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At least 775 records · Page 43

3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

3’ RNA-seq↗

Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward

The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.

Pappas, Iosif↗

In-situ/operando study of Cu-based nanocatalysts for CO 2 electroreduction using electrochemical liquid cell TEM

The structure of a nanocatalyst during electrocatalytic reactions often deviates from its pristine structure due to intrinsic properties, or physical and chemical adsorption at the catalytic surfaces. Taking Cu-based catalysts for CO 2 electroreduction reactions (CO 2 RR) as an example, they often experience segregation, leaching, and alloying during reactions. With the recent breakthrough development of high-resolution polymer electrochemical liquid cells, in-situ electrochemical liquid cell transmission electron microscopy (EC-TEM) alongside other advanced microscopy techniques, has become a powerful platform for revealing electrocatalysts restructuring at the atomic level. Considering the complex reactions involving electrified solid-liquid interfaces and catalyst structural evolution with intermediates, systematic studies with multimodal approaches are crucial. In this article, we demonstrate a research protocol for the study of electrocatalysts structural evolution during reactions using the in-situ EC-TEM platform. Using Cu and CuAg nanowire catalysts for CO 2 RR as model systems, we describe the experimental procedures and findings. We highlight the platform’s crucial role in elucidating atomic-scale pathways of nanocatalyst restructuring and identifying catalytic active sites, as well as avoiding potential artifacts to ensure unbiased conclusions. Using the multimodal characterization toolbox, we provide the opportunity to correlate the structure of a working catalyst with its performance. Finally, we discuss advancements as well as the remaining gap in elucidating the structural-performance relationship of working catalysts. We expect this article will assist in establishing guidelines for future investigations of complex electrochemical reactions, such as CO 2 RR and other catalytic processes, using the in-situ EC-TEM platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Applications and Techniques for Fast Machine Learning in Science

In this community review report, we discuss applications and techniques for fast machine learning (ML) in science—the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Recovering the effects of subgrid heterogeneity in simulations of radionuclide transport through fractured media

Groundwater flow and contaminant transport through fractured media can be simulated using Discrete Fracture Network (DFN) models which provide a natural description of structural heterogeneity. However, this approach is computationally expensive, with the large number of intersecting fractures necessitated by many real-world applications requiring modeling simplifications to be made for calculations to be tractable. Upscaling methods commonly used for this purpose can result in some loss of local-scale variability in the groundwater flow velocity field, resulting in underestimation of particle travel times, transport resistance and retention in transport calculations. In this paper, a transport downscaling algorithm to recover the transport effects of heterogeneity is tested on a synthetic Brittle Fault Zone model, motivated by the problem of large safety assessment calculations for geological repositories of spent nuclear fuel. We show that the variability in the local-scale velocity field which is lost by upscaling can be recovered by sampling from a library of DFN transport paths, accurately reproducing DFN transport statistic distributions and radionuclide breakthrough curves in an upscaled model.

54 ENVIRONMENTAL SCIENCES↗

Editorial: Innovations in climate resilience

At Battelle’s second Annual Innovations in Climate Resilience Conference, we were inspired this year by the phrase “Bold Leaps and Action.” Climate resilience is a goal and a field that requires boldness. Achieving a state in which societies, countries, continents, and even the globe is robust to changes in climate is often met with doubt, speculation, and indifference. Boldness is required to overcome the gap between an individual’s personal experience and the sheer scale of climate interactions that span from microbes to planets and from nanoseconds to millennia. Moreover, individual scientists, government leaders, and industrialists might each make a small impact and never directly see a measurable effect in Earth’s climate resilience. Is the scientific work in this area futile? Are we as a community on the right path or are we on the right track? Or are we collectively leveraging our potential and contributions toward scalable and more impactful climate resilience solutions that create compounding effects for cities, regions, countries? That leads us to the second part of the phrase that inspired us. It is not just bold leaps but it is action too. The scientific community must put into effect the discoveries that come along with our work in climate resilience. This includes the processes or activities that translate foundational science into real products that society can use. Never before in the history of this country have we had such a commitment to the Research Topic of climate resilience. The White House has made it a major part of their platform. Congress has appropriated and authorized billions of dollars in support. The part we need next is real action. Through our efforts we can discover the interconnected scientific breakthroughs at many spatial scales from city/regional/state to global that were not possible without those government programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗

A review on experimentally observed mechanical and microstructural characteristics of interfaces in multi-material laser powder bed fusion

Additive manufacturing (AM) is a revolutionary technology. One of the key AM categories, metal powder-based fusion processes, has many advantages compared to conventional methods for fabricating structural materials, such as permitting increased geometric complexity. While single material metal powder AM has advanced significantly in the past decade, multi-material AM is gradually attracting more attention owing to the recent breakthrough in multi-material feedstock delivery and the growing interest of fabricating functionally graded components. Multi-material AM offers an alternative route for applications that require location dependent material properties and high geometrical complexity. The AM community has invented several ways to achieve compositional gradients and discrete boundaries in two and three dimensions using mechanical spreading, nozzle-based, electrophotographic, and hybrid techniques. This article reviews the current state of laser powder bed fusion based multi-material AM of metals with focuses on the characteristics of the material interface as well as the properties and performance of the AM built functionally graded materials. We show the common challenges and issues related to material transitions, such as defects, segregation, phase separation, and the efficacy of some potential solutions including material and process optimizations. Additionally, this study evaluates the applicability and limitations of the existing testing standards and methods for measuring mechanical performance of functionally graded materials. Finally, we discuss mechanical testing development opportunities, which can help multi-material AM move towards higher technological maturity. In general, we find that the link between gradient microstructure and mechanical properties is not well understood or studied and suggest several mechanical tests that may better inform this knowledge gap.

42 ENGINEERING↗

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗

Editorial: Functional microcircuits in the brain and in artificial intelligent systems

Fundamental principles underlying higher-order cognitive functions remain elusive, but recent breakthroughs in neurophysiology and deep learning offer new perspectives. First, experimental studies have uncovered neural circuit motifs consisting of various neuron types; see Brain Initiative Cell Census Network (https://www.nature.com/collections/cicghheddj). For example, inhibitory neuron types expressing exclusive genes have specific targets and distinct functions (Pfeffer et al., 2013). Furthermore, diverse neuron types in cortex and their connectomes were identified in cortical columns (Jiang et al., 2015); see also Barth et al. (2016) for a debate on neuron types. Second, artificial neural networks were originally inspired by structures of the brain (McCulloch and Pitts, 1943) and could be trained to perform complex functions similar to human perception/cognition by deep learning (DL) (Lecun et al., 2015).

59 BASIC BIOLOGICAL SCIENCES↗

Soft X-Ray Spectroscopy of Low-Valence Nickelates

Low-valence nickelates—including infinite-layer (IL) and trilayer (TL) compounds—are longstanding candidates for mimicking the high-temperature superconductivity of cuprates. A recent breakthrough in the field came with the discovery of superconductivity in hole-doped IL nickelates. Yet, the degree of similarity between low-valence nickelates and cuprates is the subject of a profound debate for which soft x-ray spectroscopy experiments at the Ni L - and O K -edge provided critical input. In this review, we will discuss the essential elements of the electronic structure of low-valance nickelates revealed by x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS). Furthermore, we will review magnetic excitations observed in the RIXS spectra of IL and TL nickelates, which exhibit characteristics that are partly reminiscent of those of cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Direct air capture of CO2: from insights into the current and emerging approaches to future opportunities

The rapid development of direct air capture (DAC) technologies has become critical in order to remove CO 2 from the atmosphere and limit global warming to a maximum of 1.5°C. In this perspective, we provide a mini review of the current research on the emerging liquid- and solid-based sorbent materials to capture CO 2 , summarize the existing challenges of DAC technologies, and suggest future research directions to accelerate the development of DAC systems. In particular, the desired properties for a breakthrough sorbent that efficiently captures CO 2 from the air and releases it for sequestration are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Anthropology of Aquaculture

Aquaculture is nothing new. It has a long, fascinating history that stretches from antiquity at least 8,000 years ago. What is new is the evolution of aquaculture in modern times into highly intensive monocultures which arose in the 1970–1980's. Modern aquaculture production has grown worldwide but remains concentrated in Asia due to the: (1) increased demands for aquatic foods as explosive population growth occurred in coastal cities with increasing affluence, (2) expansion of scientific and engineering breakthroughs, (3) high export values of aquatic foods, and (4) sharp decline of costs of global to local transport/shipping. The pioneering anthropologist Claude Levi-Strauss brought the idea of “structuralism” to anthropology: the concept that societies throughout history followed universal patterns of behavior. A qualitative document analysis of the key anthropological literature to assess aquaculture developments from antiquity to the beginning of the modern era was conducted to evaluate if there was adequate evidence to support a theory of anthropological “structuralism” for aquaculture in human history. Seven case studies of the cultural/environmental history of aquaculture were reviewed in diverse parts of the world (China, Australia, Egypt, Europe, South America, Canada/USA, Hawai'i). Analysis supports the structural theory that whenever the demands of aquatic/seafood-eating peoples exceeded the abilities of their indigenous fishery ecosystems to provide for them, they developed aquaculture. Modern aquaculture concepts and new communities of practice in “restoration aquaculture” have beginnings in Indigenous anthropology and archeology in aquaculture and point the way for Indigenous nations to engage as leaders of the United Nations Food and Agriculture Organization (FAO) ecosystem approach to aquaculture worldwide. Bringing ancient knowledge of Indigenous aquaculture into the modern context is an essential part of an alternative, “radical transformation” of modern aquaculture. There is an urgent need to develop and promote locally designed and culturally appropriate aquaculture systems that fit into the livelihoods of communities as part of a larger, diverse portfolio of food security.

54 ENVIRONMENTAL SCIENCES↗

Complex Attosecond Waveform Synthesis at FEL FERMI

Free-electron lasers (FELs) can produce radiation in the short wavelength range extending from the extreme ultraviolet (XUV) to the X-rays with a few to a few tens of femtoseconds pulse duration. These facilities have enabled significant breakthroughs in the field of atomic, molecular, and optical physics, implementing different schemes based on two-color photoionization mechanisms. In this article, we present the generation of attosecond pulse trains (APTs) at the seeded FEL FERMI using the beating of multiple phase-locked harmonics. We demonstrate the complex attosecond waveform shaping of the generated APTs, exploiting the ability to manipulate independently the amplitudes and the phases of the harmonics. The described generalized attosecond waveform synthesis technique with an arbitrary number of phase-locked harmonics will allow the generation of sub-100 as pulses with programmable electric fields.

47 OTHER INSTRUMENTATION↗

The DREAM Endstation at the Linac Coherent Light Source

Free-electron lasers (FEL), with their ultrashort pulses, ultrahigh intensities, and high repetition rates at short wavelength, have provided new approaches to Atomic and Molecular Optical Science. One such approach is following the birth of a photo electron to observe ion dynamics on an ultrafast timescale. Such an approach presents the opportunity to decipher the photon-initiated structural dynamics of an isolated atomic and molecular species. It is a fundamental step towards understanding single- and non-linear multi-photon processes and coherent electron dynamics in atoms and molecules, ultimately leading to coherent control following FEL research breakthroughs in pulse shaping and polarization control. A key aspect for exploring photoinduced quantum phenomena is visualizing the collective motion of electrons and nuclei in a single reaction process, as dynamics in atoms/ions proceed at femtosecond (10 –15 s) timescales while electronic dynamics take place in the attosecond timescale (10 –18 s). Here, we report on the design of a Dynamic Reaction Microscope (DREAM) endstation located at the second interaction point of the Time-Resolved Molecular and Optical (TMO) instrument at the Linac Coherent Light Source (LCLS) capable of following the photon–matter interactions by detecting ions and electrons in coincidence. The DREAM endstation takes advantage of the pulse properties and high repetition rate of LCLS-II to perform gas-phase soft X-ray experiments in a wide spectrum of scientific domains. With its design ability to detect multi-ions and electrons in coincidence while operating in step with the high repetition rate of LCLS-II, the DREAM endstation takes advantage of the inherent momentum conservation of reaction product ions with participating electrons to reconstruct the original X-ray photon–matter interactions. In this report, we outline in detail the design of the DREAM endstation and its functionality, with scientific opportunities enabled by this state-of-the-art instrument.

47 OTHER INSTRUMENTATION↗

Molecular-Scale Considerations of Enhanced Oil Recovery in Shale

With only less than 10% recovery, the primary production of hydrocarbon from shale reservoirs has redefined the energy equation in the world. Similar to conventional reservoirs, Enhanced Oil Recovery (EOR) techniques could be devised to enhance the current recovery factors. However, shale reservoirs possess unique characteristics that significantly affect the fluid properties. Therefore, we are adopting a molecular simulation approach that is well-suited to account for these effects to evaluate the performance of three different gases, methane, carbon dioxide and nitrogen, to recover the hydrocarbons from rough pore surfaces. Our hydrocarbon systems consists of either a single component (decane) or more than one component (decane and pentane). We simulated cases where concurrent and countercurrent displacement is studied. For concurrent displacement (injected fluids displace hydrocarbons towards the production region), we found that nitrogen and methane yielded similar recovery; however nitrogen exhibited a faster breakthrough. On the other hand, carbon dioxide was more effective in extracting the hydrocarbons when sufficient pressure was maintained. For countercurrent displacement (gases are injected and hydrocarbons are produced from the same direction), methane was found to be more effective, followed by carbon dioxide and nitrogen. In all cases, confinement reduced the recovery factor of all gases. This work provides insights to devise strategies to improve the current recovery factors observed in shale reservoirs.

04 OIL SHALES AND TAR SANDS↗

Multi-Scale Microfluidics for Transport in Shale Fabric

We develop a microfluidic experimental platform to study solute transport in multi-scale fracture networks with a disparity of spatial scales ranging between two and five orders of magnitude. Using the experimental scaling relationship observed in Marcellus shales between fracture aperture and frequency, the microfluidic design of the fracture network spans all length scales from the micron (1 μ) to the dm (10 dm). This intentional `tyranny of scales’ in the design, a determining feature of shale fabric, introduces unique complexities during microchip fabrication, microfluidic flow-through experiments, imaging, data acquisition and interpretation. Here, we establish best practices to achieve a reliable experimental protocol, critical for reproducible studies involving multi-scale physical micromodels spanning from the Darcy- to the pore-scale (dm to μm). With this protocol, two fracture networks are created: a macrofracture network with fracture apertures between 5 and 500 μm and a microfracture network with fracture apertures between 1 and 500 μm. The latter includes the addition of 1 μm ‘microfractures’, at a bearing of 55°, to the backbone of the former. Comparative analysis of the breakthrough curves measured at corresponding locations along primary, secondary and tertiary fractures in both models allows one to assess the scale and the conditions at which microfractures may impact passive transport.

58 GEOSCIENCES↗

Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO2, rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Energy & Fuels↗