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DOE OSTI2024

Optimal Zeno Dragging for Quantum Control: A Shortcut to Zeno with Action-Based Scheduling Optimization

The quantum Zeno effect asserts that quantum measurements inhibit simultaneous unitary dynamics when the “collapse” events are sufficiently strong and frequent. This applies in the limit of strong continuous measurement or dissipation. It is possible to implement a dissipative control that is known as “Zeno dragging” by dynamically varying the monitored observable, and hence also the eigenstates, which are attractors under Zeno dynamics. This is similar to adiabatic processes, in that the Zeno-dragging fidelity is highest when the rate of eigenstate change is slow compared to the measurement rate. We demonstrate here two theoretical methods for using such dynamics to achieve control of quantum systems. The first, which we shall refer to as “shortcut to Zeno,” is analogous to the shortcuts to adiabaticity (counterdiabatic driving) that are frequently used to accelerate unitary adiabatic evolution. In the second approach, we apply the Chantasri-Dressel-Jordan stochastic action [PRA 88, 042110 (2013)], and demonstrate that the extremal-probability readout paths derived from this are well suited to setting up a Pontryagin-style optimization of the Zeno-dragging schedule. A fundamental contribution of the latter approach is to show that an action suitable for measurement-driven control optimization can be derived quite generally from statistical arguments. Implementing these methods on the Zeno dragging of a qubit, we find that both approaches yield the same solution, namely, that the optimal control is a unitary that matches the motion of the Zeno-monitored eigenstate. We then show that such a solution can be more robust than a unitary-only operation and we comment on solvable generalizations of our qubit example embedded in larger systems. These methods open up new pathways toward systematically developing dynamic control of Zeno subspaces to realize dissipatively stabilized quantum operations. Published by the American Physical Society 2024

Physics↗

DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗

DOE OSTI2020

Functional methods for Heavy Quark Effective Theory

We use functional methods to compute one-loop effects in Heavy Quark Effective Theory. The covariant derivative expansion technique facilitates the efficient extraction of matching coefficients and renormalization group evolution equations. This paper pro- vides the first demonstration that such calculations can be performed through the algebraic evaluation of the path integral for the class of effective field theories that are (i) constructed using a non-trivial one-to-many mode decomposition of the UV theory, and (ii) valid for non-relativistic kinematics. We discuss the interplay between operators that appear at intermediate steps and the constraints imposed by the residual Lorentz symmetry that is encoded as reparameterization invariance within the effective description. The tools presented here provide a systematic approach for computing corrections to higher order in the heavy mass expansion; precision applications include predictions for experimental data and connections to theoretical tests via lattice QCD. A set of pedagogical appendices comprehensively reviews modern approaches to performing functional calculations algebraically, and derives contributions from a term with open covariant derivatives for the first time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Radiation Detection Data Competition Report

In FY2018 through FY2020, NA-22, the Defense Nuclear Nonproliferation Research and Development Program, funded a Data Science project to develop and implement statistical methodology to effectively host data competitions with the goal of leveraging the opportunity provided by crowdsourcing. By accessing and engaging expertise from a broader research community, there is an opportunity to attract innovative solutions from a variety of different research disciplines to advance the ability to solve important non-proliferation problems. This report summarizes the key results of this project after hosting two data competitions focused on urban radiation detection. The first competition was focused on attracting participants from the U.S. national laboratories, while the second, hosted by TopCoder, was open to the broader international community and awarded prize money to the top 10 competitors. At the start of the project, there was strong interest from NA-22 to explore and develop the capability to host data competitions as a means of leveraging the broader community to solve important nuclear nonproliferation problems. Having a standard data set on which to compare different approaches based on clearly defined criteria was desirable to be able to evaluate the state of solutions for important problems. Initially, it was not clear that it would even be possible logistically and bureaucratically to host a competition with an international field of competitors and to award the prize money needed to attract solutions from top competitors. Happily, a path to host the competitions was ultimately found that allowed this powerful accelerator of improvements to be leveraged.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Phase noise limited frequency shift impulsive Raman spectroscopy

We introduce a method to enable optical amplification of a coherent Raman spectroscopy signal, which we call radio frequency (RF) Doppler Raman spectroscopy. In this article, we consider the perturbation of a probe pulse in a sample due to an excited Raman vibrational coherence as a generalized Doppler shift, which connects a time-varying optical path length (the product of the propagation length and refractive index, OPL = n ℓ) with an optical frequency shift. Amplification of a Raman signal outside of the focused interaction is enabled by converting the Doppler frequency shift experienced by a laser probe pulse into a periodic timing jitter. This transit time perturbation is detected through the phase of a RF electronic signal measured at a harmonic of the probe pulse train with a method adapted from precision metrology techniques used to measure laser pulse train timing jitter. Measurement of a timing jitter allows access to much lower noise floors than other coherent Raman techniques, and by exploiting the new capability to scale the signal of a coherent Raman spectroscopic signal, this method opens the potential to detect very weak Raman signals that are currently not observable due to limits of illumination intensity imposed by laser damage to the specimen and noise.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Magnetic dipole γ-ray strength functions in the crossover from spherical to deformed neodymium isotopes

We calculate the magnetic dipole $\gamma$-ray strength functions in a chain of even-mass neodymium isotopes $^{144-152}$Nd in the framework of the configuration-interaction (CI) shell model. We infer the strength function by applying the maximum entropy method (MEM) to the exact imaginary-time response function calculated with the shell-model Monte Carlo (SMMC) method. The success of the MEM depends on the choice of a good strength function as a prior distribution. We investigate two choices for the prior strength function: the static path approximation (SPA) and the quasiparticle random-phase approximation (QRPA). We find that the QRPA is a better approximation at low temperatures (i.e., near the ground state), while the SPA is a better choice at finite temperatures. We identify a low-energy enhancement (LEE) in the MEM deexcitation $M1$ strength functions of the even-mass neodymium isotopes and compare with recent experimental results for the total deexcitation $\gamma$-ray strength functions. The LEE is already seen in the SPA strength function but not in the QRPA strength function, indicating the importance of large-amplitude static fluctuations around the mean field in reproducing the LEE. Our method is currently the only one which can reproduce LEE in heavy open-shell nuclei where conventional CI shell model calculations are prohibited. With the onset of deformation as number of neutrons increases along the chain of neodymium isotopes, we observe that some of the LEE strength transfers to a low-energy excitation, which we interpret as a finite-temperature ``scissors'' mode. Here, we also observe a finite-temperature spin-flip mode.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

DAMSA Experiment Conceptual Design White Paper

DAMSA (DArk Messenger Searches at an Accelerator) is a novel short-baseline accelerator experiment aimed at probing short-lived physics processes, including searches for evidence of a dark sector of particle physics and well-motivated Standard Model signals. Motivated by open questions in neutrino physics and the absence of conclusive evidence for conventional weakly interacting massive particles, DAMSA targets MeV-to-sub-GeV dark-sector messengers with feeble couplings that can be produced in abundance at the PIP-II LINAC. By employing an ultra-short baseline of order one meter, DAMSA is uniquely positioned to overcome the beam-dump "ceiling" that limits sensitivity to promptly decaying particles in longer-baseline experiments. The conceptual design emphasizes a beam-dump production scheme combined with a compact detector optimized for rare decays while mitigating intense neutron-induced backgrounds inherent to high-power proton beams. To validate the experimental strategy and detector technologies, the Little DAMSA Path-Finder (LDPF) proof-of-concept experiment is proposed, focusing on axion-like particles decaying to two photons and operating with 300 MeV electron beams at FAST. Successful realization of LDPF will establish the feasibility of the DAMSA approach, enabling a broad and powerful program to explore short-lived new physics and precision Standard Model processes in a previously inaccessible regime. This conceptual design document outlines the technical details of DAMSA's physics goals, the beam facility proposals, key experimental challenges and how to overcome them, and the proposed experimental staging campaigns.

Bhattarai, Prithak [Texas U., Arlington]↗

DOE OSTI2023

Physics–Informed Neural Networks of the Saint–Venant Equations for Downscaling a Large–Scale River Model

Large-scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics near the river-ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state-of-the-art physics-informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one-dimensional (1-D) Saint-Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN-based downscaling can produce more reasonable subgrid solutions of the along-channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path towards improving emulation capabilities in large-scale models to characterize fine-scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Women in Environmental Science

Despite the prominent role that women have traditionally played in environmental activism and initiatives to promote environmental justice, women’s representation in most environmental science fields remains low. The first environmental laws in the U.S., established in the 60’s and 70’s, were propelled by movements evolved out of male dominated scientific professions, mainly engineering. To this day, environmental fields are still perceived as not open to women. Yet the field being so broad, it offers many opportunities for women scientists to contribute to the advancement of science and technology needed to address the most pressing environmental issues. To this end, the Society for Industrial Microbiology and Biotechonology organized a session at its 2019 General Meeting entitled Women in Environmental Science that showcased the work of women leading efforts in environmental fields. The session was convened by Dr. Gemma Reguera (Michigan State University) and Dr. Arpita Bose (Washington University in St. Louis) and included 4 additional speakers whose work spans basic and applied environmental research yet impacts discovery-driven science, technology development, science policy and communication, in addition to environmental advocacy and stewardship. The talks highlighted the career path of women-led teams whose research and professional activities are contributing to the development of “biobased solutions to DOE mission challenges in energy and environment”.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Designing for Supply and Return Air System Interaction in Residential Buildings

Standard practice for HVAC return design has evolved from running a dedicated return to each room with a supply, to systems with returns in more centrally located areas of the home with jump ducts, transfer grilles, or simply door undercuts used as return air pathways from isolated rooms . In these latter systems, hallways and stairwells act as large open ducts for conveying air back to a single (or sometimes multiple) central return. When partition doors to an isolated room are closed, the return airflow resistance goes up, significantly impacting airflow balance if an adequate relief pathway is not installed. Airflow imbalances can lead to comfort and building durability issues and increased envelope leakage. To combat this, some jurisdictions have requirements for return air pathways. The supply system topology – or layout - impacts the airflow balance stability in response to adjustments of return pathway resistances. Branching supply topologies typically have reduced static pressure after each split. The static pressure at the final split will be lower than the primary supply plenum. Because of this, if there is a restriction in a room’s return path, supply airflow will tend to redistribute to adjacent ducts at the end of the branch. A properly designed trunk and branch supply system can effectively equalize static pressure by reducing the cross sectional area after each takeoff . Maintaining static pressure within the trunk will reduce the system’s sensitivity to changes in return paths. However, in practice, it is difficult to design and time consuming to install a complex supply plenum. Velocity effects and poor takeoff placement also impact airflow balance. This fact sheet considers return systems in three main categories: distributed, with a return duct to each room; multiple central, with one return grille on each floor of a home; and single central, with a single return grille located near the air handling unit. Three supply categories are also considered: radial splitter box, trunk and branch, and home-run with all ducts connecting directly to a central manifold. A complete description of the modeling work and results can be found in the companion technical report.

buildings↗

DOE OSTI2025

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing

The surge in scientific literature obscures breakthroughs and hinders the discovery of new research paths. We propose an artificial intelligence (AI) powered framework using large language models (LLMs) and knowledge graphs (KGs) to automate parts of scientific discovery, focusing on energy-efficient AI circuits. Our hybrid approach combines LLMs, structured data, and ontology-based reasoning to construct a comprehensive knowledge graph that integrates insights across computational neuroscience, spiking neuron models, learning rules, architectural motifs, and neuromorphic device technologies. This multi-domain representation enables the generation of hypotheses that connect biological function with implementable, energy-efficient hardware architectures. Using KG embeddings and graph neural networks, the framework generates hypotheses for novel circuits, validates them through optimization on exascale HPC systems, and with tools like SuperNeuro and Fugu, the most promising designs will be prototyped in hardware. This open-source system aims to accelerate discoveries and bridging neuroscience with hardware innovation, drive collaboration, and unlock new opportunities in low-power AI computing.

Gautam, Ashish [ORNL]↗

DOE OSTI2022

Material aspects of giga-Hertz ZnO TFTs for wireless systems

Abstract Having enabled high-value application capabilities through mass production of flat-panel displays, X-ray imagers, and solar panels, Large-Area Electronics (LAE) holds potential to open new frontiers in wireless applications for the Internet of Things and 5G/6G, by enabling unprecedented spatial control and power efficiency through large size and flexible form factor of radiative apertures. However, this requires boosting operation frequencies from the traditional limits in the range of 10–100’s of mega-Hertz to multi giga-Hertz. In this paper, we discuss critical device metrics, to characterize zinc-oxide (ZnO) thin-film transistor (TFT) operation frequency for both active (for signal amplification) and passive components in LAE-based circuits and systems. We then describe the key structural and material approaches towards recently demonstrated LAE-based giga-Hertz wireless systems employing ZnO TFTs. Bringing LAE to the giga-Hertz regime provides a path towards flexible and meter-scale monolithic integrated wireless systems. Graphical abstract

Ma, Yue (ORCID:0000000186724090)↗

DOE OSTI2022

Approaching PetaVolts per Meter Plasmonics Using Structured Semiconductors

A newly uncovered class of plasmons in the strongly excited limit opens access to unprecedented Petavolts per meter electromagnetic fields with wide-ranging, transformative impact. Unlike conventional plasmons, such plasmons are constituted by non-perturbative, large-amplitude oscillations of the ultradense, delocalized free electron Fermi gas inherent in conductive media. Here structured semiconductors doped to have an appropriate conduction electron density are introduced to tune the properties of the Fermi gas for matched excitation of large-amplitude plasmons using readily available electron beams which enables immediate experimental validation. Specifically, an electrostatic, surface “crunch-in” plasmon is collisionlessly excited by the beam launched inside a tube. Strong excitation due to matching results in relativistic oscillations of the electron gas and unravels unique phenomena. Relativistically induced ballistic electron transport comes about due to relativistic multifold increase in the mean free path and also leads to unconventional heat deposition beyond Ohm’s law. This explains the absence of observed damage or solid-plasma formation in past experiments on conductive samples interacting with electron bunches shorter than 10-13 seconds. Furthermore, relativistic momentum leads to copious tunneling of electron gas across the surface, which then crunches inside the tube. Relativistic effects along with large, localized electron density variations underlying these modes necessitate kinetic approach to theoretical and computational modeling. Kinetic model presented here demonstrates experimental viability of observing tens of gigavolts per meter plasmonic fields excited by matching readily available electron beams to plasmons in semiconductors with 1018cm-3 free electron density, and paves the way for Petavolts per meter plasmonics.

42 ENGINEERING↗

DOE OSTI2021

Fission-product decay studies with the FRIB Decay Station

The Facility for Rare Isotopes Beams (FRIB) will be the flagship facility in low-energy nuclear physics when it comes online in 2022. This U.S. Department of Energy Office of Science user facility will open up a multitude of new opportunities to study exotic nuclei and will lead to new discoveries in nuclear structure, nuclear astrophysics, fundamental symmetries, and isotopes of importance to nuclear applications. The b-decay properties of neutron-rich isotopes will be measured with the FRIB Decay Station, a sophisticated state-of-the-art modular multi-detector system envisioned to perform b, g, n, and charged-particle spectroscopy. In this feasibility study, we use nuclear decay data collected with the FRIB Decay Station precursor, the Beta-Counting Station, currently used at Michigan State University with a radioactive beam produced at the National Superconducting Cyclotron Laboratory to identify the FRIB Decay Station capabilities for future measurements of neutron-rich exotic nuclei at FRIB to help provide a path forward for future measurements of interest to the lab’s mission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Peptide‐Induced Ferroelectricity in Charge‐Transfer Supramolecular Materials

Organic ferroelectrics are of great interest in sustainable energy conversion, information storage, flexible electronics, and potential biomedical applications as soft implants, among many other applications. Despite their broad potential, the development of organic ferroelectrics has remained limited, with only a few known examples in solid-state systems, primarily due to the lack of well-established design strategies compared to inorganic systems. Bio-inspired supramolecular chemistry offers a path to create functional nanostructures that are water-processable and biocompatible. We report here on supramolecular charge transfer (CT) systems in which peptides are covalently linked to dyads of electron-donating and electron-accepting moieties, creating amphiphiles that self-assemble into nanoscale ribbons in water. The peptide chirality-induced symmetry breaking in these crystalline nanostructures not only results in second harmonic activity but also generates ferroelectric behavior across multiple CT systems, demonstrating a versatile supramolecular approach to the design of new organic ferroelectrics. Furthermore, culturing primary neuron cells on coatings of the ferroelectric materials promoted axonal growth and enhanced action potentials, indicating improved neuronal maturity facilitated by the polar structure of the ferroelectric nanomaterials. The supramolecular strategy used here holds promise to create new water-processable ferroelectric biomaterials, opening avenues for innovative applications in cell charge transfer, neuronal axon growth, peptide symmetry breaking, self-assembling peptides, supramolecular ferroelectrics, proliferation, and bioelectronics.

charge transfer↗

DOE OSTI2021

Bulk photovoltaic effect in hexagonal LuMnO 3 single crystals

Hexagonal manganites, such as h-LuMnO 3 , are ferroelectric and have a narrow electronic band gap of ≈1.5eV. Here we report on the photoresponse of h-LuMnO 3 single crystals. It is found that the short circuit photocurrent density (J sc ) and the open circuit voltage (V oc ) are dependent on the direction of the polarization plane of a linearly polarized impinging light. Its angular dependence indicates the contribution of bulk photovoltaic effect to the short circuit photocurrent (J BPE ). It is also observed that a switchable drift photocurrent, originating from the depoling field of the ferroelectric and thus tunable(<10%) by its polarization direction, also contributes to J sc . Although its presence precludes accurate determination of the bulk photovoltaic tensor elements and Glass coefficients, some bounds can be established. The Glass coefficients are found to be significantly larger than those obtained in BiFeO 3 . We argue that the smaller band gap of h-LuMnO 3 , its distinctive bipyramidal crystal field, and electronic configuration (3d 4 vs 3d 5 ), account for the difference and suggest a path towards ferroelectrics of higher photoconversion efficiency.

14 SOLAR ENERGY↗

DOE OSTI2020

Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency

Neuromorphic computing offers one path forward for AI at the edge. However, accessing and effectively utilizing a neuromorphic hardware platform is non-trivial. In this work, we present a complete pipeline for neuromorphic computing at the edge, including a small, inexpensive, low-power, FPGA-based neuromorphic hardware platform, a training algorithm for designing spiking neural networks for neuromorphic hardware, and a software framework for connecting those components. We demonstrate this pipeline on a real-world application, engine control for a spark-ignition internal combustion engine. We illustrate how we connect engine simulations with neuromorphic hardware simulations and training software to produce hardware-compatible spiking neural networks that perform engine control to improve fuel efficiency. We present initial results on the performance of these spiking neural networks and illustrate that they outperform open-loop engine control. We also give size, weight, and power estimates for a deployed solution of this type.

Schuman, Catherine↗

DOE OSTI2025

Rules for the crystallite size and dislocation density evolution in phases during α-ω transformation in Zr under high-pressure and severe plastic flow

The first in-situ X-ray diffraction (XRD) study of the evolution of the crystallite size and dislocation density in phases during plastic strain-induced phase transformation (PT) is performed utilizing α-ω PT in strongly pre-deformed commercially pure Zr as an important example. Rough diamond anvils (rough-DA) are introduced to intensify all occurring processes during heterogeneous compression of Zr in a diamond anvil cell (DAC). The main rule is found that during α-ω PT the crystallite size and dislocation density in ω-Zr depend solely on the volume fraction of ω-Zr and are independent of pressure, plastic strain tensor, its path, and initial nanostructure. Crystallite size in ω-Zr increases from 10 to 60 nm during the PT, while dislocation density reduces from 1.83×10 15 /m 2 to 0.6×10 15 /m 2 . Rough-DA produce a steady nanostructure in α-Zr before PT with smaller crystallite size and larger dislocation density than smooth-DA, leading to a reduction of the minimum pressure for α-ω PT to a record value 0.67 GPa, 9 times smaller than under hydrostatic loading and 5.1 times lower than the phase equilibrium pressure. In addition to strain, the kinetics of strain-induced PT unexpectedly depends on time. Also, strain-controlled part of kinetics is zero order, in contrast to the first-order kinetics with smooth-DA. The obtained results open a new window for understanding the mutual effects of nanostructure evolution and PT during severe plastic flow in various technological and natural processes. In conclusion, they may bring up economic strategies of producing nanocomposites and single-phase nanostructured materials with optimal properties.

Crystalline size↗