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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Potential absence of observed π2 linear-chain structures in 14O via 10C(α,α) resonances scattering

Background: The preference for light nuclear systems to coagulate into -particle clusters has been well-studied. The possibility of a linear chain configuration of -particles would allow for a new way to study this phenomenon. Purpose: A rotational band of states in C has been claimed showing a linear chain structure. The mirror system, O, has been studied here to examine how this linear chain structure is affected by replacing the valence neutrons with protons. Method: A beam of C was incident into a chamber filled with He:CO gas with the tracks recorded inside the TexAT Time Projection Chamber and the recoil -particles detected by a silicon detector array to measure the cross section. Results: The experimental cross section was compared with previous studies and fit using R-Matrix theory with the previously-observed O states being transformed to the C using mirror symmetry. The measured cross section does not replicate the claimed states, with the predicted cross section exceeding that observed at several energies and angles. Conclusion: A series of possibilities are highlighted with the most likely being that the originally-seen C states did not constitute a rotational band with a potentially incorrect spin assignment due to the limitations of the angular correlation method with non-zero spin particles. The work highlights the difficulties in measuring broad resonances corresponding to a linear chain state in a high level density.

Bishop, J.↗

DOE OSTI2022

Tracking the evolution from isolated dimers to many-body entanglement in $\mathrm{NaLu}_x \mathrm{Yb}_{1-x}\mathrm{Se_2}$

Here, we synthesize homogeneous compositions of NaLu x Yb 1-x Se 2 , connecting nonmagnetic NaLuSe 2 to the triangular lattice spin liquid candidate NaYbSe 2 . Thermal and magnetic properties are studied as the system evolves from one with dilute magnetic defects to one of a dense magnetic lattice. The field- and temperature-dependent heat capacity show the carriers of entropy cross over from isolated magnetic ions to a correlated lattice born from spin dimers. For the dilute system we estimate the single-ion anisotropy (g ⟂ /g ∥ =3.13) and also the dimer exchange couplings J ⟂ (=5.4 K) and J ⟂ (=9.6 K), in order to draw comparison to the half-doped and full magnetic compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Consequently, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. In this work, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMeta™) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A stress-sensitive precipitate nucleation model beyond classical nucleation theory

The dynamic evolution of precipitates and second phases dictates the strength and stability of most engineering alloys. By design, or as a consequence of thermo-mechanical aging, engineering metals and alloys often form precipitates of second phases when subjecting to diverse thermal and mechanical loads. Precipitation is governed by several factors, including the alloy’s composition, processing/operating temperature, and stresses — either as a result of external loads or from residual stresses. However, state-of-the-art models for precipitate nucleation (i.e., classical nucleation theory) typically lacks consistent method to capture the effects of externally applied and/or internal stresses on nucleation; thereby severely limiting the applicability of these models to complex materials systems and to representative loading scenarios. Here, in this work, we extend upon classical nucleation theory to account for the effect of stresses on precipitation kinetics and thermodynamics. This is achieved via the use of an Eshelbian micromechanics framework keeping track of (i) the stress build up resulting from second phase formation as a function of mechanical load and, (ii) the effects of dislocations on precipitate formation. This new model is applied to σ precipitate in Fe–Cr binary alloys and M 23 C 6 precipitate in 316H stainless steel (SS). Simulations demonstrate the important role of both the remotely applied loads and dislocation pile ups on precipitate nucleation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Formation and surface melting of nanoparticle superlattices in a solution

The wisdom in the saying of “There are no two snowflakes alike” lies in the importance of history or kinetic pathways in the phase transitions of solids. Likewise, “artificial solids,” namely superlattices consisting of functional nanoparticles, have lattice size, surface morphology, crystallinity, symmetry, and structural reconfiguration (for example, transition into a disordered state) highly dependent on the kinetic pathways as the nanoparticles interact with each other in solution [1]. Great progresses have been made in understanding the formation pathways of superlattices using liquid-phase transmission electron microscopy (TEM) [2-4]. For example, by tracking single nanoparticle’s trajectories, especially aided by U-net neural network-based machine learning, previous studies mapped the fundamental nanoparticle interactions at nanometer resolution [5]. Nonclassical, two-step nucleation pathway has also been elucidated in the system of nanoprisms, by optimizing protocols such as loading nanoparticle suspensions over the supersaturation threshold and minimizing particle‒substrate interaction [2]. Surface morphologies or exposed facets of superlattices have been shown to follow the principles of Wulff construction rule, where the facet-dependent surface energy can be measured based on the capillary wave theory [4]. However, the reverse process of crystallization of superlattices, the conversion from crystalline to disordered state, has been much less explored. On one hand, the melting of nanoparticle superlattices can provide a preferred pathway to induce structural reorganization or shuffling of building blocks for them to transform into different types of crystal structures. On the other hand, understanding nanoscale superlattice melting and comparing such behaviors with the prevailing surface melting theories developed for atomic/molecular solids can provide a potent way to engineer phase transitions of supra- and hierarchical structures constructed from nanoscale entities (e.g., DNA-coated nanoparticles, proteins), for their applications in reprogrammable and switchable materials with multifunctional properties [6, 7]. The experimental challenges to observe melting of superlattices are twofold. Practically it is difficult to load the initial superlattice form, in an intact manner, into the highly confined liquid-phase TEM chamber for in-situ observation. Here, the triggering of melting also needs meticulous manipulation of nanoparticle concentration, interparticle interaction, and solution environment.

Kim, Ahyoung↗

DOE OSTI2025

Unsupervised discovery of extreme weather events using universal representations of emergent organization

Spontaneous self-organization is ubiquitous in systems far from thermodynamic equilibrium. While organized structures that emerge dominate transport properties, universal representations that identify and describe these key objects remain elusive. Here, we introduce a theoretically grounded framework for describing emergent organization that, via data-driven algorithms, is constructive in practice. Its building blocks are spacetime lightcones that embody how information propagates across a system through local interactions. We show that predictive equivalence classes of lightcones—local causal states—capture organized behaviors in complex spatiotemporal systems. Employing an unsupervised physics-informed machine learning algorithm and a high-performance computing implementation, we demonstrate automatically discovering organized structures in two real-world domain science problems. We show that local causal states identify vortices and track their power-law decay behavior in two-dimensional fluid turbulence. We then show how to detect and track familiar extreme weather events—hurricanes and atmospheric rivers—and discover other novel structures associated with precipitation extremes in high-resolution climate data at the grid-cell level.

Rupe, Adam [Pacific Northwest National Laboratory ↗

DOE OSTI2024

Colossal magnetoresistance from spin-polarized polarons in an Ising system

Recent experiments suggest a new paradigm toward novel colossal magnetoresistance (CMR) in a family of materials EuM 2 X 2 (M = Cd, In, Zn; X = P, As), distinct from the traditional avenues involving Kondo–Ruderman–Kittel–Kasuya–Yosida crossovers, magnetic phase transitions with structural distortions, or topological phase transitions. Here, we use angle-resolved photoemission spectroscopy and density functional theory calculations to explore their origin, particularly focusing on EuCd 2 P 2 . While the low-energy spectral weight royally tracks that of the resistivity anomaly near the temperature with maximum magnetoresistance ( T MR ) as expected from transport-spectroscopy correspondence, the spectra are completely incoherent and strongly suppressed with no hint of a Landau quasiparticle. Using systematic material and temperature dependence investigation complemented by theory, we attribute this nonquasiparticle caricature to the strong presence of entangled magnetic and lattice interactions, a characteristic enabled by the p - f mixing. Given the known presence of ferromagnetic clusters, this naturally points to the origin of CMR being the scattering of spin-polarized polarons at the boundaries of ferromagnetic clusters. These results are not only illuminating to investigate the strong correlations and topology in EuCd 2 X 2 family, but, in a broader view, exemplify how multiple cooperative interactions can give rise to extraordinary behaviors in condensed matter systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Enabling reactive microscopy with MicroMator

Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Operando XPS for Plasma Process Monitoring: A Case Study on the Hydrogenation of Copper Oxide Confined under h-BN

Here, we demonstrate that ambient pressure x-ray photoelectron spectroscopy (APXPS) can be used for in situ studies of dynamic changes in surface chemistry in a plasma environment. This opens a new and vast application space for XPS and greatly complements modern spectroscopy techniques to probe plasma-solid/liquid interactions relevant to process monitoring in the semiconductor industry, bio-medical plasma applications and plasma remediation technologies. Hexagonal boron nitride (h-BN) grown on Cu was used in this study as a well-defined model system for plasma process monitoring and because of its unique chemical, optical and electrical properties that make it a prospective material for advanced electronics. To better understand the stability and surface chemistry of h-BN during plasma assisted processing, we track in real time the plasma-induced chemical state changes of B, N and the underlying Cu substrate using APXPS equipped with an AC discharge plasma source operating at 13 Pa. Residual gas analysis (RGA) mass-spectra were concurrently collected during plasma-XPS to track reaction products formed during plasma exposure. A clear reduction of Cu x O is seen, while an h-BN layer remains intact, suggesting hydrogen radical (H • ) species can attack the exposed and h-BN covered Cu oxide patches and partially reduce the underlying substrate without significantly damaging the overlaying h-BN, which is of practical importance for development of h-BN encapsulated devices and interfaces. In addition to demonstration of plasma-XPS capabilities we discuss the observed challenges (e.g., parasitic plasma-chamber walls reactions and charging effects) and propose potential solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Connecting Hindered Transport in Porous Media across Length Scales: From Single-Pore to Macroscopic

Hindered mass transport is widely observed in various porous media, including filtration membranes and porous rocks. However, there is no universal model capable of predicting transport in porous media due to the heterogeneity of porous structures and the complexity of the underlying microscopic mechanisms, including electrostatic and hydrodynamic effects. Here, we used a highly ordered porous medium (i.e. a silica inverse opal film) as a model system to directly explore the effects of geometric parameters (i.e. pore size, pore throat size and tracer particle size) and microscopic interaction parameters (e.g. controlled by ionic strength) on nanoparticle transport in porous environments using three-dimensional single-particle tracking. We found a linear scaling relation between the macroscopic diffusion coefficient and microscopic diffusion behaviors and a combination of parameters associated with microscopic features and phenomena, including both geometric effects and particle-level interactions. The proportionality coefficient relating micro and macro behaviors was complex and related to the connectivity of the matrix and pore-size variation, which could lead to tortuous diffusion pathways, hindering macroscopic transport. Furthermore, these findings provide important insights into nanoparticles and macromolecules transport in various porous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Phase Transformations among TiO2 Polymorphs

Polymorphs widely exist in nature and synthetic systems and are well known to determine material properties. Understanding phase transformation mechanisms among polymorphs enables the design of structures and tuning of phases to tailor material properties. However, current understanding is limited due to the lack of direct observations that track the processes and the structural evolution is not known at atomic scale. Here, integrating (semi) in situ transmission electron microscopy and density functional theory, we report atomic structural evolutions of phase transformation from anatase (A) to rutile (R), brookite (B), R-phase, and TiO. Besides the consistent paths with previous reports, we discover several unreported paths, including a [001] direction and (020) plane of anatase to [100]A and (011)R of rutile, respectively, ( , ) and , . Density functional theory analysis elucidates atomic structural evolution during the processes and over 16% of Ti-O bonds break and reform during the processes with energy barriers of ~0.7-1.0 eV per TiO2 formula unit. Under electron-beam irradiation, anatase particles transform into TiO2-R phase or TiO at high or room temperature, respectively. We also reveal the anisotropic nature of electron-beam effect, which is seldom discussed: dependence of crystallographic orientation with respect to electron-beam irradiation direction. Understanding the atomic structural evolution sheds light on interpreting and controlling TiO2 polymorphs and interface structures for various applications. The revealed electron-beam effects in our work provide guidance for in situ transmission electron microscopy studies.

Song, Miao↗

DOE OSTI2025

A two-and-a-half dimensional symplectic space-charge solver

The nonlinear space-charge effect plays a significant role in high-intensity accelerators and has been extensively studied using multi-particle tracking methods. In this paper, we present a novel 2.5- dimensional symplectic space-charge solver specifically designed for long beam bunches. We begin by detailing its application to a transverse Gaussian density distribution under open boundary conditions in a straight system, where a semi-analytical expression is derived. We then demonstrate the solver’s adaptation to arbitrary distributions in open space, as well as within rectangular and round conducting pipes. Finally, we discuss the extension of this solver to circular accelerator systems. This study shows that the fast 2.5-dimensional solver can be a good approximation to the fully three-dimensional solver for long bunches in large circular accelerators.

Beam code development & simulation techniques↗

DOE OSTI2022

Superconductivity and phase diagrams of CaK(Fe 1- x Mn x ) 4 As 4 single crystals

In order to study the effects of Mn substitution on the superconducting and magnetic ground state of CaKFe 4 As 4 (T c = 35 K), members of the CaK (Fe 1–x Mn x ) 4 As 4 series have been synthesized by high-temperature solution growth in single-crystalline form and characterized by elemental analysis, thermodynamic, and transport measurements. These measurements show that the superconducting transition temperature decreases monotonically and is finally suppressed below 1.8 K as x is increased from 0 to 0.036. For x values greater than 0.016, signatures of a magnetic transition can be detected in both thermodynamic and transport measurements in which kinklike features allow for the determination of the transition temperature T* that increases as Mn substitution increases. Here, a temperature-composition (T–x) phase diagram is constructed, revealing a half-dome of superconductivity with the magnetic transition temperature T* appearing near 26 K for x ~ 0.017 and rising slowly up to 33 K for x ~ 0.036. In addition to the creation of the T–x phase diagram for CaK(Fe 1–x Mn x ) 4 As 4 , specific-heat data are used to track the jump in specific heat at T c ; the CaK(Fe 1–x Mn x ) 4 As 4 data do not follow the scaling of ΔC p with $T$$^{3}_{c}$ as many of the other Fe-based superconducting systems do. These data suggest that, as magnetic pair breaking is present, the jump in C p for a given T c is reduced. Elastoresistivity coefficients 2m 66 and m 11 – m 12 as a function of temperature are also measured. 2m 66 and m 11 – m 12 are qualitatively similar to CaK(Fe 1–x Ni x ) 4 As 4 . This may indicate that the magnetic order in Mn-substituted system may be still the same as CaK(Fe 1–x Mn x ) 4 As 4 . Superconductivity of CaK(Fe 1–x Mn x ) 4 As 4 is also studied as a function of magnetic field. A clear change in H' c2 (T)/T c , where H' c2 (T) is dH' c2 (T)/dT, at x ~ 0.015 is observed and probably is related to change of the Fermi surface due to magnetic order. Coherence lengths and the London penetration depths are also calculated based on H c1 and H c2 data. Coherence lengths as the function of x also show the changes near x = 0.015, again consistent with Fermi-surface changes associated with the magnetic ordering seen for higher-x values.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

COMPASS-FME Synoptic Sites Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-0 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

COMPASS-FME Synoptic Sites Level 2 Sensor Data v2-1

This is the version 2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. Please see v2-1 L2 Sensor Package QStart.pdf for detailed information on data package structure, temporal coverage, and versioning.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

DOE OSTI2025

Hardware-Efficient Quantum Phase Estimation via Local Control

Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary evolution conditioned on the state of one or more auxiliary qubits, posing a significant challenge for current quantum devices. In this work, we present an approach to quantum phase estimation that uses only locally controlled operations, resulting in a significantly reduced circuit depth. At the heart of our approach are efficient routines to measure the complex phase of the expectation value of the time-evolution operator, the so-called Loschmidt echo, for both circuit dynamics and Hamiltonian dynamics. By tracking changes in the phase during the dynamics, the routines trade circuit depth for increased sampling cost and classical postprocessing. Our approach does not rely on reference states and is applicable to any efficiently preparable state, regardless of its correlations. We provide a comprehensive analysis of the sample complexity and illustrate the results with numerical simulations. Our methods offer a practical pathway for measuring spectral properties in large many-body quantum systems using current quantum devices.

Schiffer, Benjamin F. [Max Planck Institute of Qua↗

DOE OSTI2026

First Observation of Multiphonon 𝛾-Vibrations in an Odd-Odd Nuclear System

Here, the identification of the first multiphonon 𝛾-vibrational bands in an odd-odd neutron-rich nucleus of the nuclear chart is presented. These high-spin structures of hard to access $^{104}_{41}\textrm{Nb}_{63}$, produced in fission, were studied by combining a spectrometer with isotopic resolution coupled to a 𝛾-ray tracking array and independently from high-fold 𝛾 coincidence measurements. Triaxial projected shell model calculations for the high-spin states are in good agreement with the measured observables for the yrast, one-phonon, and two-phonon 𝛾 bands. The possibility of an oblate shape of an isomeric state and coexistence of triaxial and oblate configurations is investigated from the decay of the 141 keV isomer. The present Letter illustrates the robustness of vibration excitations in the presence of an odd valence proton and neutron as well as the possibly coexisting shapes beyond the 𝑁 = 60 transitional region.

Wang, E. H. [Shandong Univ., Jinan (China); Vander↗

DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗