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DOE OSTI2024

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics↗

DOE OSTI2025

Cooperative and inhibitory ion transport in functionalized angstrom-scale two-dimensional channels

Significant success has been achieved in fabricating angstrom-scale artificial solid ionic channels aiming to replicate the biological ion channels (BICs). Besides high selectivity, BICs also exhibit sophisticated ion gating and interplay. However, such behavior and functionality are seldomly recreated in the artificial counterparts due to the insufficient understanding of the molecular origin. Here we report cooperative and inhibitory ion transport in angstrom-scale acetate functionalized MoS 2 two-dimensional channels. For cooperative ion transport, the permeability of K + is doubled in the presence of only 1% Pb 2+ (versus K + by molarity), while the permeability of Pb 2+ is independent of K + . Molecular dynamics simulations reveal complex interplay among K + , Pb 2+ , and the anions in governing the cooperativity, such that Pb 2+ ions capture and slow down the anions via long-range interaction, which leads to the synchronization of anions with K + to transport as ion pairs with reduced interaction with the channel surface. For inhibitory ion transport, divalent Co 2+ (or Ba 2+ ) and Pb 2+ can replace each other in the confined channel and compete for the limited transport cross section. Our work reveals ion transport phenomena in extreme confinement and highlights the potential of manipulating ion interplay in confinement for achieving advanced functionalities.

Functionalized Angstrom↗

DOE OSTI2026

Locating the atoms at the hard-soft interface of gold nanoparticles

Surface structure affects the growth, shape and properties of nanoparticles. In wet chemical syntheses, metal additives and surfactants are used to modify surfaces and guide nanocrystal growth. To understand this process, it is critical to understand how the surface structure, and hence its energy, is modified. However, measuring the type and arrangement of atoms at hard-soft interfaces on nanoscale surfaces, especially in the presence of surfactants, is extremely challenging. Here, we determine the atomic structure of the hard-soft interface in a metallic nanoparticle by developing low-dose imaging conditions in four-dimensional scanning transmission electron microscopy that are preferentially sensitive to surface adatoms. By revealing experimentally the copper additives and bromide surfactant counterion at the surface of a gold nanocuboid and quantifying their interatomic distances, our direct, low-dose imaging method provides atomic-level understanding of chemically sophisticated nanomaterial surface structures. These measurements of the atomic structure of the hard-soft interface provide the information necessary to understand and quantify surface chemistries and energies and their pivotal role in nanocrystal growth.

Li, Weilun [Monash University, Melbourne, VIC (Aus↗

DOE OSTI2021

Reply to: Is the debate over grana stacking formation finally solved?

In plants, the photosynthetic pigment–protein complexes catalysing energy conversion are harboured in the thylakoid membrane system of chloroplasts. Recent breakthroughs in electron tomography reveal the sophisticated architecture of this unique membrane system with stacked grana as a structural hallmark. Here, a long-standing question has been whether the combination of physicochemical forces alone can explain the strict stacking of grana with an intermembrane separation of 3–4 nm. In our 2017 Nature Plants paper, we argued that the balance between attractive van der Waals (vdW) forces (F vdW ) and repulsive electrostatic (F el ) and hydrostructural (F hydro ) forces could explain grana stacking, in contrast with previous reports. Our finding was challenged in the report by Gudarzi et al. This reply addresses this critique.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Quantitative dissection of Agrobacterium T-DNA expression in single plant cells reveals density-dependent synergy and antagonism

Agrobacterium pathogenesis, which involves transferring T-DNA into plant cells, is the cornerstone of plant genetic engineering. As the applications that rely on Agrobacterium increase in sophistication, it becomes critical to achieve a quantitative and predictive understanding of T-DNA expression at the level of single plant cells. Here we examine if a classic Poisson model of interactions between pathogens and host cells holds true for Agrobacterium infecting Nicotiana benthamiana. Systematically challenging this model revealed antagonistic and synergistic density-dependent interactions between bacteria that do not require quorum sensing. Using various approaches, we studied the molecular basis of these interactions. To overcome the engineering constraints imposed by antagonism, we created a dual binary vector system termed ‘BiBi’, which can improve the efficiency of a reconstituted complex metabolic pathway in a predictive fashion. Our findings illustrate how combining theoretical models with quantitative experiments can reveal new principles of bacterial pathogenesis, impacting both fundamental and applied plant biology.

Alamos, Simon↗

DOE OSTI2020

Quantum anomalous Hall effect in two-dimensional magnetic insulator heterojunctions

Abstract Recent years have witnessed tremendous success in the discovery of topological states of matter. Particularly, sophisticated theoretical methods in time-reversal-invariant topological phases have been developed, leading to the comprehensive search of crystal database and the prediction of thousands of topological materials. In contrast, the discovery of magnetic topological phases that break time reversal is still limited to several exemplary materials because the coexistence of magnetism and topological electronic band structure is rare in a single compound. To overcome this challenge, we propose an alternative approach to realize the quantum anomalous Hall (QAH) effect, a typical example of magnetic topological phase, via engineering two-dimensional (2D) magnetic van der Waals heterojunctions. Instead of a single magnetic topological material, we search for the combinations of two 2D (typically trivial) magnetic insulator compounds with specific band alignment so that they can together form a type-III broken-gap heterojunction with topologically non-trivial band structure. By combining the data-driven materials search, first-principles calculations, and the symmetry-based analytical models, we identify eight type-III broken-gap heterojunctions consisting of 2D ferromagnetic insulators in the MXY compound family as a set of candidates for the QAH effect. In particular, we directly calculate the topological invariant (Chern number) and chiral edge states in the MnNF/MnNCl heterojunction with ferromagnetic stacking. This work illustrates how data-driven material science can be combined with symmetry-based physical principles to guide the search for heterojunction-based quantum materials hosting the QAH effect and other exotic quantum states in general.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2024

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗

DOE OSTI2021

Efficient verification of anticoncentrated quantum states

I present a method for estimating the fidelity F(μ, τ) between a preparable quantum state μ and a classically specified pure target state τ=|τ> <τ|, using simple quantum circuits and on-the-fly classical calculation (or lookup) of selected amplitudes of |τ>. The method is sample efficient for anticoncentrated states (including many states that are hard to simulate classically), with approximate cost 4ϵ –2 (1 – F)dpcoll where ϵ is the desired precision of the estimate, d is the dimension of the Hilbert space, and pcoll is the collision probability of the target distribution. Furthermore, this scaling is exponentially better than that of any method based on classical sampling. I also present a more sophisticated version of the method that uses any efficiently preparable and well-characterized quantum state as an importance sampler to further reduce the number of copies of μ needed. Though some challenges remain, this work takes a significant step toward scalable verification of complex states produced by quantum processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Seismic constraints from a Mars impact experiment using InSight and Perseverance

NASA’s InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has operated a sophisticated suite of seismology and geophysics instruments on the surface of Mars since its arrival in 2018. On 18 February 2021, we attempted to detect the seismic and acoustic waves produced by the entry, descent and landing of the Perseverance rover using the sensors onboard the InSight lander. Similar observations have been made on Earth using data from both crewed and uncrewed spacecraft, and on the Moon during the Apollo era, but never before on Mars or another planet. This was the only seismic event to occur on Mars since InSight began operations that had an a priori known and independently constrained timing and location. It therefore had the potential to be used as a calibration for other marsquakes recorded by InSight. Here we report that no signal from Perseverance’s entry, descent and landing is identifiable in the InSight data. Nonetheless, measurements made during the landing window enable us to place constraints on the distance–amplitude relationships used to predict the amplitude of seismic waves produced by planetary impacts and place in situ constraints on Martian impact seismic efficiency (the fraction of the impactor kinetic energy converted into seismic energy).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Spontaneous assembly of hierarchical phases

We report the grand promise of self-assembly is the creation of target nanostructures through spontaneous molecular organization, a process that is — in principle — simpler and more scalable than laborious top-down nanofabrication methods. Yet self-assembly faces a fundamental challenge: the structures that form thermodynamically tend to minimize surface area and maximize symmetry; the most readily-accessible structures are thus quite simple. Block copolymer (BCP) self-assembly, for example, takes advantage of the chemical incompatibility along a polymer backbone to drive local phase separation; frustrated assembly leads to a nanoscale morphology whose unit cell is dictated by chain architecture. Canonical BCPs (linear chains with two blocks) form alternating lamellae and hexagonally-packed cylinders in a straightforward manner; but more exotic phases require additional control, for example directing the assembly using external forces, such as shear or chemical templates. An elegant alternative is to use synthetic methods to design more sophisticated chain architectures, which may give rise to new morphologies. An outstanding challenge is to achieve morphological control without undue synthetic burden. Sun et al. now report in Nature Nanotechnology the design and synthesis of novel triblock copolymers that give rise to structural order at multiple length scales, thereby forming complex and hierarchical nanoscale phases.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Tunable coherent mixed-dimensional perovskite heterojunctions and quantum wells grown from solution

Coherent heterojunctions, quantum wells and multiple quantum wells are needed for high-performance devices; these are generally grown via a dedicated vapour phase epitaxy process. Here we demonstrate the growth of coherent perovskite heterojunctions and quantum wells made of mixed-dimensional perovskites using a solution process. By exploiting the solubility difference of methylammonium (MA + ) and 4-(aminomethyl)piperidinium (4AMP 2+ ), we assemble layered perovskites with different layer numbers. The resulting 4AMP-MA n–1 Pb n I 3n+1 materials each with different layer numbers or bandgaps form quantum wells. Heterojunctions and quantum wells made of 4AMP-MA 2 Pb 3 I 10 (n = 3) and 4AMP-MAPb 2 I 7 (n = 2) with various barrier thickness are tailored by the solution temperature profile during crystal growth. Multiple quantum wells have been formed by cycling temperature profiles. The planar heterojunction and quantum wells have lattice matching without interfacial defects, and exhibit strong thermal stability. Type I band alignment at the n = 2/n = 3 heterojunction is confirmed by both computation and optical studies. In conclusion, this study opens a new direction for the development of sophisticated perovskite heterojunction and quantum well devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Ultrafast lattice disordering can be accelerated by electronic collisional forces

In the prevalent picture of ultrafast structural phase transitions, the atomic motion occurs in a slowly varying potential energy surface determined adiabatically by the fast electrons. However, this ignores non-conservative forces caused by electron-lattice collisions, which can significantly influence atomic motion. Most ultrafast techniques only probe the average structure and are less sensitive to random displacements, and therefore do not detect the role played by non-conservative forces in phase transitions. Here we show that the lattice dynamics of the prototypical insulator-to-metal transition of VO 2 cannot be described by a potential energy alone. We use the sample temperature to control the preexisting lattice disorder before ultrafast photoexcitation across the phase transition and our ultrafast diffuse scattering experiments show that the fluctuations characteristic of the rutile metal develop equally fast (120 fs) at initial temperatures of 100 K and 300 K. This indicates that additional non-conservative forces are responsible for the increased lattice disorder. In conclusion, these results highlight the need for more sophisticated descriptions of ultrafast phenomena beyond the Born-Oppenheimer approximation as well as ultrafast probes of spatial fluctuations beyond the average unit cell measured by diffraction.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Single-defect phonons imaged by electron microscopy

Crystal defects affect the thermal and heat-transport properties of materials by scattering phonons and modifying phonon spectra. To appreciate how imperfections in solids influence thermal conductivity and diffusivity, it is thus essential to understand phonon–defect interactions. Sophisticated theories are available to explore such interactions, but experimental validation is limited because most phonon-detecting spectroscopic methods do not reach the high spatial resolution needed to resolve local vibrational spectra near individual defects. In this paper, we demonstrate that space- and angle-resolved vibrational spectroscopy in a transmission electron microscope makes it possible to map the vibrational spectra of individual crystal defects. We detect a red shift of several millielectronvolts in the energy of acoustic vibration modes near a single stacking fault in cubic silicon carbide, together with substantial changes in their intensity, and find that these changes are confined to within a few nanometres of the stacking fault. These observations illustrate that the capabilities of a state-of-the-art transmission electron microscope open the door to the direct mapping of phonon propagation around defects, which is expected to provide useful guidance for engineering the thermal properties of materials.

42 ENGINEERING↗

DOE OSTI2022

A sustained high-temperature fusion plasma regime facilitated by fast ions

Nuclear fusion is one of the most attractive alternatives to carbon-dependent energy sources. Harnessing energy from nuclear fusion in a large reactor scale, however, still presents many scientific challenges despite the many years of research and steady advances in magnetic confinement approaches. State-of-the-art magnetic fusion devices cannot yet achieve a sustainable fusion performance, which requires a high temperature above 100 million kelvin and sufficient control of instabilities to ensure steady-state operation on the order of tens of seconds. Here, in this study, we report experiments at the Korea Superconducting Tokamak Advanced Research device producing a plasma fusion regime that satisfies most of the above requirements: thanks to abundant fast ions stabilizing the core plasma turbulence, we generate plasmas at a temperature of 100 million kelvin lasting up to 20 seconds without plasma edge instabilities or impurity accumulation. A low plasma density combined with a moderate input power for operation is key to establishing this regime by preserving a high fraction of fast ions. This regime is rarely subject to disruption and can be sustained reliably even without a sophisticated control, and thus represents a promising path towards commercial fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes

Abstract In the ongoing debates about eukaryogenesis—the series of evolutionary events leading to the emergence of the eukaryotic cell from prokaryotic ancestors—members of the Asgard archaea play a key part as the closest archaeal relatives of eukaryotes 1 . However, the nature and phylogenetic identity of the last common ancestor of Asgard archaea and eukaryotes remain unresolved 2–4 . Here we analyse distinct phylogenetic marker datasets of an expanded genomic sampling of Asgard archaea and evaluate competing evolutionary scenarios using state-of-the-art phylogenomic approaches. We find that eukaryotes are placed, with high confidence, as a well-nested clade within Asgard archaea and as a sister lineage to Hodarchaeales, a newly proposed order within Heimdallarchaeia. Using sophisticated gene tree and species tree reconciliation approaches, we show that analogous to the evolution of eukaryotic genomes, genome evolution in Asgard archaea involved significantly more gene duplication and fewer gene loss events compared with other archaea. Finally, we infer that the last common ancestor of Asgard archaea was probably a thermophilic chemolithotroph and that the lineage from which eukaryotes evolved adapted to mesophilic conditions and acquired the genetic potential to support a heterotrophic lifestyle. Our work provides key insights into the prokaryote-to-eukaryote transition and a platform for better understanding the emergence of cellular complexity in eukaryotic cells.

Science & Technology - Other Topics↗

DOE OSTI2023

First observation of 28 O

Subjecting a physical system to extreme conditions is one of the means often used to obtain a better understanding and deeper insight into its organization and structure. In the case of the atomic nucleus, one such approach is to investigate isotopes that have very different neutron-to-proton ($N/Z$) ratios than in stable nuclei. Light, neutron-rich isotopes exhibit the most asymmetric $N/Z$ ratios and those lying beyond the limits of binding, which undergo spontaneous neutron emission and exist only as very short-lived resonances (about 10 -21 s), provide the most stringent tests of modern nuclear-structure theories. Here we report on the first observation of 28 O and 27 O through their decay into 24 O and four and three neutrons, respectively. The 28 O nucleus is of particular interest as, with the $Z$ = 8 and $N$ = 20 magic numbers, it is expected in the standard shell-model picture of nuclear structure to be one of a relatively small number of so-called ‘doubly magic’ nuclei. Furthermore, both 27 O and 28 O were found to exist as narrow, low-lying resonances and their decay energies are compared here to the results of sophisticated theoretical modelling, including a large-scale shell-model calculation and a newly developed statistical approach. In both cases, the underlying nuclear interactions were derived from effective field theories of quantum chromodynamics. Finally, it is shown that the cross-section for the production of 28 O from a 29 F beam is consistent with it not exhibiting a closed $N$ = 20 shell structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Learning protein fitness models from evolutionary and assay-labeled data

Machine learning-based models of protein fitness typically learn from either unlabeled, evolutionarily related sequences or variant sequences with experimentally measured labels. For regimes where only limited experimental data are available, recent work has suggested methods for combining both sources of information. Toward that goal, we propose a simple combination approach that is competitive with, and on average outperforms more sophisticated methods. Our approach uses ridge regression on site-specific amino acid features combined with one probability density feature from modeling the evolutionary data. Within this approach, we find that a variational autoencoder-based probability density model showed the best overall performance, although any evolutionary density model can be used. Moreover, our analysis highlights the importance of systematic evaluations and sufficient baselines.

59 BASIC BIOLOGICAL SCIENCES↗