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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Simulation of adiabatic quantum computing for molecular ground states

Quantum computation promises to provide substantial speedups in many practical applications with a particularly exciting one being the simulation of quantum many-body systems. Adiabatic state preparation (ASP) is one way that quantum computers could recreate and simulate the ground state of a physical system. In this paper, we explore a novel approach for classically simulating the time dynamics of ASP with high accuracy and with only modest computational resources via an adaptive sampling configuration interaction scheme for truncating the Hilbert space to only the most important determinants. We verify that this truncation introduces negligible error and use this new approach to simulate ASP for sets of small molecular systems and Hubbard models. Furthermore, we examine two approaches to speeding up ASP when performed on quantum hardware: (i) using the complete active space configuration interaction (CASCI) wave function instead of the Hartree–Fock initial state and (ii) a nonlinear interpolation between the initial and target Hamiltonians. We find that starting with a CASCI wave function with a limited active space yields substantial speedups for many of the systems examined, while nonlinear interpolation does not. In additional, we observe interesting trends in the minimum gap location (based on the initial state) as well as how state preparation time can depend on certain molecular properties, such as the number of valence electrons. Importantly, we find that the required state preparation times do not show an immediate exponential wall that would preclude an efficient run of ASP on actual hardware.

Kremenetski, Vladimir↗
DOE OSTI2020

Improving Arsenic Tolerance of Pyrococcus furiosus by Heterologous Expression of a Respiratory Arsenate Reductase

Arsenate is a notorious toxicant that is known to disrupt multiple biochemical pathways. Many microorganisms have developed mechanisms to detoxify arsenate using the ArsC-type arsenate reductase, and some even use arsenate as a terminal electron acceptor for respiration involving arsenate respiratory reductase (Arr). ArsC-type reductases have been studied extensively, but the phylogenetically unrelated Arr system is less investigated and has not been characterized from Archaea. Here, we heterologously expressed the genes encoding Arr from the crenarchaeon Pyrobaculum aerophilum in the euryarchaeon Pyrococcus furiosus, both of which grow optimally near 100°C. Recombinant P. furiosus was grown on molybdenum (Mo)- or tungsten (W)-containing medium, and two types of recombinant Arr enzymes were purified, one containing Mo (Arr-Mo) and one containing W (Arr-W). Purified Arr-Mo had a 140-fold higher specific activity in arsenate [As(V)] reduction than Arr-W, and Arr-Mo also reduced arsenite [As(III)]. The P. furiosus strain expressing Arr-Mo (the Arr strain) was able to use arsenate as a terminal electron acceptor during growth on peptides. In addition, the Arr strain had increased tolerance compared to that of the parent strain to arsenate and also, surprisingly, to arsenite. Compared to the parent, the Arr strain accumulated intracellularly almost an order of magnitude more arsenic when cells were grown in the presence of arsenite. Furthermore, x-ray absorption spectroscopy (XAS) results suggest that the Arr strain of P. furiosus improves its tolerance to arsenite by increasing production of less-toxic arsenate and nontoxic methylated arsenicals compared to that by the parent.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Algorithm Theoretical Basis Document For PreMevE 2.0 Model

Man-made satellites operating in medium- and high-altitude Earth orbits are continuously exposed to hazardous space radiation originated from different sources. Among them, one major contributor is the relativistic electron population—with kinetic energies comparable to or larger than their rest energy of 0.511 Megaelectron-volt (MeV)—trapped inside Earth’s outer Van Allen belt. Owing to their high penetration capability, these MeV electrons are difficult to be fully stopped by normal shielding. Particularly, during MeV electron events when electron intensities across the outer belt are greatly elevated to sustaining high levels—up to 10 3 - 10 4 times as observed in the geosynchronous (GEO) orbit and low-Earth-orbits (LEOs), space-borne electronic systems with inadequate hardening are susceptible to deep-dielectric charging and discharging phenomenon caused by those electrons, and thus may suffer severe damages or even stop functioning. Therefore, protecting critical space infrastructures from harsh space weather conditions– including MeV electron events – has high priority for many space sectors, such as the aerospace industry, service providers and government agencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Equation-of-Motion Coupled-Cluster Cumulant Green’s Function for Excited States and X-ray Spectra

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states and spectra. Conventional methods using the Dyson equation or the cumulant expansion are typically based on the GW self-energy approximation. In order to extend this approximation in molecular systems, a non-perturbative real-time coupled-cluster cumulant Green’s function approach has been introduced, where the cumulant is obtained as the solution to a set of coupled first order, non-linear differential equations. This approach naturally includes non-linear corrections to conventional cumulant Green’s function techniques where the cumulant is linear in the GW self-energy. The method yields the spectral function associated with the core Green’s function, which is directly related to the x-ray photoemission spectra (XPS) of molecular systems. The approach also yields very good results for binding energies and satellite excitations. The x-ray absorption spectrum (XAS) is then obtained as a convolution of the core spectral function and an effective one-body absorption spectrum. Here this approach is extended to include the full coupled-cluster-singles (CCS) core Green’s function by including the complete form of the non-linear contributions to the cumulant as well as all single, double, and triple cluster excitations in the CC amplitude equations. This approach naturally builds in orthogonality and shake-up effects analogous to those in the Mahan-Noizeres-de Dominicis edge singularity corrections that enhance the XAS near the edge. Themethod is illustrated for the XPS and XAS of NH 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Innovating Distributed Embedded Energy Prize (InDEEP): A Lessons Learned Report

The U.S. Department of Energy's Water Power Technologies Office (WPTO) launched the Innovating Distributed Embedded Energy Prize (InDEEP) in March 2023 to accelerate innovation in Distributed Embedded Energy Conversion Technologies (DEEC-Tec) for ocean wave energy. Administered by the National Laboratory of the Rockies (NLR) with technical support from Sandia National Laboratories (SNL), InDEEP focused on the development of small, distributed, and embeddable energy converters (DEECs) and their integration into scalable DEEC-Tec metamaterials for marine renewable energy applications. Spanning three phases over two years, InDEEP awarded approximately $2.3 million to teams from academia, industry, and startups. Phase I emphasized conceptual design. Phase II moved into the prototyping of individual DEECs. Phase III required integration into functional DEEC-Tec metamaterial prototypes. Across 60 submissions, teams explored a wide range of energy conversion mechanisms - including piezoelectric, variable-capacitance, ionic, and inductive methods. Note, the prize did not include the design nor demonstration of ocean wave energy conversion systems. Rather, the prize only required participants to design and demonstrate individual DEECs and corresponding DEEC-Tec metamaterials. This prize utilized a mix of novel and proven techniques to attract participants from outside marine energy, including an engagement leaderboard, robust recruitment, technical expert mentorship, and a suite of technical trainings. Key insights from the competition emphasized that DEEC-Tec metamaterials must be intentionally designed to produce beneficial emergent behaviors - advantages that go beyond simply combining multiple DEEC units. Top-performing teams showed that thoughtful design of system architecture, coordinated deformation, and systems adaptabilities could unlock meaningful performance gains both at the DEEC system level and DEEC-Tec metamaterial system level. A critical realization was that many DEEC-Tec metamaterials could benefit from being designed to accept lower-frequency energy inputs and shift those into higher-frequencies per each DEEC making up the respective DEEC-Tec metamaterial. Other important takeaways included the need for rigorous and quantitative performance testing, effective integration of power conditioning electronics, and the pivotal role of material science in enabling innovative, adaptive DEEC-Tec-based energy conversion designs. InDEEP also helped establish a growing DEEC-Tec community of practitioners, attracting participants from beyond traditional marine energy sectors. Through a strong support infrastructure, InDEEP fostered early-stage innovation and laid a foundation for future DEEC-Tec-based ocean wave energy conversion solutions - positioning DEEC-Tec as a promising pathway toward scalable, resilient ocean wave energy conversion. Through focused R&D of individual DEECs and their integration into DEEC-Tec metamaterials, alongside a growing, multidisciplinary community catalyzed by InDEEP, there is a strong opportunity to drive a disruptive shift in ocean wave energy conversion design and development. This convergence of novel architectures, emergent behaviors, and collaborative innovation positions DEEC-Tec as a transformative approach, moving the field from rigid, centralized energy conversion-based designs to resilient, modular systems highly adaptable for real-world ocean wave energy conversion applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗
DOE OSTI2021

Recent Developments in Femtosecond Laser-Enabled TriBeam Systems

Streams of multimodal three-dimensional (3D) and four-dimensional (4D) data are revolutionizing our ability to design and predict the behavior of a broad array of advanced materials systems. Over the last 10 years, a new 3D imaging platform consisting of a femtosecond (fs) pulsed laser coupled with a focused ion beam scanning electron microscope (FIB SEM) has been developed by UC Santa Barbara in collaboration with Thermo Fisher Scientific (formerly FEI). The femtosecond-laser-enabled FIB SEM, called the TriBeam, has become one of the only 3D serial sectioning methods available that can gather millimeter-scaled multimodal datasets at sub-μm voxel resolutions; these length scales are critical for many materials problems. Multimodal chemical, crystallographic, and morphological information can be gathered rapidly on a layer-by-layer basis and reconstructed in 3D. Large (gigabyte to terabyte scale) 3D datasets have been generated for a broad array of materials systems, including metallic alloys, ceramics, biomaterials, polymer- and ceramic-matrix composites, and semiconductors. The research tasks conducted have resulted in a completely new design, operating with a dual-wavelength femtosecond-pulsed laser on a plasma focused ion beam (PFIB) platform.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Excited-state potentials for modelling dense plasmas from first principles

The modelling of dense plasmas using finite-temperature density functional theory has proven very successful in determining transport properties and the equation of state of systems where quantum many-body effects and correlations play a key role in their structure. Here we show how excited-state projector augmented- wave potentials can be used to extend these calculations to explicitly model core-hole states, allowing for the calculation of the electronic structure of a range of integer charge configurations embedded in a dense plasma environment. Our excited-state potentials show good agreement with all-electron calculations at finite-temperatures, motivating their use as an efficient approach in modelling from first principles both the structure of strongly-coupled non-equilibrium plasmas and their interaction with intense X-rays.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
DOE OSTI2023

Stability of the interorbital-hopping mechanism for ferromagnetism in multi-orbital Hubbard models

The emergence of insulating ferromagnetic phase in iron oxychalcogenide chain system has been recently argued to be originated by interorbital hopping mechanism. However, the practical conditions for the stability of such mechanism still prevents the observation of ferromagnetic in many materials. Here, we study the stability range of such ferromagnetic phase under modifications in the crystal fields and electronic correlation strength, constructing a theoretical phase diagram. We find a rich emergence of phases, including a ferromagnetic Mott insulator, a ferromagnetic orbital-selective Mott phase, together with antiferromagnetic and ferromagnetic metallic states. We characterize the stability of the ferromagnetic regime in both the Mott insulator and the ferromagnetic orbital-selective Mott phase forms. We identify a large stability range in the phase diagram at both intermediate and strong electronic correlations, demonstrating the capability of the interorbital hopping mechanism in stabilizing ferromagnetic insulators. Our results may enable additional design strategies to expand the relatively small family of known ferromagnetic insulators.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diffusion quantum Monte Carlo approach to the polaritonic ground state

Making and using polaritonic states (i.e., hybrid electron-photon states) for chemical applications has recently become one of the most prominent and active fields that connects the communities of chemistry and quantum optics. Modeling of such polaritonic phenomena using ab initio approaches calls for new methodologies, leading to the reinvention of many commonly used electronic structure methods, such as Hartree-Fock, density functional, and coupled cluster theories. Here in this work, we explore the formally exact diffusion quantum Monte Carlo approach to obtain numerical solutions to the polaritonic ground state during the dissociation of the H 2 molecular system. Here, we examine various electron-nuclear-photon properties throughout the dissociation, such as changes to the minimum of the cavity Born-Oppenheimer surface, the localization of the electronic wave function, and the average mode occupation. Finally, we directly compare our results to that obtained with state-of-the-art, yet approximate, polaritonic coupled cluster approaches.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Quantum Spin Probe of Single Charge Dynamics

Electronic defects in semiconductors form the basis for emerging quantum technologies, but many defect centers are difficult to access at the single-particle level. A method for probing optically inactive spin defects would reveal semiconductor physics at the atomic scale and advance the study of new quantum systems. Here, we exploit the intrinsic correlation between the charge and spin states of defect centers to measure the charge populations and dynamics of single substitutional nitrogen spin defects in diamond. By probing their steady-state spin population, read out at the single-defect level with a nearby nitrogen vacancy center, we directly measure the defect ionization-corroborated by first-principles calculations-an effect we do not have access to with traditional coherence-based quantum sensing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Soliton formation and topology manipulation of coupled spins via ultrafast re-magnetization

The major goal of the project was to explore the properties of magnetic order driven far out of equilibrium by optical excitations. These include fundamental questions related to the interplay of magnetic, structural and electronic degrees of freedom in materials that are optically excited. These problems break down in short term quenching of the magnetization as a results of the energy of the optical pulse studying how the energy of the optical pulse and the angular momentum of the magnetization flow between the different degrees of freedom. This is followed by the longer time re-emergence of the magnetism as the system cools. Within this goal we explored the formation of solitons, both with and without non-trivial topology, via rapid re-magnetization processes after optical-driven ultrafast demagnetization. Guided by theory, we predict that turbulence and modulational instabilities will drive the formation of solitons, including dispersive shock waves, magnon droplets, and skyrmions. In the case of topological defect formation, i.e. skyrmion generation, related processes have long been predicted based on general principles of symmetry-breaking phase transitions; the density of topological defects in a long-range-ordered phase can be controlled by varying the quench rate through the second-order phase transition, i.e. the Kibble-Zurek (KZ) mechanism. We, more broadly, had the goal to study a range of other emergent magnetic behaviors after optical excitation. While great attention has been given to ultrafast demagnetization, less is known of the subsequent spin dynamics and coupling to the lattice. What is increasingly appreciated is that ultrafast demagnetization leads to spin currents that can carry angular momentum from the rapidly demagnetized sample. These spin currents appear in many ways but fundamentally controls demagnetization, drives interactions between regions of the material, and control the spin resulting structure. They can be probed many ways including THz emission which, in turn, gives insight into the demagnetization processes. Simultaneously if there is magneto-elastic coupling ultrafast demagnetization can drive structural excitations that are not expected from thermal energy added to the lattice. We explored a range of complex phenomena that arise from photo-excitation of magnetic systems with the coupling of electronic, magnetic and structural degrees of freedom. We have made a number of fundamental discoveries that are reflected in our publications list with additional work still being prepared for publication. Highlights of this work include (i) ultra-efficient, nonlinear THz surface acoustics (ii) spin-current-mediated rapid magnon localization and coalescence, (iii) spin-wave soliton formation in ferromagnetic FePt nanoparticles, (iv) dynamic phonon coupling in elemental antiferromagnetic Cr, (v) THz emission from Co/Pt bilayers and FeRh/Pt bilayers, (vi) theoretical investigation of spin hydrodynamics, solitons and shock waves, and (vii) ultrafast perturbation of magnetic domains by optical pumping.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Introduction: Neuromorphic Materials

The explosive growth in data collection and the need to process it efficiently, as well as the desire to automate increasingly complex tasks in transportation, medical care, manufacturing, security and many other fields have motivated a growing interest in neuromorphic computing. Unlike the binary, transistorbased ON/OFF logic gates and separate logic and memory functionalities employed in digital computing, neuromorphic computing is inspired by animal brains that use interconnected synapses and neurons to perform processing, storage and transmission of information at the same location, while only consuming ~20 W or less of power. Motivated by the brain’s efficiency, adaptability, self-learning and resiliency qualities, neuromorphic computing can be broadly defined as an approach to processing and storing information using hardware and algorithms inspired by models of biological neural systems. Present research in neuromorphic computing encompasses approaches that vary significantly in their degree of neuro-inspiration, from systems that only incorporate features such as asynchronous, event-driven operation or use crossbar arrays of non-volatile memory (NVM) elements to accelerate deep neural networks (DNNs), to designs that embrace the extreme parallelism, sparsity, reconfigurability, adaptability, complexity and stochasticity observed in nervous systems. The term ‘neuromorphic’ computing is often credited to Carver Mead, who in the 1980s investigated Si-based analog electronics to replicate functions of the animal retina. Earlier important advances in this field include the work of Frank Rosenblatt, who proposed the concept of the perceptron, Bernard Widrow, who used this concept to build one of the first analog neural networks, the Adaline and many other researchers (see ref. 6 for an historical perspective on neuromorphic computing). With the recent increase in the use of artificial intelligence and large language models, and rising concerns over the associated energy costs, interest in neuromorphic hardware has expanded rapidly. According to some estimates, driven largely by the drastic growth in the training use of artificial intelligence (AI) models using the current computing architectures, the energy cost of computing is projected to reach the energy supply worldwide by 2045. Furthermore, while this is not a realistic outcome, it means that, if more efficient computing technologies are not developed -- soon -- the world will soon become one where demand for energy and market constraints limit the continued increase of societal access to AI and cloud services from data centers. Data centers used for training and use of these models consume hundreds of terawatt hours of electricity, already past 4% of the US electricity demand.

Circuits↗
DOE OSTI2024

Theoretical Studies of Polar Systems near Ferroelectrics Quantum Critical Points (Final Report)

The PI has studied emergent quantum phases near polar quantum critical points. A first challenge was to develop a theoretical description of the observation that many polar materials undergo classical first-order transitions while displaying quantum criticality. The possibility of novel metallic states near polar quantum critical points was then studied; identification and characterization of a non-Fermi liquid phase was made in a multiband system. In dilute quantum critical polar metals, electronic coupling to polar energy fluctuations was shown to result in attractive electron-electron interactions and to superconductivity. A spin-phonon resonance measurement in applied magnetic field was proposed to determine the magnitude of spin-orbit mediated electron-phonon coupling; furthermore in the polar phase new field-induced phonon collective modes were identified with specific signatures for experiment. In order to keep current, the PI has also worked on other types of strongly correlated problems. With experimental groups, she has developed phenomenologies to identify and explain observed dynamical critical behaviors. The PI has studied the interplay of topology, fractionalization and deconfinement in a minimalist spin model. An emergent phase transition in a 1 + 1 frustrated spin nanotube has also been identified and characterized. The PI has also begun exploring criticality out of equilibrium, characterizing rich dynamical phases associated with photoinduced polar transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A novel experimental system for the KDK measurement of the 40 K decay scheme relevant for rare event searches

Potassium-40 ( 40 K) is a long-lived, naturally occurring radioactive isotope. The decay products are prominent backgrounds for many rare event searches, including those involving NaI-based scintillators. 40 K also plays a role in geochronological dating techniques. The branching ratio of the electron capture directly to the ground state of argon-40 has never been measured, which can cause difficulty in interpretingcertain results or can lead to lack of precision depending on the field and analysis technique. Additionally, the KDK (Potassium (K) Decay (DK)) collaboration is measuring this decay. A composite method has a silicon drift detector with an enriched, thermally deposited 40 K source inside the Modular Total Absorption Spectrometer. This setup has been characterized in terms of energy calibration, gamma tagging efficiency, live time and false negatives and positives. A complementary, homogeneous, method is also discussed; it employs a KSr 2 I 5 :Eu scintillator as source and detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Sympathetic cooling of positrons to cryogenic temperatures for antihydrogen production

The positron, the antiparticle of the electron, predicted by Dirac in 1931 and discovered by Anderson in 1933, plays a key role in many scientific and everyday endeavours. Notably, the positron is a constituent of antihydrogen, the only long-lived neutral antimatter bound state that can currently be synthesized at low energy, presenting a prominent system for testing fundamental symmetries with high precision. Here, we report on the use of laser cooled Be + ions to sympathetically cool a large and dense plasma of positrons to directly measured temperatures below 7 K in a Penning trap for antihydrogen synthesis. This will likely herald a significant increase in the amount of antihydrogen available for experimentation, thus facilitating further improvements in studies of fundamental symmetries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗