi-brittle metal components. Crack evolution statistics, including the number, length, and orientation of individual cracks, are extracted from high-fidelity, finite discrete element method (FDEM) simulations and used to generate effective material moduli that reflect the material’s damaged state over time. This strategy allows for the retention of small-scale physical behaviors such as crack growth and coalescence in continuum scale hydrodynamic simulations. However, the high-fidelity simulations required to generate the crack statistics are computationally expensive. Thus, steps were taken to produce a flexible constitutive model to reduce the number of costly high-fidelity simulations needed to produce accurate results. A new stress based degradation criterion is introduced for the degradation of individual material zones. This allows for the development of a heterogeneous damage distribution within the bulk material. Then a flow stress model is added to the hydrodynamic simulation to account for plasticity in quasi-brittle materials. As a result, the effective moduli model can be applied to a larger range of materials. The effective moduli constitutive model is used to simulate beryllium flyer plate experiments. The results from the continuum scale simulations using statistics from a single high-fidelity simulation are found to be in excellent agreement with numerical and experimental velocity interferometer data. The same set of crack statistics are used to extrapolate the results of a higher rate flyer plate case using the effective moduli model. In conclusion, the extension of this model to higher rate cases shows promise for further reducing the number of costly high-fidelity simulations needed to generate crack statistics.

36 MATERIALS SCIENCE↗

Roadmap to 100 GWDC: Scientific and supply chain challenges for CdTe photovoltaics

This roadmap highlights pathways to expand the CdTe module manufacturing capacity per year to 100 GW DC by 2030 by improving Te extraction from existing supply chains, minimizing Te usage in modules by leveraging thinner absorbers, and focusing research efforts in key areas to improve module efficiencies. Both scientific and supply chain innovations will be necessary to maintain the high compound annual growth rate of the CdTe photovoltaic (PV) industry and cement its role as a key technology for multi-TW-scale PV deployment.

14 SOLAR ENERGY↗

Dissolution of the Solid Electrolyte Interphase and Its Effects on Lithium Metal Anode Cyclability

At >95% Coulombic efficiencies, most of the capacity loss for Li metal anodes (LMAs) is through the formation and growth of the solid electrolyte interphase (SEI). However, the mechanism through which this happens remains unclear. One property of the SEI that directly affects its formation and growth is the SEI’s solubility in the electrolyte. Here, in this work, we systematically quantify and compare the solubility of SEIs derived from ether-based electrolytes optimized for LMAs using in-operando electrochemical quartz crystal microbalance (EQCM). A correlation among solubility, passivity, and cyclability established in this work reveals that SEI dissolution is a major contributor to the differences in passivity and electrochemical performance among battery electrolytes. Together with our EQCM, X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) spectroscopy results, we show that solubility depends on not only the SEI’s composition but also the properties of the electrolyte. This provides a crucial piece of information that could help minimize capacity loss due to SEI formation and growth during battery cycling and aging.

25 ENERGY STORAGE↗

Orthogonal glycolytic pathway enables directed evolution of noncanonical cofactor oxidase

Abstract Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN + ) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN + -based reducing power. This is based on an orthogonal, NMN + -dependent glycolytic pathway in Escherichia coli which can be coupled to any reciprocal enzyme to recycle the ensuing reduced NMN + . With a throughput of >10 6 variants per iteration, the growth selection discovers a Lactobacillus pentosus NADH oxidase variant with ~10-fold increase in NMNH catalytic efficiency and enhanced activity for other NCBs. Molecular modeling and experimental validation suggest that instead of directly contacting NCBs, the mutations optimize the enzyme’s global conformational dynamics to resemble the WT with the native cofactor bound. Restoring the enzyme’s access to catalytically competent conformation states via deep navigation of protein sequence space with high-throughput evolution provides a universal route to engineer NCB-dependent enzymes.

59 BASIC BIOLOGICAL SCIENCES↗

Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems

The fast-paced growth in digitization of smart grid components enhances system observability and remote-control capabilities through efficient communication. However, enhanced connectivity results in heightened system vulnerability towards cybersecurity risks in the cyber-physical power system. Coordinated cyber-attacks (CCA), when undetected, lead to system-wide impact in terms of large disturbances or widespread outages. Detecting CCA in the cyber layer is critical to thwart cyber-attacks in real-time before the attack impacts the physical system. The challenge of locating CCA stems from the complex grid dynamics, making it difficult to distinguish between normal operational variations and cyber-attack impact. CCA often employs multiple attack vectors targeting geographically distributed components, further complicating CCA identification. Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. In this paper, a novel proactive DCA strategy is proposed for early detection of CCA by establishing correlations among distinct attack events through model-based reinforcement learning that utilizes abductive reasoning to conclude the attacker goal. The solution includes understanding the system model, learning the system dynamics, and correlating individual cyber-attacks to extract the attacker’s objective. The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. A DNP3-based cyber-physical co-simulation testbed is developed to test the proposed algorithm using the IEEE 13-node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Novel Algae Technology for CO2 Utilization

The United States, the world’s largest energy user and second largest CO2 emitter, is heavily dependent on fossil energy. In 2014, U.S. coal burning utilities emitted ~1562 million (MM) tons/year (TPY) of CO2 into the atmosphere, accounting for 76% of the total US power sector emissions1. Hence, reducing the CO2 emission footprint from coal plants is widely viewed as a key element in mitigating global warming. Despite significant interest, implementation of CO2 capture technologies has been constrained by the high capture cost which significantly increases the total cost of electricity. Not only is capturing CO2 with traditional technologies expensive, but generally the CO2 has little value and additional expense must be incurred for sequestration. This project funded by a SBIR grant from the U.S. D.O.E. to Helios-NRG in collaboration with the State University of New York at Buffalo (UB) and Membrane Technology and Research Inc. (MTR) aimed to develop a novel, algae based technology to capture CO2 from the effluent of coal-based power plants and convert it to renewable bio-fuels and higher value co-products such as animal feed and nutraceuticals with the potential to enable a substantial reduction in the net cost of carbon capture. The Phase 2 project was aimed at further demonstrating the technical feasibility of the proposed multi-stage continuous (MSC) flow CO2 capture system and the generation of high-value co-products to offset the CO2 capture cost. The project was completed and the project objectives were met and exceeded. A first-of-a-kind integrated, laboratory scale MSC process unit was fabricated and tested in a greenhouse. The tests were conducted with the preferred algae species identified in Phase I and simulated flue gas containing contaminants at levels typically present in the post flue gas desulfurization (FGD) stream, including ~12% CO2, acid gas (SOX, NOX), and a large number of heavy metals. The tests were successful and demonstrated a 25g/m2/day seasonal average algae productivity and an 80% CO2 capture efficiency. Two new algae species were identified for high-value nutraceutical production. Studies to improve growth rate and nutraceutical content of these algae species were performed and a pathway for further improvements was identified. A new dewatering technology called DeAqua was further advanced. Significant improvement in the performance index was achieved. The anti-fouling membrane was developed and fabricated into a module. The fabricated membrane module was tested with algae slurry and demonstrated improved fouling resistant properties, that can potentially reduce the cost and energy of the critical dewatering step. Test data were used to simulate operation of the overall process. The preliminary economic analysis was updated and modelled based on a 5000-acre algae farm. To the extent possible, the financial and operating assumptions used were the same as those used in the DOE’s 2022 projections for algae technology for CO2 capture and utilization. The results showed the proposed technology’s potential to significantly reduce the cost of CO2 capture compared to current options and that the high value products generated from the CO2 captured can make a step change in the cost of carbon capture. Plans to advance the technology to Phase 2B were developed and potential end-user partners were identified.

Maloney, James↗

A Single Amino Acid Substitution in the Matrix Protein (M51R) of Vesicular Stomatitis New Jersey Virus Impairs Replication in Cultured Porcine Macrophages and Results in Significant Attenuation in Pigs

In this study, we explore the virulence of vesicular stomatitis New Jersey virus (VSNJV) in pigs and its potential relationship with the virus’s ability to modulate innate responses. For this purpose, we developed a mutant of the highly virulent strain NJ0612NME6, containing a single amino acid substitution in the matrix protein (M51R). The M51R mutant of NJ0612NME6 was unable to suppress the transcription of genes associated with the innate immune response both in primary fetal porcine kidney cells and porcine primary macrophage cultures. Impaired viral growth was observed only in porcine macrophage cultures, indicating that the M51 residue is required for efficient replication of VSNJV in these cells. Furthermore, when inoculated in pigs by intradermal scarification of the snout, M51R infection was characterized by decreased clinical signs including reduced fever and development of less and smaller secondary vesicular lesions. Pigs infected with M51R had decreased levels of viral shedding and absence of RNAemia compared to the parental virus. The ability of the mutant virus to infect pigs by direct contact remained intact, indicating that the M51R mutation resulted in a partially attenuated phenotype capable of causing primary lesions and transmitting to sentinel pigs. Collectively, our results show a positive correlation between the ability of VSNJV to counteract the innate immune response in swine macrophage cultures and the level of virulence in pigs, a natural host of this virus. More studies are encouraged to evaluate the interaction of VSNJV with macrophages and other components of the immune response in pigs.

59 BASIC BIOLOGICAL SCIENCES↗

Review of Direct Neutron Conversion and Detection Processes

Commercial and laboratory neutron detection systems use indirect neutron response of materials like pressurized helium-3 (via nuclear reaction 3He(n, p)3H) to measure and count neutrons emanating from a source. Recently a host of semiconductors, especially a ternary semiconductor of lithium indium diselenide (6LiInSe2) and a quaternary alloy of enriched lithium-6, indium, phosphorous, and selenium (6LiInP2Se6), have shown promising neutron counting possibilities by directly converting neutrons into charge-carrying elements within the body of the semiconductor. These semiconductors have high thermal neutron capture cross sections, suitable energy bandgaps (~2.0 electron volts) for room-temperature operations, and a favorable electronic band structure for efficient electron charge transport. The article examines the semiconductor properties of these compounds in terms of their neutron counting capabilities and possible ways to extract neutron energy information from them. Lithium-6 and boron-10 (with thermal neutron absorption cross sections of 938 ± 6 and 3855 ± 26 barns, respectively) produce charged particles to be measured via indirect neutron interactions. The efficiency of indirect conversion neutron detectors is limited because of the inefficiencies in conversion mechanism. In case of direct conversion, the neutrons create charged particles in a single material for neutron capture and charge collection, increasing detection efficiency. Unlike 3He proportional counters, which provide no neutron energy information, the semiconductors can be used as neutron energy spectrometer. Fully resolved neutron energy by 6LiInP2Se6 from a plutonium-beryllium source has been reported in the literature. We will discuss the influence of these multilayered semiconductors’ crystallographic structures and growth techniques on neutron energy determination.

61 RADIATION PROTECTION AND DOSIMETRY↗

Expression of a bacterial 3-dehydroshikimate dehydratase (QsuB) reduces lignin and improves biomass saccharification efficiency in switchgrass (Panicum virgatum L.)

Abstract Background Lignin deposited in plant cell walls negatively affects biomass conversion into advanced bioproducts. There is therefore a strong interest in developing bioenergy crops with reduced lignin content or altered lignin structures. Another desired trait for bioenergy crops is the ability to accumulate novel bioproducts, which would enhance the development of economically sustainable biorefineries. As previously demonstrated in the model plant Arabidopsis, expression of a 3-dehydroshikimate dehydratase in plants offers the potential for decreasing lignin content and overproducing a value-added metabolic coproduct (i.e., protocatechuate) suitable for biological upgrading. Results The 3-dehydroshikimate dehydratase QsuB from Corynebacterium glutamicum was expressed in the bioenergy crop switchgrass ( Panicum virgatum L.) using the stem-specific promoter of an O-methyltransferase gene ( pShOMT ) from sugarcane. The activity of pShOMT was validated in switchgrass after observation in-situ of beta-glucuronidase (GUS) activity in stem nodes of plants carrying a pShOMT::GUS fusion construct. Under controlled growth conditions, engineered switchgrass lines containing a pShOMT::QsuB construct showed reductions of lignin content, improvements of biomass saccharification efficiency, and accumulated higher amount of protocatechuate compared to control plants. Attempts to generate transgenic switchgrass lines carrying the QsuB gene under the control of the constitutive promoter pZmUbi-1 were unsuccessful, suggesting possible toxicity issues associated with ectopic QsuB expression during the plant regeneration process. Conclusion This study validates the transfer of the QsuB engineering approach from a model plant to switchgrass. We have demonstrated altered expression of two important traits: lignin content and accumulation of a co-product. We found that the choice of promoter to drive QsuB expression should be carefully considered when deploying this strategy to other bioenergy crops. Field-testing of engineered QsuB switchgrass are in progress to assess the performance of the introduced traits and agronomic performances of the transgenic plants.

59 BASIC BIOLOGICAL SCIENCES↗

Stability and Characteristics of Lower-hybrid Drift Waves: Dependence on Electron Beta and Cross-field Relative Drift

Lower-hybrid drift waves (LHDWs) are frequently observed microinstabilities in both space and laboratory plasmas. Despite decades of study, the relationship between electrostatic (ES-LHDW) and electromagnetic (EM-LHDW) variants and the plasma parameters controlling their stability remains unclear. Here, we systematically examine LHDW behavior by solving the local linear dispersion relation over a wide range of plasma and field conditions. Our results demonstrate that ES-LHDWs and EM-LHDWs are not distinct modes but rather two different regimes of the same drift wave whose character evolves smoothly with electron beta (β e ) and the cross-field electron drift velocity relative to ions, normalized to the ion sound speed (u 0x /C s ). The nature of the waves changes from electrostatic to electromagnetic when β e increases. Growth rates increase with u 0x /C s but decrease with β e , while the most unstable wavelength remains nearly universal, with kρ e ∼ 0.8 (k is the magnitude of the wave vector and ρ e is the electron gyroradius). We further present quasi-linear estimates of nonlinear saturation properties, including energy partition among electric fields, magnetic fields, and particle kinetic responses. We show that ES-LHDWs reach higher electric-field saturation amplitudes, whereas EM-LHDWs generate strong magnetic perturbations and parallel electric fields that may enable efficient particle heating. Comparisons with the classical model reveal that retaining electromagnetic effects is essential for accurate predictions of frequency, growth rate, and the propagation angle. These findings provide a unified framework for understanding LHDWs across diverse collisionless plasma environments, including current sheets of magnetic reconnection, shear layers, collisionless shocks, and boundary regions.

Solar coronal waves↗

Electrolyte-phobic Surface for the Next-Generation Nanostructured Battery Electrodes

Nanostructured electrodes are among the most important candidates rationally designed to enable high capacity battery chemistry. Nanostructures can solve issues such as the volume change and mechanical fragmentations. However, the high surface area they usually possess would decrease the Coulombic efficiencies, since the side chemical reactions scale with surface area. Moreover, electrodes comprised of nanomaterials have significant intakes of liquid electrolytes, which reduces the overall energy density and increases the cost of the battery. Here we present a new strategy of limiting effective surface area by introducing an “electrolyte-phobic surface”. In this study, a porous Si anode functions as a model material to demonstrate this concept. Silicon boasts high theoretical capacity, but experiences large volume change during its lithiation and delithiation processes. Porous Si can address this volume change problem with the buffer effect of its inner pores. However, porous silicon shows low initial Coulombic efficiencies and high irreversible lithium loss, owing to its intrinsic high surface area. In this report, a covalently linked perfluorinated surface coating layer on porous Si particles serves as an electrolyte-phobic protection layer, minimizing the accessible surface area for the electrolytes, decreasing the side reactions between the electrolyte and Si surface, and thus significantly enhancing the initial Coulombic efficiencies, up to ~88% compared to ~60% for the pristine porous silicon. Meanwhile, the electrolyte-phobic protection layer of Si particles keeps the silicon surface compatible with the conventional polyvinylidene fluoride (PVDF) binder, which helps to stabilize the Si electrode for long-term battery cycling.

Qian, Chenxi↗

Engineered reduction of S-adenosylmethionine alters lignin in sorghum

Abstract Background Lignin is an aromatic polymer deposited in secondary cell walls of higher plants to provide strength, rigidity, and hydrophobicity to vascular tissues. Due to its interconnections with cell wall polysaccharides, lignin plays important roles during plant growth and defense, but also has a negative impact on industrial processes aimed at obtaining monosaccharides from plant biomass. Engineering lignin offers a solution to this issue. For example, previous work showed that heterologous expression of a coliphage S -adenosylmethionine hydrolase (AdoMetase) was an effective approach to reduce lignin in the model plant Arabidopsis. The efficacy of this engineering strategy remains to be evaluated in bioenergy crops. Results We studied the impact of expressing AdoMetase on lignin synthesis in sorghum ( Sorghum bicolor L. Moench). Lignin content, monomer composition, and size, as well as biomass saccharification efficiency were determined in transgenic sorghum lines. The transcriptome and metabolome were analyzed in stems at three developmental stages. Plant growth and biomass composition was further evaluated under field conditions. Results evidenced that lignin was reduced by 18% in the best transgenic line, presumably due to reduced activity of the S -adenosylmethionine-dependent O -methyltransferases involved in lignin synthesis. The modified sorghum features altered lignin monomer composition and increased lignin molecular weights. The degree of methylation of glucuronic acid on xylan was reduced. These changes enabled a ~20% increase in glucose yield after biomass pretreatment and saccharification compared to wild type. RNA-seq and untargeted metabolomic analyses evidenced some pleiotropic effects associated with AdoMetase expression. The transgenic sorghum showed developmental delay and reduced biomass yields at harvest, especially under field growing conditions. Conclusions The expression of AdoMetase represents an effective lignin engineering approach in sorghum. However, considering that this strategy potentially impacts multiple S -adenosylmethionine-dependent methyltransferases, adequate promoters for fine-tuning AdoMetase expression will be needed to mitigate yield penalty.

Tian, Yang↗

Advances in Mixed Tin‐Lead Narrow‐Bandgap Perovskites for Single‐Junction and All‐Perovskite Tandem Solar Cells

Abstract Organic–inorganic metal‐halide perovskites have received great attention for photovoltaic (PV) applications owing to their superior optoelectronic properties and the unprecedented performance development. For single‐junction PV devices, although lead (Pb)‐based perovskite solar cells have achieved 26.1% efficiency, the mixed tin‐lead (Sn‐Pb) perovskites offer more ideal bandgap tuning capability to enable an even higher performance. The Sn‐Pb perovskite (with a bandgap tuned to ≈1.2 eV) is also attractive as the bottom subcell for a tandem configuration to further surpass the Shockley–Queisser radiative limit for the single‐junction devices. The performance of the all‐perovskite tandem solar cells has gained rapid development and achieved a certified efficiency up to 29.1%. In this article, the properties and recent development of state‐of‐the‐art mixed Sn‐Pb perovskites and their application in single‐junction and all‐perovskite tandem solar cells are reviewed. Recent advances in various approaches covering additives, solvents, interfaces, and perovskite growth are highlighted. The authors also provide the perspective and outlook on the challenges and strategies for further development of mixed Sn‐Pb perovskites in both efficiency and stability for PV applications.

14 SOLAR ENERGY↗

High-Efficiency, Low-Cost III-V Solar Cells by Dynamic Hydride Vapor Phase Epitaxy Coupled with Rapid, Polishing-Free Wafer Reuse through Orientation-Optimized (110) Spalling

We demonstrated (110) GaAs solar cells grown by D-HVPE with equivalent performance and material quality relative to (100) devices. Also, we developed a procedure for repeatable wafer-scale spalling of (110) GaAs. Spalled surfaces were free of the facets founds in (100) GaAs spalling, the large arrest lines found in (100) Ge spalling, and surface features greater than 3 µm in peak-to-valley height, which can otherwise degrade the efficiency of regrown III-V devices. A sub-µm step-terrace morphology was discovered on the post-spall wafer surface, resulting from the restricted cleavage system of GaAs, but we developed understanding of the factors that determine the resulting morphology, enabling ample opportunity for optimization of morphologies suitable for device growth and spall depth waste minimization on (110) GaAs. Lastly, we demonstrated a device grown on a previously spalled surface with only 8% relative efficiency difference to a cell grown on a new unspalled wafer. Significant optimization of the substrate regrowth conditions are required to enable higher efficiency, but these results highlight the promise of (110)-oriented devices coupled with substrate reuse by spalling as a pathway for low-cost III-V photovoltaics.

14 SOLAR ENERGY↗

Mortality predispositions of conifers across Western USA

Conifer mortality rates are increasing in North America, but the physiological mechanisms underlying this trend are still not well understood. We examined tree-ring based growth rates, stable carbon and oxygen isotope ratios (d13C and d18O, respectively) of dying and surviving conifers at eight old-growth forest sites across a strong moisture gradient in the western USA to retrospectively investigate mortality predispositions. Compared to surviving trees, lower growth of dying trees was detected at least one decade prior to mortality at seven of the eight sites. Intrinsic water-use efficiency (iWUE) increased over time in both surviving and dying trees, with a weaker increase in dying trees at five of the eight sites. The relationship between iWUE and d18O was much stronger and steeper for surviving trees, suggesting an important hydraulic role in mortality. Carbon starvation was a strong correlate of conifer mortality based on a conceptual model incorporating growth, d13C, and d18O. Our results provide a direct link of mortality to growth constraints in western USA conifers.

Wang, Wenzhi↗

Metabolic Synergy between Human Symbionts Bacteroides and Methanobrevibacter

Trophic interactions between microbes are postulated to determine whether a host microbiome is healthy or causes predisposition to disease. Two abundant taxa, the Gram-negative heterotrophic bacterium Bacteroides thetaiotaomicron and the methanogenic archaeon Methanobrevibacter smithii, are proposed to have a synergistic metabolic relationship. Both organisms play vital roles in human gut health; B. thetaiotaomicron assists the host by fermenting dietary polysaccharides, whereas M. smithii consumes end-stage fermentation products and is hypothesized to relieve feedback inhibition of upstream microbes such as B. thetaiotaomicron. To study their metabolic interactions, we defined and optimized a coculture system and used software testing techniques to analyze growth under a range of conditions representing the nutrient environment of the host. Here we verify that B. thetaiotaomicron fermentation products are sufficient for M. smithii growth and that accumulation of fermentation products alters secretion of metabolites by B. thetaiotaomicron to benefit M. smithii. Studies suggest that B. thetaiotaomicron metabolic efficiency is greater in the absence of fermentation products or in the presence of M. smithii. Under certain conditions, B. thetaiotaomicron and M. smithii form interspecies granules consistent with behavior observed for syntrophic partnerships between microbes in soil or sediment enrichments and anaerobic digesters. Furthermore, when vitamin B 12 , hematin, and hydrogen gas are abundant, coculture growth is greater than the sum of growth observed for monocultures, suggesting that both organisms benefit from a synergistic mutual metabolic relationship.

59 BASIC BIOLOGICAL SCIENCES↗

Towards Sustainable Post-Exascale Leadership Computing

As computing systems approach the limits of traditional silicon technology, the diminishing returns in performance per watt present a significant barrier to sustaining growth in HPC. From a large-scale scientific supercomputing facility point of view, we propose a multifaceted strategy toward specialized hardware and architectures that are optimized for energy efficiency in specific applications. We also emphasize the need for integrating energy-aware practices across all levels of HPC, from system design and software development to operational policies. We discuss strategic opportunities such as the adoption of application-specific accelerators, the development of energy-efficient algorithms, and the implementation of data-driven operational analytics. Our goal is to develop a comprehensive roadmap ensuring that future leadership systems at OLCF can meet scientific demands while operating within stringent energy budgets, thereby supporting sustainable computing growth.

Shin, Woong↗