ChipGPT: How far are we from natural language hardware design

As large language models (LLMs) like ChatGPT exhibited unprecedented machine intelligence, it also shows great performance in assisting hardware engineers to realize higher-efficiency logic design via natural language interaction. To estimate the potential of the hardware design process assisted by LLMs, this work attempts to demonstrate an automated design environment that explores LLMs to generate hardware logic designs from natural language specifications. To realize a more accessible and efficient chip development flow, we present a scalable four-stage zero-code logic design framework based on LLMs without retraining or finetuning. At first, the demo, ChipGPT, begins by generating prompts for the LLM, which then produces initial Verilog programs. Second, an output manager corrects and optimizes these programs before collecting them into the final design space. Eventually, ChipGPT will search through this space to select the optimal design under the target metrics. The evaluation sheds some light on whether LLMs can generate correct and complete hardware logic designs described by natural language for some specifications. It is shown that ChipGPT improves programmability, and controllability, and shows broader design optimization space compared to prior work and native LLMs alone

Application of HJ-1B Data in Monitoring Water Surface Temperature

AbstractThe water surface temperature (WST) regarded as an important indicator of water environment, have been obtained from remotely sensed thermal data widely. One thermal band of the new HJ-1B satellite, provided with relatively both high temporal and spatial resolution may provide us a good chance for water thermal dynamic study. The suitability of HJ-1B data was evaluated, in simultaneously obtaining WST for large area, through a case study in Wuhan city. WSTs retrieved by different methods were compared with the MOD 11 product and the in situ measurements. Validation results show that more accurate result was obtained by using the revised single channel (Re_SC) algorithm, with the root mean square error (RMSE) and systematic error (SE) were 0.73K and -0.17K compared with the MOD 11. Its’ advantages in spatial and temporal resolution make the HJ-1B imageries to be an useful data source for monitoring water environment, as far as some related issues are resolved properly

Half-Sandwich Scorpionates as Nitrene Transfer Catalysts

Scorpionate complexes of the middle to late 3d transition metals [(L)­M­(NCMe)₃]­(BF₄)_<i>n</i> (M = Mn, Fe, Co, Ni: <b>1</b>^M, L = tris­(3,5-dimethylpyrazol-1-yl)­methane, Tpm^Me,Me, <i>n</i> = 2; <b>2</b>^M, L = tris­(3-phenylpyrazol-1-yl)­methane, Tpm^Ph, <i>n</i> = 2; <b>3</b>^M except <b>3</b>^Mn, L = hydrotris­(3,5-dimethylpyrazol-1-yl)­borate, [Tp^Me,Me]⁻, <i>n</i> = 1; <b>4</b>^M, L = hydrotris­(3-phenyl-5-methylpyrazol-1-yl)­borate, [Tp^Ph,Me]⁻, <i>n</i> = 1) were examined as catalysts for styrene aziridination and THF amination using phenyl-<i>N</i>-tosyliodinane as a nitrene donor. [(Tpm^Me,Me)­Fe­(NCMe)₃]­(BF₄)₂ (<b>1</b>^Fe) was identified as the most active catalyst, giving nearly quantitative nitrene transfer yields at 5 mol % loadings. The reactivity of <b>1</b>^Fe with a wider range of organic substrates was also explored, and a striking observation was strong selectivity for aromatic rather than benzylic amination for alkylaromatic substrates

The development of boundary layer structure index (BLSI) and its relationship with ground air quality

Journal articleAmbient air quality monitoring data and radar tracking sonde data were used to study the atmospheric boundary layer structure (ABLS) and its changing characteristics over Wuhan. The boundary layer structure index (BLSI), which can effectively describe the ABLS, was accordingly developed and its ability to describe the near-surface air quality was analyzed. The results can be summarized as follows. (1) An analysis of the ABLS during seriously polluted cases revealed that the ABLS was usually dry and warm with a small ventilation index (VI); meanwhile, the ABLS during clean cases was usually wet and cold with a large VI. (2) The correlation between the air quality and BLSI at 100~300 m was good and passed the confidence level limit at 99%. Moreover, the correlation coefficient increased with the altitude at 10~250 m and showed a downward trend at 250~500 m. The correlation between the BLSI at 250 m and the ground air quality was the most significant (r = 0.312), indicating that the layer ranging from 0 to 250 m is essential for determining the ground air quality. (3) The BLSI considers both the vertical diffusion capability and horizontal removal capability of the atmosphere. Therefore, it is highly capable of describing the ABLS and the ground air qualit

The Development of Boundary Layer Structure Index (BLSI) and Its Relationship with Ground Air Quality

Ambient air quality monitoring data and radar tracking sonde data were used to study the atmospheric boundary layer structure (ABLS) and its changing characteristics over Wuhan. The boundary layer structure index (BLSI), which can effectively describe the ABLS, was accordingly developed and its ability to describe the near-surface air quality was analyzed. The results can be summarized as follows. (1) An analysis of the ABLS during seriously polluted cases revealed that the ABLS was usually dry and warm with a small ventilation index (VI); meanwhile, the ABLS during clean cases was usually wet and cold with a large VI. (2) The correlation between the air quality and BLSI at 100~300 m was good and passed the confidence level limit at 99%. Moreover, the correlation coefficient increased with the altitude at 10~250 m and showed a downward trend at 250~500 m. The correlation between the BLSI at 250 m and the ground air quality was the most significant (r = 0.312), indicating that the layer ranging from 0 to 250 m is essential for determining the ground air quality. (3) The BLSI considers both the vertical diffusion capability and horizontal removal capability of the atmosphere. Therefore, it is highly capable of describing the ABLS and the ground air quality

Compression-Induced Tensile Mechanical Behaviors of the Crystalline Rock under Dynamic Loads

Characterization of the tensile mechanical behaviors of rocks under dynamic loads is of great significance for the practical engineering. However, thus far, its micromechanics have rarely been studied. This paper micromechanically investigated the compression-induced tensile mechanical behaviors of the crystalline rock using the grain-based model (GBM) by universal distinct element code (UDEC). Results showed that the crystalline rock has the rate- and heterogeneity-dependency of tensile behaviors. Essentially, dynamic Brazilian tensile strength increased in a linear manner as the loading rate increased. With the size distribution and morphology of grain-scale heterogeneity weakened, it increased, and this trend was obviously enhanced as the loading rate increased. Additionally, the rate-dependent characteristic became strong with the grain heterogeneity weakened. The grain heterogeneity prominently affected the stress distribution inside the synthetic crystalline rock, especially in the mixed compression and tension zone. Due to heterogeneity, there were tensile stress concentrations (TSCs) in the sample which could favor microcracking and strength weakening of the sample. As the grain heterogeneity weakened or the loading rate increased, the magnitude of the TSC had a decreasing trend and there was a transition from the sharp TSC to the smooth tensile stress distribution zone. The progressive failure of the crystalline rock was notably influenced by the loading rate, which mainly represented the formation of the crushing zone adjacent to two loading points. Our results are meaningful for the practical engineering such as underground protection works from stress waves

Progressive Failure Characteristics of Brittle Rock under High-Strain-Rate Compression Using the Bonded Particle Model

This paper microscopically investigated progressive failure characteristics of brittle rock under high-strain-rate compression using the bonded particle model (BPM). We considered the intact sample and the flawed sample loaded by split Hopkinson pressure bar respectively. Results showed that the progressive failure characteristics of the brittle rock highly depended on the strain rate. The intact sample first experienced in microcracking, then crack coalescing, and finally splitting into fragments. The total number of the micro cracks, the proportion of the shear cracks, the number of fragments and the strain at the peak stress all increased with the increasing strain rate. Also, a transition existed for the failure of the brittle rock from brittleness to ductility as the strain rate increased. For the flawed sample, the microcracking initiation position and the types of the formed macro cracks were influenced by the flaw angle in the initial stage. However, propagation of these early-formed macro cracks were prohibited in the later stages. New micro cracks were produced and then coalesced into diagonal macro cracks which could all form &lsquo;X&rsquo;-shape failure configuration regardless of the incline angle of the flaw. We explored micromechanics on progressive failure characteristics of the brittle rock under dynamic loads

Sources Profiles of Volatile Organic Compounds (VOCs) Measured in a Typical Industrial Process in Wuhan, Central China

Industrial emission is an important source of ambient volatile organic compounds (VOCs) in Wuhan City, Hubei Province, China. We collected 53 VOC samples from petrochemical, surface coating, electronic manufacturing, and gasoline evaporation using stainless canisters to develop localized source profiles. Concentrations of 86 VOC species, including hydrocarbons, halocarbons, and oxygenated VOCs, were quantified by a gas chromatography&ndash;flame ionization detection/mass spectrometry system. Alkanes were the major constituents observed in the source profile from the petrochemical industry. Aromatics (79.5~81.4%) were the largest group in auto-painting factories, while oxygenated VOCs (82.0%) and heavy alkanes (68.7%) were dominant in gravure printing and offset printing factories, respectively. Acetone was the largest contributor and the most frequently monitored species in printed circuit board (PCB) manufacturing, while VOC species emitted from integrated chip (IC) were characterized by high contents of isopropanol (56.4&ndash;98.3%) and acetone (30.8%). Chemical compositions from vapor of gasoline 92#, 93#, and 98# were almost identical. Alkanes were the dominant VOC group, with i-pentane being the most abundant species (31.4&ndash;37.7%), followed by n-butane and n-pentane. However, high loadings of heavier alkanes were observed in the profile of diesel evaporation