Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Loại bỏ chọn lọc Arsenic từ bụi chứa nhiều Arsenic trong hệ kiềm và mô hình dự đoán sử dụng mạng nơ-ron nhân tạo
Tóm tắt
Nghiên cứu này điều tra việc loại bỏ chọn lọc arsenic từ bụi chứa nồng độ arsenic cao trong các hệ kiềm và ảnh hưởng của các điều kiện rửa khác nhau. Kết quả cho thấy tỷ lệ dung dịch-rắn, nồng độ NaOH và liều lượng lưu huỳnh có ảnh hưởng đáng kể đến quá trình. Hiệu suất rửa của arsenic đạt 99,57%, trong khi đó hiệu suất của chì chỉ đạt 0,03% dưới các điều kiện thích hợp. Đặc biệt, việc bổ sung lưu huỳnh có thể thúc đẩy hiệu quả quá trình hòa tan arsenic và giảm hòa tan chì trong các dung dịch. Một mạng nơ-ron nhân tạo đã được sử dụng để mô hình hóa quá trình rửa. Nó bao gồm một mô hình mạng nơ-ron nhân tạo với phương thức lan truyền ngược có cấu trúc "6–10–2" có thể mô phỏng và dự đoán giá trị với độ chính xác trên 99%. Dựa trên sự khác biệt trong trọng số của các thông số khác nhau trong mô hình mạng nơ-ron, tầm quan trọng tương đối của các thông số liên quan đến hiệu suất rửa arsenic và chì đã được xác định, theo thứ tự là nồng độ NaOH, tỷ lệ dung dịch-rắn, liều lượng lưu huỳnh, nhiệt độ, thời gian và tốc độ khuấy.
Từ khóa
#Arsenic #chì #loại bỏ chọn lọc #hệ kiềm #mô hình mạng nơ-ron nhân tạoTài liệu tham khảo
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