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import streamlit as st
import pandas as pd
import json
from pathlib import Path
from PIL import Image, ImageOps
st.set_page_config(layout="centered")
st.markdown(
"""
<style>
.aim-section {
background-color: #f4f7fb;
color: #1f2937;
padding: 30px;
border-radius: 12px;
line-height: 1.6;
}
</style>
<div class="aim-section">
<h1 style='text-align: center;'>AIM EFRC InDeS</h1>
</div>
""",
unsafe_allow_html=True
)
st.write("")
col1, col2, col3 = st.columns([1, 2, 1])
with col2:
st.image("src/images/images/Home.png", width=700)
st.write("")
st.markdown(
"""
<style>
.aim-subheading {
font-size: 26px;
font-weight: 600;
margin-top: 25px;
margin-bottom: 15px;
}
</style>
<div class="aim-subheading">
Artificially Intelligent Manufacturing Paradigm (AIM) for Composites
</div>
<p>
The AIM Database tool serves as a powerful, centralized hub designed to streamline collaboration and information
exchange within the composite materials research community. As illustrated in the diagram, the platform enables
researchers to actively contribute to a shared knowledge base by directly uploading vital experimental datasets
through secure terminals. Users can submit specific measurements regarding mechanical properties, thermal behavior,
and rheology, alongside their published journal papers, ensuring that both raw data and peer-reviewed findings are
integrated into one cohesive system.
</p>
<p>
All contributed information is securely aggregated within a central cloud architecture, allowing for efficient storage,
organization, and retrieval by authorized users. The database is structured to comprehensively manage data across
essential material categories, specifically organizing inputs into distinct clusters for polymer data, fiber data,
and final composite data. By consolidating these diverse resources into a single accessible location, the AIM
Database tool empowers scientists to cross-reference findings, avoid duplicating efforts, and ultimately accelerate
innovation in the development of advanced materials.
</p>
""",
unsafe_allow_html=True
)
BASE = Path(__file__).resolve().parent
IMG_DIR = BASE / "images" / "images"
TARGET_SIZE = (213, 310)
def fixed_image(name):
img = Image.open(IMG_DIR / name).convert("RGB")
return ImageOps.fit(img, TARGET_SIZE, Image.LANCZOS, centering=(0.5, 0.5))
# Title
c1, c2, c3 = st.columns([1, 2, 1])
with c2:
st.subheader("Team Members")
# ---------- ROW 1 (3 members) ----------
col1, col2, col3 = st.columns(3)
with col1:
st.image(fixed_image("GangLi.jpg"))
st.markdown("""
**Gang Li**
Professor of Mechanical Engineering, Clemson University
gli@clemson.edu
""")
with col2:
st.image(fixed_image("Mathias.jpeg"))
st.markdown("""
**Heider, Mathias**
Research Assistant - CSE PhD Student
University of Delaware
mheider@udel.edu
""")
with col3:
st.image(fixed_image("Abhijit.jpg"))
st.markdown("""
**Abhijit Varanasi**
Lab Specialist - Clemson University
MFA Graduate, Clemson University
BE - CSE
avarana@clemson.edu
""")
st.write("")
# ---------- ROW 2 (2 members, centered) ----------
sp1, col4, sp2, col5, sp3 = st.columns([1, 3, 1, 3, 1])
with col4:
st.image(fixed_image("Tejaswi.jpeg"))
st.markdown("""
**Tejaswi Gudimetla**
Lab Aide - Clemson University
vgudime@clemson.edu
""")
with col5:
st.image(fixed_image("Pradeep.jpg"))
st.markdown("""
**Sai Aditya Pradeep**
Research and Development Engineer, University of Delaware
spradeep@udel.edu
""")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
st.sidebar.write("")
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