Engineering topics

Zhang, Zhao

Publications and source records attributed to Zhang, Zhao.

8 records

DOE OSTI2025

Demystifying the Resilience of Large Language Models: An End-to-End Perspective

Deep neural networks are known to be resilient to random bit-wise faults in their parameters. However, this resilience has primarily been established through evaluations of classification models. The extent to which this claim holds for large-language models remains underexplored. In this work, we conduct an extensive measurement study on the impact of random bitwise faults in commercial-scale language models. We perform an in-depth analysis of the resulting generation outputs. We first expose that these language models are not truly resilient to random bit-flips. While aggregate metrics such as accuracy may suggest resilience, an in-depth inspection of the generated outputs shows significant degradation in text quality. Our analysis also shows that tasks requiring more complex reasoning suffer more from performance and quality degradation. Moreover, we extend our analysis to models with augmented reasoning capabilities, such as Chain-of-Thought or Mixture of Experts architectures, and characterize their failure scenarios under random bit-flips.

Sun, Yu↗

DOE OSTI2024

Transient energy dissipation at the Fermi velocity in a magnetocaloric metal

Realizing fast energy dissipation in crystalline materials over macroscopic length scales is critical for energy-efficient devices and applications toward a carbon-neutral society but is usually dominated by electron-lattice interactions that cap the energy dissipation at the phonon velocity. Going beyond this velocity has been the focus of many studies, and the physical limit is the Fermi velocity where the energy is predominantly carried away by electrons throughout the materials. However, whether and how the Fermi velocity can be reached over macroscopic distances experimentally remain largely elusive. Here we show ultrafast energy dissipation at the Fermi velocity in the magnetocaloric metal LaFe 10.6 Co 1.0 Si 1.4 . Using time-resolved powder x-ray diffraction, we observe negative thermal expansion of the lattice throughout the micron-sized crystals in less than 600 fs with an incident optical fluence higher than 8 J cm -2 . The ultrafast timescale is in sharp contrast to the normal energy dissipation and shows the existence of a macroscopic momentum-relaxing electron mean free path immediately after the optical excitation. In conclusion, our findings open a different regime in energy dissipation and demonstrate the possibility of manipulating macroscopic material properties by strong optical pulses.

Chen, Yanna↗

DOE OSTI2024

Multifunctional entinostat enhances the mechanical robustness and efficiency of flexible perovskite solar cells and minimodules

Flexible perovskite solar cells (F-PSCs), prized for their nature of soft and high power-weight compatibility, have attracted intensive attention. However, inferior buried perovskite-substrate interfaces due to low interfacial adhesion between perovskites and substrates and large deformation of flexible substrates have greatly limited the performance of F-PSCs. Here, we add organic molecule Entinostat (ET) into hole extraction material Poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA) to enhance the adhesion at the perovskite/substrate interface using the interactions of ET with perovskites, PTAA and indium tin oxide (ITO) through its multiple function groups. Meanwhile, ET added into perovskites reduces the voids at the bottom perovskite film, due to its capability to tune the crystallization of perovskites by forming adduct with lead. Consequently, the inverted small area F-PSCs achieved an efficiency of 23.4%. The flexible perovskite minimodule with an area of 9 cm 2 achieved an aperture efficiency of ~19.0% certified by National Renewable Energy Laboratory. Furthermore, the optimized unencapsulated flexible minimodule retained 84% of the initial efficiency after 5000 bending cycles and retained 90% of the initial PCE (T90) after light soaking for >750 hours.

14 SOLAR ENERGY↗

DOE OSTI2023

Interfacial Fabrication of Supramolecular Polymer Networks Using Mussel-Inspired Catechol–Iron Complexes

The liquid–liquid interface provides a promising platform to construct supramolecular polymers and materials with advanced functions. However, supramolecular polymerization at the interface usually requires monomers with different or even orthogonal solubilities, which significantly limit the number of usable monomers. Here, in this work, we report a new strategy to construct supramolecular polymer networks at the oil–water interface using a water-soluble catechol–iron complex and an oil-soluble diend-functionalized polymer. Owing to the dynamic catechol–iron coordination bond and imine bond, the resulting supramolecular polymer networks demonstrate excellent dynamic features and responsiveness to different stimuli including the pH, redox, competing ligands, and temperature. With a supramolecular polymer network serving as a building block, emulsions and 2D films can be generated that have potential applications in encapsulation, release, and molecular separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA

The extreme-scale computing landscape is increasingly dominated by GPU-accelerated systems. At the same time, in-situ workflows that employ memory-to-memory inter-application data exchanges have emerged as an effective approach for leveraging these extreme-scale systems. In the case of GPUs, GPUDirect RDMA enables third-party devices, such as network interface cards, to access GPU memory directly and has been adopted for intra-application communications across GPUs. In this paper, we present an interoperable framework for GPU-based in-situ workflows that optimizes data movement using GPUDirect RDMA. Specifically, we analyze the characteristics of the possible data movement pathways between GPUs from an in-situ workflow perspective, and design a strategy that maximizes throughput. Furthermore, we implement this approach as an extension of the DataSpaces data staging service, and experimentally evaluate its performance and scalability on a current leadership GPU cluster. The performance results show that the proposed design reduces data-movement time by up to 53% and 40% for the sender and receiver, respectively, and maintains excellent scalability for up to 256 GPUs.

Zhang, Bo↗

DOE OSTI2023

Lead-chelating hole-transport layers for efficient and stable perovskite minimodules

The defective bottom interfaces of perovskites and hole-transport layers (HTLs) limit the performance of p-i-n structure perovskite solar cells. We report that the addition of lead chelation molecules into HTLs can strongly interact with lead(II) ion (Pb 2+ ), resulting in a reduced amorphous region in perovskites near HTLs and a passivated perovskite bottom surface. Here, the minimodule with an aperture area of 26.9 square centimeters has a power conversion efficiency (PCE) of 21.8% (stabilized at 21.1%) that is certified by the National Renewable Energy Laboratory (NREL), which corresponds to a minimal small-cell efficiency of 24.6% (stabilized 24.1%) throughout the module area. Small-area cells and large-area minimodules with lead chelation molecules in HTLs had a light soaking stability of 3010 and 2130 hours, respectively, at an efficiency loss of 10% from the initial value under 1-sun illumination and open-circuit voltage conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2018

Climate Change Impact and Adaptation for Wheat Protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

grain protein↗

NASA NTRS2014

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

crop-model ensembles↗