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The acceleration of intense proton and ion beams by ultra-intense lasers has matured to a point where applications in basic research and technology are being developed. Crucial for harvesting the unmatched beam parameters driven by the relativistic electron sheath is the precise control of the beam. We report on recent experiments using the PHELIX laser at GSI, the VULCAN laser at RAL and the TRIDENT laser at LANL to control and use laser accelerated proton beams for applications in high energy density research. We demonstrate efficient collimation of the proton beam using high field pulsed solenoid magnets, a prerequisite to capture and transport the beam for applications. Furthermore we report on two campaigns to use intense, short proton bunches to isochorically heat solid targets up to the warm dense matter state. The temporal profile of the proton beam allows for rapid heating of the target, much faster than the hydrodynamic response time thereby creating a strongly coupled plasma at solid density. The target parameters are then probed by X-ray Thomson scattering (XRTS) to reveal the density and temperature of the heated volume. This combination of two powerful techniques developed during the past few years allows for the generation and investigation of macroscopic samples of matter in states present in giant planets or the interior of the earth.

Experiments using high-energy/high-power lasers have being pursued for almost a decade at GSI. In the regime of ultra-intense lasers, the PHELIX (Petawatt High-Energy Laser for heavy-Ion experiments) system has reached the 20 TW level and first successful experiments have been done. In addition to the experiments on heavy-ion energy loss in laser produced plasmas, our research will focus on laser-assisted particle acceleration and the use of high-energy petawatt lasers (HEPW) for the diagnostics of dense plasmas which has raised great interest in the international community. The plasma physics group at GSI, based on experiments in France, the UK and the U.S., has contributed significantly to this field of research in recent years. Now, with the upcoming commissioning of different power levels of PHELIX our experimental activities can be performed at GSI. Due to the funding of a virtual institute by the Helmholtz Association, the opportunities for new experiments at GSI have grown significantly. The paper will give an overview of recent experimental results, show the link to the future GSI experimental program (including FAIR) and present the experiments that will be done at GSI for the years to come.

Ultra-intense lasers that ionize atoms and accelerate electrons in solids to near the speed of light can lead to kinetic instabilities that alter the laser absorption and subsequent electron transport, isochoric heating, and ion acceleration. These instabilities can be difficult to characterize, but X-ray scattering at keV photon energies allows for their visualization with femtosecond temporal resolution on the few nanometer mesoscale. Here, we perform such experiment on laser-driven flat silicon membranes that shows the development of structure with a dominant scale of 60 nm in the plane of the laser axis and laser polarization, and 95 nm in the vertical direction with a growth rate faster than 0.1 fs−1 . Combining the XFEL experiments with simulations provides a complete picture of the structural evolution of ultra-fast laser-induced plasma density development, indicating the excita- tion of plasmons and a filamentation instability. Particle-in-cell simulations confirm that these signals are due to an oblique two-stream filamentation instability. These findings provide new insight into ultra-fast instability and heating processes in solids under extreme conditions at the nanometer level with possible implications for laser particle acceleration, inertial confinement fusion, and laboratory astrophysics.

Electric vehicle (EV) users who aim to become flexibility providers face a tradeoff between staying in control of charging and minimizing their electricity costs. The common practice is to charge immediately after plugging in and use more electricity than necessary. Changing this can increase the EV’s flexibility potential and reduce electricity costs. Our extended electricity cost optimization model systematically examines how different changes to this practice influence electricity costs. Based on the Prospect Theory and substantiated by empirical data, it captures EV users’ tradeoff between relinquishing control and reducing charging costs. Lowering the need to control charging results in disproportionally large savings in electricity costs. This finding incentivizes EV-users to relinquish even more control of charging. We analyzed changes to two charging settings that express the need for control. We found that changing only one setting offsets the other and reduces its positive effect on cost savings. Behavioral aspects, such as rebound effects and inertia that are widely documented in the literature, support this finding and underline the fit of our model extension to capture different charging behaviors. Our findings suggest that service providers should convince EV-users to relinquish control of both settings., Energy and Industry

The potential of households to adapt their energy use to the conditions of the energy system remains largely untapped due to shortcomings in consumer governance (i.e., the organization of household energy use). A lack of price signals and services leads to uncoordinated household energy use. Various proposals exist for updating consumer governance (e.g., virtual power plants, variable tariffs, energy communities). A research gap arises from the fact that a single governance design cannot meet all household needs and that the priorities of household needs are ambiguous. The empirical research in this dissertation demonstrates that a governance design should focus on enabling households to achieve energy cost savings, convincing them to participate by safeguarding their control needs and keeping them involved by limiting their operational burden. These priorities speak for virtual power plants as consumer governance design. If intermediaries could anticipate latent, upcoming household needs in the design, make tradeoffs transparent for households, and create dedicated points for decision-making, then they would support households in making more informed decisions and taking on an active role in the energy system., Energy and Industry

Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO2 emissions and costs. Nudges are proposed as one behavioral intervention to orchestrate such changes. At the same time, fragmented findings in the literature make it challenging to identify suitable behavioral interventions for specific households and contexts - specifically for optimizing self-consumption. We test three sequentially applied interventions (feedback, benchmark, and default) delivered by digital tools in a field experiment with 111 German households with rooftop-photovoltaics. The experiment design with a control-group, baseline measurements, and high-frequency smart-meter-data allows us to examine the causal effects of each intervention for increasing self-consumption. While feedback and benchmark deliver small self-consumption increases (3–4 percent), the smart changing default leads to a 16 percent increase for active participants. In general, households with controllable electric vehicles show stronger effects than those without. For upscaling behavioral interventions for other prosumers, we recommend interventions that require little interaction and energy literacy because even the self-selected, motivated sample rarely interacted with the digital tools., Energy and Industry

Households equipped with flexible technologies, such as electric vehicles, can support the energy transition by shifting electricity consumption to times of high renewable supply and by preventing consumption peaks that cannot be covered by existing grid and generation infrastructure. Demand response services support households in performing these consumption shifts. Households ask for specifications of services that stand partly in contrast to each other. For instance, while electric vehicle owners tend to insist on retaining control over their charging, others prefer data-driven automation to minimize their active involvement. Recent studies exploring the acceptance of demand response services focused either solely on specific household groups (e.g. electric vehicle users) or on a broad representative sample without further differentiation. Complementarily to fill this gap, we examine differences in preferences for contrasting service designs between household groups. Specifically, we consider: (i) the type of flexible technology to which demand response is applied, and (ii) the adoption level, i.e., whether the households plan to, or currently own, a flexible technology. In a vignette survey, we examine the preferences towards four contrasting service designs with German households that either own or have expressed interest in acquiring a flexible technology (n = 962). Our results show that the preferences do not fundamentally differ between the kind of flexible technology and adoption level. Generally, participants prefer automated demand response services with data sharing. The added value of realizing energy cost savings effectively and efficiently stands out as the main driver for the diffusion of demand response services, outweighing data privacy concerns. Contrary to our expectations, electric vehicle owners did not show a special need for control and households not yet owning flexible technologies did not express a need for little effort. We discuss the, Energy and Industry