About

Tao Sun is an Associate Professor of Mechanical Engineering at Northwestern University. He holds a PhD in Materials Science and Engineering from Northwestern University, an MS in Materials Science and Engineering from Tsinghua University, and a BS in Materials Science and Engineering from Tsinghua University. His research focuses on additive manufacturing, in situ and operando characterization and metrology, synchrotron x-ray imaging and scattering techniques, ultrafast dynamics in soft and hard condensed matters, machine design and process sensing, data analytics, and machine learning. He has received significant recognition for his work, including being named a Clarivate Highly Cited Researcher and receiving awards such as the TMS Young Innovator in the Materials Science of Additive Manufacturing Award and the TMS Structural Materials Division JOM Best Paper Award.

Research topics

• Materials science
• Composite material
• Optics
• Metallurgy
• Computer Science
• Physics
• Nanotechnology
• Mechanics
• Thermodynamics
• Chemistry
• Acoustics
• Mathematics
• Philosophy
• Linguistics
• Mechanical engineering
• Engineering
• Geology

Selected publications

• Aeroacoustic signatures reveal fast transient dynamics of vapor-jet-driven cavity oscillations in metallic additive manufacturing

  Research Square · 2026-04-20

  preprintOpen access
  PublisherDOI

• Characterization of the complete chloroplast genome of <i>Acroptilon repens</i> (L.) DC. (Asteraceae)

  Figshare · 2026-04-20

  datasetOpen access

  <i>Acroptilon repens</i> (L.) DC. is a rhizomatous perennial species and plays significant ecological role in steppe and desert-steppe communities by contributing to soil stabilization and vegetation coverage. In this study, we assembled and annotated the chloroplast genome of <i>A. repens</i>. The complete chloroplast genome was 152,574 bp in-length, including 35 tRNA genes, 8 rRNA genes and 85 protein-coding genes (PCGs). Among all these genes, eighteen genes contained one intron and two genes possessed two introns. The <i>rps12</i> gene exhibited trans-splicing, with exons 2 and 3 located within the inverted repeat (IR) regions. The phylogenetic tree indicated that <i>A. repens</i> had the closest relationship to <i>Leuzea carthamoides</i> DC., and clustered with other species from tribe Cardueae, subfamily Carduoedeae. The phylogenetic analysis supported the current taxonomic framework of the Asteraceae family. Our findings will enrich the complete chloroplast genome resources of Asteraceae and provide valuable data for further studies on taxonomy, evolution, and biogeography within the family.

  PublisherDOI

• Characterization of the complete chloroplast genome of <i>Acroptilon repens</i> (L.) DC. (Asteraceae)

  Figshare · 2026-04-20

  datasetOpen access

  <i>Acroptilon repens</i> (L.) DC. is a rhizomatous perennial species and plays significant ecological role in steppe and desert-steppe communities by contributing to soil stabilization and vegetation coverage. In this study, we assembled and annotated the chloroplast genome of <i>A. repens</i>. The complete chloroplast genome was 152,574 bp in-length, including 35 tRNA genes, 8 rRNA genes and 85 protein-coding genes (PCGs). Among all these genes, eighteen genes contained one intron and two genes possessed two introns. The <i>rps12</i> gene exhibited trans-splicing, with exons 2 and 3 located within the inverted repeat (IR) regions. The phylogenetic tree indicated that <i>A. repens</i> had the closest relationship to <i>Leuzea carthamoides</i> DC., and clustered with other species from tribe Cardueae, subfamily Carduoedeae. The phylogenetic analysis supported the current taxonomic framework of the Asteraceae family. Our findings will enrich the complete chloroplast genome resources of Asteraceae and provide valuable data for further studies on taxonomy, evolution, and biogeography within the family.

  PublisherDOI

• Nitrogen nutritional diagnosis of winter oilseed rape (Brassica napus L.) using fractional-order derivative hyperspectral indices: Field evaluation of dual nitrogen nutritional indices

  Industrial Crops and Products · 2025-08-07 · 7 citations

  articleOpen access

  In the rainfed Loess Plateau, diverse soil mulching practices alleviate water stress but complicate crop nitrogen diagnostics, which still rely on destructive sampling and inflexible models. From 2020–2024, we conducted field trials on winter oilseed rape ( Brassica napus L.) under ridge furrow mulching, straw mulching, and no mulching with graded nitrogen rates. At key growth stages, we measured leaf area index (LAI), leaf nitrogen concentration (LNC), seed yield, and canopy hyperspectral reflectance. First, using 2020–2023 data, we developed an integrated LAI– Nc dilution curve ( Nc =a × LAI −b ) to derive a theoretical nitrogen nutrition index ( NNI t ), which was validated against an empirical index ( NNI e ). Second, we applied fractional order differentiation (0.2–2.0) to the reflectance spectra, selected optimal spectral indices via correlation analysis, and combined them with a random forest model to invert NNI t . Third, we evaluated the “FOD index + RF” framework on independent 2023–2024 data and produced a spatiotemporal map of NNI t . Results showed that (1) the LAI– Nc curve robustly captured nitrogen dilution, with the mulched 210 kg ha -1 treatment achieving yields equivalent to 280 kg ha -1 at NNI t = 1; (2) the best FOD index correlated 0.698 with NNI t , and the RF inversion achieved R²= 0.769, RMSE= 0.131, MRE= 17.60 % for 2020–2023; and (3) 2023–2024 validation returned R²= 0.770, RMSE= 0.118, MRE= 12.93 %, while the spatiotemporal map vividly depicted nitrogen surplus–deficit dynamics. This framework overcomes model adaptability and sensitive band identification challenges, offering actionable spatiotemporal guidance for precision nitrogen management across multiple field practices. • Film mulching with 210 kg N ha⁻¹ boosts yield under reduced nitrogen conditions. • NNI theoretical values effectively reflect winter oilseed rape’s N status. • FOD with machine learning improves NNI theoretical values estimation accuracy. • The NNI map enables real-time assessment of nitrogen status in winter oilseed rape.

  PublisherDOI

• Evolution of dislocations during the rapid solidification in additive manufacturing

  Nature Communications · 2025-05-20 · 46 citations

  articleOpen accessSenior author

  Materials processed by fusion-based additive manufacturing (AM) typically exhibit relatively high dislocation densities, along with cellular structures and elemental segregation. This representative structural feature significantly influences material performance; however, post-mortem microstructure characterizations of AM materials cannot capture the dynamic evolution of dislocations during the manufacturing process, thereby offering limited mechanism-based guidance for further advancing AM techniques and facilitating the qualification and certification of AM products. In this study, we conduct operando high-energy synchrotron X-ray diffraction experiments on wire-laser directed energy deposition of 316 L stainless steel. Through a unique configuration, our operando synchrotron experiments semi-quantitatively probe the dislocation density in solid phases and their dynamic changes during solidification and subsequent cooling. By integrating this advanced synchrotron technique with multi-physics simulation, in-situ neutron diffraction, and multi-scale electron microscopy characterization, our mechanistic study aims to elucidate the effects of rapid cooling and subsequent thermal cycling on the dislocation generation and evolution. This study aims to address a critical knowledge gap concerning the unique microstructure in 3D-printed metals by quantitatively characterizing the phase and dislocation density during the printing process using operando synchrotron X-ray diffraction.

  PublisherOA PDFDOI

• Evolution of powder-entrapped pores in Ti–6Al–4V fabricated with powder bed fusion-laser beam process

  Additive manufacturing · 2025-06-18 · 3 citations

  articleOpen access

  X-ray micro computed tomography (X- μ CT) of bulk powder bed fusion - laser beam (PBF-LB) Ti-6Al-4V samples shows that, within the optimal process window – where lack-of-fusion and keyhole porosity are minimized – higher laser power reduces the number density of powder-entrapped pores when hatch spacing, layer thickness, and laser spot size remain fixed. To gain insight into this observation, the X- μ CT measurements of powder-entrapped pores are combined with a computational model to simulate pore trajectories in the PBF-LB melt pool. More than 100,000 independent pore trajectories are simulated at two different combinations of laser power and scanning velocity, where the forces acting on the pores are quantified using melt pool temperatures, pressures, and fluid flow velocities from multi-physics simulations. The model is then used to predict the pore size distributions in bulk samples fabricated within the optimal process window at 150 W, 700 mm/s and 370 W, 1200 mm/s. At both laser power settings, the total number density of pores predicted by the model is within one order of magnitude of the experimental values. The model suggests that the differences in the pore size distributions measured with X- μ CT are caused by differences in melt pool overlap (i.e., remelting). Using the model, a process map is constructed to predict porosity as a function of hatch spacing and layer thickness, suggesting that the number density of powder-entrapped pores can vary by two orders of magnitude within the optimal process window. This result suggests that the elimination of powder-entrapped pores poses an obstacle to increasing build rates by increasing the hatch spacing and layer thickness. While previous investigations of pore evolution during PBF-LB focused on experimental approaches, this work will enable the development of model-driven processing strategies to promote pore elimination.

  PublisherDOI

• UAV autonomous obstacle avoidance via causal reinforcement learning

  Displays · 2025-01-27 · 6 citations

  article1st author
  PublisherDOI

• Estimating Soil Moisture Content in Winter Wheat in Southern Xinjiang by Fusing UAV Texture Feature with Novel Three-Dimensional Texture Indexes

  Plants · 2025-09-23 · 2 citations

  articleOpen access1st author

  Winter wheat is a major staple crop worldwide, and real-time monitoring of soil moisture content (SMC) is critical for yield security. Targeting the monitoring needs under arid conditions in southern Xinjiang, this study proposes a UAV multispectral-based SMC estimation method that constructs novel three-dimensional (3-D) texture indices. Field experiments were conducted over two consecutive growing seasons in Kunyu City, southern Xinjiang, China, with four irrigation and four fertilization levels. High-resolution multispectral imagery was acquired at the jointing stage using a UAV-mounted camera. From the imagery, conventional texture features were extracted, and six two-dimensional (2-D) and four 3-D texture indices were constructed. A correlation matrix approach was used to screen feature combinations significantly associated with SMC. Random forest (RF), partial least squares regression (PLSR), and back-propagation neural networks (BPNN) were then used to develop SMC models for three soil depths (0–20, 20–40, and 40–60 cm). Results showed that estimation accuracy for the shallow layer (0–20 cm) was markedly higher than for the middle and deep layers. Under single-source input, using 3-D texture indices (Combination 3) with RF achieved the best shallow-layer performance (validation R2 = 0.827, RMSE = 0.534, MRE = 2.686%). With multi-source fusion inputs (Combination 7: texture features + 2-D texture indices + 3-D texture indices) combined with RF, shallow-layer SMC estimation further improved (R2 = 0.890, RMSE = 0.395, MRE = 1.91%). Relative to models using only conventional texture features, fusion increased R2 by approximately 11.4%, 11.7%, and 18.1% for the shallow, middle, and deep layers, respectively. The findings indicate that 3-D texture indices (e.g., DTTI), which integrate multi-band texture information, more comprehensively capture canopy spatial structure and are more sensitive to shallow-layer moisture dynamics. Multi-source fusion provides complementary information and substantially enhances model accuracy. The proposed approach offers a new pathway for accurate SMC monitoring in arid croplands and is of practical significance for remote sensing-based moisture estimation and precision irrigation.

  PublisherOA PDFDOI

• Full-Scale Experimental Study on Temperature Field Distribution of PBL-Based Steel–UHPC Composite Structures during the Early Stage and Steam Curing Period

  Journal of Bridge Engineering · 2025-05-06 · 1 citations

  article

  As one of the most innovative cement-based engineering materials, ultrahigh-performance concrete (UHPC) has attracted increasing attention in civil engineering over the last few decades. Recently, a new steel–UHPC composite bridge deck that uses perfobond strips (PBLs) to enhance the connection between the steel plate and the UHPC layer instead of the studs is proposed. Since UHPC uses large amounts of cementitious materials with low water–cement ratios, its hydration heat release and total shrinkage are much greater than normal concrete. To speed up construction and eliminate shrinkage during operation, UHPC components are usually cured using high-temperature steam. For composite structures consisting of two or more materials with different linear expansion coefficients, rapid changes in the temperature field of components caused by high-temperature steam curing may decrease the interface bonding strength and generate relatively larger initial stress or even crack. Therefore, it is necessary to investigate the influence of high-temperature steam curing on the initial stress of the proposed PBL-based steel–UHPC composite structures. Prior to this, it is necessary to understand the temperature field distribution on the PBL-based steel–UHPC composite structures under high-temperature steam curing conditions. In this work, a full-scale (7 m × 38 m) experiment on temperature field distribution of the PBL-based steel–UHPC composite structures was carried out. The time-varying temperature field distribution and the temperature gradient effect were experimentally observed. In addition, based on ABAQUS (version 2021), a fast explicit simulation method was adopted to simulate the temperature field distribution of the composite structures, which shows a good agreement with the measured results. Compared to the traditional implicit simulation method, the calculation efficiency is improved by 66.7% with considerable accuracy. Moreover, a parametric analysis is presented to investigate the distribution pattern of temperature considering factors such as molding temperature, ambient temperature, and steam curing temperature. This study provides a comprehensive analysis of the temperature field changes in steel–UHPC composite structures and can provide a basic reference for the subsequent initial stress analysis of composite structures.

  PublisherDOI

• Interactive effects of field mulching and nitrogen management on leaf photochemical efficiency, water use, and yield formation in winter oilseed rape (Brassica napus L.): A three-year appraisal

  Agricultural Water Management · 2025-12-15 · 1 citations

  articleOpen access
  PublisherDOI

Frequent coauthors

• Kamel Fezzaa

  Argonne National Laboratory

  113 shared

• Hong Yu

  Sun Yat-sen University

  100 shared

• Niranjan D. Parab

  Argonne National Laboratory

  86 shared

• Xiaoqi Chen

  75 shared

• Yuchao Wang

  Wuhan University of Technology

  75 shared

• Yang Liu

  Beihua University

  75 shared

• Jinglong Wu

  Central South University of Forestry and Technology

  75 shared

• Cang Zhao

  Argonne National Laboratory

  70 shared

Education

• Ph.D., Materials Science and Engineering

  Northwestern University

  2009

• Master, Materials Science and Engineering

  Tsinghua University

  2004

• Bachelor, Materials Science and Engineering

  Tsinghua University

  2002

Awards & honors

• Clarivate Highly Cited Researcher
• TMS Young Innovator in the Materials Science of Additive Man…
• TMS Structural Materials Division JOM Best Paper Award