Rational Strain Engineering in Delafossite Oxides for Highly Efficient Hydrogen Evolution Catalysis in Acidic Media

The rational design of hydrogen evolution reaction (HER) electrocatalysts which are competitive with platinum is an outstanding challenge to make power-to-gas technologies economically viable. Here, we introduce the delafossites PdCrO$_2$, PdCoO$_2$ and PtCoO$_2$ as a new family of electrocatalysts for the HER in acidic media. We show that in PdCoO$_2$ the inherently strained Pd metal sublattice acts as a pseudomorphic template for the growth of a strained (by +2.3%) Pd rich capping layer under reductive conditions. The surface modification continuously improves the electrocatalytic activity by simultaneously increasing the exchange current density j$_0$ from 2 to 5 mA/cm$^2_{geo}$ and by reducing the Tafel slope down to 38 mV/decade, leading to overpotentials $\eta_{10}$ < 15 mV for 10 mA/cm$^2_{geo}$, superior to bulk platinum. The greatly improved activity is attributed to the in-situ stabilization of a $\beta$-palladium hydride phase with drastically enhanced surface catalytic properties with respect to pure or nanostructured palladium. These findings illustrate how operando induced electrodissolution can be used as a top-down design concept for rational surface and property engineering through the strain-stabilized formation of catalytically active phases

MERIC and RADAR generator: tools for energy evaluation and runtime tuning of HPC applications

This paper introduces two tools for manual energy evaluation and runtime tuning developed at IT4Innovations in the READEX project. The MERIC library can be used for manual instrumentation and analysis of any application from the energy and time consumption point of view. Besides tracing, MERIC can also change environment and hardware parameters during the application runtime, which leads to energy savings. MERIC stores large amounts of data, which are difficult to read by a human. The RADAR generator analyses the MERIC output files to find the best settings of evaluated parameters for each instrumented region. It generates a Open image in new window report and a MERIC configuration file for application production runs

Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models

The energy requirements of current natural language processing models continue to grow at a rapid, unsustainable pace. Recent works highlighting this problem conclude there is an urgent need for methods that reduce the energy needs of NLP and machine learning more broadly. In this article, we investigate techniques that can be used to reduce the energy consumption of common NLP applications. In particular, we focus on techniques to measure energy usage and different hardware and datacenter-oriented settings that can be tuned to reduce energy consumption for training and inference for language models. We characterize the impact of these settings on metrics such as computational performance and energy consumption through experiments conducted on a high performance computing system as well as popular cloud computing platforms. These techniques can lead to significant reduction in energy consumption when training language models or their use for inference. For example, power-capping, which limits the maximum power a GPU can consume, can enable a 15\% decrease in energy usage with marginal increase in overall computation time when training a transformer-based language model

Cloud computing: survey on energy efficiency

International audienceCloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions

Printable magnesium ion quasi-solid-state asymmetric supercapacitors for flexible solar-charging integrated units.

Wearable and portable self-powered units have stimulated considerable attention in both the scientific and technological realms. However, their innovative development is still limited by inefficient bulky connections between functional modules, incompatible energy storage systems with poor cycling stability, and real safety concerns. Herein, we demonstrate a flexible solar-charging integrated unit based on the design of printed magnesium ion aqueous asymmetric supercapacitors. This power unit exhibits excellent mechanical robustness, high photo-charging cycling stability (98.7% capacitance retention after 100 cycles), excellent overall energy conversion and storage efficiency (ηoverall = 17.57%), and outstanding input current tolerance. In addition, the Mg ion quasi-solid-state asymmetric supercapacitors show high energy density up to 13.1 mWh cm-3 via pseudocapacitive ion storage as investigated by an operando X-ray diffraction technique. The findings pave a practical route toward the design of future self-powered systems affording favorable safety, long life, and high energy

A Kinetic Monte Carlo Study of Mesoscopic Perovskite Solar Cell Performance Behavior

Perovskite solar cells have received considerable attention in recent years due to their low processing cost and high energy conversion efficiency. However, the mechanisms of perovskite solar cell performance are not fully understood. Models based on probabilistic and statistical approaches can be used to simulate, optimize, and predict perovskite solar cell photovoltaic performance, and they can also guide experimental processing and fabrication conditions to achieve higher photovoltaic efficiency. This work developed a 3D model based on the kinetic Monte Carlo (KMC) approach to simulate 3D morphology of perovskite-based solar cells and predict their photovoltaic performance. The model incorporated the physical behavior of perovskite cells with respect to their charge generation, transport, and recombination characteristics. KMC simulation results showed that perovskite films with the pin holes-free and a homogenous perovskite capping layer of 400 nm thickness produced a maximum photovoltaic efficiency of 20.85%, resulting in minimal charge transport time (τt) and maximum charge carrier recombination lifetime (τr). Photovoltaic performance from the fabricated device has been used to validate this simulation model. This model provides significant conceptual advances in identifying current performance constraints and guiding novel device designs that enhance overall perovskite photovoltaic performance

Structural, Optical and Transport Properties of Copper Chalcogenide Nanocrystal Superlattices

This cumulative thesis is based on three publications. It investigates the self-assembly of nanocrystal (NC) superlattices, charge transport in NC assembly, and application of these superlattices in optoelectronic and vapor sensing. The materials of choice are copper chalcogenide NCs such as binary copper sulfide Cu1.1S NCs, binary copper selenide Cu2Se NCs and ternary Cu2-xSeyS1-y NCs and the organic semiconductors metal (Cu or Co) centered -4,4′,4″,4″,4‴-tetraaminophthalocyanine (Cu/CoTAPc). Macroscopic superlattices of NCs are prepared by Langmuir-type self-assembly at the air/liquid interface followed by simultaneous ligand exchange with an organic semiconductor. To enhance interparticle coupling, we cross-link the nanocrystals with the organic π-system Cu-4,4′,4″,4″,4‴-tetraaminophthalocyanine and observe a significant increase in electrical conductivity. Ultraviolet-visible-near-infrared (UV-vis-NIR) and Raman spectroscopy are used to track the chemical changes on the nanocrystals’ surface before and after ligand exchange and develop a detailed picture of the various components which dominate the surface chemistry of this material. Grazing-incidence small-angle X-ray scattering (GISAXS) serve to study the importance of electronic conjugation in the organic π-system vs interparticle spacing for efficient charge transport. Transport measurements reveal that Cu4APc provides efficient electronic coupling for neighboring Cu1.1S NCs. The electrical properties of monolayers of this hybrid ensemble are consistent with a two-dimensional semiconductor and exhibit two abrupt changes at discrete temperatures (120 and 210 K), which may be interpreted as phase changes. This material provides the opportunity to apply the hybrid ensemble as a chemiresistor in organic vapor sensing. The vapor sensing experiments exhibits a strong selectivity between polar and nonpolar analytes, which we discuss in light of the role of the organic π-system and its metal center. Next, we choose ternary alloyed Cu-based chalcogenide NCs Cu2SeyS1–y and checked the effect of ligand exchange with the organic π-system Cobalt β-tetraaminophthalocyanine (CoTAPc) along with its binary counterpart Cu2Se NCs. We analysed changes in the structural, optical as well as electric properties of thin films of these hybrid materials. Strong ligand interaction with the surface of the NCs is revealed by UV/vis absorption and Raman spectroscopy. GISAXS studies show a significant contraction in the interparticle distance upon ligand exchange. For copper-deficient Cu2-xSe, this contraction has a negligible effect on electric transport, while for copper-deficient Cu2-xSeyS1-y, the conductivity increases by eight orders of magnitude and 8 results in metal-like temperature-dependent transport. We discuss these differences in the light of varying contributions of electronic vs. ionic transport in the two materials and highlight their effect on the stability of the transport properties under ambient conditions. With photocurrent measurements, we demonstrate high optical responsivities of 200-400 A/W for CoTAPc-capped Cu2SeyS1–y and emphasize the beneficial role of the organic π-system in this respect, which acts as an electronic linker and an optical sensitizer at the same time. Finally, we report on the in-situ monitoring of the formation of conductive superlattices of Cu1.1S nanodiscs via cross-linking with semiconducting Co-4,4′,4″,4″,4‴-tetraaminophthalocyanine (CoTAPc) molecules at the liquid/air interface by real-time grazing incidence small angle X-ray scattering (GISAXS). We determine the structure, symmetry and lattice parameters of the superlattices, formed during solvent evaporation and ligand exchange on the self-assembled nanodiscs. Cu1.1S nanodiscs self-assemble into two-dimensional hexagonal superlattice with a minor in-plane contraction (~ 0.2 nm) in the lattice parameter. A continuous contraction of the superlattice has been observed during ligand exchange, preserving the initial hexagonal symmetry. We estimate a resultant decrement of about 5% in the in-plane lattice parameters. The contraction is attributed to the continuous replacement of the native oleylamine surface ligands with rigid CoTAPc. The successful cross-linking of the nanodiscs is manifested in terms of the high electrical conductivity observed in the superlattices. This finding provides a convenient platform to understand the correlation between the structure and transport of the coupled superstructures of organic and inorganic nanocrystals of anisotropic shape

LASER ABLATION IN LIQUID FOR THE CONTROLLED PRODUCTION OF PHOTOLUMINESCENT GRAPHENE QUANTUM DOTS AND UPCONVERTING NANOPARTICLES

Photoluminescent­ (PL) nanomaterials play an important role in areas including displays, sensing, solar, photocatalysis, and bio applications. Traditional methods to prepare PL materials suffer many drawbacks such as harsh chemical precursors, complicated synthetic steps, and production of many byproducts. Laser ablation in liquid (LAL) has emerged as a promising alternative to prepare materials that is single-step, fast, uses fewer precursors, produces fewer side products, and has simple purification steps. During LAL, a solid target is irradiated with a pulsed laser source. The laser pulses cause plasma plumes of the target material to form which are cooled, condensed, and can react with the surrounding liquid. This dissertation explores LAL as an alternative method to produce two important classes of PL nanomaterials: graphene quantum dots (GQDs) and upconverting nanoparticles (UCNPs). GQDs are a class of carbon PL materials that are lightweight, biocompatible and can be produced from cheap and abundant carbon sources. Their PL properties depend on both radiative recombination of intrinsic states through their carbon backbone as well as defect like states from surface functionalization. LAL of carbon nano-onions in water was used to produce GQDs. These GQDs were systematically compared to those produced by a traditional chemical oxidation method and showed blue shifted emission, higher fractions of hydroxyl-groups, and smaller sizes. Nitrogen doping with controlled chemical composition allowed further tuning of the PL and was achieved by including dopant molecules in the liquid during LAL. Lifetime measurements showed three emissive pathways and provided greater understanding of the roles of intrinsic and defect like emissive states. UCNPs composed of NaYF4:Yb3+/Er3+ are interesting for many bio applications but are challenging to prepare with both high upconversion efficiency and water solubility. Control of the UCNP phase is important for high efficiency. LAL was used to address these issues by irradiating a target of desired phase in an aqueous solution containing capping agents which allowed for formation of water soluble UCNPs of the desired phase. Tuning of laser parameters allowed control of the size, composition, and PL of the UCNPs. This work showcases LAL as a method to efficiently produce PL nanomaterials with controlled properties

Optics and Quantum Electronics

Contains reports on eleven research projects.National Science Foundation (Grant EET 87-00474)Joint Services Electronics Program (Contract DAALO03-86-K-O002)Charles Stark Draper Laboratory, Inc. (Grant DL-H-2854018)National Science Foundation (Grant DMR 84-18718)National Science Foundation (Grant EET 87-03404)National Science Foundation (ECS 85-52701)US Air Force - Office of Scientific Research (Contract AFOSR-85-0213)National Institutes of Health (Contract 5-RO1-GM35459)US Navy - Office of Naval Research (Contract N00014-86-K-0117